ISSUES IN DEVELOPMENTDiscussion Paper

33

PAKISTAN:Employment, Output and

Productivity

Nomaan Majid

International Labour Office Geneva

Copyright © International Labour Organization 2000 ISBN 92-2-111977-7

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TABLE OF CONTENTS

ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

PREFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii

INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1A. Recent changes in the macro environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1B. The argument . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

CHAPTER ONE - Labour Force and Employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71. The data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72. Growth of population and labour force . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83. Labour force and employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Definitions of labour utilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9The self-employed amongst the employed . . . . . . . . . . . . . . . . . . . . . . . . . 10Underemployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10Unemployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11Employment and labour force: An overview . . . . . . . . . . . . . . . . . . . . . . . 12

4. Changing trends in the rural-urban distribution of labour force . . . . . . . . . . . . . . . 125. Why are labour force participation rates (LFPRs) low? . . . . . . . . . . . . . . . . . . . . . 13

Education and the labour force . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Emigration and the labour force . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Gender and the labour force . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

6. On the changing abilities of the labour force . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15Labour force expectations and the structure of the job market . . . . . . . . . . 16

7. Upshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16Participation Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Training and skills . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Implications for a strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

CHAPTER TWO - Output Employment and Productivity: Lessons for an Employment Strategy . . 181. A dual focus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182. Examining shares of employment and output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183. Sectoral shares of employment and output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194. Growth of employment and output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195. Sectoral employment absorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206. Decomposing output growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227. Wages and poverty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Real Wages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Poverty Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24Poverty, Wages and Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

8. Elasticity, employment, labour productivity and output: An integrated view . . . . . 269. Employment and output growth linkages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2810. The agenda for an employment strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

CHAPTER THREE - The Agricultural Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312. The special nature of employment and output in agriculture . . . . . . . . . . . . . . . . . . 31

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Measurement of employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31The special nature of output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31A combined effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

3. Output and employment growth rates in Pakistan’s agriculture . . . . . . . . . . . . . . 334. Agricultural employment and total employment . . . . . . . . . . . . . . . . . . . . . . . . . . . 345. Decomposing the sources of output growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346. Unemployment and underemployment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357. Labour demand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Cropping patterns and profitability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36Size and productivity: Increasing family labour use . . . . . . . . . . . . . . . . . . 37Mechanization: Reducing labour requirements . . . . . . . . . . . . . . . . . . . . . 37Tenurial shifts: Creating an available labour pool . . . . . . . . . . . . . . . . . . . 37

8. Wages and poverty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379. Upshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

CHAPTER FOUR - The Manufacturing Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 401. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402. Elasticity, employment and output growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403. Decomposing output growth in the manufacturing sector . . . . . . . . . . . . . . . . . . . . 414. Output and employment in the manufacturing sector . . . . . . . . . . . . . . . . . . . . . . . 425. The large-scale sector: Main features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 446. An examination of productivity in the large-scale manufacturing sector . . . . . . . . . 457. The structure of large-scale manufacturing in the 1980s and 1990s . . . . . . . . . . . . 46

The high-growth 1980s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47The 1990s: A period of low growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

8. Towards a policy outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50Criteria of sectoral choices in an employment-friendly investment plan . . . 51Fiscal expansion and demand . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51The budget deficit and working capital . . . . . . . . . . . . . . . . . . . . . . . . . . . 51Promotion of sub-sectors through tariff rationalizations . . . . . . . . . . . . . . . 51Capital pricing and directing new investment . . . . . . . . . . . . . . . . . . . . . . . 51The co-ordination of capital flows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52The revival of sick industries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52Tax policy and flow of goods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52Energy pricing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

9. Upshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

CHAPTER FIVE - The Small-Scale Enterprise Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541. Information and data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 542. Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 543. Estimates of output and employment in SSE manufacturing . . . . . . . . . . . . . . . . . . 544. Characteristics of the SSE sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

The SSE firm: Subcontracting and demand . . . . . . . . . . . . . . . . . . . . . . . . 56Labour use in the SSEs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57Capital stock ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57Credit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58Incomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

5. Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

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6. The Supply and demand for sse goods and services . . . . . . . . . . . . . . . . . . . . . . . . 59Changes in purchasing power of social groups and demand . . . . . . . . . . . . 59Remittances . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60The green revolution and differentiation of the peasantry . . . . . . . . . . . . . . 60The income and technical change effect of the green revolution . . . . . . . . . 60Depreciation of exchange rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

7. Some inferences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 618. Policy areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Credit policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62Tax policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62Infrastructure policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62

9. A strategic policy corollary and some specific measures . . . . . . . . . . . . . . . . . . . . 6210. Upshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

CHAPTER SIX - An Employment Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 651. Elements of an employment strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

On labour force and employment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65On sectoral strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

APPENDIX -The Economic Reforms Context of Growth and Employment . . . . . . . . . . . . . . . . . . 70The periodization and salient features of Pakistan’s development history . . . . . . . . . . . . . . 70The non-economic correlates of macroeconomic policies and growth . . . . . . . . . . . . . . . . . 71Two symptoms of the problem of growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72Assessing the policy-growth linkage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73The aggregate overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73Indicators on economic growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74Indicators on price stability in the economy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75Indicator on external balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75Indicators on labour market conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75A thematic assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76On the sequencing of reforms and the reform policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Fiscal Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77Monetary Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Trade and exchange rate liberalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82Exchange Rate Reforms (1982- ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82Trade liberalization (1983- ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Non-tariff barriers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Tariff reforms (1990-) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84Upshot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

ANNEXES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

CHAPTER ONEAnnex 1.1: Sources of data on labour and human resources . . . . . . . . . . . . . . . . . . . . 89Annex 1.2: Youth employment and child labour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91Annex 1.3: Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

CHAPTER TWOAnnex 2. Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105

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CHAPTER THREEAnnex 3. Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

CHAPTER FOURAnnex 4 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128

CHAPTER FIVEAnnex 5.1: The small-scale enterprise sector in main data sources . . . . . . . . . . . . . . 137

Rates of growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137Broad characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137

Annex 5.2: Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142

BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

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Acknowledgments

This report is based on the work carried out during 1997-98. Nomaan Majid of the Employment Sectorof the ILO, Geneva is the coordinator and principal author of the report. The work is based oncontributions from a team comprising of Arshad Zaman Associates, A.R.Kemal, M. Irfan, M. Mahmood,G. Chaudhry and Nomaan Majid. Particular thanks are due to A.K. Ghose, M. Mahmood and AkmalHussain for detailed comments on earlier drafts. Thanks are also due to Samir Radwan, Rolph Van derHoeven and Rashid Amjad for suggestions on the final draft. A.S.Oberai of ILO-SAAT, provided constantsupport and encouragement for the project from its inception. ILO-SAAT, the ILO Office in Islamabadand the UNDP in Islamabad actively facilitated the progress of this report, in its most critical phases.Very special thanks are due to them.

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PREFACE

This report is an outcome of work done by the ILO, on an employment strategy for Pakistan during 1997and 1998, an activity which was funded under the UNDP’s SPPD facilty. One objective of the core workdone for this exercise was to contribute an input to Planning Commission for their employment andmanpower related work on the Ninth five Year Plan. Another objective was to produce a employmentstrategy document, that was cognizant both of sectoral employment issues and the macro economicenvironment in which a future employment strategy needs to be conceived. It is hoped that work is seenas a step in the right direction. More thinking however, needs to be done in detailing the proposedemployment strategy, in addition to addressing the implications of this strategy for social groups withinsectors. It is expected that the ILO in collaboration with the UN agency system will carry this work further.

Two central issues need to be emphasized. This document argues that in the Pakistan context the key toan employment growth revival is the revival of the manufacturing sector. The particular forms that sucha revival may take, the linkages with other sectors, and some of the policy elements required for such arevival are delineated. The document also suggests in a separate section why the role of the macro policyenvironment in the growth process is critical from an employment perspective. It argues where and howPakistan came to its fiscal crisis. This event, which is a result of imperatives on the part of State as wellas ill-conceived reform sequencing on the part of donors, preceded the post nuclear situation of additionaleconomic constraints that the country has faced and the more recent changes in government.

Today when the elements of adjustment packages and their relationship to growth are being seriouslyquestioned by Bretton Woods institutions themselves because of the high social costs of adjustment asevidenced by the Asian and Russian crises, it is important to directly examine the nature of policypackages necessary for a revival of employment-friendly growth in developing countries. The challengeis not easy for Pakistan, but the international environment is sufficiently changed and the domesticemployment crisis sufficiently serious, to pursue the matter with new vigour.

Samir RadwanDirector, Development Policies Department

1 The policy of non convertibility of domestic foreign currency deposits that was compelled, according to the centralbank, by excessive public borrowing against these deposits, was an effort to miser precious foreign reserves.

INTRODUCTION

This study on employment in Pakistan was conducted in 1997-98. Its objective has been toanalyse trends in the labour market in the country, and develop possible elements of anemployment strategy during Pakistan’s Ninth Five Year Plan period ( 1997-98 to 2001-02).

A. Recent Changes in the macro environment.

Since the completion of this work in 1998, some factors have entered into Pakistan’s planningprocess that have affected it significantly. The first is a rapidly changing macro environment.The second are the results of the 1998 Population Census. The report argues that these factorsheighten the need for an employment strategy being proposed in this document. Its shouldhowever be finessed towards the transforming macro environment, and our better post-censusperception of it.

Pakistan’s macroeconomic performance, while showing indications of improvement at the timeof the 1998 budget, has since been subject to fiscal stress. The central point that is worth makingis that over the fiscal year 1997/98, growth had picked up in Pakistan to the five per cent level,while the IMF stipulated targets in macro fundamentals were met to the satisfaction of theevaluating mission to Pakistan at the time. However, domestic fiscal policy, perhaps inanticipation of an impending sanctions based global environment due to the nuclearisation of thecountry, (and possible investment behaviour based on this global environment), moved towardsregulation in a number of areas1. A major result of this macro transformation had been thecessation of the Enhanced Structural Adjustment Facility (ESAF) and Extended Fund Facility(EFF) agreements signed with the IMF, and a renegotiated new loan.

Although the external environment is now more stable, and donor links have been reestablished,changes in the macro environment need to be tracked as they can have critical implications forgrowth and employment in Pakistan. Clearly this issue needs to be assessed in future work. It isalso critical to recognise the status of the specific macroeconomic policy environment for thequestion of whether growth is employment-friendly or not. Since the link between macropoliciesand employment is generally mediated by growth, this provides an overarching context tounderstanding different phases of (employment focussed) economic development in Pakistan. Thereport devotes a separate Appendix to this issue. The reason to keep this discussion separate fromthe main body of the report is two fold. First that the assessment of the linkage betweenmacropolicies and employment in this report is itself limited to an historical overview. Second,that it is the last phase of macropolicies in operation in Pakistan that are of greater importanceto an employment strategy, than what can be argued for earlier phases.

B. The argument

The position of this study on employment and its determinants in Pakistan is the following. Wageemployment in Pakistan is approximately one half of all employment, its proportion is high for a

2

low income country. On the other hand self-employment comprises the other half of employment(Chapter 1). The share of the labour force in the estimated population for 1997, according topre-1998 Census projections( on which this study has been based, and on which more below) islow. It was 37 million from a universe 135 million, which suggests a low participation rate. In factthe labour force participation rate (LFPR) in Pakistan has been decreasing over time. It is nowdown to around 27 per cent, therefore implying a high and increasing dependency ratio for therest of the population. While we can explain to some extent, the drop in the LFPR to be due toincreasing school enrollments (which is therefore in some respect desirable), there is clearly apossible trade off involved due the narrowing of the earning base in the country, which can putdownward pressures on per capita income. This can have implications for poverty and livingconditions of households. We actually find a mixed result on poverty in Pakistan, but it is onewhich is not inconsistent with the hypothesis of a downward pressure on living standards due toincreasing dependence during the growth process.

The next question the report asks is what determines the low labour force participation and itsincome? The labour force, by definition, comprises of the employed and the unemployed, givenat around 35 million and 2 million respectively. Before summarising the answer to this question,some qualifiers need to be made. There has been considerable debate and now recognition, inPakistan, that women’s income enhancing labour, whether in self-employment or in the wagelabour market has been considerably under-enumerated due to non-sampling errors like malesocial biases, that render women’s labour “invisible”. This feature also reduces the overallestimates of the size of the employed. The second qualification is that under enumeration of theunemployed obtains because the survey- definition used in Pakistan requires them to be availablefor work in the reference week. Moreover it is to be remembered that these qualifiers obtain inthe context of a labour market where formal institutions for employment are eclipsed by informalinstitutions. So, our estimates of both the employed and the unemployed, and the size of the totallabour force are probably low.

This study assumes that given the labour force size, perhaps in this case based on consistentunderestimation, what will determine the level of employment in the economy is firstly growthitself. On the other hand what determines the earnings of the employed are the wage rate andreturns to self-employment in different sectors of the economy. In order to investigate therelationship between employment and growth, this study uses two analytical devices. One is astandard elasticity coefficient for employment with respect to growth. Problematic as the specificmagnitude of the elasticity measure is, in the view taken here, it is considered at least qualitativelyand directionally indicative of the employment-output linkage. This of course gives a range ofvalues indicating say high, medium, or low responsiveness of employment to growth. The seconddevice dis-aggregates change in output over time into (i) an output change caused byemployment change; (ii) an output change that is caused by productivity changes; and (iii) anoutput change that is caused by a multiple effect of both employment and productivity changes.We refer to this as the decomposition exercise. The results of both exercises ( elasticity anddecomposition) are used as summary perspective devices in the overview as well as sectoralchapters.

Chapter 2 of this study shows that over the last three decades, Pakistan’s growth has been highfor a low income country, around six per cent on trend till 1992/93, with a two per cent variation.However, against this high GDP growth, employment growth has been much lower, at two per

3

cent on trend. As a result the elasticity of employment has remained medium to low, rangingbetween 0.6 and 0.3. The periodicity of this growth of output and employment is revealing, if weabstract for the moment from the issue of the particular periodisation chosen.

Output growth in Pakistan was low over the 1970s at under five per cent, it increased over the1980s to above six per cent, and has dropped again over the 1990s to near about four per cent.Employment growth interestingly follows an opposite pattern, being at its highest at three percent over the 1970s and lapsing to two per cent over the 1980s and the 1990s. Does thisconstitute some prima facie evidence for a trade off between employment and output growth?A further subdivision of these periods shows that there was a period of high employment in the1970s, stable employment till the mid-1980s and a total break between growth and employmentsubsequently. The aforementioned decomposition exercise adds an insight to this pattern.Growth of output was based predominantly on an employment effect in the 1970s, on aproductivity effect in the 1980s, and a mixed productivity and employment effect in the 1990s.So the answer to the trade off question posed above is not straight forward, and apart from havinga source of output growth dimension ( productivity or employment) the answer is likely to havea sectoral dimension as well.

We know that generally low elasticities accompanying growth in Pakistan tend to conceal thefact that the source of growth (employment or productivity) itself has been varying over time.This is an important point to note. It is this changing relationship between growth of output andemployment over time that is traced to its major sectoral components in the rest of the report.

In output growth, manufacturing is the leading sector (and agriculture contributes progressivelyless over time), over the low growth period of the 1970s, the high growth period of the 1980s,and the lower growth period of the 1990s. In employment growth, during the low growthperiod of the 1970s manufacturing leads, and with the relapsed of growth of the 1990s,employment growth in manufacturing turns negative.

The explanation for the changing overall relationship between output and employment growthover time then finds a possible sectoral reason. It has been said that employment growth washigh over the 1970s and then stable till the mid 1980s, after which it de-linked from outputgrowth. Manufacturing contributed relatively more to employment growth than agriculture in the1970s, relatively less than agriculture in the 1980s, and negatively in the 1990s. So the overallbreak between output growth and employment seems to be more associated with themanufacturing sector. It is also true that we find some evidence to suggest that agriculture andconstruction are becoming possible refuge sectors for labour after this de-linking of employmentand output growth. This explanation is further enhanced when we examine output andemployment growth relationships at the sectoral level through the same two analytical devices ofsectoral elasticities and the decomposition exercises. Chapters 3 to 5 examine sectors.

Chapter 3 on agriculture shows that output growth and employment growth (and therefore,employment elasticity) were stable in the 1970s till the mid-1980s, barring states of nature basedinterventions. Therefore, output and employment growth are connected till the mid-1980s. Afterthe mid-1980s, output and employment growth became volatile. The elasticity of employmentin agriculture is thus positive and stable till the mid-1980s then subsequently starts fluctuating.The decomposition exercise for agriculture shows that agricultural output growth was driven

2 For effective purposes the 1934 Factories Act cuts off enterprises employing more than ten workers, from thoseemploying less.

4

predominantly by the employment effect in the 1970s, largely by the productivity effect in the1980s and then again largely by the employment effect in the 1990s. The report does pursuealternative explanations for the contribution of agriculture to the fluctuations in employment fromthe mid-1980s onwards, in terms of the increasing sensitivity of a post-High Yielding Variety(HYV) agriculture to states of nature, and the casualisation of the labour force based onincreasing mechanisation.

In contrast, to agriculture, Chapter 4 shows that in the case of manufacturing, employmentgrowth was stable and high over the 1970s, when in fact output growth was low. In the 1980s,output growth in manufacturing rose, but employment growth dropped to a stable low, theaforementioned critical disjuncture become evident by 1980. By the mid 1980s, output andemployment growth both become unstable. Elasticity of employment in manufacturing, barringa peak in the mid-1970s remains at a continuously low level. The decomposition exercise for themanufacturing sector highlights this break between employment and output growth after the1970s. Over the 1970s output growth in manufacturing is driven equally by the employmenteffect and the productivity effect. Over the 1980s the employment effect becomes negligible,while over the 1990s it turns negative.

So, the disjuncture between employment and output growth rates in manufacturing reflect andtrack the economy-wide break between employment and output growth rates better. Low outputgrowth accompanies high employment in the aggregate over the 1970s, high output growthaccompanies low but stable employment growth till the mid-1980s, after which employment andoutput growth become volatile. It is fairly clear that both agriculture and manufacturing contributeto output through a predominant employment effect in the 1970s, but for the 1980s and 1990s,only agriculture contributes through an employment effect, while manufacturing’s employmentgrowth breaks away from its growth of output.

Having focussed on the manufacturing sector, we need to trace the causality further. In otherwords we need to determine the causes for this break between employment and output growthin manufacturing itself. The first point to note here is that while the share of manufacturing inGDP has increased over time from 15 per cent to 18 per cent, its share in employment hasdeclined from 14 per cent to 10 per cent. To explain why the manufacturing sector has becomeentirely labour productivity driven rather than in some measure employment-driven, we have torecognise some structural features of the sector. The critical feature of manufacturing in Pakistan,as in many developing economies is its duality. The large scale (LS) sector and a small scale (SS)sector are two classifications of manufacturing and the cutoff point between the two has beendefined variously over time by the government of Pakistan (GOP)2. The LS sector (examined inChapter 4), produces two-thirds of the value added in manufacturing, but employs only 17 precent of the approximately 4 million labour force in manufacturing. The SS sector (examined inChapter 5), produces one third of the value added in manufacturing, but employs 83 per cent ofthe labour. So the LS sector dominates output, while the SS sector dominates employment.Further, the output and employment shares of the LS and SS sectors have remained fairly stableover the last two decades.

3 Chapter 4 shows that over the 1980s the capital labour ratio in the LS sector increased from Rs. 50,000/ to Rs.192,000/.

4 This was akin to the pattern of restructuring of capital followed in some Industrialised countries (ICs) over the1980s, in reprisal to the three decades of post-war Keynesian full employment policies.

5

The differential between the two manufacturing sectors, LS and SS, is in labour productivity; andthis in turn is reflected in a differential in their capital-labour ratios. The LS sector has a highercapital labour ratio by a factor of 17, and therefore a much higher labour productivity. It also has higher wage rates and greater job security, and it is argued over the course of Chapters 3 and 4,that LS growth rates are higher growth rates than those in the SS sector. Other productioncharacteristics of the SS sector are detailed in Chapter 5, these are fragile vending linkages toother parts of the economy and negligible formal credit. The typical SS unit is based on selfemployment and family labour; with earnings approximating the LS sector’s wage rate, with lowvintage, and limited vertical transition out of the sector. These characteristics of the SS sector,while not completely homogenising potentially render a large part of it, a refuge labour sector inPakistan.

The following question then is, if the SS sector has in large part been or become moribund withall its disincentives, why has the LS sector failed to expand its employment levels significantlyover time, say between 1980 and 1995, when employment grew at 2.3 per cent, employment inthe LS sector grew at under 1.8 per cent. The first element in our answer is an increase in capitalproductivity in large scale manufacturing over time3. Furthermore, Chapter 4 also shows for theLS sector, that while this increase in capital productivity was positively correlated to labourproductivity, it was significantly negatively correlated to employment. As a result the wage sharein output dropped from 0.4 to 0.29. This is accompanied by the fact, as Chapter 1 shows, thatthe real wage in Pakistani industry barely creeps up over the last two decades. It is worthpointing out that this pattern of growth in the LS sector was enabled by a large increase ininvestment in manufacturing, and liberal financial sector lending. So over the period 1982/83 to1992/93, private investment in manufacturing increased from 1.7 per cent of GDP to 4.2 per cent.In other words, the pattern of investment and growth in manufacturing, over the 1980s, wascapital augmenting and labour displacing, and it increased profitability and reduced the wageshare in output. The evidence tends to favour this view 4.

The second element in our answer to the disjuncture between growth of output and employmentin the LS sector lies in the creation of excess capacity in the 1990s. Private investment inmanufacturing halves after 1993/94 from 4.2 per cent of GDP to 2.2 per cent with a decliningtrend, as Chapter 4 shows. This results in a declining trend in capacity utilisation in the fourmajor industries of the LS sector, spinning, weaving, cement and sugar. The economic positiontaken here is that this downturn in investment, capacity utilisation, and growth in manufacturingis caused in large part by a failure in demand, significantly associated with the deflationarypolicies pursued by GOP in accordance with the Structural Adjustment (SA) programme signedwith the IMF, in successive protocols since the 1988 .

What probably happened was a coincidence of events. Growth in Pakistan has always beensusceptible to states of nature caused downs in agriculture, given its preponderant reliance on the

6

textile industry and export of cotton and its products. The dips in GDP in each decade, examinedin Chapter 2, are related to flooding in agriculture in the early 1970s and in the early 1980s, anda pest attack on cotton in 1992/93. However in the 1970s and the 1980s, the economy recoveredwith a one to two-year lag, returning to trend growth. In the 1990s, however, this return to trendgrowth has arguably been inhibited by the simultaneity of deflationary SA policies with themassive decline in cotton output for two years running. Just when the state of nature causedslump needed a reflationary policy, the SA programme veered the economic managers towardspolicies effectively increasing the incidence of general taxation and a decline in subsidies. This wasaffected through the imposition of a Value Added Tax (VAT) and successive annual increasesin its rate and coverage; and through a reduction in the budgetary deficit especially affectingagricultural subsidies and therefore production and recovery. This was also manifested in adecreased purchasing power and effective demand.

In summary, we have found that the relationship between growth in employment and output isstrong over the 1970s, and stable over the first half of the 1980s, but becomes negativesubsequently. Manufacturing is the leading sector in growth of output and employment in the1970s, but contributes little to employment in the 1990s. The manufacturing sector is seen to becharacterised by a dualism, with an LS sector dominating output, and an SS sector dominatingemployment over time. Given low capital labour ratios in the SS sector and all the disadvantagesin production conditions that this entails, the central question that emerged was why the relativelymore advantaged LS sector had constrained its employment levels over time, especially over the1980s and the 1990s. Two elements were identified to answer this question. One, that over the1980s, the LS sector in Pakistan followed an internationally established pattern of capitalaugmenting, labour substituting growth, increasing profit shares and reducing the wage share.Two, that over the 1990s, deflationary SA policies dampened recovery from a state of naturecaused blip in growth, especially for manufacturing, constraining capacity utilisation andemployment further.

An employment strategy for Pakistan must then seek to redress this disjuncture between growthof output and employment, caused in large part by the LS sector in manufacturing. This is whatis proposed in this report. The key constraints are an overwhelming capital augmenting growthpath, and deflationary SA policies. This brings us back full circle to the starting point thisargument. With an impending, and even larger, SA programme in the offing, Pakistan faces theprospect of possibly low growth and low rate of recovery from a fiscal crisis as in 1992/93, andpossibly employment-less growth as in the 1980s. This makes a planned employment strategy forthe NFYP period difficult but imperative. On the other hand, the more recent changes in thethinking of Bretton Woods institutions, with respect to the recognition of social outfalls ofadjustment programmes, allows Pakistan, as indeed other developing countries, a better contextin which to make a case for a macro and social policy framework which is consistent with apositive employment strategy.

1 For example, due to exclusion of women’s household work and of women and men’s work in the informal sector(especially in the school-going age group).

2 Population censuses have been conducted every ten years 1880. The census for 1971 was delayed by one year, andthat for 1991 has not been conducted so far. There is now evidence to show that there may be serious problems associated withthe 1961 census. Consequently the need for a consistent series is real. The 1997 figures are estimates.

3 Since 1990-91 the surveys are based on an improved questionnaire.

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CHAPTER ONELabour Force and Employment

1. THE DATA

A well-known shortcoming of analysis on labour markets in Pakistan is the internal limitations of the dataproduced on population, labour force and employment. Coverage of the labour force surveys (LFS) isknown to be low, with the result that both participation rates and employment elasticities based on LFSdata are thought to be underestimated. The population census scheduled for 1991 had been delayed, leavinga gap of over seventeen years since the previous census was taken. The full results of the PopulationCensus of 1998 were still unavailable at the time of the writing of this report. The absence of regular andbetter data confines us to work, with due care, with the data available (Annex 1). There is, however, adistinction (if not a choice) here which needs to be made. In view of the weight of empirical evidence thatdoes (or does not) exist, there are two courses open for further investigation. The first is to accept thetrends from large-scale data as a starting point and then investigate the issues and problems this datathrows up at the disaggregated level, in order to qualify the existing trends – both sectorally and withrespect to special categories/groups of labour that require focus. The second course is to reject the censusand survey data on the grounds that the true labour supply is understated1 and proceed with analysessupported by the micro evidence that can be marshalled, without regard for the larger picture.

The view taken in this report is that there is a need for greater caution in rejecting the burden of numeroussurveys, irregular and imperfect as they may be and even if they yield apparent inconsistencies in theirresults, as surveys anywhere are apt to do. The size of the information that does exist in Pakistan issubstantial. In order to judge the validity of anomalies in the larger data sets, what is ideally needed is aspecific survey, of equal or greater coverage, which provides empirical proof of the alleged bias inprevious census and survey data. There is both an absence and a critical need for information on labourmarket indicators in Pakistan. Given the lack of a perfect series or a second-best one, we will work withwhat is available, using annual data from labour force surveys. These are subject to much fluctuation,suggesting a weakness in data source. Our emphasis is therefore more on trends than on explaining annualfluctuations, where they seem inexplicable.

The earliest and, probably, still the more reliable data on population and labour force are provided by thepopulation censuses of 1951, 1961, 1972, and 19812 (See tables A1.1, A1.2 and A1.3). In lieu of the muchdelayed census for 1991, we have used population and labour force data from the Demographic Survey of1991 and the annual labour force surveys carried out since. These are used to assess the employmentsituation, especially after 1981 (Table A1.2).3

4 This is subject to confirmation by the impending Population Census.

5 Average growth of population for the 1970s (1970-80) was 3.14 per cent; for the 1980s (1981-1990) it was 3.10 percent and for the 1990s (1992-1996) it has been estimated at 2.98 per cent. Labour force growth for the same periods has been3.31 per cent; 2.42 per cent and 2.4 per cent. The last-mentioned is the case only if we exclude 1990-91(which is thedefinitional change year). Strictly speaking, it is not legitimate to compare trends before and after 1990-91. The 1970s to 1980strend shows a decline in labour force growth, which is likely to have continued.

6 The 1990-91 Labour Force Survey changed some definitions in such a way that (a) activity rates of womenincreased by inclusion of some homeworkers as part of the labour force; (b) total labour force increased; and (c) unemploymentrates increased. This essentially makes the comparison of pre- and post-1990-91 LFSs difficult.

8

Figure 1.1: Growth of Population, Labour Force and Employment

-4 .00

-2 .00

-

2.00

4.00

6.00

8.00

Years

%

Grth(Pop) Grth(LF) Grth(Emp)

2. GROWTH OF POPULATION AND LABOUR FORCE

The labour force (around 37 million in 1997) is not a very large proportion of the population (135 millionin 1997) in Pakistan. Its is estimated to be around 28-29 per cent. Population growth had been increasingover the years, up to and including 1970s. Although the last census was carried out in 1980, projectionson the population growth rate suggest that it is likely to have fallen and has probably stabilized now tojust under 3 per cent4.

Labour force growth rates on the other hand were higher than that of population in 1970s (figure 1.1 andTable A1.1) but have been generally lower after the 1970s. Although the labour force survey figures forthe 1990s can also be interpreted to suggest a decline in labour force growth on trend5, there are problemsin comparing the labour force trends before and after 1990-916. There is however a clear decline betweenthe two definitionaly comparable periods of the 1970s and 1980s.

This means that labour force growth, which is significantly lower than population growth, is likely to befalling while the growth of population is likely to be stabilizing.

7 Pakistan uses the “labour force” approach, to measure employment, unemployment and underemployment. Thisapproach uses hours of work as the criterion and aims basically at measuring labour utilization. The definitions used in therecently conducted surveys are given above. The differences in the old (1987-88 and prior) and new (1990-91) concepts maybe seen in Annex 1.

9

F ig ure 1 .2 : P o p ulatio n , L a b o u r F o r c e a n d E m p l o y m e n t

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

1 4 0

1 6 0

P o p ulatio n Lab . F o r . E m p lo y e d L a b o u r f o r c e

If serious data problems are excluded as a cause, then one of the main reasons for falling labour forcegrowth rates is reflected in the decline in participation rates due to withdrawal of sections of persons ofworking age from the labour force. Educational enrolments for an increasingly younger population ofworking age mean that the labour force growth will begin to rise in the near future. This has implicationsfor trends on unemployment and underemployment in the present situation. These are likely to be magnifiedwith an increase the growth rate of the labour force in the future.

3. LABOUR FORCE AND EMPLOYMENT

Definitions of labour utilization

The “economically active population” comprises persons of either sex who furnish the supply of labourfor the production of goods and services, during a specified time reference period. But not all these personsare currently active (or in the labour force) at any particular point of time. In Pakistan, the currently activepopulation or labour force comprises of all persons ten years of age and over who fulfil the requirementsfor inclusion among employed or unemployed, defined as follows, during the reference period i.e. one weekpreceding the date of interview.7

• The “employed” comprise all persons ten years of age and over who worked at least one hourduring the reference period, and were either “paid employed” or “self-employed”. (Persons holdingpermanent jobs, who for any reason had not worked during the reference period are treated asemployed).

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• The “unemployed” comprise all persons ten years of age and over who during the reference periodwere:

– “Without work,” i.e. were not in paid employment or self-employment;

– “Currently available for work,” i.e. were available for paid employment or self-employment; and

– “Seeking work,” i.e. had taken specific steps in a specified recent period to seek paidemployment or self-employment.

• The underemployed comprise all employed persons who during the reference period were workingless than the “normal” duration on an involuntary basis and were seeking or were available foradditional work. In Pakistan, the underemployment rate is estimated as a ratio of the employed(who worked less than 35 hours a week) to total labour force. With the help of the available data,we analyze below the latest employment, unemployment and under-employment situation inPakistan.

The self-employed amongst the employed

Employment is divided into two categories in Pakistan: the self-employed and the hired. The self-employedare only marginally less in number than the hired within the labour force. During 1983-95, the self-employed, on an average, constituted 44 per cent of the employed work force: 46 per cent in the rural areasand 37 per cent in the urban areas. The percentage of the self-employed increased from 40.3 in 1982-83to 47.9 in 1987-88 but was at 42.3 in 1994-95. This percentage increased in the rural areas and declinedin urban areas during the period 1982-83 and 1994-95 (table A10).

In 1987-88, the agricultural sector accounted for 53.6 per cent of the self-employed, followed by trade(16.8 percent) and manufacturing (10.9 percent). In the rural areas, agriculture accounted for 66.6 per centof the self-employed followed by 9.8 per cent in trade. In the urban areas, the wholesale and retail tradesector accounted for the major share of 41.8 per cent (Table A1.11).

Another distinct feature of the self-employed is that compared to the national average, the share of self-employed who worked full time was higher (except for women in rural areas). Moreover, the level ofeducation of the self-employed was also lower than the national average (Table A1.12).

The self-employed are sizeable, significantly agrarian, work long hours and are relatively less literate thantheir counterparts in employment. It is important to bear in mind that self-employment in Pakistan ispredominantly in agriculture and more symptomatic of poverty than prosperity.

Underemployment

The underemployment rate is estimated as a ratio of employed who worked less than 35 hours a week tothe total labour force (Table A1.13). There were nearly 4 million persons underemployed in Pakistan in1994-95.

The proportion of employed persons who worked for less than 35 hours, which had declined from 14 percent of the employed work force in 1982-83 to 11.1 per cent in 1987-88, was at 12.2 per cent in 1994-95.Underemployment was much more prevalent in rural than in urban areas. In 1987-88, it was 2.8 times thatof urban areas. In 1993-94 it was almost double. Unpaid family helpers constituted about half of theunderemployed, followed by the self-employed. This is true in the aggregate as well as in the rural areas.Underemployment among employers was almost negligible.

8 This is also true for female participation rates as we shall see below.

9 There is slight decline between the 1970s and 1980s and no pattern after in the 1990s. Comparisons with the 1990sare, however, suspect for this category.

11

Within rural areas the share of underemployed declined from 16.3 per cent in 1982-83 to 13.4 per cent in1987-88, but was at 14 per cent in 1994-95. In contrast, the share of underemployed in urban areasdeclined from 7 per cent in 1982-83 to 4.8 per cent in 1987-88, but was at 7.1 per cent in 1994-95(Table A1.14).

It is also interesting note that in the 1993-94 LFS (when this question was asked) a four-fifths majority ofthose who were underemployed, considered their working hours as “normal”. This implies a “normality”of being permanently underemployed, in an “enclave” of the labour market where most of theunderemployed are not so out of choice (only 2.6 per cent in this group describe their underemploymentas voluntary) and where the severity of underemployment is unlikely to decrease.

Unemployment

In a developing economy characterized by significant poverty, minimal social insurance and welfaremechanisms, unemployment is probably the least appropriate indicator of labour market conditions. Mostpeople of working age, who are not in full-time education, need to work to survive. With this proviso inmind, we will examine unemployment data.

First, it is necessary to clarify a definitional problem. Before 1990-91, the LFS recorded those persons asunemployed who were without work (i.e. were not in paid employment or self-employment) and were bothcurrently available and seeking work during the reference period of one week. Those who may have beenavailable for work but for some reason were not seeking it (i.e. not taken specific steps to seek paid or self-employment) were not recorded as unemployed. The unemployment rates prior to this period weretherefore recorded at a low figure of about 3 per cent. From 1990-91 onwards, the condition of beingavailable for work was sufficient to be recorded as unemployed. This resulted in the unemployment ratein 1990-91 jumping to 6.3 from 3.1 per cent in 1989-90 (Table A1. 15) and implies that comparisons onunemployment8 are not legitimate across the year 1990-91.

The number of unemployed persons was two million in 1990-91. This figure was one million in 1989-90and much of the increase occurred because of the change in definition of the term. The overallunemployment rate declined in 1991-92 and 1992-93 but it went up in 1993-94 and remained at the samelevel in 1994-95 and declined again afterwards. There is no real trend which is discernible9. For generalpolicy purposes, it may not be wrong to assume that currently about two million people are unemployedin Pakistan. According to data, 63 per cent are men and 37 per cent women. Of the total unemployed in1994-95, about 60 per cent were in rural areas. However, the unemployment rate (ratio of unemployedpersons 10 years of age and over to labour force) was much higher in urban areas (6.51 per cent in urbanas against 4.22 per cent in rural areas). Available figures for 1984-85 to 1987-88 show that the severityof unemployment as judged by its duration as well as the percentage of unemployed with previousexperience has been increasing (Table A1.16).

10 See Annex 1: Labour and Employment Statistics

11 Employment levels are generally close to those of the labour force and both have increased steadily over the years.However, growth rates of employment have both been lower as well as higher than that of the labour force in the past. Thereis some pattern. Up to the mid-1970s employment growth rates were higher than labour force growth; from the mid-1970s tothe early 1980s they were lower. In the mid-1980s they were higher again and since the late 1980s they have remained lowerfor most years.

12 The 1990-91 Labour Force Survey changed definitions in such a way that unemployment rates as well as femaleparticipation rates increased.

13 The education-based withdrawals are likely to swell the labour force with a time lag.

12

Unemployment rates are higher both for older and younger workers. Whereas the high unemployment ratesfor the 10-14 age group may be attributed to restrictions on (child) labour below the age of 14, the highrates in the 60 plus age group is explained by the non-availability of jobs suiting older workers.10 Withinthe unemployed, the share of literates has increased on trend from 42.8 per cent to 48.8 per cent(Table A1.17).

At the aggregate level the unemployment rate has averaged around 5.0 per cent a year during 1990-91 to1994-95. Of two million unemployed in Pakistan, nearly half of them are literate and the severity of theirunemployment is likely to be increasing.

Employment and labour force: An overview

Employment growth rates generally increased in the 1970s, and from the end of the 1970s declined on trendtill the late 1980s. In the 1990s, although it is difficult to make a comparative statement, employmentgrowth is falling on trend.11 The variability in growth rates is partly explained by definitional changes.12

In sum:

• the gap between the number of persons in the labour force (employed or otherwise) and thepopulation is likely to widen for a little longer before it starts closing;13

• the size of the underemployed is around 4 million (12 per cent underemployment rate) and is likelyto have been increasing in recent years; and

• close as they are in levels compared to the population, the gap between the labour force and theemployed within it as a proportion of the labour force, is wider now it was during the 1970s andsuggests a persisting unemployment problem.

Given that labour force growth is expected to increase in the future, those employment-related problemsthat exist now, under falling labour force growth conditions, are likely to worsen.

We now make some further observations on the data available.

4. CHANGING TRENDS IN THE RURAL-URBAN DISTRIBUTION OF LABOUR FORCE

In absolute numbers, the labour force in Pakistan has increased from 18.1 million to 35.2 million between1972 and 1995 (Table A1.3). The male labour force has increased from 16.7 million to 30.5 million andthe female labour force from 1.4 million to 4.7 million. Compared to an average annual increase of 2.7 per

14 For the period 1991-92 to 1996-97 (estimated), the rate of growth of the overall labour force is 2.42 per cent; itis 2.96 per cent for the rural labour force and 1.08 for the urban labour force.

15 Differences in urban and rural LF growth can be attributed to the net effects of rural-to-urban and urban-to-overseas migration and reverse flows, none of which are precisely known.

16 The crude activity rate, also called the crude labour force participation rate (LFPR), is defined as the ratio oflabour force to the population. The participation rate of the labour force was around 27.5 per cent in 1994-95. This is not onlyextremely low but has been declining on trend (Table A1.4).

17 The 1990-91 LFS improved the activity rates for women due to definitional changes.

13

cent in the total labour force between 1972-95, the urban labour force increased by 3.5 per cent per year,while the rural labour force increased by 2.5 per cent per year in the same period. As a result, the share ofthe urban labour force in the total labour force increased from 23.3 per cent in 1971-72 to 27.3 per centin 1994-95. This difference in growth rates was largely the result of rural-urban migration. The growthof the rural labour force in the late 1970s and the first half of the 1980s was also affected (restricted) byemigration, which is much less important today.

Traditionally, and certainly since 1975 onwards the growth of the urban labour force has been faster thanthat of the rural labour force. This was to be expected. However, the reversal of trends in growth rates inthe 1990s (rural labour force growth rates being higher than urban ones)14 suggest that, if no serious dataproblem exists, there may be an emerging barrier on internal rural urban migration15 (Table A1.3). Thisissue has implications for the size of the labour force in the rural areas, particularly in agriculture, andneeds to be explored.

5. WHY ARE LABOUR FORCE PARTICIPATION RATES (LFPRS) LOW?

The size of the labour force is determined by the size of the working-age population and its activity orparticipation rates16, adjusted for migration into and out of the country. This population has already beenborn; the demographic changes which occur today will affect labour supply with a time lag of about 10years. The “activity rate” is therefore the key determinant of the currently active population or laboursupply.

We need to explain why the participation rates of labour force are declining in Pakistan. The LFPR peakedto 31 per cent in 1978-79 and declined to 27.5 per cent in 1994-95. The falling labour force participationrate has clearly restrained the growth of the domestic labour force (Table A1.4).17 It is worth noting thatrural participation rates are generally higher than urban ones, another reason why when labour forcegrowth declines it does so less in rural areas. This is also reflected in the fact that while the rates of maleparticipation in the labour force do not vary so much across the rural and urban divide, and they do soless over time, the gap between rural and urban participation rates for women is significant and persistsover time. The greater participation in rural areas is due to a greater inclusion of women in what constitutesthe labour force, in spite of the reporting biases on women's household activities in both rural and urbanareas. This feature comes into sharp relief when we consider the size of the excluded labour force inPakistan.

We discuss below three tendencies for changes in the LFPRs in Pakistan whose net impact is clearly adecline. These pertain to education, emigration and gender.

18 This fact has implications for the incidence of child labour. We should expect it decline (Annex 2).

19 Non-inclusion of housewives (home-makers) as well as other categories of persons such as rentiers, thievesbeggars, smugglers, prostitutes, etc., in the labour force has been a matter of debate for a long time. Until the definition ofthe term <labour force’ is changed, we have restricted to the bias of the official figures of the labour force. The non-inclusionsare often for ideological or moral reasons.

20 The figures are telling that after accounting for students enrolled in government institutions, about 32.8 millionpersons, comprising 2.7 million men and 30.1 million women, were not in the labour force.

14

Education and the labour force High population growth in Pakistan has also been associated with an increasing proportion of populationin the lowest age cohorts (Table A1.5). The proportion of population in the 0-14 years age group increasedfrom 44.5 per cent in 1981 to 45.8 per cent in 1988 and to 46.3 per cent in 1995, thus raising dependencyratios and depressing labour force participation rates. In part, age compositions do explain why the overallparticipation rates are low. The 10-14 years age group show a decline in participation rates, suggesting awithdrawal of the young (who are counted as economically active) from the labour force, possibly due toincreased school attendance.18 The decline in participation rates, in the 15-19 years age group may besimilarly attributed to increasing college enrolment.

Emigration and the labour force

Increasing emigration from the mid-1970s to the mid-1980s had constrained growth in domestic labour.According to the report of the National Manpower Commission (Government of Pakistan, 1989, p. 101),during 1978-83, almost 25 per cent of the incremental labour force found employment abroad. This helpedin sustaining employment growth at 2.8 per cent. However, return migration in 1982-87 dominated thestream of migration and may have played some part in accentuating pressures on the domestic employmentsituation (Table A1.6). For the more recent sub-period there is evidence of net out-migration. The netoutflow in 1993-95 period is, however, a much lower percentage of the labour force, in comparison withthe past peak of the 1980s. The size of the labour force today is not subject to pressures return migrationand is unlikely to be seriously constrained by out-migration.

Gender and the labour force

This is an area which requires serious analytical and empirical disentangling.

Due to the way the term ‘labour force’ is defined, a number of persons, particularly women engaged inhousehold duties, are not included in the term ‘population currently active’ or labour force (table A7). Thisreduces the number of labour force as well as the participation rate, a shortcoming that was partly madeup for in Pakistan by adopting a new definition in the 1990-91 LFS, in which women were identified asemployed if they spent time on any of the 14 specified agricultural and non-agricultural activities definedin the Intentional Standard Industrial Classification, (ISIC).19 This partly redresses the definitional bias.However, it is interesting to note that in 1994-95 about 59 per cent of the economically active populationwere excluded from the labour force. Of these, about 27 per cent were men and 73 per cent were women.Clearly, the bulk of the ‘excluded labour force’ are women.20

An obvious reason for this in Pakistan is that social perceptions restrict the ‘admission’ of the existenceof female work, by a not too insignificant section of the population. This implies a reporting bias due to

21 See Sathar and Kazi (1997).

22 Shah and Sathar (1978).

23 Within the literate labour force, pre-matriculates in 1994-95 accounted for a major share (57 per cent) followedby matriculates (23 per cent) and those with intermediate degrees (9 per cent). Graduates accounted for about 9 percent of theliterate labour force. Within graduates, about 90 percent hold degrees in subjects other than engineering, medicine andagriculture. Engineering graduates were 12.3 percent; medical, 4.5 percent; and agricultural graduates, 1.2 percent.

24 The composition of employed work force by sectors shows wide variations. According to the latest LFS (1994-95), about 74 per cent of the employed labour force in the agriculture sector was illiterate as against 7.8 per cent in finance,insurance and business services, and 17.1 per cent in the electricity and gas distribution sectors. Next to agriculture, theilliterate accounted for 69.4 per cent in construction and 58.3 per cent in mining sectors. Within the literate, the most highlyqualified persons were found in finance, services and electricity and gas sectors.

25 The declining share of medical graduates is not easily explained. Perhaps they are included in the “postgraduate”group, which has registered a growth of about 13.3 per cent per annum.

15

which female participation rates and employment can be seriously under-reported. Secondly, in Pakistan,much of the employment data, irrespective of its source, is collected by male investigators interviewing malerespondents.21 Apart from the degree of authenticity of responses, variations in reported employment may alsoresult from variations in the education, training or supervision of investigators; the periods chosen for the survey;and the language used in the questionnaire.22 These elements vary from survey to survey and can lead to seriousinconsistencies in the published data.

The definitional changes in LFSs in 1990-91 (apart from increasing the proportion of unemployed in the labourforce) improved women’s participation rates in general. This may be more an effect of a categorical change andless of an actual improvement in women participation rates, which are still very low. This low rate accounts forthe low overall level of participation of the labour force shows up as a trend decline in participation rates and thelabour force growth over the years. For the 1990s the improvement in coverage of working women is offset bythe withdrawal of the young from the labour force.

6. ON THE CHANGING ABILITIES OF THE LABOUR FORCE

The composition of labour force by level of education has witnessed changes in Pakistan (Table A1.8). With theimprovement in the literacy rate, the proportion of the literate labour force has increased from 39.9 per cent in1990-91 to 43.6 per cent in 1994-95. While the share of literate men in the labour force increased from 37.3 percent to 40.1 percent, that of women increased only marginally from 2.57 per cent to 2.67 per cent.23 Clearly, ifone criterion for employability is literacy, then an explanation of low participation rates of women is low literacy,which needs to be a policy focus.

The literacy rate of the labour force has risen from 35.3 per cent in 1987-88 to 43.2 per cent in 1994-95. Overthis period, the share of degree holders has shown the sharpest rise (from 1.8 per cent to 2.9 per cent), followedby that of matriculates (from 9.4 per cent to 13.2 per cent). The composition of employed work force by the levelof education has also undergone significant changes (Table A1.9).24

Within the literate labour force, employment growth rates have been positive for all levels of educationexcept for the holders of degrees in medicine and those with no formal education25. The proportion ofliterates in the labour force is also increasing albeit slowly.

16

Although literacy is increasing 56 per cent of the labour force are still illiterate and about another 10 per centliterate only at pre-matriculate levels or with no formal education. Efforts to introduce new technologies andmanagement techniques in the short-run, essential for the improvement of productivity and efficiency, are likelyto be constrained.

Labour force expectations and the structure of the job market

Although it may be true that economic growth itself is fundamental as a final adjuster of the labour market in themedium run, it is also arguable that, at least in part, mechanisms of adjustment depend upon the perceptions ofthose who bear the burden of adjustment in the labour market, namely the unemployed and the underemployed.

A question was put in the LFS of 1993-94 to those who were not working in the reference week regarding workexpectations. These expectations are indicative of a mismatch with prevailing sectoral, as well as locational,conditions of employment. This is an interesting finding, which needs some elaboration. In the LFS of 1993-94,nearly two-thirds of the unemployed expressed the wish for employment with government, a proportion which,if realized, would be more than twice the current governmental share in employment. Nearly one-fourth of theunemployed preferred clerical and related jobs. This is mainly the response of the matriculates andintermediates. On the other hand, only 1 per cent of the unemployed said that they would like to work in theagricultural sector while nearly half of Pakistan’s employed are still in the occupational category ofagriculturalists and forestry workers. Occupational preferences of the unemployed do partly reflect theireducational background, but the dissonance which is being reflected here is really between the development ofan educational system and the production structure and needs of the economy.

Orientating a future labour force (which will increase in growth and literacy) towards the types of activities thefuture holds should be an essential part of the training and skilling efforts being made today. This is an importantchallenge for the future of both the labour force and the country.

7. UPSHOT

Pakistan had a population of around 128.3 million in 1994-95 of whom 85.4 million were above the age of 10.The labour force size is 35.2 million (29.3 employed; 4.0 underemployed and 2 unemployed). Those who wereoutside the labour force, excluding students (17.4 million) were around 32.8 million, 30.1 million of whom werewomen. The growth of the labour force has been lower than that of population on trend in the past. Urban labourforces have also been growing faster than rural ones due to rural-urban migration, although there are someindicators in the 1990s that internal migration may be halting and trends could be reversing.

The rate of growth of the labour force in Pakistan has been falling in the past but it is expected to rise in the nearfuture. Unemployment and underemployment trends suggest a worsening or certainly no improvement in therecent past. This means that the problems associated with those who are not fully employed is likely to increasewhen labour force growth picks up. The labour force is also slowly becoming more literate in Pakistan.

Apart from the matters pertaining to restrictions in the growth of population, there are three areas which requirefocusing from an employment perspective. These relate to data, participation rates and training.

Data

The coverage of the LFS must improve. This is with respect to the excluded sections of the adult population,which are dominated by women. Moreover, definitions need to further improve to include home workers, as wellas other categories of persons who may be excluded for non-technical reasons. The Population Census must be

17

conducted without delay. It is the fundamental basis of any serious policy work, quite apart from being anecessary cross-check on the Labour Force Surveys. A country the size of Pakistan cannot afford to avoid aPopulation Census for seventeen years, no matter what the domestic political fall out of this may be. Consistencyexercises must continue to be in built into data collection, as was the case in the 1990-91, whenever definitionalchanges take place, so that trends can be readjusted. A consistent series of best-possible estimates of all labourmarket indicators in Pakistan needs to be built, which adjusts and reconciles the data available from differentsources.

Participation Rates

Clearly, participation rates have been very low and declining in Pakistan. These need to be improved for theproductive absorption of the labour force in the economy. The issue of female participation rates is a subset ofthe general issue. The reason for the increase in the low participation rates for women is not necessarily onlybecause more women are working but because definitions have improved. The causes for the low participationrates as well as high incidence of women in those excluded from the labour force need to be ascertained carefully.The extent to which this is due to social factors, definitional problems, or coverage need to be distinguishedempirically. On a general plane, the low participation rates needs to be improved to effect a more productive useof labour in the economy.

Training and skills

There must be a conscious attempt made to bring the expectations of the literate labour force which is either notin employment or likely to come into the labour force in the future, into line with actual possibilities in the jobmarket. This should be done both at an educational level as well as at the level of training programmes.

Implications for a strategy

From the perspective of a strategy, two issues are important:

• the labour force growth is expected to increase in the future;

• problems associated with those who are less than fully employed, are likely to worsen with the expectedrise in labour force growth.

1 On their criteria of “basket of basic needs”, (Gazdar et al. 1994) find a very drastic decline (18.7 per cent) inpoverty in Pakistan between 1984-85 and 1987-88, which is clearly a period when employment growth outstripped labour forcegrowth. Their estimates for 1990-91 show a much smaller decline (9.1 per cent), which was a period in which labour forcegrowth was generally matched by employment growth. Poverty gap measures like the ‘poverty gap’ (PG) and ‘Forster-Greer-Thorbecke’ (FGT) Index, which take into account the average income of the poor and its distance to the poverty line confirmthis observation more conclusively. From 1984-85 to 1987-88 to 1990-91 the PG declined from .111 to .077 to .071, while theFGT declined from .038 to .023 to .022 (Table A2.8).

2 ILO-SAAT, Arshad Zaman Associates, 1997 (mimeo).

18

CHAPTER TWOOutput Employment and Productivity:Lessons for an Employment Strategy

1. A DUAL FOCUS

The magnitude of the employment problem facing Pakistan in the future is considerable. Even if the rateof growth of the labour force is likely to pick up in the near future, the deteriorating employment situationis likely to worsen more than present trends anticipate.

There are two related matters for concern: the gap between population and the labour force and a risinglabour force in comparison to the “fully employed” within it. An increasing gap between population andlabour force growth for a given output implies the increasing dependency of a rapidly growing part of thepopulation on a slowly rising labour force. Under these same conditions, the increase in the gap betweenthe fully employed and the labour force implies constraints on the earning capacity of the labour forceitself. This has direct and demonstrable implications for poverty.1

One goal of a future employment strategy is therefore to reduce the growth of population. The other, andwhat we are concerned with in this report, is to productively increase the participation of the labour forcein the economy. In doing so, the aim is to improve aggregate employment and attack the twin problems ofunemployment and underemployment head on. The next sections take a more detailed view of theemployment situation.

2. EXAMINING SHARES OF EMPLOYMENT AND OUTPUT

Given the critical situation described above, employment strategies need to be devised in order to face theemployment challenge. The absorption of a larger percentage of population in gainful work, as well as thereduction of the under employed and unemployed, are important goals.

It would, however, be hazardous to proceed as if all that needs doing is to direct efforts towards anexpansion of sectors with higher employment elasticities and wait for employment to happen. Theprecarious nature of estimating elasticities of employment in Pakistan has been discussed elsewhere2. Forthe purposes of the present analysis, our position is that elasticity estimates, though useful in thegeneration of ball-park projections, are on their own, insufficient for planning an employment strategy.Moreover, the estimates tend to become more inconclusive the better the methodology used. Elasticitieshave generally been low in Pakistan and they have been lower in the high growth period of the 1980s

3 They have increased in the 1990s compared to the 1980s.

19

than they were in the relatively lower growth periods of the 1970s and 1990s 3. The increasing trend inemployment elasticities are however, is not a simple index of ascertaining the “labour absorptioncapacity”of an economy. We need to look at other indicators implicit in the elasticity measure, in order tomake some judgements on the quality of the labour absorption which the elasticity measure signifies.

Although sector-specific analyses are necessary for producing the details of an employment strategy thatcan lead to concrete policies, an aggregative analysis of the sort attempted in this chapter can still providea plausible a sectoral prioritization within an economy-wide framework. The following sections examinethe sectoral trends in employment in Pakistan before proceeding to study the indicators of employmentimplicit in an elasticity measure: growth in output, employment and labour productivity.

3. SECTORAL SHARES OF EMPLOYMENT AND OUTPUT

As far as sectoral distribution of output shares are concerned, in the long run agriculture’s share declinedfrom 39 per cent in 1971 to 24.3 per cent in 1997 (Table A2.2). GDP shares of manufacturing haveincreased on trend; they were 14.16 per cent in 1971 and 17.92 per cent in 1997. There are small increasesin other sectors’ GDP shares. The decline has essentially been for agriculture and the gain for most ofthe other major sectors. This is to be expected in the process of development.

Sectoral shifts have also taken place in employment shares over time. Once again for agriculture there hasbeen a long-run trend decline but from the mid-1980s the share has been fluctuating between the 45 percent and 55 per cent mark (Table A2.3). It can be argued that although the share of employment hasdeclined for agriculture, over the longer-run period, it has been fluctuating within a range in the last decade.On the other hand, contrary to expectation, there has been a declining trend in the share of manufacturingin employment from 1969-70 (15.57 per cent) to 1993-94 (10.12 per cent), although employment shareson average rose slightly from the 1970s to the 1980s and then declined in the 1990s. All other sectors whichinclude construction, trade and the “other” activities category over a longer-run period, from say 1970-71to 1994-95, have shown an increase in employment shares. It is therefore quite reasonable to argue thataccompanying the longer run decline in employment in agriculture, say from 1969-70 onwards, there havebeen increases in employment shares of sectors other than manufacturing.

In the recent and shorter-run period of the 1990s, however, agriculture’s fluctuating share of employmentforms no trend (except that it breaks from the past trend of a declining share of employment), while theshare of manufacturing (and mining) in employment has definitely fallen from 12.54 per cent in 1990-91to 10.12 per cent in 1993-94.

4. GROWTH OF EMPLOYMENT AND OUTPUT

Although we need to be aware of the standard limitations of the elasticity measure, it is still worthexamining the trend in employment elasticities, and of output and employment growth for the economy asa whole over the years. This in conjunction with other measures can help identify general trends. Figure2.1 below splits the employment elasticity measure into its two components: employment growth and outputgrowth.

3 The answer as to why GDP growth has declined from the 1980s to the 1990s is complex and requires both a sectorspecific view as well as analysis of macroeconomic policies.

4 The net change in any year is the difference between the positive change and the negative change.

20

Figure 2.1: Growth of Real GDP & Employment, andthe Output-Elasticity of Employment, 1971-72 to 1996-97

- 4 . 0 0

- 2 . 0 0

-

2 .00

4 .00

6 .00

8 .00

Fiscal Years Ending June 30

Gro

wth

Rat

e (%

)

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

Ela

stic

ity

GDP Employment Elasticity

The economy-wide picture shows a few features clearly.

• GDP growth rates were low in the 1970s, highest in the 1980s and have fallen in the 1990s again.Excluding the past couple of years, they are nevertheless reasonable growth rates.

• In relation to GDP growth, employment growth has been low in Pakistan’s economy. In the early1970s employment growth hit a sustained high level. During the high growth period of the 1980s,employment growth was very low and since the mid-1980s it has been much more variable.

• The elasticities of employment have generally followed employment growth, confirming the viewthat output growth has been the relatively more stable part of the employment elasticity measurein Pakistan.

This leaves the matter of the recent volatility in employment growth, which appears seems to be a newstructural feature in the Pakistan economy, as an issue that needs to be explained. Examining sectoralemployment changes over time delineates the sources of this volatility.

5. SECTORAL EMPLOYMENT ABSORPTION

One question that needs answering in an economy-wide context is: why has the structure of employmentgrowth become so volatile?3 As a first step, this requires one to explore sectoral trends in employment inmore detail. The Figure below presents data on annual changes in the number of persons employed bysectors.4

5 Especially the significant falls in employment in agriculture in 1990-91 (when there were major floods) and 1994-95, lesser declines including in “other” sectors in six other years, and the sharp rise in 1986-87, which requires furtherinvestigation.

21

Figure 2.2. Changes in Employment (000) 1971-96

- 2 . 5 0

- 2 . 0 0

- 1 . 5 0

- 1 . 0 0

- 0 . 5 0

-

0 . 5 0

1 . 0 0

1 . 5 0

2 . 0 0

70-71

71-72

72-73

73-74

74-75

75-76

76-77

77-78

78-79

79-80

80-81

81-82

82-83

83-84

84-85

85-86

86-87

87-88

88-89

89-90

90-91

91-92

92-93

93-94

94-95

95-96

Agriculture Mining & Manufacturing

Construction Trade

Others Elec.Gas& Trans.

Although the data presented are not free of problems,5 they do show that:

1. Three kinds of trends are discernible: first, a period of high and rising labour absorption in theearly 1970s (until 1978-79); second, a period of stable job creation (about 500,000 jobs per year)from 1979-80 to 1984-85; third, an unstable trend in labour absorption since then, which reacheda high in the 1991-92 period and seems to be on a cyclical downward trend.

2. Employment in general has definitely become more volatile since the mid-1980s and agricultureto account for the largest share of changes in employment (positive and negative). Volatility inemployment is thus partly connected to the agricultural sector.

3. Unlike the early years (the 1970s), manufacturing has not played a major role in labor absorption,although it has contributed both positively and negatively in specific years (especially 1986-87,1987-88, and 1992-93). This means that manufacturing is also a contributor to the volatility inemployment.

4. In recent years (especially since the late 1980s) the wholesale and retail trade sector tends to playa large role in employment creation. This also true for the residually defined “others” category. Alarge part of these sectors are likely to be in the SSE (Small-Scale Enterprise) sector.

6 The following is a symbolic decomposition of Output change in to: (i) employment effects, (ii) productivity effects,and (iii) multiple (of employment and productivity ) effects. The basic symbols are:Output = Y; Employment = N; Productivity= P; Intitial time period = to ; Change over time = M .P= Y'N N= Y'PY= P @ N Then, Change in Output is:M Y = M P @ Nto % M N @ Pto % M N@ M PDividing by M Y M P @ Nto'M Y % M N @ Pto 'M Y % M N@ M P'M Y = 1The Change in Output decomposes in to:(i) An employment effect=M N @ Pto 'M Y (ii)A productivity effect=M P @ Nto'M Y(iii)A multiple effect = M N@ M P'M Y

7 For a recent review see Amjad and Kemal, 1997, (mimeo) ILO-SAAT.

22

6. DECOMPOSING OUTPUT GROWTH

The employment swings discussed above and the trends in elasticity observed are consistent with thedecomposition of output growth presented for the 1970s, 1980s and 1990s decades in Table 2.1 below.Output growth decomposes into two contributing components: employment expansion and labourproductivity and accordingly periodizes the Pakistan economy since the 1970s.6

Table 2.1: Decomposing output growth, productivity and employment effects

MM P @@ Nto'M'M YProductivity

Effect

MM N @@ Pto 'M'M Y Employment

Effect

MM N @@ MM P'M'M Y Multiple Effect

1969/70 – 1980/81 0.292 0.615 0.118

1980/81-1990/92 0.578 0.273 0.148

1991/92 – 1994/95 0.400 0.571 0.028

Source: National Income Accounts and Labour Force Survey (various years).

The employment effect was strongest in the 1970s after which there was productivity- led growth in the1980s. The high growth period (1980s) was least driven by employment expansion as a contributor. In the1990s, there was a shift back towards a growth process which is partly based on increasing employment.Given that the 1990s are a relatively lower growth period, we need to probe further into the nature of thisemployment expansion. In the section following we examine the employment conditions whichcharactercized the changes, as reflected in wages and poverty.

7. WAGES AND POVERTY

Where organized labour is not the largest part of the hired labour force7, and where a multiplicity ofcontractual arrangements exist, it is important to analyse not only real wages over time but poverty as well.Unfortunately, the database on wages is limited in Pakistan and poverty assessments not only differ inmethodology but are also constrained by data sources that are not current. The importance of wages and poverty indicators necessitates an attempt at their assessment. We start by discussing wage rates(Table A2.10).

8 An indication of this can be gauged from the distribution of job by the organization. In 1993-94 LFS 9.5 per centof the employed were the `formal’ employment, the rest were in semi-formal (22.9 per cent), agriculture (47.8 per cent) andinformal (19.8 per cent) employed. It is also the case that in 1993-94 only 33 per cent of the employed were categorized as`employees’. If we add the semi-formal and informal employed nearly 43 per cent are likely to be “unorganized” workers. Thisis the lower-bound since the bulk of hired workers in agriculture are also likely to be of the casual variety, and therefore a partof the unorganized labour force.

23

2.3 a: Real Wage Index- Industrial and Skilled

0

50

100

150

200

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

Industry M asons

Real Wages

Wages rates are clearly more relevant to that part of the labour force which is hired, a figure previouslymentioned as not much more than half of the employed labour force. About 56 per cent of the employedlabour force is hired., the rest are self-employed. It is, however, not inconceivable that the poorer sectionsof the self-employed in Pakistan (particularly in agriculture) also offer themselves on the labour market aspart-time casual workers. 8

The percentage of hired labour which is permanent relative to those on casual contracts is likely to besmall. Much of this organized labour force is either in salaried government jobs or in the organized privatesector of the economy. A smaller proportion is likely to be in the organized industrial workforce.Consequently, the dominant form of hired labour in Pakistan, in an economy-wide sense, is casual workers,some who offer themselves on casual wages throughout the year, others who do casual work only as a part-time activity.

There are three wage rates available for the agricultural sector from the 1980s. One for each season (Rabiand Kharif), and a general casual wage rate. It can be argued that the dominant type of casual labour usedin agriculture is season-specific and not of a general variety, the latter usually representing the casuallabour available in rural areas. The wage rates for two seasons (Rabi and Kharif) in agriculture show anincrease up to the end of 1980s and then a decline in the 1990s. The general and non-seasonally specificcasual wage rates in agriculture also suggest an increasing trend till the end of 1980s and have thenfluctuated. It is clear that overall real wage rates in agriculture increased in the 1980s and are witnessinga decline in the 1990s (Figure 2.3a).

Real wages of the organized industrial sector, have increased on trend from the 1970s, although there isno data available for recent years. As suggested earlier, this is likely to be a small proportion of the totalemployed labour force ( not exceeding 10 per cent). The category of skilled workers can be seen in realwages of masons: an increase in real wages in the 1970s, a decline in the early 1980s and an increase ontrend from the late 1980s onwards (Figure 2.3b).

9 The reason is that employment conditions in Pakistan are reflected in the poverty levels of a society which ischaracterized by multiple contractual arrangements (implicit and explicit) and extended family systems.

10 The consumption limit is that of 2250 calories per day. The methodology is from Mujahid (1973) . The samemethodology is used to estimate the series through to the 1990s. The Figure on poverty trends is based on this series. It is aconsistent series.

11 It is true that if a poverty trend is fitted over the longer term then poverty will appear to be declining on trend.This however is not legitimate, there seems to be some change coming about in the late 1980s. This argument is sometimesused in order to imply a correspondence between economic reforms and poverty alleviation and is not legitimate.

24

Figure 2.3 b: Real Wage Index - Seasonal Agricultulture

0

20

40

60

80

100

120

140

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

Rabi(ag) Kharif(ag)

The real wage index of unskilled labourers is based on data of casual workers in construction. It can betaken as a proxy for non-agricultural urban casual workers, which are likely to dominate the urban small-scale and informal enterprise sector. This also shows a trend increase in the 1970s, and then a decline tillthe mid-1980s, which increases briefly during the late 1980s and then shows a slow decline through the1990s. The pattern is clearer for real wages of unskilled casual labour an increase in the 1970s and adecline in the 1990s (Figure 2.3c).

Poverty Trends

Trends in poverty are difficult to estimate in Pakistan because research is often based on different povertylines and a number of problems also exist with the types of data often available. There is, however, a needto view the trends in poverty in Pakistan, both rural and urban, from an employment perspective.9 Malik(1988) has estimated poverty lines from 1963-64 to 1984-85 on a consistent methodology based on calorienorm.10 Figure 2.4 shows that poverty increased in Pakistan during the 1960s (although urban povertydeclined). It began declining during the 1970s and this decline continued up to the late 1980s. After the late1980s (1987-88) there is every likelihood that poverty increased, at least up to 1990-91, after which it haseither increased or remained the same. The 1990s trend is therefore likely to be one of increase.11 It is truethat the total poverty trend described above is generally reflected in the trends in rural poverty and noturban poverty. Urban poverty has shown significant declines when total poverty has increased (1960s andthe 1990s). Urban poverty may have started declining again in the 1990s, while rural poverty is probablyeither not declining or is increasing. This is of immediate relevance for our impression of wages for theearly 1990s and is quite consistent with the reversal of past urban-rural labour force growth trends in the1990s.

12 One needs to be careful in qualifying this inverse relation. The relevant real wage is important. The correlationbetween real wages ( industrial) which have been increasing over time and poverty which on trend in the longer run isdecreasing can be shown to be reflective of the inverse relation. In fact it is not because industrial wage earners are in aminority in the employed labour force.

25

2.3 c: R eal Wage Index: A g ricultural/R u ral (C asual) Urban Unskilled(C asual)

0

50

100

150

Agr icu l tu re U nski l led Labour

F ig u r e 2 . 4 : P o v e r t y i n P a k i s t a n : H e a d C o u n t s

0

1 0

2 0

3 0

4 0

5 0

6 0

%

Total Rural

Urban 2 per. Mov. Avg. (Rura l)

2 per. Mov. Avg. (Tota l) 2 per. Mov. Avg. (Urban)

Poverty, Wages and Growth

It is also useful to make some qualitative assessments about poverty and wages and growth taken together.

For the 1970s, it is fairly clear that poverty declines in both urban and rural areas were matched by auniversal increase in all types of real wage rates for most of the period. Whereas GDP growth was not sohigh, the growth that took place was driven by employment expansion. It very clearly demonstrates theinverse relation between poverty and real wages.12

In the 1980s, when poverty continued to decline but less fast than it did in the 1970s, we have a mixedpicture of real wages. In this situation we need to make judgements on the weight of activities in the

13 ILO-SAAT/Arshad Zaman Associates, 1997 (mimeo).

26

economy for which the real wage is a proxy. In our view it is the casual wages in agriculture, especiallythe seasonal ones and the urban casual unskilled wage rates which would affect most of those offeringthemselves on the labour market. General agricultural/rural wage rates (which reflect the rural non- farmsector as well) showed an increase until the late 1980s; agricultural (seasonal) wages increased on trendin this period. The wages of the unskilled urban workers declined and increased again. There was anincrease in skilled workers wages and that of the organized industrial sector. On the whole those real wageswhich showed a cyclical trend balanced out, while others increased until the late 1980s. The net effect wasan increase in real wages and reduction in poverty. This period was one of high growth which wasdominantly labour-productivity driven. The inverse relation between real wages and poverty is thereforemaintainable for the 1980s.

The 1990s show a decline in real wages of the agricultural seasonally specific wages and a fluctuatingcyclical trend in general agricultural/rural wages. Unskilled urban casual wages have also declined. Povertyas we know has probably increased and has certainly not declined in the 1990s. This too confirms theinverse relation between poverty and real wages. It is, however, also evident that the 1990s (like the 1970s)are not a high growth period such as the 1980s were. Growth in the 1990s is less driven by employmentexpansion than was the case in the 1970s.

In general it may be arguable that in Pakistan, although poverty and real wages are related inversely, asshould be the case in an economy in which hired labour constitutes more than half of the employed, bothhigh and low GDP growth situations have led to the alleviation of poverty. However, in the low growthscenario the composition of growth needs to be dominated by employment expansion (as opposed to labourproductivity), in order to reduce poverty and improve employment conditions. This is probably nothappening in Pakistan in the 1990s. We can now return to examining the employment indicators implicitin the elasticity measure which, as we have seen, had increased from the 1980s to 1990s.

8. ELASTICITY, EMPLOYMENT, LABOUR PRODUCTIVITY AND

OUTPUT: AN INTEGRATED VIEW

Quite apart from problems of estimation,13 it is the case that employment elasticities implicitly containinformation that may be useful in assessing the employment situation. The overall association ofproductivity growth and employment growth in any given period is implicit in the elasticity measure bydefinition. It is, however,m partly determined by technological relationships that obtain within sectors,which are likely to differ across sectors and which are smoothed out or concealed when represented(implicitly) in an elasticity measure or aggregated at an economy-wide level.

It can be argued that during the development process a negative relationship between labour productivitygrowth and employment growth is to be expected, even a strengthening one. This can be consistent withboth employment and productivity increasing at positive rates. Four interesting cases may be defined.

Case 1: When employment and productivity growth are both sizably positive, and there is thelikelihood of continuing conditions of healthy economic growth which are not employmentunfriendly.

Case 2: When very low (or negative) growth rates in both employment and productivity occur, itmay be a sign of a potential sectoral slowdown towards stabilization. This is acceptable,

14 Depending upon the importance of the sector for overall growth, it is entirely possible that such a shift has positiveemployment effects on the rest of the economy, even if employment levels are contracting in the sector itself.

15 The relationship between agricultural productivity and poverty is a negative one, Amjad and Kemal, ILO-SAAT,1997 ( mimeo).

16 It needs to be explicitly recognized that sustained agricultural output and increasing productivity in are necessaryfor the economy not only because it produces the main input (cotton) for manufacturing, which goes in to Pakistan’s majorexport industry ( textiles), but because it also provides a large portion of the economy’s wage goods. In order for growth to

27

as long as the sector is unlikely to become a natural refuge sector for labour, in times ofoverall deceleration of growth.

Case 3: When there is negative or very low productivity growth and there is sizeable positivegrowth in employment, it may be indicative of stagnation in the sector. This is likely tobe accompanied by increasing surplus labour and underemployment and falling real wagerates. It is important to note that this may be owing not to an unsatisfactory rate of outputgrowth in the sector but to the employment expansion taking place within it. This ischaracteristic of a classic refuge sector.

Case 4: When there is positive growth in productivity and a negative or very low growth inemployment, it may be indicative of a fundamental technological shift taking place in thesector.14

We now discuss productivity and employment growth simultaneously, for the major sectors (Tables A2.5and A2.6). The following observations can be made from examining the data.

1. A negative association between productivity growth and employment growth is discernible(Table A2.6). It was weakest in the 1970s and strongest in the 1980s but the intensity of themeasure in the 1990s is still greater than that of the 1970s. What it does show is that the economyin the 1990s, as a whole, is less able to absorb labour than was the case in the 1970s, althoughthe situation has altered somewhat compared to the 1980s. It is, however, very important to notethe increase in intensity of this negative relation for agriculture and construction over the sameperiods, particularly as sectors are usually associated with high shares of employment.

2. In the first period (1970s) productivity increased at a low rate, output growth was reasonable, andhigh growth in employment took place. In the 1980s, productivity growth was higher than the1970s, employment growth lower, and output growth very high. In the 1990s productivity growthhas fallen again, employment growth continues near the 1980s rate, while output growth has alsodeclined. What has happened is that the lower output growth of 1990s is sustaining anemployment growth at a level which was associated with the higher output growth of the 1980s,which has meant a decline in productivity growth. Employment elasticities, as we know, werehigher in the 1970s, declined in the 1980s and rose again in the 1990s.

3. In agriculture, productivity growth was negative in the 1970s, increased in the 1980s and hasshown a decline in the 1990s, employment growth has shown gradual decline over the period butis still positive.15 Output growth has followed the pattern of productivity growth: it increasedbetween the first two decades and then declined slightly in the 1990s. It should be noted thatemployment and productivity growth rates have all fallen in agriculture over the 1980s and the1990s while the rate of output growth of the sector improved from the 1970s to the 1980s and,even in the 1990s when it declined somewhat, it has not been unsatisfactory.16 So output growth,

proceed smoothly agricultural surpluses are critical.

28

though slightly falling has been reasonable (around 3.4 per cent) and productivity growth hasdeclined to a lower rate. Employment growth on the other hand has also fallen, although it is stillpositive. This does not explain the new volatility in agricultural employment observed earlier.Further sector-specific investigation is needed. The situation in the agricultural sector in Pakistanis similar to Case 2 (low-productivity/low employment-growth) described above.

4. The construction sector’s productivity growth has consistently fallen from the 1970s to the 1980sand 1990s, when it became negative. Employment growth in this sector has fallen although it hasremained high and positive throughout. Output growth has fallen consistently over the threeperiods. Therefore construction seems to be a sector which is likely to be facing a crisis withincreasing employment and negative productivity. This is similar to Case 3 (a stagnating refugesector) described above.

5. In the manufacturing sector, productivity growth was very low (1.3 per cent) in the 1970s, itincreased to a very high rate in the 1980s (7 per cent) and has declined to a middling (4.6 per cent)rate in the 1990s. Employment growth has very clearly seen a decline from the 1970s, through the1980s to the 1990s. During the 1990s it has become negative. Output growth in manufacturingwas around 4.7 in the 1970s, it rose to a very high 8.4 per cent in the 1980s and returned to alower level of 4.2 per cent in the 1990s. Clearly, manufacturing is a sector where there is primafacie evidence on a de-linking of output and employment growth. The case of manufacturing issimilar to Case 4 (technological shifts) described above.

6. There has been a high growth of employment in the retail and trade sector in the 1990s, as well asthe residually defined “other” sector as was observed in the 1970s. Many activities in these sectorsare likely to be located in the non- manufacturing smaller scale and informal sectors.

If the indicative schema and observations made above are to be accepted, then the agricultural sector islikely to be moving towards low productivity conditions (although from the productivity perspective it isnot as bad as the 1970s) while manufacturing is likely to be undergoing a fundamental technological shift,in which its growth process is becoming de-linked, at least from direct employment generation.Construction is likely to have become a sponge or refuge sector, which is simply absorbing labour atnegative productivity levels. There is an increase in employment growth in the retail and trade sector andthe ‘other’ sectors group in the 1990s which is symptomatic of informal and small-scale enterprise sectorsgrowth. This expansion seems associated with relatively lower levels of GDP growth (1970s and 1990s).It has also played an active role in labour absorption in the 1990s, as we have seen earlier.

9. EMPLOYMENT AND OUTPUT GROWTH LINKAGES

It is fairly obvious that the growth of the manufacturing sector has strong growth multiplier effects on therest of the economy (Table A2.7iii), but in looking at employment growth rates for different sectors of theeconomy we find an interesting set of relationships between employment growth in manufacturing andemployment growth in the rest of the economy. Examining simple correlations between sectoralemployment growth rates (Table A2.7i), it is clear that growth in manufacturing employment is moststrongly related to economy-wide employment growth and, in particular, has positive and relatively strongerlinkage effects on employment growth in most other (non-agricultural) sectors of the economy. This is anencouraging finding from the point of view of setting up guidelines for an employment strategy.

29

The greater the extent to which growth in manufacturing is employment-based, the greater will be itsemployment multiplier effects on the rest of the economy. However, promoting employment friendly growthdoes have a potential problem that employment elasticities in manufacturing are low and productivitygrowth during the 1990s has been associated with a negative employment growth. Hence, the situation inmanufacturing is that output growth cannot be expected to generate much direct employment. This is anarea which requires special focus in a sector-specific analysis, with special attention paid to the distinctionsbetween the large and small-scale manufacturing sectors.

10. THE AGENDA FOR AN EMPLOYMENT STRATEGY

The trends in the labour force and employment in Pakistan suggest that with the already low and decliningparticipation rates of labour in the economy, labour force growth is itself declining. In this situation,unemployment persists and underemployment is increasing. The indicators of employment conditions, i.e.real wages and poverty, reflect this worsening in the 1990s. In our view, there are also good reasons toexpect an increase in labour force growth in the near future. This swelling in the labour force growth is alsolikely to change the composition of the labour force to a more literate one. In short, the current employmentproblems facing the economy are likely to magnify in the near future. The major challenge is to attack theproblems of unemployment and underemployment and to increase aggregate employment significantly aswell.

Apart from controlling population growth, which is an important part of an employment strategy, we needto look closely at the changing features of employment as a whole and in particular sectors of the economy.These issues stand out:

1. An important matter that has emerged concerns growth itself. It is clear from the periodization ofPakistan’s history that although high growth periods, lead by increases in labour productivity, canbe accompanied by improving wage rates and declining poverty, a low growth period, if it is toimprove wage rates and decrease poverty, cannot be based excessively on labour productivity.

2. There is a certain volatility to employment patterns observable in recent years at the economy-widelevel. This may reflect widespread shifts in contractual arrangements and is an essential issue toexplore.

3. The role of agriculture in future employment absorption needs to be very seriously examined. Untilnow it has only performed reasonably in terms of growth but appears to have been involved in theswings in employment absorption in recent years. Rural-urban labour force growth rates may alsobe reversing, and this requires special consideration from the point of view of agriculture. Sincepoverty is inversely related to productivity in agriculture, a swelling of the labour force in ruralareas, if there is insufficient absorptive capacity in the rural non-farm sector, could put pressureon the already low and slowly increasing productivity growth rates.

4. There is a growth and employment linkage between the economy as a whole and the manufacturingsector.

5. Manufacturing is not only critical for output growth but its role in employment-generation needs

to be explored. It has clearly faced a crisis of sorts in recent years, but it should be noted that itsoutput growth, though much lower than the 1980s, has not been all that low in the 1990s,exclusing the past two years. Manufacturing is critical for growth and growth is crucial forproductive employment. However, the crisis is in employment within manufacturing. For anemployment strategy, both a ‘revival of output growth’ of manufacturing as a whole and the

30

location of its employment crisis need to be assessed. The manner in which employment linkagesare affected between manufacturing and other sectors is also important to assess. In short, therevival of growth and the nature of low employment elasticities must be the critical focus of anemployment review of manufacturing.

6. There is a need to examine the growth of the small-scale enterprise sector and its employmentabsorption which not only covers manufacturing but other labour intensive-sectors of the economy.The necessary focus is on the nature of growth and the potential in it for employment-generation.Taking into account the caution required for greater employment absorption in agriculture and theapparent limits to employment growth in manufacturing, it is clear that those sectors of theeconomy covered by the SSE sector become critical from the perspective of an employmentstrategy.

1 Although it has expectedly been lower than overall rates of growth.

2 See Chapter1 Annex Table A1.5.

3 The assumption that is implicitly made is on the duration of work-time and effort associated with a unit of labour.The quantitative difference between family labour and hired permanent labour which are both full-time is that the formerrequires supervision while the latter does not. Therefore aggregating the two may not be strictly appropriate. But there is aneven more fundamental and qualitative difference between a ‘unit’ of family labour and permanent labour on the one hand,and casual labour on the other. No assumptions on comparability can be made on time and effort between these two units,yet employment figures do a headcount of all labour. Non-homogeneity in agricultural labour can lead to a fallacy ofaggregation.

31

CHAPTER THREEThe Agricultural Sector

1. INTRODUCTION

Agriculture in Pakistan has had reasonable output growth in the past.1 At the aggregate level, its growthwas showing signs of decline from the 1980s to the 1990s.2 On the other hand, employment growth in thesector continued to be positive though it also declined on trend in the 1990s. The sector could be movingtowards a situation where it may be forced to absorb large sections of the labour force, possiblyunemployable in other sectors that face a slow-down in output growth. This possibility is also reflectedin labour absorption in the sector, which showed that it was the main sector ‘adjusting’ to employmentfluctuations in the economy. Part of the reason for this is external to the sector. When the overall economyfaces a slowdown, its largest employer (even if its sectoral employment share is declining over the longerrun) is likely to experience a swelling in its labour force relative to the output it produces. In the presentchapter, we explore these external causes of change as well as what may have happened to the structureof output and employment within the agricultural sector.

2. THE SPECIAL NATURE OF EMPLOYMENT AND OUTPUT IN AGRICULTURE

Some points need to be noted about employment and output that are specific to agriculture and necessaryfor interpreting the trends in Pakistan.

Measurement of employment

Employment in agriculture is family-based and also uses hired labour both on a casual/part-time and wellas a permanent basis. In other words, employment in agriculture is non-homogenous3 and does not directlydepend on the labour market for all its supply of labour. Seasonal demand for agricultural labour meansthat those employed, can be expected to be “underemployed” at least some of the time. The notion of full-time work; the role of the labour market in the supply of labour and the aggregation of different types ofworkers into the employed category are less straightforward in the agricultural sector.

The special nature of output

The determinants of agriculture output are also different from those of output in other sectors. Inagriculture, output is partly dependent on external uncertainty, this means that weather is an importantdeterminant of output, especially at low levels of output. Therefore, whenever there are conditions of animmanent collapse of output, labour which has already been employed, appears less productive

4 The application of complementary inputs (seeds, fertilizers, pesticides, irrigation, labour) may also be costly aseveryone does not have equal access to the capital market.

5 See e.g. Sen (1980).

6 There are other reasons for the increased use of casual labour: (a) the profitability considerations of land ownersin a situation where potentially higher yields prevail; and (b) their need to expand production on wage labour and reduce sharetenancy (in which output sharing parameters are considered to be norm-determined and inflexible). The problems withpermanent labour are supervision costs and underemployment due to seasonality. This suggests casual labour use as a solution.Increasing landlessness also tends to provide a pool for such labour.

32

(productivity declines). Agricultural output collapses are less often failures of demand and are more supply-side determined. Clearly then the measure of labour productivity in such a situation is not so much a proxyof the contribution of labour assuming employment is counted properly) to production but reflects the over-determining influence of other external causes that influence output.

Thus, we need to be cautious in using ‘employment’ and ‘output’ categories in themselves or in standardmeasurements, when analyzing the agricultural sector. We now select two features of this discussion,external uncertainty with output and casual labour use in employment, to posit a combined effect whichmay be of special relevance in Pakistan.

A combined effect

The degree of external risk in agriculture is also sensitive to the technological features of the productionprocess. The HYV technical input package, in use in Pakistan, which is based on robust varieties of seeds,also requires the use of complementary inputs,4 the application of which is subject to serious timeconstraints.5 It can be argued that the widespread use of the package, though growth- enhancing onaverage could also increase the sensitivity of the production process to this external uncertainty. If thisis the case then it should be reflected not only in an increasing level of output on average but also in relativeoutput instability post-adoption.

One response to increased external risk (due to the profitable technological package and uncertainty), isthat land-owning employers move towards flexible arrangements with labour, to reduce a part of theirwage-cost risk due to the vagaries of weather. The use of casual labour,6 particularly during labourdemand peaks, can generate this flexibility.

It also means that the greater the proportion of casual labour in the agricultural labour force, the moreclosely the employment growth trend in agriculture is likely to follow the output growth trend, because itis precisely the casual labour component of the labour force that becomes its variable part.

This would also imply that in conditions of economy-wide low growth, levels of surplus labour in theagrarian economy will be high and underemployment and poverty due to the changes in the compositionof the labour force and its casualisation will become increasingly visible.

7 Agricultural output growth was been 2.1 per cent for the 1970s; 3.9 per cent for 1980s and 3.3 per cent for the1990s (See Chapter Two, A3, table A3).

8 Labour force survey figures are therefore more appropriate for capturing total employment growth rates The dataon casual labour use in agriculture are available on the incidence of farms using casual labour in the Agricultural Census. Thisshow s 60 per cent and 48 per cent increases in casual labour over the decade of the 1970s and the 1980s respectively.

33

Figure 3.1: AgricultureGrow th of Real Value-Added & Employment ,

and the Output-Elasticity of Employment

- 1 0 . 0

- 5 .0

-

5 .0

1 0 .0

1 5 .0

Fisca l Year En d i n g J u n e 3 0

Gro

wth

Rat

e (%

)

-3.0

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

Ela

stic

ity

V alue added Employment Elasticity

3. OUTPUT AND EMPLOYMENT GROWTH RATES IN PAKISTAN’S AGRICULTURE

The growth of output in agriculture has been positive and increasing (tables A3.1 and A3.2, A3.3) inPakistan. The sector has by and large under-performed GDP growth but its growth rate is reasonable.Figure 3.1 shows that the pattern of output and employment growth has been fluctuating much more sincethe mid-1980s. Although it is quite true that output growth was much more stable in the 1970s, whichmeant stable employment growth and stable elasticities, it is likely that the fluctuations apparent from themid-1980s have contributing factors other than external uncertainty.

These patterns may have something to do with the changing nature of both output and employment. Foroutput, the country-wide use of the HYV technological package by the 1980s (tables A3.3a and 3.3b)meant that its sensitivity to the timing of inputs, as well as external weather conditions with respect to thattiming, became more accentuated. This may explain the increasing amplitude of movements in outputgrowth over the years as shown in Figure 3.1.7

Because family labour and permanent labour are a constant part of the employed labour force inagriculture, the changes that may result from output booms and slumps are likely to be due to changes inthe employment of the casual labour force. We therefore need to examine changes in the composition ofthe labour force (table A3.4). According to Agricultural Census data agricultural “employment” witnesseda 0.62 per cent annual growth in the 1980s. This excludes casual labour use, which is known to haveincreased phenomenally in the same period (see table A3.5)8. Permanent hired labour use has altered but

9 Growth rates of the labour force have been positive and declining since 1989-90.The percentage drop in the rurallabour force growth rate from 1989-90 to 1994-95 was -10.1 per cent ; the drop in the urban labour force growth rate for theperiod was -39.9 per cent; and the overall drop in the growth rate of the labour force as a whole was -20.2 per cent.

10 Note this period corresponds to what is the slump in employment of the small-scale enterprises (SSE) sector ofwhich rural employment is very significant.

11 We have already observed the phenomenon of relative decline in the rural urban labour force growth rates in thechapter on labour force.

34

the weight of permanent hired labour in the census figures of permanent agricultural employment is notlarge enough to warrant comment (2.7 per cent).

4. AGRICULTURAL EMPLOYMENT AND TOTAL EMPLOYMENT

Throughout the 1970s the rate of growth of economy-wide employment has been, on a trend, higher thanthat of agricultural employment. The LFS figures are, as suggested earlier, likely to capture employmentin agriculture data, which includes casual labour (table A3.5) and are therefore preferable, at least in termsof coverage, to the Agricultural Census (AC) figures. Both figures for the 1980s (AC and LFS) are,however, lower than the overall growth rate of employment. Since the mid-1980s (which is also the peakperiod of growth after which a gradual decline sets in), there is no longer a discernible pattern; agriculturalemployment growth has been higher as well as lower from the overall rate of employment growth (tableA3.2). There is also a changing pattern of rural-urban migration, with rural Pakistan increasingly retainingmore of the labour force (table A3.6).9 It is worth noting that for the second half of the 1980s decade,10

there is a greater increase in growth of ‘agricultural employment’ than is the case in the first half(table A3.4).11 Consequently, there are signs of a swelling in the size of the agricultural labour force.

5. DECOMPOSING THE SOURCES OF OUTPUT GROWTH

In the 1970s output growth was not too high (2.0 per cent) but it was positive and so was employment(2.1 per cent). This trend altered in the 1980s, when output growth on average was higher (3.9 per cent),and employment growth remained a little lower (1.9 per cent) but switched to an increased use of casuallabour. In the 1990s output growth continues at a slightly lower rate (3.3 per cent) and employment growthis also low (1.6 per cent) but both output and employment growth patterns are more volatile (table A3.2).

We now come to the decomposition of growth exercise, which looks at the contribution of labourproductivity and employment expansion to output growth, bearing in mind the qualifications made earlierregarding output, employment and productivity in agriculture. Basically, employment expansion-basedgrowth dominated in the 1970s, shifting to productivity-dominated growth in the 1980s, and shifting backto employment expansion based growth in the 1990s, though it is now ‘shared’ with labour productivity.

In the 1970s, a more stable period of lower output growth, the employment expansion effect dominatedthe productivity effect for several reasons . The nineteen seventies were a period when the green revolution,although significant, had not spread nationwide (table A3.7a). The popular belief that effective land reformmay come about in Pakistan encouraged landed agriculturists with significant holdings to stay in sector.This was also reflected in a spate of land resumptions, a decline in absenteeism and the expansion of

12 See Mahmood (1993), Hussain (1980), Majid (1995).

35

cultivable land cultivation. Also, growth in other sectors is this period was low. A combination of theseconditions may explain the dominance of the employment effect.12

Table 1: Decomposing output growth , productivity and employment effects -agriculture

Year Productivity Effect Employment Effect Multiple Effect

1969/70 - 1980/81 0.063 0.918 0.018

1980/81 - 1991/92 0.664 0.236 0.100

1991/92 - 1994/95 0.361 0.623 0.040

The 1980s story is slightly different. Labour productivity dominated contributions to output growth (whichwas also higher than in the 1970s). Reasons include the less costly expansion of land frontier (already donein the 1970s); the widespread use of a HYV input package (Table A3.7 a and A3.7 b), and greatertractorisation in parts of the country other than the Punjab, where the green revolution had becomewidespread earlier. The possibility of land reform had also receded from the agenda of the then militaryregime. But equally significantly, the decline in the employment contribution to growth in the 1980s maybe due to higher growth in other sectors of the economy. Sectors that were drawing productive labour outof agriculture particularly manufacturing. It is worth noting that SSE manufacturing, which has a largerural component, was witnessing employment and output growth at least up to the mid-1980s.

The 1990s reverted to an employment expansion based effect (at levels of agricultural output growthsimilar to the 1980s but more volatile on an annual basis) and may reflect a deceleration of growth in othersectors, particularly manufacturing. There is nonetheless a significant contribution of labour productivityin this period as well.

Employment expansion in the presence of as large a casual labour force as exists in Pakistan in the 1990ssays little about the quantum of labour used or its returns. It is worth recalling that the composition of theagricultural labour force has changed in the 1990s compared with the 1980s, and volatility of output inthe sector is reflected more in employment growth than previously it is also likely to have generated aprecariousness in the livelihoods of those now employed as ‘casual labour’ in the agricultural sector.

6. UNEMPLOYMENT AND UNDEREMPLOYMENT

Agricultural employment is a dominant part of rural employment. Trends of unemployment andunderemployment in the rural areas reflect labour market conditions in the agricultural sector. However,unemployment, in a developing country context, in particular in agriculture, is not a good indicator oflabour market conditions. In the absence of social welfare and insurance, the unemployed are generallyavailable for work in any sector, and often do work to survive. Underemployment is therefore a betterindicator of conditions in the labour market. The trends in unemployment and underemployment areexamined below.

13 Between 1990-91 and 1991-92 there is continuity, a drop in 1993-94 , continuity in 1993-94 and then an increaseagain to 1994-95. The general trend across the 1980s and 1990s may be of an increase, it is unlikely to be of a decline.

14 It is arguable that underemployment in the 1980s was lower than what it was in the 1990s, which fits in withthe picture of economy-wide high growth 1980s, continuing rural-urban migration and increases in the SSE manufacturingsectors employment in the first half of the decade and a possible decline in the second.

15 A given level of underemployed in the labour force is likely to understate the degree of underemployment more,the greater the proportion of casual labour in the labour force.

16 Although the share of rural non-farm employment in rural areas on trend has increased since the 1980s(table A3.11), agriculture was around 62 per cent of rural employment and has shown a fluctuating pattern of employmentshares from 1991-92 to 1993-94.

36

The data (table A3.8) show that unemployment increased on trend in the 1980s, from 1979-80 to 1987-88. It is not legitimate to observe trends on unemployment without qualification across the year 1990-91when LFS data is used, as in this year definitional changes took place which particularly affected theunemployed. The data show that unemployment was increasing on trend in rural Pakistan during the 1980sand was showing a trend decline in the 1990s.13

The case for rural underemployment is also mixed. It shows a decline from early to mid-1980s and anincreasing trend through the second half of the 1980s and the 1990s.14 What is clear is that the ruralunderemployment rate is high in Pakistan.

By 1993-94 about 20 per cent of the rural labour force was either not working or only partially workingin rural areas, consistent with a fluctuating pattern of growth in output and employment, which as weargued is increasingly based on the use of casual labour.15 An agricultural sector with low levels ofproductivity, coexisting with other sectors with limited employment absorption capacities, is likely to havea large reserve army of the underemployed with a high degree of underemployment.

If non-farm employment growth (which is the rural part of the SSE sector) had started slowing down sincemid-1980s, then it can be assumed that the bulk of labour absorption in the 1990s would be in theagricultural sector, possibly as underemployment and casual labour.16

7. LABOUR DEMAND

It has been suggested above that, owing to the non-homogenous nature of the employed, increasing levelsof employment (numbers of employed) may not translate into increasing use of labour (amount of labour).Consequently we need to look at the requirements of labour and the many factors which affect them. In theshort-run they are best reflected in estimations based on cropping patterns.

Cropping patterns and profitability

Driven by profitability considerations, there has been an increase in the cultivation of crops with a higherlabour input in Pakistan. This is clearly a trend across the 1980s and 1990s (table A3.9 ). These changesin cropping patterns which require more labour are also consistent with trends in rates of profits ofindividual crops (table A3.10 ).

There are two ways to respond to increases in labour requirements. One is by actually increasing labourinputs to meet those requirements. The other is by capital-labour substitutions which may reduce those

17 The relationship is slightly exaggerated because of the casual-worker factor, as larger farms are likely to usecasual labour which does not figure in the calculations. In general the relationship is supposed to be the most robust for therelation between size and of productive factors.

18 Or due to the resumption of land from owner-cum-tenants.

19 There are limits to activities within agriculture which can feasibly be mechanized. Mechanization is especiallydifficult for peak period labour activities, which is where the demand of labour is concentrated.

37

requirements. Increasing labour inputs can be done by hiring additional labour or by increasing the use ofexisting labour (either family or hired or both).

Size and productivity: Increasing family labour use

Changes in average sizes of farms may have automatically led to the internalization of some of theseincreased labour requirements due to changing cropping patterns. The changes in farm size over theintercensal period have increased the incidence of small farms in Pakistan. It can be argued from researchon the farm size–productivity relationship in Pakistan, that an inverse relation between farm size and labourinput exists (table A3.12 ).17 So the fall in farm size due to the sub-division of holdings18 over time wouldincrease the potential availability of labour inputs, especially family labour inputs.

It is also the case that small farms have higher total productivities and greater cropping intensities thanlarger ones, whereas they may have lower individual-crop yields than large farms ( Mahmood, 1997b,mimeo).

This means that small farms maximize returns through their choice of cropping patterns and greater useof labour. This response to the increasing requirements of labour is one that automatically comes aboutwhen productivity led cropping pattern changes made possible by the new technology take place over time.Large farms still have to contend with the hiring-in of extra labour, much of which is likely to be of acasual variety.

Mechanization: Reducing labour requirements The second way to respond to increasing labour requirements is mechanization 19. Some economy- wideevidence exists here as well. Farm area exclusively using bullock power has declined over the 1980s. Onthe other hand, farm area using a mix of bullocks and tractors as well as tractors exclusively has increased.It is clear that the effect of tractor use is the displacement of labour (table A3.13).

Tenurial shifts: Creating an available labour pool Changes in land tenure which have taken place in Pakistan in the last two decades (a decline in tenancy)may or may not have increased productivity. Evidence is mixed and depends on the existence ofdisincentives in tenancy compared with owner-farming as well as on who is resuming the tenanted land.It is likely that over time disincentives in tenancy have become marginal and insignificant, at least in theSindh province in Pakistan where the bulk of tenancy exists (Majid, 1994). Reduction in tenancy releaseslabour into the labour market as landless labour, which needs to get absorbed. Tenancy has also clearlydeclined in Pakistan (table A3.14).

8. WAGES AND POVERTY

20 As do non-agricultural casual workers and self-employed workers with assets less than Rs 1000.

21 There is a negative relationship over time between the average ( seasonal average) real agricultural wage ratesand the rural participation rate (-.69), which suggests that, imperfect as it may be, the casual labour market does operate, insome basic sense as a conventional market. This is of course not a good thing in itself. Normally labour markets where wagealso performs a signaling function are downwardly rigid at levels reasonably above the poverty line. This may not be the casefor the agricultural casual labour market.

38

Results from a recent study (Gazdar, Howe and Zaidi, World Bank, 1994) shows that in rural areas,households headed by tenants and agricultural labourers have a very high incidence of poverty(table A3.15).20 These workers are at the bottom end of the range of human capital and physical assetscategories. This suggests that casual workers constitute one of the poorest sections of the agriculturallabour force and, given that tenancy has declined and casual labour increased, these workers are likely tobe a growing section of the rural poor.

We have already discussed wage and poverty trends in Chapter Two, but a restatement is in order in theagricultural context. Nominal wage data are available on seasonal agricultural casual workers(table A3.16). Although real wages of agricultural workers improved up to the mid- 1980s, during the1990s they have probably declined. The wage data again corroborates our expectations about thecontinuing slow-down of the rural non-farm employment growth since the late-1980s and the swelling ofthe casual labour force in agriculture. The assumption here is on the nature of the labour market and itsextent of isolation. In our view the agricultural casual labour market does function in rural Pakistan; inan overall sense the wage rates are a signal of supply and demand conditions and there is some evidenceto support this view. 21 Recent poverty studies in Pakistan also tend to show a decline in rural poverty from1969-70 up to 1987-88. There is an increase in rural poverty after 1987-88 up to 1990-91, according toone study (Malik, 1996) and a slight decline according to another (Gazdar et. al., 1994), owing todifferences in assumptions made to calculate poverty lines (Kemal and Amjad, 1997). However, it can beclaimed with some degree of certainty that the declining trend in rural poverty either reversed or witnesseda severe slowdown in 1987-88 to 1990-91, the latest data period available. In our view the increase inrural poverty seems to be a more plausible result.

9. UPSHOT

Agricultural output growth rates were reasonable in the 1980s and 1990s. Employment growth andproductivity growth have declined commensurately, leaving a more or less constant elasticity ofemployment (.48). However, the low employment–low productivity growth situation is sensitive to growthconditions in the rest of the economy and the sector needs to be protected on this count. An overview of theemployment situation in agriculture suggests that over the 1970s, 1980s and 1990s, profitability-drivencropping pattern changes based on the new technological package may have increased labour requirementsin the sector. The changing distribution of operated holdings, mechanization and tenurial shifts may havepartially adapted to, as well as reduced, these increases. The rest of the adjustment has had to be borneby the new hired casual labour force, the size of which is increasing. The nature of this labour force isreflected in the extent of rural underemployment, wage rates and poverty. While underemployment issizable (around 20 per cent including the unemployed) it has shown signs of an increasing trend since thelate 1980s. The returns to casual labour suggest that both the levels of real wages and the size of the non-poor in the rural economy of Pakistan have either stagnated or declined in the last period for whichinformation exists (1987-88 to 1990-91 for poverty and up to 1994-95 for wages).

39

These changes have been accompanied by what can be seen as structural change in the agricultural sector.This change is manifest both at the level of the production and labour process on the one hand and thesupply of agricultural labour on the other. Both these changes are noteworthy from a policy point of view.

First, on the production and the labour process. What is significant about the growth of output andemployment in the agricultural sector in Pakistan, is not so much their rates of growth, but the changingcomposition of the labour force on the one hand and the increased variability in the pattern of itsproduction over time, on the other. There is much greater volatility in agricultural output since the mid-1980s, connected to the widespread assimilation of technical changes in the rural economy and nowembedded in the production process. This translates into a fluctuating trend in the employed labour force,with the increasing casual labour component on the receiving end of the adjustments to this volatility inoutput.

The second matter concerns the expanding and impoverished pool of labour reserve from which this casuallabour springs. Landlessness and near-landlessness as a consequence of declining tenancy and thesubdivision of holdings is one element in this. The other may be a return labour flow into the agriculturalsector because of low growth in other sectors of the economy, especially the rural SSE sector. Thesetendencies are likely to exacerbate the size of the labour reserve in rural areas, which then has to ‘forcibly’get ‘absorbed’ in agriculture as a last resort.

An effective policy focus to promote future growth and employment in the agricultural sector needs to havea dual aim: the dampening of the relationship between the volatility of output and the livelihoods of theworkforce; and making the livelihoods of casual labour within this workforce more sustainable.

1 For statistical purposes, manufacturing and mining are added together in Pakistan. Large-scale industries (definedas consisting of registered factories employing more than five persons) are equivalent by definition to industries covered bythe census of manufacturing industries. The census covers all factories registered under section 2(j) and 5(l) of the FactoriesAct 1934, as amended from time to time. Effectively, until 1967 this meant a coverage of all registered factories whichemployed ten or more persons, and since October 1972, five or more persons.

2 Estimates depend on the estimation method and time frame. We have already shown that employment elasticitiesin manufacturing have been declining on trend.

3 It is because of the rates of these relative declines in employment and output growth in very recent years of the1990s that elasticity seems to be increasing now.

40

CHAPTER FOURThe Manufacturing Sector

1. INTRODUCTION

In Chapter Two, we concluded that at an aggregate level an employment strategy in Pakistan has to havethe manufacturing sector as a critical focus. The argument was based on two observations. First, that giventhe problems with the elasticity measure, at least a simultaneous examination of employment and labourproductivity growth was needed. Second, that cross-sectoral employment linkages also seemed to beimportant. It was consequently argued that despite the fact that there was limited room within themanufacturing sector to generate employment directly, if manufacturing growth could be employment-based, it would have positive employment effects on the rest of the economy.

Within manufacturing, a distinction can be made between “small-” vs. “large-scale” manufacturing.1 Thissection looks at manufacturing as a whole and then focuses on large-scale sector. In a separate chapter(Chapter Five) devoted to the Small-Scale Enterprise Sector (SSE), we look at small-scale manufacturing.

2. ELASTICITY, EMPLOYMENT AND OUTPUT GROWTH

Figure 4.1 gives a visual plot of employment elasticity, as well as employment and output growth rates,in the manufacturing sector over the years in Pakistan. Plotting growth rates of employment and output isuseful for an overview and we can start with the same point we made at the economy-wide level about thelimitations of elasticity measures taken on their own. A stable and very low elasticity has accompaniedfairly diverse output and employment growth patterns in manufacturing over the years in Pakistan. Whatcan be claimed with some degree of confidence is that elasticity of employment is low2 in manufacturing,and this at least seems to be a structural feature of the sector. The latest period of the 1990s in Pakistanis showing a decline in both output and employment growth and this is a seriously worrying matter for thesector3. The reason for this low elasticity of employment in Pakistan’s manufacturing sector is thereforea critical policy question.

4 Although such a decomposition is very useful for the periodization of employment growth in a sector in aneconomy and does not make restrictive assumptions on the nature of production functions, it does stop short of deconstructinglabour productivity itself.

5 We examine the sources of labour productivity increases later.

41

- 15 .0

-10 .0

-5.0

-

5 .0

10 .0

15 .0

Gro

wth

Rat

e (%

)

-15.0

-10.0

-5.0

0.0

5.0

10.0

15.0

Ela

stic

ity

V alue added Employment Elasticity

Figure 4. 1Grow th of Real Value-Added & Employment,

and the Output-Elasticity of Employment:Manufacturing &Mining

3. DECOMPOSING OUTPUT GROWTH IN THE MANUFACTURING SECTOR

Having observed the trend of output and employment growth, we will now conduct a ‘decomposition ofgrowth’ exercise for the manufacturing sector.4 We will first examine how the contributions of labourproductivity and employment relate to output growth, and second, whether any trend can be observed inthese contributions.

In the first period of the 1970s, although growth itself was uneven (higher in the first half, lower inthe second) it was roughly equally divided between productivity and employment. The next periodof 1980-81 to 1991-92, the period of consistent high output growth, was based dominantly on theproductivity effect (about 81 per cent) while the contribution of employment to growth was low(8 per cent). Clearly, a shift was already taking place in this period of high growth of themanufacturing economy. The last period of the 1990s is one of low and declining growth, especiallyin the recent years, and the contribution of employment to output growth has been negative. The entiregrowth process now seems to be based on labour productivity.5 This trend makes the task of boostingand restructuring the industrial sector, from an employment perspective, somewhat difficult. We needto bear in mind the cross-sectoral employment linkage caveat made in the Chapter Two, to emphasizethe role of manufacturing.

6 Data produced in the Pakistan Economic Surveys show consistently higher total growth rates than growth ratesof the large-scale sector, the implication being that small-scale sector growth in manufacturing is very high. We will returnto this important matter in another section. But this qualification has a bearing on the official figures for manufacturing takenas a whole.

42

Table 4.1: Decomposing output growth: productivity andemployment effects – manufacturing

Year Productivity Effect Employment Effect Multiple Effect

1969/70 – 1980/81 0.460 0.419 0.120

1980/81 – 1991/92 0.816 0.089 0.094

1991/92 – 1994/95 1.868 -0.680 -0.188

4. OUTPUT AND EMPLOYMENT IN THE MANUFACTURING SECTOR

A low elasticity of employment has been observed in the manufacturing sector in Pakistan. Progressivelyover the last two decades growth in manufacturing has become more labour-productivity driven (thanemployment-expansion driven) and in the 1990s it seems to have been de-linked from employmentexpansion altogether. This picture is quite consistent with the low and declining elasticities of employmentalready observed. The sources of this growth need to be further explored.

While the share of manufacturing in GDP has increased from 15.1 per cent to 18.2 per cent, its share inemployment declined from 13.54 per cent to 10.12 per cent. The rate of growth of value added in themanufacturing sector as a whole has been declining on a trend in Pakistan, over the Plan periods since1982-83. This is true for manufacturing as a whole as well for large-scale manufacturing. In particular,large-scale manufacturing has experienced a serious slowdown from 1994 onwards and growth wasnegative in 1996-97. The 1980s were the high growth period of the manufacturing sector in Pakistan.There has been a clear decline, on trend, in the growth of output ever since6.

Table 4.2: Growth rates of manufacturing output over the sixth, seventh and eighth plan periods

Period Total Large-scale

1982-83 to 1987-88 8.2 8.1

1987-88 to 1992-93 5.9 4.9

1992-93 to 1996-97 3.8 1.7

1992-93 5.4 4.1

1993-94 5.5 4.3

1994-95 3.6 1.5

1995-96 4.4 2.2

1996-97 1.8 -1.4

Source: Based on Economic Survey (1996-97 and previous issues).

43

Manufacturing comprises both the small-scale and large-scale sectors in Pakistan. The small-scale sectordominates employment in it, while the large-scale sector dominates output. Table 4.3 shows that althoughoutput growth has taken place in the manufacturing sector in both its small and large-scale sections,employment began to decline in the small-scale sector in the mid-1980s. There seems to be some constraintthat the small-scale sector begins to face at this time. In other words, the de-linking of employment fromgrowth which was taking place in the manufacturing sector in the 1980s, may have been due to theoverwhelming weight of the declining employment in the small-scale manufacturing sector and notbecause of the large-scale sector as such. The picture after 1990-91 is constructed on the basis ofNational Income Accounts (NIA) and the labour force surveys (LFS), and there is not much that can besaid about the large-scale and small-scale manufacturing sector separately here, except that overall growthof the sector has fallen further, and there has been a negative employment growth. It would seem that atleast the same trend with respect to the small-scale sector employment can be assumed.

Table 4.3: Output and employment in manufacturing

Period

Output

Employment(Mill. nos.)

Share ofmanufacturingsector in totalemployment

Employment in Growthrate oftotal

employ-ment

TotalLargeScale

SmallScale

Large-scale

manufac.

Small-scale

manufac.

1982/83 45.60 33.80 11.70 3.50 13.54 0.465 3.04 0.30

1983/84 49.20 36.50 12.70 3.61 13.69 0.476 3.13 3.10

1984/85 53.20 39.40 13.80 3.73 13.84 0.493 3.24 3.30

1985/86 57.20 42.20 15.00 3.62 13.40 0.507 3.11 2.30

1986/87 61.50 45.30 16.20 4.08 14.23 0.532 3.55 12.70

1987/88 67.60 50.00 17.60 3.72 12.84 0.515 3.21 -8.20

1988/89 70.30 51.20 19.10 3.84 12.84 - - 3.20

1989/90 74.30 53.70 20.70 3.96 12.84 - - 3.10

1990/91 79.00 56.60 22.40 3.70 12.38 0.623 3.08 -6.60

1991/92 85.30 61.00 24.30 3.88 12.53 - - 4.90

1992/93 89.90 63.60 26.30 3.53 11.00 - - -10.00

1993/94 94.70 66.20 28.50 3.34 10.12 - - -4.20

1994/95 98.20 67.30 30.90 3.49 10.50 - - 3.30

Sources: Economic Survey, 1996-97; Labour Force Surveys; Censuses of Manufacturing Industries;Censuses of Small-scale and Household Establishments.

7 Of the four, textiles account for the major share of output, employment and exports.

8 As a result, the sector has always accounted for less than 2.5 per cent of total employment (in 1990-91, 2.1 percent), although its share has varied between 6-8 per cent of urban employment, and between 3-6 per cent of non-agriculturalemployment.

9 During the 1984-90 sub-period however employment in large-scale manufacturing grew by 3.9 per cent per year,with textiles and food processing accounting for 48.8 per cent and 15.5 per cent of the growth respectively.

10 The increase in labour productivity in the 1980s was spread unevenly across sectors. The largest gains were inpetroleum refining, while textiles, paper and board, and drugs and pharmaceuticals also registered significant gains. Capitalintensity measures can be seen in table A4.2.

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5. THE LARGE-SCALE SECTOR: MAIN FEATURES

Large-scale manufacturing in Pakistan is dominated by the so-called “Big Four” industries – sugar, textiles(cotton yarn and cloth), cement, and fertilizers while accounting for only 6.9 per cent of the units in thesector in 1991, consisted of 37.6 per cent of net output, 40.2 per cent of exports, 35.0 per cent ofemployment and 43.2 per cent of the capital stock employed in large-scale manufacturing.7 Unlike itscontribution to output and exports, the large-scale sector’s contribution to employment has been moderate,even in periods of rapid growth. On the whole, manufacturing industries in Pakistan, have failed to createsufficient employment: employment levels were almost the same in 1994-95 as they were in1982-83.During 1980-95, when total employment grew by 2.3 per cent per year, employment in large-scalemanufacturing increased at only 1.8 per cent per year.8 Over the same period (1980-95), large-scaleindustry absorbed only 1.4 percent of the additional employment in the economy.9 Slow job creation inlarge-scale manufacturing was accompanied by a substantial rise in capital intensity and labourproductivity in the period 10, as assets employed per worker increased from Rs. 50,000 in 1980-81 to Rs.192,000 in 1990-91. As a result, the labour content in output and the share of wages in value addeddropped in most industries (table A4.3). It is therefore quite clear that labour productivity as well ascapital intensity have risen on trend in the large-scale manufacturing sector in Pakistan (table A4.6).

It has also been suggested above that, despite the slowdown of overall growth, employment and outputgrowth have not moved in opposite directions in the large-scale sector until very recently, whereas theyshowed signs of this in the small-scale sector as early as the mid-1980s. The share of large-scalemanufacturing employment has been around 17 per cent of manufacturing employment in 1990-91, whileits output share was around 70 per cent in the same year.

From an employment point of view the separation of large from small-scale as well as the distinctness ofthe high-growth 1980s and low-growth 1990s are important facts. The centrepiece of an employmentstrategy within manufacturing is the small-scale sector, which is larger in weight and has been facingproblems since the mid-1980s, In contrast the primary focus of the revival of growth is relevant to thelarge-scale sector where the bulk of manufacturing output is produced and where employment is stillgrowing, albeit slowly. It is this sector’s growth which is likely to have positive linkages with other sectors,including activities in the manufacturing as well as non-manufacturing small-scale sector. Since we arediscussing the large-scale sector in the present section, this difference must be kept in mind.

11 Aggregate productivity can also increase if labour flows into sectors with higher levels of labour productivity,in other words through the expansion of high productivity sectors, although this is subject to demand constraints.

12 Actually, the time and value added seem to be correlated.

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6. AN EXAMINATION OF PRODUCTIVITY IN THE LARGE-SCALE

MANUFACTURING SECTOR

Apart from describing some specific features of the manufacturing sector in Pakistan, the discussion abovehighlighted that the growth process in the large-scale manufacturing sector is characterized by a lowemployment elasticity and that if it is decomposed over time, labour productivity dominate employmentexpansion as the source of growth. We also saw that both labour productivity and capital intensity haveincreased in the large-scale manufacturing sector.

We now attempt to examine the determinants of labour productivity as well as employment over time ina more systematic way. There are two basic sources of increases in labour productivity. First, there canbe an autonomous increase, arising from better management, skill upgrades (possibly via training), longerworking hours and greater effective effort. Productivity gains that result from better management and skillupgrades are desirable. These are likely to show up over time. Second, productivity can increase from increases in the use of machinery and non-labour inputs. Thiswould largely be reflected as the effect of capital intensity.11

The question to ask at this stage is: given that labour productivity has shown an increase over time, whatis the extent to which it has been driven by changes in the composition of capital (the capital-labour ratio)and to what extent is it due to autonomous increases in productivity? Since it is expected that in the courseof development the composition of capital effect is dominant, we are interested in knowing whetherautonomous increases in productivity have any potential in manufacturing in Pakistan.

A regression analysis conducted for the period 1980-97 (see table A4.4), which focuses on thedeterminants of labour productivity and employment in large-scale manufacturing, suggests that labourproductivity in Pakistan has been influenced by changes in capital intensity (i.e., the capital-labour ratio)as well as increases in ‘autonomous’ productivity. The capital intensity effect on productivity clearlydominates in manufacturing.

Labour productivity and capital intensity have a significant positive relationship (for equations in whichit used), and this is according to expectation. The level of value added in manufacturing also has a positiverelationship with labour productivity (it is significant in two specifications out of three) which suggeststhat high value added production is associated with high labour productivity, which is also expected. Thepositive relation also holds true for the time variable (statistically significant in two equations), which canbe seen as a proxy for skills development, learning or ‘autonomous’ increases in productivity.12 So thereare some grounds to expect a potential for autonomous productivity increases in Pakistan.

Employment on the other hand is significantly and positively associated with value added (in two out ofthree equations). The capital-labour ratio, the measure of capital intensity, is significantly and negativelyrelated to employment. The time variable simply shows a negative sign showing the growth rate trend.Three matters are deducible from this analysis which have strategic implications. First, that increasingcapital intensity which increases labour productivity also has a negative effect on employment. Second,that higher value added production, though positively related to labour productivity and capital intensity,is likely also to have a direct beneficial impact on employment. This means that the promotion of high

13 Total Factor Productivity is decomposable into Labour and Capital Productivity. Decomposition is based onassumptions made on the production function.

14 Declining capital productivity also suggests that a substitution between labour and capital is likely to have begunin the 1990s. Sectoral decompositions of total factor productivity can be seen in table A4.5.

46

value added production has two possible effects on employment, through capital intensity it is likely toreduce employment, but through the overall positive association between increase valued added productionand employment it is likely to increase employment.

Third, and most importantly, we know from the analysis that autonomous increases in productivity are notunknown in Pakistan. This is a significant finding and can provide a basis for an employment-friendlyinvestment plan.

7. THE STRUCTURE OF LARGE-SCALE MANUFACTURING IN THE 1980S AND 1990S

We now try to differentiate the two periods of the 1980s and 1990s. We know that one was a low-growthperiod and the other a high-growth period. We also know that the overall trend is of increasing labourproductivity and capital intensity in the sector. A decomposition of total factor productivity is useful in thiscontext. 13 The increase in productivity in the large-scale manufacturing sector shows that the increase intotal factor productivity from 1982-83 to 1996-97 has been slight, and has been declining, on trend, since1992-93. Labour productivity, as we know, has shown an increase on trend, (except for the decline for1996-97). Capital productivity shows an increase up to 1992-93 and then shows declines. Therefore, itis really both capital and labour productivity which increased in the 1980s boom. In contrast, while labourproductivity continued to increase, capital productivity showed a decline in the lower growth 1990s. Thisis a crucial difference.14

Table 4.4: Productivity in large-scale manufacturing (1980-81=100)

Labour productivity Capital productivity Total factor productivity

1982-83 122.5 110.1 101.2

1987-88 166.9 136.3 102.5

1992-93 205.2 155.8 103.0

1994-95 208.9 148.9 102.7

1995-96 211.9 143.1 102.4

1996-97 201.7 135.6 102.4

Source: DRI/PIDE Study on Technology 1997.

The output and employment growth policy in manufacturing needed in Pakistan is intrinsically tied to thelabour productivity-led growth process which the country began to witness in the 1980s. The causes for

15 This is partly due to the fact that food figures include the sugar sector and while the rest of the food sector wasin decline, there was investment in the sugar industry. Moreover food production was moving towards lower value addedactivities and thus losing its share in total value added.

16 The causes for over-capitalization in chemicals (as well as cement) may have something to do with lendingcriteria. It has been shown above that despite the slowdown in the manufacturing economy some investment is still takingplace. Given that there is under-utilized capacity in an industry, it is pertinent to ask what causes investment based increases

47

increases in labour productivity are critical to assess. We have done this across the two periods fairlysystematically in the regression analysis above, which suggested that while the capital intensity effectdominated, autonomous productivity increases were not unknown. For a periodized decomposition of totalfactor productivities we found that the difference between the 1980s and 1990s was located in capital, notlabour productivity. The 1980s saw an increase in the latter, the 1990s a decline. We now attempt anassessment for the 1980s and 1990s separately and at a sectorally more disaggregated level.

The high-growth 1980s

The 1980s were a high-growth period, particularly for the period 1982-82 to 1987-88, after which a declineset in. Indicators of capital intensity for parts covering the period also tend to confirm that capital intensityincreased in this period. This process has continued between the high-growth 1980s and the low-growth1990s (table A4.2), but for different reasons. It is reasonable to argue that if growth is positive, as it wasin the 1980s, and capital intensity also increases, as was also the case in 1980s, then labour productivity(value added per unit of labour) is also likely to rise. This is the case for the evidence we have for the 1980s(table A4.6). So the increasing capital intensity argument behind the high labour productivity is furthercorroborated for the 1980s.

There are some other indicators which explain the 1980s story a little more. Data on investment for the1980s suggest that it remained around a 3 per cent proportion of GDP from 1983-88 and increased to4.7 per cent by 1992-93 (table A4.7). This is not only consistent with the capital intensity argument madeabove, but it also shows that it was the increase in value of capital stock as well as employment increaseswhich characterized growth in the 1980s. Labour productivity driven growth in the 1980s, was due toincreasing overall capital intensity and the number of persons employed, which was being sustained bya relatively stable investment pattern.

Alterations in the composition of investment began in the 1980s. There are falls (table A4.8) during 1982-83 to 1988-89 in the shares of the chemicals sector and the cement sector, while there are increases in thetextiles and food sectors. So it would appear from investment patterns that while the overall intensity ofcapital seemed to be increasing, a sectoral shift was also taking place in the 1980s to less-capital intensivesectors. We need to examine the capital intensities of sub-sectoral shifts to explain this.

During the period 1980-81 to 1990-91, in the large-scale sector, the share of food products declined from24.3 per cent to 14.2 per cent (table A4.9). This is interesting because food was not a highly capitalintensive sector, and although the share in value added of the food sector was declining, investment in itwas increasing;15 the share of textiles increased from 24.3 per cent to 26 per cent and textiles on the wholeare even less capital-intensive than food. It is also clear that both food and textiles are on the middle tolower end of the capital intensity scale in the large-scale sector taken as a whole. The chemical sectorsshare increased from 13.2 per cent in 1980-81 to 23.5 per cent in 1985-86 and then declined to 14.9 percent in 1987-88 and further to 13 per cent by 1990-91. Industrial chemicals constitute the larger part ofthis sector and are very capital- intensive. Investment figures reported earlier which show a decline for thechemical sector after 1985-86 tend to suggests that there was over-capitalization in the sector in the early1980s.16 These are the only significant changes in the period; the rest of the sectors are mostly not major

of capacity when it is under utilized to start with? Clearly this is what is also partly responsible for the observed increasingcapital intensity in an industry. There are two sides to the issue in Pakistan. One is simply that new entrants in a free marketstructure can enter the industry (unless it is a monopoly) even if there is excess capacity in it. The matter clearly turns on thegains as well as profitability of the enterprise for the individual investor and pricing of capital. This is discussed later.

17 In a situation of positive growth, if capital flows into sectors which have higher levels of labourproductivity(which produce more value added per employed person), then aggregate labour productivity would increase.These high productivity sectors could be correlated to higher capital intensity sectors. It is therefore not plausible to argue thatsectoral flows were mainly causing a general increase in capital intensity in manufacturing in Pakistan.

18 Investment financing and the use of capital are related directly to capacity utilization. It can be argued that oneof the reasons for the recent lower levels of productivity in Pakistan is the under-utilization of capacity. Increases in capacityutilization in the sector would therefore tend to increase productivity (and reduce domestic resource costs).

48

and generally tend to fluctuate with respect to their value added shares in smaller margins. It appears thatthe net result of sectoral shifts has been an increase in capital intensity and this needs to be explained.

There are two factors at work here. Although the major sectoral changes (as well as investment patterns)suggest production may have been moving towards relatively less capital-intensive sectors in the 1980s,it is also the case that 16 out of 24 sub-sectors have individually experienced an increase in capital intensityeven in the period 1987-88 to 1990-91 (table A4.2). Furthermore, while the food sector’s (the major loser)capital intensity, contrary to the trend actually declined in the period , the capital intensity of the textilesector (the main gainer) increased. Capital intensity of the chemicals sector also declined during the late1980s.

It can be argued that taking into account overall increases in capital intensity across the manufacturingsector, and the specific changes in the capital intensity of the main losers and gainers, the sub-sectoral shiftsin the 1980s are likely to have accompanied increasing capital intensity on the whole. Although,counterfactually speaking, had the shifts in the major sectors not taken place the capital intensity wouldhave increased even more.17

Finally, data on capital-output ratios is also available. An increasing capital output ratio suggests that thevalue of capital stock in relation to the value of output is rising. Assuming stable prices, this is consistentwith either an increase in capital stock or a decline in production. A decline in production, which wouldtend to raise the capital- output ratio, is consistent with a crisis of demand and excess capacity buildingin industry. Therefore rising capital-output ratios are consistent with building excess capacity. Fallingcapital-output ratios suggest the opposite. The latter was the case in Pakistan during the 1980s (tableA4.3). To the extent, excess capacity that it existed was being used up in the 1980s. It was a relativeincrease in output despite the increases in capital stock which characterized the capital intensive–labourproductivity driven growth of the Pakistan economy in the 1980s.18

We now return to the issue of the low elasticity of the manufacturing economy. It is arguable that the1980s high-growth period’s low elasticity of employment and shifting source of growth (from beingunequally shared between employment and labour productivity to being labour productivity driven) isconsistent not only with an increasing capital intensity in general across the large-scale sector, but also acompositional shift to relatively less capital intensive sub-sectors within manufacturing.

By the end of the 1980s, a slowdown in growth began to take place. What were the characteristics of thisslowdown and what were its causes?

The 1990s: A period of low growth

19 Estimates of contract workers vary. They increased from 4.9 per cent (1980-81) to 6.3 per cent (1987-88) of thetotal industrial labour force (Shahid Associates, 1989). It is very likely that this process has continued through the 1990s.

20 Some investment is likely to occur, to replace existing capital in a low-growth situation and may itself raise thecapital–labour ratio.

21 As previously mentioned, the Census of Manufacturing Industries (CMI) data are unfortunately unavailable forperiods after 1990-91. Physical production data collected by the Federal Bureau of Statistics are used for estimating valueadded for the large-scale sector after 1990-91.

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During the 1990s growth has moved from positive to negative. We cannot say much about employmentlevels because of data constraints. With increasing flexibility in labour markets, it is likely that employmentmay have declined, and contractual changes occurred.19

Even if growth is declining and turns negative (output increases less and less and then declines) a capitalintensity rise (which reduces employment in relation to capital) will show up as an increase in labourproductivity (the production of output or value added per unit of labour) but this will be for differentreasons than in a high growth situation. Capital intensity can rise for two reasons: an increase in capitalstock and a decline in employment. In a period of zero or negative growth, a rise in capital intensity islikely to be due to a decline in employment as opposed to an increase in capital stock.20 This means thatif labour productivity increases it does so because the rate of fall of output (value added) is less than therate of fall of employment. The issue really turns on how flexible the labour market is. If the number ofemployed decline, and output declines as well, an increase in labour productivity is as possible as a declineis. It depends on the respective rates of decline. It is not clear whether Pakistan is already in this situation,but it may be close to it.

Consequently, the same indicators of increasing capital intensity and increasing labour productivity cancharacterize two very different situations. It is fairly clear from the data that growth in the 1990s sloweddown (table 4.2). Declining and low as it was it is equally clear that growth was even more dominantlybased on labour productivity increases than employment expansion than in the 1980s. What was thesectoral basis of this rising labour productivity?

Investment declined in the sector from 4.7 per cent of GDP to 2.7 per cent from 1992-93 to by 1996-97.It is, however, still likely that capital intensity in the sector increased, from the foregoing discussion andthe data at our disposal. The 1990s also indicate only slight changes in the composition of output (tableA4.10). 21 By and large, shares of output show variations of a small margin for the main sectors. The1990-91 pattern of industrial composition continues. The only sector which shows any serious increaseis the textile sector. The relatively more capital-intensive sectors reveal a trend decline within a smallmargin.

It is, however, very clear that unlike the 1980s, there is an excess capacity build-up in some of the majorsectors of the economy (table A4.11). We have information for 1990-91 when capacity utilization wasaround 60 per cent. Recent trends based on Planning Division estimates suggest a declining trend inselected sub-sectors. In the recent period from 1992-93 to 1995-96, capacity utilization has declined ontrend in the spinning, sugar, and cement sectors. It has remained stagnant in weaving and increased onlyin fertilizers. This clearly suggests an overall decline.

It can be argued that the 1990s picture is characterized partly by a failure of demand in the large-scalemanufacturing sector. The low level and declining growth of output and employment, declining investmentsand the build-up of excess capacity all point to this failure. The increase in capital intensity (like theincreasing labour productivity in the 1990s) which characterizes the growth process, needs to be matched

22 The point is general, but one that is often missed. An adjustment and reform period is likely to depress demandand an overall slowdown in growth and investment is to be expected. This affects the investment climate. If the adjustmentprocess is also accompanied by the withdrawal of public sector from the economy, it is more than likely that the private sectorwould not, due to the altered investment climate, immediately step into public-sector shoes. Even if the theory is right, thismove is likely to take place after a substantial lag. In the case of Pakistan it is arguable that there has been a failure in thesequencing of reforms which may have affected growth.

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with declining capital productivity and is therefore more indicative of shrinking employment than anincreasing capital stock and value of output.

What is responsible for the slowdown in growth? Apart from the general failure of demand argument, thereare two broad answers to this question. One relates to macroeconomic policies and the other to theinvestment climate.

From the macroeconomic perspective, Pakistan has pursued deflationary policies since the beginning ofthe reforms in 1988. This is supposed to have short-run consequences for growth, which are notinconsistent with what can be discerned for the 1990s. Among other issues this also includes thewithdrawal of the public sector in the economy under depressed demand conditions.22

Since the decline in investment is also for the more recent years, it may partly be due to the unstableconditions of production and investment (i.e., the law and order situation) in both Karachi and the Punjab,which have clearly deteriorated in the recent past.

8. TOWARDS A POLICY OUTLINE

The challenge for the manufacturing sector in Pakistan is considerable. A concerted effort is neededtowards increasing the low elasticity of employment as well as output growth. This effort needs to focuson reviving demand and improving the social climate for investment, on increasing the utilization ofexisting capacity and promoting growth in sectors with a potential for autonomous productivity increases.

Criteria of sectoral choices in an employment-friendly investment plan

Some of the above findings can assist in the formulation of an employment-friendly investment plan for thefuture. It is therefore recommended that in the selection of activities to be promoted, the following factorsmust be borne in mind when developing the criteria for sectoral choice:

• sectors should have some potential for autonomous productivity growth; • sectors should have some employment-generating capacity; • sectors should be producing sufficient value added (such that the capital intensity/negative

employment effect is offset by the expansion-high value added/positive employment effect); and • there should be a separate assessment of demand conditions in such sub-sectors and those which

seem relatively unconstrained must be promoted.

The mechanism of sectoral promotion should be affected through two means. First, via the bankingsystem, which should try to guide investment. Sub-sectors fulfilling composite measures based on the abovecriteria need to be identified and a system of incentives offered through the financial system to realize thedesired flows into these sub-sectors.

Fiscal expansion and demand

23 The idea is to decrease unproductive as opposed to productive expenditure of government.

24 In fact one of the failures of sequencing of economic reforms in Pakistan has been to go ahead with financialliberalization before a budget reform.

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Given that part of the problem may be in government pursual of deflationary policies under the reforms,which has led to a decline in demand for manufactured goods, it may be worth examining the worth ofexpansionary fiscal policies, to revive demand. To the extent that capacity is under-utilized (investmentrequirements become less) and the manufacturing sector is not primarily export-based, the case may havesome merit.23

The budget deficit and working capital

A critical factor in freeing affordable resources for the manufacturing sector is the degree to which thegovernment budgetary deficit falls and the government borrows a smaller amount of money from thebanking sector. Capacity utilization and employment can increase without substantial increases ininvestment. There is a clear link between the budget reform government and the relief of working capitalconstraints in manufacturing. This is, however, not inconsistent with the selective fiscal expansionsuggested above.24

Promotion of sub-sectors through tariff rationalizations

In order to revive growth in manufacturing, the profitability issue needs to be addressed directly. Thisentails a serious examination of the structure of tariff rationalizations and the matter is likely to becritical. The development of the manufacturing sector has become somewhat lop-sided over the years, asproduction has moved against high value added products. If corrected this may benefit the sector as awhole. Tariff rationalization can result in improvements in the relative profitability of the chemicals andengineering sectors (the sectors falling behind) and arrest the trend in the overall composition ofinvestment and output in the large-scale sector. This is important to do for the general health of the large-scale manufacturing sector, even though it may be true that some parts of these non-traditional sectors maycomprise relatively capital intensive activities.

Capital pricing and directing new investment

Another issue concerns investment itself and the price of capital. It is questionable if capital is priced inrelation to its opportunity cost. If capital were priced at its opportunity cost with prudential regulations,then the true costs of investment would be transparent to investors and lenders. This is clearly not the casein Pakistan, and the crisis of bad loans that the financial sector is facing is testimony to this fact. Arguablythe weakest link in the financial sector reforms which have taken place in Pakistan, it also highlightssomething that is fairly obvious but often ignored, namely that in many instances market-based reform mustbe complemented by institutional reform in order to be effective.

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The co-ordination of capital flows

Unlike the earlier period, when credit plans were coordinated by government to put sectoral ceilings onbank lending, direct leverage for credit allocation is no longer used by government and credit is controlledindirectly through discount rates, open-market operations and liquidity requirements. It is, however, stillpossible for banks to collude with respect to sectoral lending priorities, as they have a significant interestin the setting up of new plants and improving the overall use of capital. Banks therefore clearly have astake in the provision of capital which is invested and there is much that can be done in this area.

The revival of sick industries

There is another important issue which needs to be assessed concerning capacity utilization and theperformance of the manufacturing sector in Pakistan . A large number of industrial units have closed downover the last few years and a considerable number are operating below capacity; as many as 2,533industrial units are closed and another 1,252 units are running losses (Report of Committee on Sick Mills,1996). The units have become ‘sick’ for several reasons which need to be distinguished. The checklistincludes: over-capitalization of different industrial units; over-capacity in the unit’s industry as a whole;inappropriate site selection; inappropriate choice of technology, lack of working capital; and basicmismanagement. Units operating below capacity could also be facing a slackness in demand, energyconstraints via load shedding, or the non-availability of complementary inputs. Solutions vary accordingto the dominant cause of the sickness of unit and these must be identified in a fair amount of detail for aserious attempt at devising revival strategies. In general, the question is whether anything can be done toincrease the utilization of capacity in the present circumstances.

Tax policy and flow of goods

As indicated above, in recent years Pakistan has been pursuing deflationary policies in the context ofeconomic reforms, with a direct influence on the decline in demand for manufactured goods. The increasein sales tax and regulatory duties on raw materials and intermediate inputs has at the same time madedomestic manufacturing less competitive against smuggled goods. It is therefore important to assess theeffect of government taxation efforts on competition, in the presence of leaky borders. There may besomething which can be done here.

Energy pricing

Load shedding has been a constraint to industrial growth in the past in Pakistan. It is expected to beovercome because of increased capacity, although the whole matter of an inefficient energy distributionsystem still needs to be addressed. Whatever the determinants and cost parameters associated with thegrowth of the energy sector, it is fairly clear the issue of energy prices will be critical for the growthprocess. Higher energy prices may still constrain the utilization of capacity. Consequently, a critical factorin the increase in the utilization of capacity in manufacturing is the degree to which energy prices increasein the economy.

9. UPSHOT

We have attempted to explain the trends of employment and growth in the manufacturing sector in Pakistanover the 1980s and 1990s. There are some features of this review which need to be highlighted. A low employment elasticity is a structural feature of the manufacturing sector in Pakistan. We find thattrends in growth rates suggest a decline. The 1980s were a high growth period while the 1990s arecharacterized by low growth. Growth in manufacturing since the 1980s has been driven by labour

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productivity as opposed to employment expansion; the last period in which employment expansion tookplace was the (low growth) period of 1970s. It can be argued that output growth began de-linking itselffrom employment in the 1980s and became de-linked from employment expansion altogether in the 1990s.Part of the explanation of this feature lies in the distinction between the small and large-scale sectors inmanufacturing in Pakistan. It is the small-scale manufacturing sector employment which declined in themid 1980s, while its output grew. In the large-scale sector both employment and output growth have beenpositive in the 1980s and most of the 1990s. In other words, the de-linking of employment from outputgrowth which was taking place in the manufacturing sector in the 1980s and which was established in the1990s, may have been due to the overwhelming weight of declining employment in the small-scalemanufacturing sector and not because of the large-scale sector as such.

A policy implication of the above is that employment growth needs to be promoted in the small-scalemanufacturing sector, while output growth needs to be revived and the low elasticity of employmentincreased in the large-scale sector. Therefore the centrepiece of an ‘employment generation’ strategywithin manufacturing should be the small-scale sector, which is larger in weight (around 83 per cent). Incontrast, the primary focus of a ‘revival of growth’ strategy is the large-scale sector where the bulk ofmanufacturing output (around 70 per cent) is produced. It is this sector’s growth which is likely to havepositive linkages with other sectors, including the activities in small-scale manufacturing as well as small-scale non-manufacturing.

Examining labour productivity, the engine of growth in the sector, it is fairly clear that labour productivityin Pakistan’s large-scale sector has been dominantly due to increasing capital intensity, but it is worthnoting that autonomous increases in productivity are not unknown. The labour-productivity led growth isnot alarming in itself since such increases are expected over time. The periods of high growth in the 1980sand low growth in the 1990s need to be differentiated on other grounds. While both periods arecharacterized by increasing capital intensity and labour productivity in large-scale manufacturing,investment trends in the 1980s are stable and positive while in the 1990s they are declining, just as excesscapacity is declining in the 1980s and is increasing in the 1990s. The examination of total factorproductivities sums up the situation well. These increased in the 1980s and declined in the 1990s. Thedifference was not in labour productivities which rose in both periods, but in capital productivities whichincreased in the 1980s and declined in the 1990s.

The challenge for the manufacturing sector in Pakistan is considerable. A concerted effort needs to be madetowards increasing the low elasticity of employment as well as reviving growth. From our analysis it isclear that a crisis of demand may be in the process of setting in the large-scale manufacturing sector. Thecauses are complex and multiple but two issues can be singled out which may explain the slowdown of the1990s. One concerns the investment climate in Pakistan which has not only deteriorated but spread fromthe 1980s to 1990s; the second relates to post-reform deflationary policies adopted by the government (andtheir sequencing) in the late 1980s and 1990s, (which were accompanied by privatization and public-sectorretrenchments). These are likely to have dampened demand and the supply of working capital for themanufacturing sector.

A multifaceted policy initiative is required in order to revive growth in the large-scale manufacturing sector.This effort in the large-scale sector needs to focus on reviving demand and improving the social climatefor investment, on increasing the utilization of existing capacity and promoting growth in sectors whichalso have a potential for autonomous productivity increases. Some policies consistent with these aimshave been suggested.

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CHAPTER FIVEThe Small-Scale Enterprise Sector

1. INFORMATION AND DATA

There is a serious limitation of information on the Small-scale Enterprise Sector (SSE) in Pakistan andwide discrepancies exist between data available from different sources. Our earlier discussion suggests thatthis sector is of critical importance with respect to employment, especially its manufacturing component.Manufacturing employment growth as a whole has linkages with employment in other sectors of theeconomy. The structure of employment in manufacturing is such that the bulk of the manufacturing sector’semployed persons are located in the SSE sector. Thus, it is the SSE manufacturing sector which hasemployment absorption potential. In this chapter, we look at the SSE sector as a whole but with particularemphasis on SSE manufacturing.

As the data on the sector in Pakistan is often incomplete, irregular, and varying in definitions, the task ofproducing an ‘overview’ is difficult. In making this attempt, we rely on National Income Accounts, theLabour Force Surveys, each of the major surveys done for the SSE sector in Pakistan, as well as someimportant micro studies done with the SSE as a focus.

2. DEFINITIONS

Small-scale Enterprises are defined in this section as firms using less than 10 workers. However, differentdefinitions are used in Pakistan for varying purposes. The definition intended for statistical use and datageneration has undergone a change from being asset value (Rs. 2 million or less in 1976-77) based to beinglabour (less than 10 workers) based.

Definitions which are not for classification purposes but entail ‘policy support’ to the SSEs in the form ofloans and tax relief, differ widely according to the assessing authority and are almost always capital based.For example, the State Bank of Pakistan, the central government as well as provincial governments, eachinvolved in lending decisions related to the sector, have different cut-off capital values which ‘constitute’for them, the SSE sector.

3. ESTIMATES OF OUTPUT AND EMPLOYMENT IN SSE MANUFACTURING

Partial estimates of the output and employment of the sector based on National Income Accounts (NIA)and Labour Force Surveys (LFS) are reported in the Economic Surveys (ES). They suggest that the SSE’soutput share in manufacturing is around 30per cent while its employment share is nearly 83 per cent (tablesA5.1 and A5.2). These figures have already been encountered in our general discussion on manufacturing.Data reported in the Economic Survey (ES), however, calculate the size of the small-scale sector as aresidual. In short, according to this data we have a very high share of employment within manufacturingwhich goes to the SSE. Another characteristic of the SSE sector is its allegedly high growth rate of output.The combination of its high employment absorption capacities and as its high growth rate makes this sectoran appropriate focus from an employment perspective.

1 The major surveys are: The Small Household and Manufacturing Industries (SHMI) 1983-84, 1988; The Censusof Establishments 1987-88, The Household Integrated Economic Survey (HIES) 1987-88, 1990-91; The Integrated Survey ofService and Manufacturing Industries-Small, (ISSMI-Small), 1992. There are three micro studies based on sample surveyswhich are comprehensive in their coverage of many important structural characteristics of the SSE and are of interest to us.These will be referred to by name in the text. The largest survey of 1417 firms is also the most recent, conducted in 1992, byKemal and Mehmood [Kemal A.R. and Mahmood Z., 1993]. The second largest survey of 806 firms was conducted in the mid-80s by Cohen and Havinga, [Cohen S.I. and Havinga I., 1988]. The third largest of these surveys is of 328 firms conducted in1989 by Nadvi, [Nadvi K., 1990]. Two other surveys have larger samples, but their results are more limited in terms of ourcharacteristics. One is a survey by Burki in collaboration with the Freidrich Ebert Stiftung (FES), of 2,030 apprentices andtheir masters (Ustaads and their Shagirds), [Burki A.A., 1989]. The other is a survey of 600 rural firms conducted in the late1980s by Aftab, [Aftab K., 1990]. In addition there are two assessments of the role of the Panjab Small Industries Corporationand its established industrial estates by the Panjab Economic Research Institute (PERI) [PERI, 1985, 1988]. Finally there area large number of purposely partial sector coverage studies on women and children in the SSE sector; two policy studies byFrerks, Thomas, and Thomson, [Frerks G.E., Thomas H. and Thomson L.B.M., 1989], and the World Bank, [World Bank,1991].

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Levels of employment and growth rates, as reported in the Economic Survey, are shown in tables A5.3 andA5.4. Our alternative sources of information are mentioned.1 On the basis of a thorough review of muchthe information available on the SSE sector in Pakistan (Appendix 1) in the major surveys, we present oursynthesis of employment output and growth in the sector below:

4. The decline in SSE manufacturing employment in the mid-1980s discernible from the EconomicSurveys is plausible and the pattern is likely to continue. Since comparing alternative surveys overtime is not feasible, the trend is likely to have continued, especially since we do know that overallGDP growth declined and has not since picked up in the 1990s. Employment growth in SSEmanufacturing is likely to have therefore declined on trend, if it has not been negative during thepost-1991 period.

5. The level of employment in SSE manufacturing is likely to be lower than the three million ballpark figure (in 1988) based on LFSs. How much lower is a matter of guess work, it may be as lowas even half that figure, but its level does not alter our view on the trend of employment growth.

6. The growth of output of SSE manufacturing, estimated for the sector in NIA is likely to be veryseriously lower than what is reported in the Economic Surveys. Instead of averaging around the8 per cent mark, it was probably closer to 4.3 per cent in the 1976-77 to 1983-84 period and 4.7per cent for the 1983-84 to the 1988 period; and a much lower 2.6 per cent from 1983-84 to 1992-93. Therefore the 1980s figure is closer to 4-5 per cent and the 1990s figure is much lower.

7. The SSE manufacturing value added or employment shares are unlikely to exceed a quarter oftotal value added and employment in the sector. Within sub-sectors in manufacturing it is textiles,food, wood products and fabricated metals which dominate both value added and employment.Textiles in turn are dominated by weaving and the carpet industry, which also have dynamic exportlinkages.

Apart from our findings on the size and growth of the sector synthesized above, mean incomes are alsofound to be lower in SSE manufacturing than in the large-scale sector. As its growth is unlikely to be ashigh as is assumed in the data reported in the ES, we need to emphasize both the revival of growth andemployment generation in any strategy for the sector.

We have based our synthesis on a careful assessment of the numbers available from different sources.There are some implications:

2 ILO-SAAT, Mahmood, M., 1997 (mimeo).

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First, there are sufficient grounds for re-examining the growth rates assumed for the SSE manufacturingsector in the National Income Accounts. A much more detailed investigation is necessary, but thebackground research done for this report has taken a first step in this direction.2

Second, these qualifications do not alter the thrust of our employment strategy for the manufacturing sectoras a whole, or the SSE component of it. Employment is still much higher in SSE manufacturing than large-scale manufacturing. The trend of an arrested or declining employment growth evidenced in the mid-1980sis still likely to be valid.

Third, the focus of a strategy for the SSE manufacturing sector is employment expansion through growth,as this is where many of the employment linkage effects discernible for `manufacturing’ at the aggregatelevel may be forged into the rest of the economy.

4. CHARACTERISTICS OF THE SSE SECTOR

The size of the rest of the SSE sector compared with its manufacturing component is likely to be muchlarger both in terms of value added and employment. It could employ anywhere from four to six and a halfmillion persons. In our view, the figure is a closer to the former than the latter. In Annex 5.1, we examinethe basic sectoral profile of the SSE sector which can be gauged from the large-scale surveys done inPakistan during the 1980s and 1990s. It is worth noting that trade and services are the largest sub-sectorsin SSE manufacturing, which may employ up to 70 per cent of the persons working in the sector.

There are a large number of micro sample surveys of the SSE in Pakistan. We focus on four of theimportant micro analyses. These are: Kemal and Mehmood (Kemal A.R. and Mahmood Z., 1993; Cohenand Havinga, (Cohen S.I. and Havinga I., 1988); Nadvi, (Nadvi K., 1990), and Aftab (Aftab K., 1990)from now on referred to by the authors’ names. Our objective is both to get some answers to questions ofpolicy relevance and to qualify the estimates of what we already know about the broad attributes of thesector from the data in major surveys. We focus on two important areas: the demand and output of the SSEfirm; and its productivity and returns. The larger survey: ISSMI-Small, 1992-93, is mainly used as thebenchmark.

The SSE firm: Subcontracting and demand

ISSMI-Small for 1992-93 shows that the SSE sector was not ‘fully integrated’ into the large-scale sector,with no firms solely reliant on sub-contracting. SSE sector firms also seemed to be transient, the vintageof over one-third of the firms being the 1990s.

We can try and qualify this with reference to other studies. For the four sub-sectors it examines, Kemaland Mehmood’s study finds that sub-contracting is predominant (63 per cent of firms) in manufacturingonly. Cohen and Havinga differentiate between substantially self-sufficient firms (SS) and firms linkedto the modern sector (ML). They find (almost by definition), the ML firms rely more on hired labour withoutward sources of inputs and outward sources of demand such as wholesalers, middlemen andgovernment. Aftab’s survey, distinguishing between household and small-scale firms, finds sub-contractingto be very low in rural areas. Nadvi distinguishing between household firms (HH) and larger firms whichhe calls small-scale (SC) finds a high incidence of household firms tied into sub-contracting. This appearslike a ‘putting out’ system where suppliers are the main entrepreneurs and households the main labourers.

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This sub-contracting is unlikely to be a phenomenon exclusive to a large number of SSE firms, althoughin manufacturing it is likely to exist non-exclusively in a significant degree for many SSEs. It is also likelyto rely on household enterprises and have a higher urban incidence.

This clarifies a point made for the manufacturing sector in the overall employment strategy, where weviewed the growth of manufacturing sector employment as critical for employment growth elsewhere in theeconomy because of linkage effects. It is now clear that there is a growth-based linkage between the large-scale manufacturing sector and the small-scale manufacturing sector through sub-contracting. Since thebulk of manufacturing employment is in the SSE manufacturing sector, it is arguable that a decline ingrowth of the large-scale sector and loss of incomes (as in the 1990s) could adversely affect the demandside for goods produced in the SSE manufacturing sector. Consequently the growth of the large-scale sectorwould tend to revive these sub-contracting links and increase effective demand for the SSE manufacturingsector. It is through this revival that employment linkages with other sub-sectors (particularly with tradeand services) could be realized.

Labour use in the SSEs

The ISSMI-Small data shows (table A5.13), that 94 per cent of SSE firms were individual proprietorships.About 41 per cent of firms hired one employee, another 35 per cent employed two persons and another 20to 30 per cent employed between three and four persons.

Kemal and Mehmood find firms rely for about 50 per cent of labour force on family labour, with 37 percent self-employment and 13 per cent family help. The other 50 per cent of the labour force is hired,consisting of 38 per cent employees and 12 per cent apprentices. They also find a higher working week forall types of SSE labour compared with the large-scale sector. Cohen and Havinga find their self-sufficient‘SS’ firms relying more on family labour while Nadvi finds what he terms household ‘HH’ firms relyingmore on family labour.

Kemal and Mehmood find a high incidence of skilled labour in this sector, which is also confirmed for MLfirms by Cohen and Havinga. There is a clear tendency for the SSE to rely significantly on family andhousehold labour, which is used quite intensively.

Capital stock ratios

ISSMI–Small shows a low capital base for the SSE sector. However, two types of firms can bedistinguished, particularly in the manufacturing sector (tables A5.14 and A5.15). Firms with 5 persons orless had a capital-labour ratio which is around Rs 20,000. Those with more employment (excluding onesize category) had a capital-labour ratio which jumps a scalar of 1.5 to 2. These ‘capital-starved’ firms ofless than five persons comprised 83 per cent of manufacturing units. In general, just under a quarter offirms have assets between Rs 1,000 and 10,000, while 84 per cent of firms have assets of a value less than100,000.

Kemal and Mehmood find a lower capital-output ratio for the sector compared with the large-scale sector,consistent with its low capital intensity. On labour productivity, Cohen and Havinga find that their MLfirms have a higher labour productivity compared with their SS firms. Capacity utilization, however, variesin their ML firms and suggests unstable demand, which shows up as low capital-productivity.

The capital intensities in all the micro surveys vary according to expectation. Nadvi’s SC firms and Cohenand Havinga’s ML firms have higher capital-labour ratios than their household or self-sufficient

3 These mechanisms of informal credit include: high interest rate supplier’s credit which varies with the repaymentperiod (up to 15 per cent per month ); buyer’s advance with high implicit interest rates (up to 16 per cent per month); the‘parchi’ system based on discounted cash sales and IOUs; and what is known as the ‘Committee system’, which is based ona central fund with lots drawn for lump-sum withdrawals by members of the group who, on winning, exclude themselves fromsubsequent draws. Remittances, funds taken from relatives, and ‘own savings’ are also sources of capital. Moneylenders arethe most unpopular form of borrowing for the SSEs in Pakistan.

4 The general results of the self-employed being `poor’ encountered earlier in Chapter One is therefore largely dueto the agricultural sector.

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counterparts. The Kemal and Mahmood comparison of the SSE to large-scale sector shows the capital-labour ratio in the SSE to be nearly half that of the large-scale sector.

Capital intensity is low in the SSE sector is low, although firms can be differentiated on two grounds: thosewhich have external linkages are also more capital intensive; those which are capital starved, employ lessthan five persons and are in a majority in manufacturing. This also implies that it is precisely the capital-starved firm employing a lower number of persons per unit that is likely to be part of a refuge sectorwithin the SSE sector.

Credit

The low capital base in the SSE sector can be explained by low access to the formal credit market. TheSHMI 1988 data on credit is available for the manufacturing sector (table A5.16). From a total investmentof Rs 1.7 billion in 1988 over 91 per cent came from private savings, 9 per cent from the informal creditmarket and 1 per cent from the formal credit market. This is consistent with the World Bank findings whichestimate around 2 per cent of the loans flowing to the SSE from the formal sector (World Bank, 1991).

HIES 1990-91 (table A5.11) also has data on loan access and its impact on the SSE sector. Of the4.4 million units of the SSE, 26 per cent had taken loans from both formal and informal sources. Theproportion was highest for manufacturing (35 per cent) and lowest for hotels (19 per cent). Formal marketcommercial loans were however limited to only 1.5 per cent of the total units, the highest being in trade (2.4per cent). Some impact of these formal and informal loans on income or employment of these units canbe seen. The average monthly income of an SSE without any loan is Rs. 2086; of an SSE with only aninformal sector loan is Rs. 1796; and of an SSE with a formal sector loan is Rs. 2627. Similarly, in firmswith zero-borrowing average employment is 1.53 persons; firms with only informal loans have a similaremployment level of 1.51; but SSEs with formal sector loans employ 2.06 persons on an average. Formalsector credit can have a significant impact on the employment and income of SSEs.

The informal credit market is the main external source of funds for the SSE sector. A report by the WorldBank (World Bank, 1991) identifies different forms of urban informal credit mechanisms operating in thesector, although these are likely to be relevant in both urban and rural contexts.3 The access to a formalcredit market is therefore weak, especially for household-based firms, although it is clear that the links withit are beneficial for the SSE sector.

Incomes

The returns to self-employment in the SSE sector, which are returns to both capital and labour, are fourtimes greater than the hired wage rate in the SSE sector.4 The hired labour wage is also significantly lowerthan the large-scale sector wage in Kemal and Mehmood’s study. Cohen and Havinga find that their MLfirms compared with their SS firms have 66 per cent higher income. They also find income inequalitiesbetween owners and labour to be higher for ML firms than SS firms.

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It is appears that returns to both capital and labour for owners and labour are generally low in the SSEsector compared with the large-scale sector. There is demand based differentiation within the SSE sectorbetween modern sector linked (ML) and self-contained/self-sufficient(SS) firms. External linkage in theML firms is likely to improve their incomes.

5. OVERVIEW

These indicators show the SSE sector as partly a refuge sector, inflated by low productivity employmentabsorption in agriculture on the one hand and a small registered formal sector on the other. They alsoshow it to be partly integrated into the mainstream economy where its market demand is based on growingexport niches in textiles, in metal fabrication, and a growing domestic demand for consumption and capitalgoods. In particular the analysis of the sector finds:

• The output growth rate of the SSE manufacturing sector is not as high as the official 8 per centper annum, and may be between a half to a quarter of this for the last decade. The size of the entireSSE sector is large, with employment estimated to be around 4.4 million persons.

• The largest sub-sectors are trade and services which account for 60 per cent of the employmentin the SSE sector. Manufacturing accounts for around 26 per cent of the employment, (and, withinmanufacturing, textiles account for 12 per cent of total employment), followed by catering with11 per cent and fabricated metals and food processing (3 per cent each).

• Within the manufacturing sector as a whole (i.e., large-scale and SSE), the SSE employs the bulkof the labour force. The share of the SSE sector in manufacturing value added is around 33 percent. However its share of capital assets is a much lower. This gives the SSE sector a capital-labour ratio which is lower than the large-scale sectors. The estimates of the difference are wide,ranging from a factor of 2 to 17. As a result of its low (and depreciating) capital and technologybase, the SSE sector has a capital-output ratio which is considerably lower than the large-scalesector’s (probably by a factor of 10).

• The SSE manufacturing sector does however display a rich dualism within itself. Some of itsenterprises appear more integrated into the mainstream economy, act entrepreneurially, are basedon hired labour, have better access to the formal credit market, have higher capital assets, a higherproductivity, and better returns. Other enterprises are more involuted, appear to be recipients ofa ‘putting-out’ system, are based more on family labour, are more reliant on the informal creditmarket, have lower capital assets, lower productivity, and lower returns.

6. THE SUPPLY AND DEMAND FOR SSE GOODS AND SERVICES

We now examine some supply and demand side issues that have policy implications for the SSE sector.Our objective is to explore some potential sources of promoting the employment and output growth of thesector.

Changes in purchasing power of social groups and demand

It is worth investigating this issue of demand. We know from the foregoing that if our dualism hypothesisis correct, then the dynamic part of the SSE is more linked into the structures of demand in the economythan its involuted part. Demand for the sector can be articulated through cross-sectoral linkages (sub-

5 These effects should result in a relatively greater growth of the capital goods sector in the later 1980s to accountfor a lag in the accelerator of demand for consumption feeding the demand for capital goods.

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contracting) as well as through changes in the purchasing power of consumer groups. Further this demandfor the sector’s output can be directly policy-induced, as well as a result of wider changes in the economy.The latter are often expressed through changes in the purchasing power of social groups.

Remittances

An increase in the purchasing power of a significant group in the economy can lead to an increase indemand of the SSE and large-scale sectors. Remittances have clearly had an impact on the purchasingpower of families of the migrants. Pakistan has had a history of migration during the 1970s and 1980s tothe Gulf states. Many of the migrants have originated from rural areas of the country. The migration-basedremittances from the Gulf arguably had a demand-boosting effect on the SSE (Hamid, 1983). Howevernow that migration is not a major phenomenon in Pakistan, it is unlikely that the demand effect on SSEgoods would further increase from this source. Historically speaking, it is likely that (and especially to theextent that this migration was rural) there was an initial boost to SSE consumption goods demand fromremittances but with increases and stabilization in the wealth of recipients this should have been slowlyshared with demand for goods from the large-scale sector.

The green revolution and differentiation of the peasantry

A possible new source of purchasing power is the differentiation of a largely self-subsisting peasantryproducing their own consumption goods, into landless wage labour demanding both capital goods as wellas consumption goods to supplement their incomes. There has been increasing landlessness in theagricultural sector in the past two decades (Mahmood, 1993). The increased demand from these lowerincome groups will tend to be largely from the SSE sector. The assumption here is of course that landlesslabourers’ share of consumption goods (and capital goods) from SSE production is greater than therespective share of landlords and large owner operators.

An effect of remittance and landlessness should be evidenced in the growth of consumption goods in theSSE, (especially in the food, textiles, and wood sub-sectors) over the 1970s and 1980s.5 Since both out-migration and the remittance effects are now likely to be small, the landlessness effect should be what isof relevance. It is important to note that although it has the same effect on the SSE sector, the landlessnesseffect is not unambiguously a result of increasing prosperity, as is the case with the remittance effect.

The income and technical change effect of the green revolution

Another source of increasing purchasing power in Pakistan has been the profitability-enhancing, input-intensive green revolution in agriculture. The High Yielding Variety (HYV) inputs and accompanyingmechanization increased demand for capital goods from higher income groups such as large farmers andlandlords. The resultant profitability should have increased the demand for consumption goods from boththe SSE and the large-scale sector. It would seem that these income groups, after some time in whichcapital and wealth are accumulated, tend to switch expenditure to the products from the large-scale sector.

Depreciation of exchange rates

A drop in the real exchange rate can increase the demand for SSE goods. The exchange rate depreciationhas been in effect in Pakistan for the past two decades. The idea is that more expensive imports of capital

6 The impact of devaluation can be ambiguous, as seen in the analytical model by Mahmood (Mahmood, ILO-SAAT,1997). As imports drop, both the large-scale and the SSE sector can gain, depending upon the demand factors and how thelandlessness and remittance effects are balanced by the technical change effect. That is, the share of the SSE sector relativeto the share of the large-scale sector in the production of consumption goods can increase, decrease, or remain constant.Similarly, the share of the SSE sector relative to the large-scale sector in the production of capital goods can increase, decrease,or remain constant.

7 This is probably due to the exogenously given demand for carpets whose share drops over time.

8 The technical change effect does not feed through to the SSE sector fabricated metals in general, although it mustbe contributing to the increase in share of agricultural and textile machines.

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and consumer goods, mainly in the large-scale sector can increase the demand for the domestic productsof the SSE sector.6

7. SOME INFERENCES

If survey data SHMI for three points in time is assessed (See table A5.9), we can infer the following:

– The food sector's share in value added, assets, employment, and the number of units has increasedbetween 1976/77 and 1988, as expected. The data show that the textile and leather sectors havenot increased their share over this period.7 The share of the weaving sector increases in terms ofvalue added, assets, employment, and the number of units. This supports our hypothesis aboutconsumption goods produced by the SSE sector and is consistent with the landlessness andremittance effects improving the purchasing power of the poorer sections of society with respectto the SSE.

– It is also clear that while the fabricated metal sector decreases its share over time, the share ofagricultural machinery increases marginally, while the textile machinery sector is born.8 All thevariables (unit numbers, asset values, employment and value added) for these sub-sectors increase.This supports the posited income and technical change effects of the green revolution.

– The CE 1987/88 data (table A5.17) gives the vintage of firms for three periods: pre-1970, 1970to 1979, and 1980 to 1988. It shows that at least 70 per cent of the SSE firms in manufacturinghave a post-1980 vintage. This may reflect the short life of SSEs or a recent growth spurt.However, at least in relative terms, the food, textiles, and wood sub-sectors have the highestproportion of vintages for the 1970s. The metals, fabricated metals, and chemicals sub-sectorshave the highest proportion of vintages for the 1980s, which is also consistent with our hypotheses.

The above discussion suggests that many factors may work simultaneously to affect the demand of SSEsector and that these may not always work in the same direction. For example, the remittance effect islikely to favour the SSE more in the initial period. The differentiation of the peasantry (throughlandlessness) associated with the green revolution, would largely affect the SSE sector positively. Boththese effects are likely to feed into the capital goods sector with a lag. On the other hand, the income andtechnical change effects of green revolution may be biased in favour of the large-scale sector.

8. POLICY AREAS

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Government policy, as a whole, towards the SSE sector is likely to fall into two categories, committed andomitted. Committed policy is GOP attempts to help the SSE sector. Omitted policy is default policy, theactual impact of all its macro policy for non-SSE and SSE sectors, on the SSE sector.

There are three areas in which policy of the government can be strengthened.

Credit policy

The SSE sector gets an estimated 2 per cent to 4 per cent of its credit from the formal sector, despite allthe institutional schemes - this is committed policy. However, more recent data sources like ISSMI-Smallshow that formal market credit for the SSE sector may be higher, or may have increased by 1992/93 toabout 19 per cent of the units. Omitted policy is the high volume of concessionary credit mainly flowingto the large-scale sector, which results in a disincentive to invest in the SSE sector. The net result of bothcommitted and omitted policy is the low levels of investment and depreciating capital base seen for the SSEsector in manufacturing.

The provincial government credit programmes are based on subsidized mark-ups below the market rate,and along with the GOP programmes have low recovery ratios. Subsidized credit is not viable in the longrun: it contributes to low recovery ratios and is not as important a condition for growth as access to credit.The low recovery ratios reflect bad programme management, remote relationships with the clientele, thelatter's shortfalls in working capital and weak investment planning.

Tax policy

The SSE sector gets fiscal incentives through tax holidays for rural and under-developed areas, andreduction in import duties and excise taxes on industrial estates. Being less import-intensive than the large-scale sector, customs rebates do not affect the SSE significantly. The impact of tax holidays, and reducedexcise taxes on industrial estates also has the impact of industrial relocation rather than generating new netinvestment. This is the impact of committed policy. Omitted policy is that the SSE sector has to complywith 57 tax and regulation ordinances. Withholding taxes on 19 income sources and a turnover tax havebeen added to these since 1992/93. This raises the cost of `formalization’ of the SSE sector and acts as adisincentive. Increases in indirect taxes passed on to the consumer reduce the demand for SSE products.A reduction in import duties through liberalization increase cheaper competitive imports for the productsof the SSE sector.

Infrastructure policy

Of the infrastructural support programme, the industrial estates programme is relatively ineffective, andthe skilling centres programme is nascent and small in comparison to its target groups.

9. A STRATEGIC POLICY COROLLARY AND SOME SPECIFIC MEASURES

If the SSE sector is partly a refuge sector, then survival compulsions will force some SSEs to subsist inconditions of high financial and fiscal distortions. However, within the sequencing of decision making inthe production process, the cost of the input (distorted or otherwise) will often be a secondary issue,preceded by the first choice of what and how to produce. This first choice is based upon technology andskilling. Moreover, technology skilling and an increase in the knowledge base can reduce the high financialand fiscal costs caused by policy distortions.

9 Institutional support programmes, even internationally like the Grameen Bank’s credit programme in Bangladesh,tend not to discriminate sufficiently between the heterogenous segments of their poor/informal/small-scale clientele.

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Given the dichotomous nature of the SSE sector with capital, productivity, profitability and employment(definitionally) rising discretely for enterprises employing above five workers, the provision of skilling andcredit needs to be oriented towards the different nature of these two types of enterprise. Enterprisesemploying below five workers can be characterized as refuge labour and the principal constraint on theirexpansion, given their SSE-internal demand, is that they are credit- starved.

Enterprises employing above five workers can be characterized as refuge capital and the principalconstraint on their expansions given their non SSE/external demand is that they are skill-starved to increasetheir demand. In fact, the appropriate characteristic for each of these two types of SSE enterprises is thatthey are differentiated by their principal constraint. Enterprises, employing below five workers have aprimary supply constraint-credit. Enterprises employing above five workers share a primary demandconstraint - they need to increase demand, which can only be done by increasing their skill and productlevels.9

This analysis implies that policy should direct relatively more credit towards the enterprises employingbelow five workers and relatively more skilling towards the enterprises employing above five workers.Conversely, in the first stage, the refuge labour sub-sector will not be able to absorb skilling and the refugecapital sector will not have a primary credit constraint relative to their demand and production levels. Whatgood future policy must be predicated upon is a thorough study of the poor/informal/SSE sector whichidentifies its heterogeneity more precisely in terms of the sector’s own perceived needs and constraints.What is needed is a participatory appraisal (PRA) methodology applied to a conventional empirical surveyand analysis of the SSE sector.

Some specific policy measures which are likely to enhance employment and growth in the SSE sector are:

• Elimination of subsidies in credit programmes and increasing credit lines through SSE targetedinstitutions.

• A major source of effective domestic demand, as seen in East Asia, is agrarian reform. Extendingownership rights or making tenancy rights effective will boost the demand for SSE products.

• If expansion of social infrastructure, education, health, water supply, sanitation, and shelter aredecentralized down to the sub-district level, their domestic and SSE component will increase.Further, if community programs are associated with this expansion of social infrastructure, thendecentralization reaches the village level and the domestic and SSE component will increase evenmore.

• The probability of export market niching increases with the skill base. This skill base should beexpanded through dedicated institutions.

10. UPSHOT

The main point to note from the above review is that growth rates for SSE manufacturing may not be ashigh as the 8 per cent estimated by the National Income Accounts, since survey-based estimates suggestabout half this growth rate. This does not mean that the emphasis on the SSE sector for employment ismisplaced. However, nor is it as great a panacea for resolving the employment problem as its growthestimates suggest, and we may need to direct policy as much on growth as on employment generation.

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Consequently, there is little ground from a policy perspective to be complacent about SSE growth rates.Manufacturing is around a quarter of the SSE sector in terms of employment and is much the majority inemployment for the manufacturing sector taken as a whole.

This review of existing major surveys, apart from bringing in a perspective on the growth rate problem,also allows us to disaggregate the macro estimates derived for the SSE sector. The macro estimate we settleon, shows the SSE sector employing approximately four and a half million workers. Characteristicsindicate the SSE to be in substantial part a refuge sector based on a spillover of surplus labourunabsorbable in other sectors. The review also shows that trade and services account for the bulk of theSSE sector. The SSE sector is also likely to be underinvested.

Examining small micro analyses, this ‘aggregate’ view of the SSE sector can be disaggregated. There aresome important findings. The first is that the SSE may not be one large refuge sector, but instead ischaracterized by a classic dualism. The micro surveys suggest that one part of the SSE sector maycomprise firms more integrated into the mainstream economy, while the other part comprises of firms thatare more involuted. The more integrated firms are characterized by stronger demand and input linkages,entrepreneurial decision making, better access to the formal credit market, more use of hired labour, highercapital intensity, higher capital and labour productivity, and higher returns. The SSE displays a richdualism in structural characteristics.

A critical and operational result of this dualism is to have a ‘different’ policy focus on SSEs with less ormore than five persons employed. This has implications for specific policies. Targeting and improvingformal credit access and skills, simplifying tax and regulation ordinances affecting the SSE sector arecrucial supply-side measures in general, but the focus of targeting credit must be on the capital-starved,self-contained smaller-sized firms while the concentration of training must be on skill starved, externaldemand linked, larger sized ones. On the demand, side the aim should be to promote export market nicheswith a skills base, to have a decentralized expansion of social infrastructure and conduct agrarian reformwhich at least makes tenancy rights more effective. These would be useful measures for the promotion ofthe SSE sector in Pakistan.

On a broader policy note, it should be recalled that the argument made in this report is that the growth ofmanufacturing-sector employment is critical for employment growth elsewhere in the economy because ofcross-sectoral linkage effects. These are connected to the two types of demand linkages for the SSEmanufacturing sector identified in this chapter. One sort of SSE demand linkage which has been identifiedis an internal one for the manufacturing sector, i.e. the sub-contracting one, which links modern-sectormanufacturing firms to SSE manufacturing. The second type of link is that which is based on directconsumer demand, which pertains to changes occurring in the purchasing power of social groups. Theseare likely to have cross- sectoral implications for other sectors. Promoting both these links is important.

Since the bulk of manufacturing employment is in the SSE manufacturing sector, it is arguable that adecline in growth of the large-scale sector and loss of incomes (as witnessed in the 1990s) could haveadversely affected the demand side for goods produced in the SSE manufacturing sector (the sub-contracting effect). Consequently, the growth of the large-scale sector could revive these subcontractinglinks and increase effective demand for goods in the SSE manufacturing sector. It is through such a revivalas well as the promotion of direct consumer demand through the suggested policy measures, thatemployment linkages with other sub-sectors (particularly with trade and services) could be realized.

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CHAPTER SIXOutline of an Employment Strategy

1. ELEMENTS OF AN EMPLOYMENT STRATEGY

This chapter marshals the main features of the employment strategy proposed in this report. As apreliminary, it must be stated that an effective employment strategy requires as its basis reliableinformation. There is a need to develop a consistent data series on the labour force and other indicators ofemployment conditions in Pakistan based on existing information. In this respect, the urgency of publishingthe full the Population Census is of prime importance.

The employment strategy, as we have outlined it, has two areas of focus. The first concerns general goalspertaining to the labour force and employment. The second concerns sectoral strategies which provide themeans of achieving these goals.

On labour force and employment

For the labour force, we have found that its size with respect to the population of working age is small. Thisis clearly reflected in low participation rates. The rate of growth of the labour force has also been fallingover recent years and, though it has been lower than that of population , it is likely that this labour forcegrowth will pick up in the near future due to the re-absorption of the young who have opted out of it dueto education, as well as the increasing participation of women in the economy. The problems observed todaywith respect to those sections of the labour force ̀ not fully employed will be magnified in the years to come.In other words, the widening gap between the labour force and the fully employed labour force observableover the medium-run past suggests that, small as it is, the unemployment problem is likely to persist andunderemployment that has of late been increasing on trend, will continue to do so. The 16 per cent of thepresent labour force (the unemployed and underemployed) who are 'not fully employed' are therefore likelyto increase even if the present trend of a declining labour force growth were to continue. If we expect anincrease in the growth rate of the labour force for the reasons cited above, then the situation is likely tobecome worse. This is the core problem of an employment strategy.

There is a need not only to eliminate the persisting gap between the labour force and the fully employedbut to significantly increase the growth of aggregate employment in the economy as well.

There are two general implications of the above goal that this report emphasizes:

• Preparing the labour force for the future: Since one of the reasons for the decline in the labourforce growth has been the withdrawals of an increasingly younger population due to educationalenrolment, the literacy levels in the labour force though presently low and increasing, will furtherincrease. The withdrawal of a younger labour force because of education today, will be mean aswelling in the ranks of the educated labour force tomorrow. This will pose a serious employmentconcern in the years to come. The prospect has implications for planning an educational, trainingand skilling strategy commensurate with the abilities of a more literate labour force and the needsof the economy of the future.

• Improving the productive participation of women in the economy: The other feature of the labourforce and employment trends worth emphasizing is the low participation rates for women. Therecan be various reasons for this, and those related to data quality and information gathering needimprovement. Nevertheless, female participation rates are very low in Pakistan, and there is needto find out why and increase them. If this means yet another factor which increases ‘the growthrate’ of the labour force, then there is all the more reason to address the issue of productive

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absorption of labour from the demand side.

On sectoral strategies

The report argues that an employment strategy for the future needs to be sector-specific. It has to look tosectors other than agriculture for increasing productive employment and focus on the manufacturing andthe small-scale enterprise sector for employment growth. The main points of the argument are presentedbelow.

The overview of the employment situation in agriculture suggests that over the 1970s, 1980s and 1990s,profitability-driven cropping pattern changes based on the new technological package may have increasedlabour requirements in the sector. The changing distribution of operated holdings, mechanization andtenurial shifts may have partially adapted to, as well as reduced, these increases. The rest of the adjustmenthas had to be borne by the new hired casual labour force, the size of which is increasing. The nature of thislabour force is reflected in the extent of rural underemployment, wage rates and poverty. Whileunderemployment is sizeable (around 20 per cent including the unemployed) it has shown signs of anincreasing trend since the late 1980s. The returns to casual labour suggest that both the levels of real wagesand the size of the non-poor in the agrarian economy of Pakistan have either stagnated or declined in thelast period for which information exists (1987-88 to 1990-91 for poverty and up to 1994-95 for wages).

At the aggregate level of analysis, it can be said that although agricultural growth performance has not beenunsatisfactory, an employment strategy for the future has to look to sectors other than agriculture forincreasing productive employment because of low and declining rates of productivity growth in the sectorand the already massive share of employment it supports. The main focus in agriculture should be toincrease agricultural productivity, which will also mean a reduction in rural poverty, a critical indicator ofrural employment conditions in agriculture.

The structural change in the agricultural sector is manifest at the level of both the production and labourprocess on the one hand and the supply of agricultural labour on the other. Both these changes arenoteworthy from a policy point of view.

First, on the production and the labour process. What is significant about the growth of output andemployment in the agricultural sector in Pakistan, is not so much their rates of growth, but the changingcomposition of the labour force on the one hand and the increased variability in the pattern of its productionover time, on the other. There is much greater volatility in agricultural output since the mid-1980s whichis connected to the widespread assimilation of technical changes in the rural economy, now embedded inthe production process. This translates into a fluctuating trend in the employed labour force, with theincreasing casual labour component on the receiving end of the adjustments to this volatility in output.

The second matter concerns the expanding and impoverished pool of labour reserve from which this casuallabour springs. Landlessness and near landlessness as a consequence of declining tenancy and thesub„¼division of holdings is one element. The other may be a return labour flow into the agricultural sectorbecause of low growth in other sectors of the economy, especially the rural SSE sector. These tendenciesare likely to exacerbate the size of the labour reserve in rural areas, which then has to forcibly get absorbedin agriculture as a last resort.

A policy focus which promotes growth and employment in the agricultural sector in the future thereforeneeds to have as a dual aim:

• the dampening of the relationship between the volatility of output and the livelihoods of theworkforce; and

• making the livelihoods of casual labour within this workforce more sustainable.

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The whole area of provisions of micro credit in rural areas to reduce the enforced dependence of agrowing labour force on the sector and related efforts for the promotion of productive rural non-farmemployment, are of immediate relevance. On the other hand autonomous expansion of employment if it isto take place in as large a sector as agriculture, needs to be integrated with poverty alleviationprogrammes.

The active focus of an employment strategy must move towards manufacturing. Manufacturing output growth is not only strongly related to the growth of output in other sectors but to economy-wide employmentgrowth. In particular, it does have positive and relatively stronger linkage effects on employment growthin most other (non-agricultural) sectors of the economy. Therefore, the greater the extent to which growthin manufacturing is employment based, the greater will be its employment multiplier effects on the rest ofthe economy. Promoting employment-friendly growth through manufacturing does have a potential problem:employment elasticities in it are low and productivity growth during the 1990s has been associated with anegative employment growth. The situation in manufacturing therefore, at least on the face of it, has theproblem that output growth cannot be expected to generate much direct employment. This requires us tomake critical distinction between the large-scale and small-scale manufacturing sectors.

The report argues that the manufacturing sector has a role to play in the revival of employment growth justas it has a role to play in output growth, despite popular perceptions regarding its jobless-growthcharacteristics. It has to be a lead sector from the point of view of future employment generation throughits multiplier effects. We find that trends in output growth rates suggest a decline. The 1980s were a highgrowth period while the 1990s are characterized by low growth. Growth in manufacturing since the 1980shas been driven by labour productivity as opposed to employment expansion, the last period in whichemployment expansion took place was the (low growth) period of the1970s. It can be argued that outputgrowth began de-linking itself from employment in the 1980s and became de-linked from employmentexpansion altogether in the 1990s. Part of the explanation lies in the distinction between small and largescale sectors in manufacturing in Pakistan. It is the small-scale manufacturing sector employment whichdeclined in the mid 1980s while its output grew. In the large-scale sector both employment and outputgrowth have been positive in the 1980s and most of the 1990s. In other words, the de-linking of employmentfrom output growth which was taking place in the manufacturing sector in the 1980s and which wasestablished in the 1990s, may have been due to the overwhelming weight of the declining employment inthe small-scale manufacturing sector and not because of the large-scale sector as such.

An implication of the above is that employment growth needs to be promoted in the small-scalemanufacturing sector, while output growth needs to be revived and the low elasticity of employmentincreased in large-scale-scale sector. Therefore the centrepiece of an employment generation strategywithin manufacturing should be the small-scale sector, which is larger in weight (around 83 per cent). Incontrast the primary focus of a revival of growth strategy is the large-scale sector where the bulk ofmanufacturing output (around 70 per cent) is produced. It is this sectors growth which is likely to havepositive linkages with other sectors including activities in small-scale manufacturing as well as small-scalenon„manufacturing. The challenge for the manufacturing sector in Pakistan is considerable. A concertedeffort needs to be made towards increasing the low elasticity of employment as well as reviving growth.

From the analyses in this report it is also clear that a crisis of demand may be in the process of setting inthe large„scale manufacturing sector. The causes of this are complex and multiple but two issues need tobe singled out which may go some way towards explaining the slowdown of the 1990s. One concerns theinvestment climate which has not only deteriorated but spread (from Karachi to the Punjab) in Pakistanfrom the 1980s to 1990s. The second aspect is related to post-reform deflationary policies adopted by thegovernment in the late 1980s and 1990s, (which were accompanied by privatization and public-sectorretrenchments). These are likely to have dampened demand for the manufacturing sector.

A multifaceted policy initiative is required in order to revive growth in the large-scale manufacturing sector.

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This effort in the large-scale sector needs to focus on reviving demand and improving the social climate forinvestment, on increasing the utilization of existing capacity; and promoting growth in sectors which alsohave a potential for autonomous productivity increases. Policies in many areas consistent with these aimshave been suggested in this report. These include suggestions on:

• Criteria of sectoral choices in an employment friendly investment plan

• Fiscal expansion and demand

• The Budget deficit and working capital

• Promotion of sub-sectors through tariff rationalizations

• Capital pricing and directing new investment

• The co-ordination of capital flows

• The revival of sick industries

• Taxation and flow of goods

• Energy pricing

The report further argues that the sector which may still have potential for direct employment generationis the SSE sector, there are likely to be labour„intensive activities. Dynamic sub-sectors need to beidentified in the SSE sector and practical selection criteria for support need to be developed.

For the SSE sector, a central point to note from our analysis is that growth rates for SSE manufacturingmay not be as high as 8 per cent, as estimated by the National Income Accounts, since survey basedestimates suggest about half this growth rate. This does not of course mean that the emphasis on the SSEsector for employment is misplaced. However, nor is it as great a panacea for resolving the employmentproblem as may be imagined and we may need to direct policy as much on growth as on employmentgeneration. It is therefore arguable that there is little ground from a policy perspective to be complacentabout SSE growth rates. Manufacturing is around a quarter of the SSE sector in terms of employment andis much the majority in employment for the manufacturing sector taken as a whole. Since the bulk ofmanufacturing employment is in the SSE manufacturing sector, it is arguable that a decline in growth ofthe large„scale sector and loss of incomes (as witnessed in the 1990s) could have adversely affected thedemand side for goods produced in the SSE manufacturing sector (the sub„contracting effect).Consequently, the growth of the large„scale sector could revive these sub„contracting links and increaseeffective demand for goods in the SSE manufacturing sector. It is through such a revival as well as thepromotion of direct consumer demand, that employment linkages with other sub-sectors (particularly withtrade and services) could be realized.

The review of existing major surveys, apart from bringing in a perspective on the growth rate problem, alsoallows us to disaggregate the macro estimates derived for the SSE sector. The macro estimate we settle on,shows the SSE sector employing approximately four and a half million workers. Characteristics indicatethe SSE to be in substantial part a refuge sector based on a spillover of surplus labour unabsorbable inother sectors. The review also shows that trade and services account for the bulk of the SSE sector. TheSSE sector is also likely to be underinvested.

This ‘aggregate’ view of the SSE sector has been ‘disaggregated’ in this report by an assessment of theimportant micro surveys on the subject. There are some relevant findings. The first is that the SSE may notbe one large refuge sector, but is instead characterized by a classic dualism. The micro surveys suggest that

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one part of the SSE sector may comprise firms more integrated in to the mainstream economy, while theother part comprises of firms that are more involuted. The more integrated firms are characterized bystronger demand and input linkages, entrepreneurial decision making, better access to the formal creditmarket, more use of hired labour, higher capital intensity, higher capital and labour productivity and higherreturns. The SSE displays a rich dualism in structural characteristics.

A critical and operational result of this dualism is to have a different policy focus on with less or more thanfive persons employed. This has implications for specific policies. Improving formal credit access and skills,simplifying tax and regulation ordinances affecting the SSE sector are crucial supply-side measures ingeneral, but the focus of targeting credit must be on the capital starved, self-contained smaller sized firmswhile the concentration of training demand should be on skill-starved, external demand linked larger sizedenterprises.

Government policy, as a whole, towards the SSE sector is likely to fall into two categories, committed andomitted. Committed policy is the States attempts to help the SSE sector. Omitted policy is default policy,the actual impact of all its macro policy, on the SSE sector. In particular, some areas in which governmentpolicy can be strengthened with respect to the SSE have been emphasized in this report. These relate tocredit, taxation, infrastructure, training and demand creation. Some the specific policies advocated in thisreport concern:

• Refocusing committed and omitted credit policy through the elimination of subsidies in creditprogrammes and increasing credit lines through SSE targeted institutions.

• Restructuring omitted and committed taxation policies.

• Decentralization of infrastructural programmes

• Tying of skills and export markets

• Creating effective demand for SSE products

On the whole employment strategy for the future in Pakistan must aim to eliminate the gap between the‘labour force’ and ‘the fully employed’ within it. It must act not only by attacking unemployment andunderemployment head-on but by adopting policies that simultaneously and significantly increase aggregateemployment. The strategy must function at a sectoral basis. This report argues that an employment growthstrategy for the future must be built with three aims:

• the growth of output and employment in the manufacturing sector

• the limitation of increased labour absorption in agriculture

• the promotion of dynamic sub„sectors within the small-scale enterprise sector

The overarching objective of these aims is to revive growth in such a way that its employment multipliereffects in the economy are significant and there is minimum downward pressure on productivity inagriculture. The positive focus of the strategy is based on manufacturing and the small-scale enterprisesector. In the view taken by this report, this triadic approach constitutes the way towards an improvedemployment situation in Pakistan.

1 For a detailed discussion, See ILO-SAAT/ Arshad Zaman Associates (1997).

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APPENDIX

The Economic Reforms Context of Growth and Employment

1. The periodisation of growth and status of macro-economic policies

This appendix attempts to provide a macro-economic and growth context to the issue of employment inPakistan. A serious study of macro-economic policies and their effects on the different parts of the realeconomy is a more complex and detailed exercise, which is beyond the scope of the present report. It ishowever, the view taken here, that a perspective on macroeconomic policies and growth is a necessarystarting point for an analysis of the employment situation in Pakistan today. In fact, in a dynamic sense,it may be necessary to take in to account the macro policy regime, for a revival of growth that entailsemployment expansion.

The link between macroeconomic policies followed by the government on the one hand and employmenton the other, is mediated by the level and pattern of growth. In Pakistan the links between macro policiesand growth, at least until recently, have involved both economic and non economic aspects. Examiningtrends over the longer historical period we find, that although macroeconomic policies undoubtedlyinfluenced growth, the periodisation of growth itself into high and low phases, introduces factors that arebeyond economic policy itself.

To emphasize the point about non-economic factors, and as a useful perspective on Pakistan’s growthprocess, Table 7.1 attempts a periodisation of its economic and political history simultaneously. There aremany ways in which periods can be distinguished. Of the many demarcation criteria for periods ofdevelopment in Pakistan, the timing of the flow of foreign aid; the forms of political governments; the twomartial law periods (1958-73 and 1977-85); and legal-institutional watersheds such as the threeconstitutions (1956, 1962, and 1973) are important markers. Another criterion, which is more economicpolicy related is the set of eight Five-Year Plans – especially the Second Plan (1965-70) and to a muchlesser extent the Sixth Plan (1982-87) – which lay out strategies and policy frameworks. Since the roleof macroeconomic policies has acquired centre stage in policy debates in the economic reforming Pakistanof today, the periodisation is also given according to both pre and post-economic reform periods. Inaddition our focus within this classification is the set of macro economic policies of the early period ofreforms and the more recent years.

A brief description of the longer historical period is in order, as a starting point..The first two periods inthe Table 1.1 correspond to a Pakistan which includes what is now Bangladesh (1947-71), while the lastthree periods (1971-97) correspond to the present boundaries of Pakistan1. Under pre-1971 Pakistan, fourphases can be identified: 1947-53, was characterized by reconstruction and self-reliant development; 1953-58 was occupied with the preparation of the First Five-Year Plan (1955-60), achieved with considerableexternal assistance; 1958-65 were the “miracle” years of aid reliant development; and 1965-71 can be seenas a period of disintegration, leading to the independence of the eastern wing of the country as a separatenation State.

In the contemporary period (1971-97), three political phases can be readily identified. In the first, 1971-77,an elected government sought to re-orient the path of growth that Pakistan had embarked upon in the 1960s,and ushered in a period of greater state intervention in the economy characterized by widespreadnationalizations. In the next period, 1977-88, a military government which replaced the elected

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government, undid the nationalizations of the first period. In the present phase, 1988-98 , democraticgovernments returned to the country and the economy was re-oriented towards private-sector-led growth.This period is also characterized by economic reforms which the government is now in the process ofimplementing and which are the focus of this Appendix..

Table 1.1:Growth and structural change, 1950-97

1950-58a 1958-71a 1971-77 1977-88 1988-97

Growth rates (% p.a. by OLS method)

Population 2.5 2.8 3.2 3.1 3.0

Real GNP (mp) per capita 0.9 4.2 3.3 3.0 1.1

Consumer prices 2.3 3.2 17.4b 7.5 10.4

Real GDP (fc) Value added in agriculture Value added in LS manufacturing

3.31.8

19.8

6.24.3

12.1

4.82.22.3

6.63.99.4

4.83.94.0

Employment In agriculture In large-scale manufacturing

..

..

..

1.60.83.6

3.01.83.0

2.42.01.7

2.11.0

- 0.9

Structure (% GDP, end period)

Agriculture 51.8 41.2 36.6 22.9 22.4

Large-scale manufacturing 6.1 11.9 10.3 11.6 11.1

Overall budget deficit (-) .. .. -8.6 -8.5 -6.3

Trade deficit (-) -4.9 -3.2 -7.8 -5.0 -4.8

Current account deficit on the BOP (-) .. .. -7.0 -4.4 -7.1

M&LT external debt (DOD US$ billion) (as % of GNP)

..

......

8.352.6

20.049.9

30.046.6

Liquid external reserves (US$ billion) (as months of merchandise imports)

..(..)

0.1(2.3)

0.4(1.9)

0.5(0.9)

2.5(2.5)

Notes: All growth rates have been calculated by fitting an ordinary least squares (OLS) trend... not available.a (West) Pakistan only.b Only 11.1% (OLS, or 9.5% simple average), if 1971-72 and 1973-74 (when imported inflation was anextraordinarily high) are excluded.

Source: Economic Surveys, Annual, and Federal Bureau of Statistics. See ILO-SAAT/Arshad Zaman Associates (1997).

The non-economic correlates of macro-economic policies and growth

In general it can be argued that in Pakistan, the degree of causality between macro policies and growth isweak and it may be difficult explicitly inferring outcomes from the policy. The argument for the

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importance of non-economic policy factors is straight forward. Two overdetermining correlates of thephases of growth (high/low) in Pakistan are:

• the timing of flows of external assistance (economic and military aid) which the State has receivedover time; and

• the performance of the agricultural sector.

It is noteworthy that both correlates are subject to external influences which are governed in part by noneconomic considerations. In the case of external flows, there is a whole set of international geo-strategicconsiderations as well as the nature of government, which may be of relevance. In the case of agriculturalperformance, there is clearly a feature of external natural uncertainty at work. It can be argued thatthroughout the almost 50-year period the volume of external assistance received (on which reliable datais easier to acquire on the economic side) and the performance of the agricultural sector have been theproximate determinants of economic performance. If this is indeed the case, it leads to a peculiar difficultyin attempting any serious analysis of the impact of development strategies and macro-policies on economicoutcomes.

This knowledge of crucial external determinants at the policy level has implications for institutionalbehaviour. It has meant that economic strategy and policy statements have been, at least in some measure,motivated by a concern for maximizing foreign assistance. In particular, the nature of this relation between‘stated growth strategy’ and ‘access to capital’ has had two specific effects on policy making in Pakistan.One concerns state action and the other the robustness of policy itself. First, it has made plans of actionby government, subject to ad hoc executive decisions, which are not transparent. Second, and at theanalytical level, the link between ‘strategy’ and ‘outcome’, when it has been invoked, has often been afortuitous one, even though plan and programme reviews submitted by government to donors have onoccasion sought to establish such links.

However, in the present phase , it is precisely the adoption of specific macro-policies themselves that havearguably come to play an influencing role in the timing of external flows. It is therefore important to assessif these policies have performed the role that they were supposed to, given their raison d’etre.

In any periodization of the political economy of Pakistan, therefore, broader conditions for the sources andflow of foreign assistance must constitute an important criterion of demarcation. This slightly cross-cutsour classification of decades, the 1970s , 1980s and 1990s phases chosen for the analysis of the labourforce and sectors of the economy.

Given the external determinants of past growth and their impact on the nature of the decision makingprocess in Pakistan, two important symptoms of what can be termed the problem of growth anddevelopment in Pakistan become easier to understand.

Two symptoms of the problem of growth

There are two important symptoms of the problem of growth and development in Pakistan, which need tobe singled out for the purpose of our discussion. First, the country’s economic performance has been suchthat growth and structural change have not improved the lives of a majority of the population by anywhere

2 The argument which can be developed here can be based on two points. The first point is that a long history ofnon-democratic periods of government entrenches State structures that are less pressured to be distribution-sensitive. Secondly,a history of excessive reliance on external flows of funds erodes the institutional incentives to develop a progressive taxationsystem to be applied on civil society in order to finance economic development.

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near what that growth process could have achieved. Growth has been insensitive to distribution.2 Asecond symptom of the problem of Pakistan’s growth has been the government’s inability to establish asustainable pattern of public finance, historically relying first on foreign grants, then loans, supplementedby domestic non-bank borrowing, and of late, even by borrowing from short-term private sources. As aresult, Pakistan faces a profile of high increasing future debt service payments. These two symptoms arealso mutually reinforcing. A growth process insensitive to distribution is complemented by theunwillingness or the inability of the State to tax the better-off sections of society (which, in part, is whatmakes the public finance structure narrow and precarious).

Assessing the policy-growth linkage

The employment situation in Pakistan, both in general and at a sectoral level, has been discussed in thisreport. One central concern in this assessment pertains to the 1990s overall slowdown of growth after the1980s boom and, in particular, the crisis of growth in the manufacturing sector. In our view, thisconstitutes a critical matter to address, for any future employment revival strategy. Here we attempt amacro policy based explanation of what happened to growth in the 1980s and 1990s.

Notwithstanding the problems in choosing the right periodization and the matter of external determinantsof growth, an basic assessment of the association between growth and macro-economic policies is at bothan aggregate as well as a thematic level is attempted below.

The aggregate assessment gauges the impact of macro policies taken together during a pre-selected period( i.e. the reform period). The same assessment also to distinguishes between sub-periods within the reformperiod. The thematic assessment on the other hand, gauges results of each type of macro policy area (e.g.trade, fiscal or monetary policy). The latter can also be phased in terms of the pre given periodization (e.g.trade policy in the reform period) or can move across periods (e.g. trade policy from the 1970s onwards).Particular reform policies undertaken by government are distinct insofar as they pertain to different areasof the macroeconomy as well as their implementation over different time periods. Finally, since theexpected effects of macro policies on growth depend, in part, on the interaction between the individualpolicies themselves, it is important to look out for sequencing of reform policies as well.

The aggregate overview

For the aggregate overview, the reform policies can be taken as the ‘package’ and the reform period asstarting from when the first reform initiatives were taken up, to the present. However, in order ask thelarger question on the ‘effect of reforms’, we first need to identify some core objectives of the reforms andthen select the appropriate indicators of their performance. We list below what can be termed the threecore objectives of the economic reforms:

• One objective is that of sustainable growth, if the reform package ‘as a whole’ works it should bereflected in a healthy growth process which is sustainable.

• A second objective is to achieve price stability

• A third objective is balance of payments viability.

3 Because annual data is presented we can do different periodizations. We have also stated on the x-axis aclassification based on reforms and forms of government.

4 The SAL broke down eventually because of differences between the government and the lender. Accordingly, itwas followed by sectoral adjustment loans (SECALs) in energy (1985) and export development (1986). The latter was acompromise option, as the government was not prepared to accept the trade liberalization measures being proposed by the WBfor a trade sector loan at the time.

5 The government has presently negotiated a US$1.6 billion extended structural adjustment facility (ESAF) and EFF,with a first tranche of US$200-250 million.

6 It is of course possible to argue that the reforms undertaken in this period were ‘soft’, and this freedom of notbeing forced in to taking ‘hard’ options was due the political and diplomatic relationships that Pakistan enjoyed internationallyat the time.

7 We will see later, in a thematic assessment, that exchange rate reforms and import liberalization (non-tarrif barrierremoval) were the focus of the first period and financial sector liberalization and tariff reforms the added focus of the second.

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Figure 1 presents trends in major macroeconomic variables since 1971, along with a demarcation of theperiods identified (for data on period averages, see Table 7.1 above).3 We have separated the reform fromthe pre-reform period. Moreover, the reform period has been divided into two sub-periods. It is the casethat one phase of the sub-division can be associated with the part of the 1980s in which manufacturinggrowth occurred. In terms of a reform history, the first reform period marks the first extended fund facility(EFF, 1980-83) obtained for debt rescheduling from the International Monetary Fund (IMF) by Pakistan.In 1982, the World Bank (WB) also extended a structural adjustment loan (SAL) to complement the IMF’sEFF,4 which was later abandoned and then followed by two sectoral adjustment loans (SECALS). Thethird period (from 1988 to the present) has been characterized throughout by intermittent long-termarrangements with the IMF.5

The indicator on economic growth

The data represented in Figure 1 suggests that there has been a downward drift in the rate of economicgrowth, on average at least since the mid-1980s. Therefore, for the initial part of the 1980s, it can beargued that reforms, to whatever extent they were occurring at the time, did not harm growth and may haveenhanced it. In fact, if we recall the data on large scale manufacturing in Chapter Four, the bulk of the highgrowth during the 1980s was in 1982-83 and 1987-88 (the growth rate in this period was 8.2 per cent).Since the reforms affected large scale manufacturing more directly than other sectors, a growth-enhancingrelationship can be posited for this period.6 By the same logic, the next period is one of economicslowdown and declining growth, which can be associated with the nature of reforms undertaken in thatsecond phase.7

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Figure 1: Growth, Inflation, Unemployment Rate, Budget Deficit & the Current Account Deficit on the Balance of Payments

0

2

4

6

8

10

12

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

Fiscal Years Ending June 30

Def

icit

(%

of

GD

P)

0

5

10

15

20

25

30

35

per

cen

t

Budget Deficit BOP Deficit Grow th Inflation Unemployment Rate

Reform Period I /

Military Government

Reform Period II /Elected Governments

1stEFF

State Capitalism /Elected Government

The indicator on price stability in the economy

There has been a secular upward drift in the rate of inflation, during the later reform years. Inflation fellbelow 5 per cent in 1987, but has been rising sharply since then. It is the second reform period which isassociated with rising prices. It is to be noted that these trends on performance indicators appear to beindependent of the size of the budget or the balance of payments deficits - although, naturally, it iscounterfactually arguable that higher deficits would have led to higher inflation and lower growth.

Indicator on external balance

On the count of the balance of payments situation, Pakistan continues to seek extraordinary externalfinance despite over ten years of adjustment programmes, as figure 7.1 shows.

Indicators on labour market conditions

It is useful to review the results in Chapter Two, of the indicators of labour market conditions in Pakistan.Although improvement here may not be an explicit reform objective, labour market conditions have beenaffected in the period and are a central concern for the ILO. The rate of unemployment rose after 1975,stabilized (at around 5 per cent) from 1979 to 1990 and, given comparability problems, is unlikely to havedeclined since then. We have, however, seen in detail (in Chapter One) the underemployment situation aswell, which is a better indicator of employment conditions and, in our assessment, this situation is notimproving. Indicators on poverty and wages (in Chapter Two), which are probably even morecomprehensive signals of labour market conditions in countries where formal labour markets are limitedin scale and scope, show a deterioration in the 1990s.

The overall assessment of the reform experience in Pakistan, taken across sub-periods, therefore requirescircumspection. It is clear from the above evidence that adjustment programmes may not have been able

8 See Thomas et. al., 1991.

76

to achieve at least three of their main aims: (i) sustainable growth; (ii) price stability; and (iii) balance ofpayments viability – in the sense that at the end of the programme there would be no need for furtherextraordinary external financing. In addition, labour market indicators of employment conditions havedeteriorated in the recent period. However, on balance, it also seems clear that it is the second period ofadjustment that has been characterized by falling growth, rising inflation and worsening employmentconditions, while in the first period the economy had performed better.

On the evidence of these indicators, we need to look more closely at the type and nature of reforms beingundertaken in the first period, largely covering the 1980s and those in the second period (from the late1980s to the present). This is a periodic demarcation which is suggested by the distinctness of the indicatorsof achievement in the two periods and brings us directly to the thematic analysis referred to above, thefocus of the next section.

7. A THEMATIC ASSESSMENT

On the sequencing of reforms and the reform policies

Why have the achievements of the reform package been so modest in Pakistan? One argument is that thesequencing of reform policies is as critical as their content, and that there has been improper sequencingof reforms in Pakistan. There is ample evidence from both IMF/WB studies and from independent researchthat macroeconomic stability - which in Pakistan also means budgetary stability is an essential preconditionfor the success of economic liberalization.8

Unfortunately, in the face of binding political constraints to budget and institutional reform (especiallywhen democratically elected governments are in power) international lending and financial agencies,possibly facing their own operational exigencies, have gone ahead with such “reforms” as the governmentcould agree to. This may have occurred even though the sequencing conditions considered important forthe success of these reforms may not have been met.

There is much to be said about sequencing, although it must be emphasized that the argument invokinga sequencing failure is agnostic on the validity or appropriateness of the individual policies whosesequencing is in question. These must be assessed on their own merit. In other words, correct sequencingis only a necessary condition for reform success; the individual reforms must also be suitable for thecountry involved. This is important to bear in mind because of a tendency in policy debate to use“sequencing failure” as a reason to ignore the assessment of individual reform measures.

Having noted the important issue of sequencing, which will be illustrated by example later, we nowexamine three thematic areas of intervention by government which circumscribe the main reform agenda.These pertain to fiscal policy, monetary policy and the trade regime.

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Fiscal Policy

Fiscal policy can be seen as a set of measures taken by the State, that are concerned with income andexpenditure of government. On the income side, there is direct revenue generation (taxation) and deficitfinancing; the expenditure side is self-evident. In the absence of a formal model, we use the likely key staticfirst-round effects of the impact of fiscal policy on economic growth as described in the followingprocesses:

• government revenues reduce disposable income and hence private savings, private investment andgrowth. The effect on growth is therefore likely to be negative;

• deficit financing, which absorbs a large share of private savings and raises interest rates, reducesinvestment and growth (among other effects). Thus the growth effect is also likely to be negative;

• government expenditures can lead to domestic income redistribution, incremental demand for goodsand services and capital formation, all of which should have a likely net positive impact oninvestment and growth, depending on the level and composition of government expenditure. So thegrowth effect is likely to be positive.

In principle, the tax-revenue effect and the deficit financing effect are negative and the expenditure effectis positive. Consequently, in principle, as long as fiscal policy is also redistributive, the expenditure effectcan be made to dominate the expected negative tax and deficit-financing effects. It should be recalled thatin the opening section we noted two symptoms of the weakness of the growth process in Pakistan: namelythat it was insensitive to distribution and relied on a narrow base of public finance. This combination isclearly not conducive to a growth-enhancing fiscal policy thrust.

Government revenues in Pakistan have remained at around 17 per cent of GDP for a very long time - thehigher budget targets for the present years are unlikely to be attained. Also, the direct impact of therevenue-effect on disposable incomes and saving has not been onerous. The bulk of tax revenues, however,arise from indirect taxes, mainly import duties; their effects on industrial incentives will be examinedfurther in our discussion of trade policy. Over the last decade, sales tax (mainly as a surcharge on importduties) and excise duties (collected mainly from a few items) have grown. On balance, however, the averageburden of taxation has been moderate, although the incidence of salaried tax-payers already in the tax nethad become quite high. This has been corrected in the 1997-98 budget.

The major impact of the budget on investment and growth, however, has come from expenditures and theirnon-revenue financing. First, the accumulated burden of inadequate taxation has led to an unsustainablerise in the debt burden so that, over the decade, debt service payments have been growing, at a rate ofnearly 20 per cent per year.

As a result of the rising burden of debt service payment and government expenditure on defence,development and civil administration have been severely curtailed. Clearly the restriction on developmentexpenditure is not without social costs, particularly when indicators of labour market conditions are alsoworsening. The decline in public investment has arguably had both a direct impact on capital formationand an indirect one on conditions of work through inadequate provision of public goods (especially thephysical and social infrastructure). Also, as the government has sought to mobilize increasingly higheramounts of money from the capital markets, interest rates have risen and private investment incentives havedeteriorated.

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Table 2: Indicators of fiscal policy, 1980-97

1979-80 1987-88 1994-95 1995-96a 1996-97b

Structure (as % of GDP)

Revenues 16.4 17.3 16.9 17.5 18.7

Expenditures 23.3 26.7 22.8 23.9 22.7

Debt service 4.6 6.8 8.7 8.7 9.3

Foreign 3.4 3.2 4.4 4.1 4.5

Domestic 1.2 3.6 4.3 4.6 4.8

Defence 5.4 7.0 5.6 5.5 5.2

Development 9.3 6.9 4.4 4.3 4.2

Administration, etc. 4.0 6.0 4.1 5.4 4.0

Overall deficit 6.3 8.5 5.6 6.3 4.0

Domestic financing (Net) 3.3 6.6 4.0 5.1 3.3

Non-Bank 0.6 4.5 2.6 2.7 2.5

Banking System 2.7 2.1 1.4 2.4 0.8

External financing (Net) 3.0 1.9 1.6 1.2 0.7

Memorandum (as % of GNP):

Public Debtc .. 73.9 79.0 79.3 ..

External debtc .. 33.0 36.5 37.3 ..

Domestic debt .. 40.9 42.5 41.9 ..

External liquidity (as % of imports) 17.5 7.7 29.4 21.9 ..

Notes: Consolidated federal and provincial government budget figures, as presented by the Ministry ofFinance in their Economic Survey. In the past few years, these figures have differed from thosepresented by the State Bank of Pakistan (SBP) in its Annual Report. The overall deficit is the differencebetween revenues and expenditures plus the surplus of autonomous bodies (not shown)... not available.a Provisional actuals.b Budget estimates.c Outstanding and disbursed.

Source: Economic Survey 1996-97, Statistical Supplements, and SBP Annual Reports.See ILO-SAAT/ArshadZaman Associates (1997).

9 The State Bank of Pakistan Order 1948 was succeeded by the State Bank of Pakistan Ordinance of 6 July 1955(converted to an Act of 18 April 1956).

10 According to Hasan (1997, p. 10): “…reliance on credit controls has not disappeared completely although formalcredit controls no longer exist. In practice, formal controls have been replaced by equally effective jawboning [i.e. making firm‘suggestions’ which are carried out for fear of offending the authorities] when a bank’s credit expansion gets out of line in theopinion of the authorities.”

79

Figure 2 External Debt & Debt Service

0

5

10

15

20

25

1991 1992 1993 1994 1995 1996Fiscal Years Ending June 30

US

$ b

illio

n

0

500

1000

1500

2000

2500

US

$ m

illio

n

LT Debt ST DebtLT Debt Service ST Debt Service

Thus, the pattern of government expenditure has become less growth-enhancing and has relied for itsincome more on non-revenue-based deficit finance. The net impact of the government’s fiscal operationsespecially in the 1990s, has therefore been to contribute to macroeconomic instability and lower the rateof investment and growth.

Monetary Policy

Monetary policy primarily affects investment and growth through its impact on incentives to save, investand produce. It does so mainly by ensuring that credit is available, at as low interest rates as possible, ina stable macroeconomic environment. Until February 1994, when the State Bank of Pakistan Act, 1956was amended to give the State Bank greater autonomy, monetary policy in Pakistan was conducted largelyto accommodate the financial requirements of government.9 It is still too early to predict the impact of thisnew autonomy on the government’s future conduct. Although early signs suggest possible areas of conflictbetween an elected government’s need to facilitate its own access to capital and a central bank’sresponsibility to have a broader economy-wide stability as an objective10 . In the past, however, the roleof monetary policy per se had been minor, as the State Bank’s intervention in financial markets hadconsisted mainly of the direct regulation of credit, in support of the government’s economic objectives.

11 First, there was the Credit Inquiry Commission of 1959 and the Credit Inquiry Committee of 1962 , that providedthe State Bank of Pakistan (SBP) with clear directions to micro-manage the process of credit distribution - to primary-producingsectors, and small and medium-scale enterprises – through the establishment of new institutions. Second, under the bankingreforms introduced in May 1972, elaborate institutions, consisting of the National Credit Consultative Committee (NCCC) andits sub-committees, were set up to ensure that the credit needs of specific sub-sectors were met.

12 As distinct from monetary policy, the financial sector in Pakistan was affected by three major developments inthe banking sector. First, the establishment of United Bank Limited (UBL) in 1959 introduced the culture of aggressive depositmobilization in commercial banking in Pakistan. Second, the nationalization of banks on 1 January 1974 inaugurated aneventful era of government control over banks. This era came to a close in 1991 when the government partially disinvestedtwo nationalized banks, and granted licenses to 10 new private banks, while 6 investment banks (licensed earlier in 1989)started operations.

13 Serious questions can be raised about the contribution to higher profits of inadequacies in banking supervisionand regulation and the lack of competition in the banking sector.

14 High interest rates have also inhibited private investment, although there have been other non-economic reasonsfor this as well.

15 In an important report, the World Bank (1987, vol. 2, pp. 6-7) also stressed the need for “careful sequencing” ofreforms – identifying price stability and the maintenance of external balance, through deficit reduction, exchange rate action,and conservative monetary policies, as pre-requisites for the success of trade reform, financial sector reform and deregulation– and warned that “financial sector reform will not be successful unless accompanied by reduction in the budget deficit.”

80

There have been three major landmarks in the history of credit regulation in Pakistan11. More recently, in1990-91, under a Financial Sector Adjustment Loan (FSAL) from the World Bank and technical assistancefrom the IMF, a transition from instruments of direct control over credit to indirect influence of monetaryaggregates (mainly through open-market operations) was effected.12

Whether it had other costs or not, there should be little controversy in assuming that the direction of creditflows to priority sectors led to an improved fulfilment of the government’s priorities: promoting investmentand growth, and partly meeting its distributional objectives. At the same time, there is considerableevidence that without prior budget reform, financial – sector reform can be seriously counterproductive.In the context of Pakistan, this essentially translates into putting in place legislative constraints to fiscalindiscipline. It is reasonable to argue that financial-sector liberalization was premature. Whatever impactit had on the efficiency of the banking sector,13 the rise in interest rates that followed had disastrousconsequences for the budget,14 and may have led to a crowding-out of genuine private investment.

The idea that, by confronting government with higher interest rates, the government’s recourse to non-bankdomestic borrowing would be curtailed, was flawed from the start. In the event, after the switchover tomarket-based instruments, recourse to domestic non-bank borrowing - after turning negative in the yearof the switchover, 1991-92 - rose rapidly, and at higher rates of interest (Figure 7.3).

The common-sense view was that without putting in place effective constraints on budgetary indiscipline,financial sector liberalization would lead to higher interest rates and hence a rise in the government deficit.15

On the basis (presumably) of a judgement that budget deficits could be controlled, the financial sectorliberalization was supported through substantial loans. Surprisingly, and on a priori reasoning, it washeld that the higher interest cost on market-based government borrowing (estimated at Rs 3.2 billion overthe nine-year period 1985-86 to 1996-97) would be offset by lower

16 World Bank 1987, vol. 1, p. 27.

17 Figure 3 is based on data provided by State Bank of Pakistan (1996, p. 91). The interest rate is estimated as theratio of interest payments to the stock of debt outstanding at the end of the previous year.

18 This was compounded by the fact of an early disinvestment of some of the banks and the losses absorbed by theState Bank on the provision of forward exchange cover [i.e forward selling of foreign exchange at a fixed rate].

81

Figure 3 Domestic Debt: Interest Rate & Stock Outstanding

0

200

400

600

800

1000

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

Fiscal Year Ending June 30

Rs

bill

ion

02468101214

% p

er y

ear

Outstanding Debt Interest Rate

short-term rates on national saving schemes and greater dividends and taxes from increased earnings ofthe banking sector (estimated at Rs 14.5 billion):16

‘‘Overall, the government would gain Rs 17 billion, over a nine year period, (US$100million equivalent per year) if it pursued the proposed strategy as against following theexisting financing pattern.” (Underlining in original)

These expectations did not materialize. First, budget deficits did not decline progressively from 8.7 per centof GDP in 1986-87 to 4.2 per cent in 1996-97, leading to much larger borrowing requirements than hadbeen anticipated. Second, the rise in interest rates on domestic public debt envisaged - from 11.2 per centin the base case to 11.67 per cent in the recommended (staged introduction of market-based borrowing)case – proved unrealistic. Both the interest cost and the stock of government domestic debt rose muchfaster, as figure 7.3 shows.17 Finally, the assumption that government would be able to “earn an additionalRs 14.5 billion through higher earnings of SBP/NCB [State Bank of Pakistan/Nationalized CommercialBanks]” proved to be incorrect.18

Consequently, monetary policy as far as it brought in financial sector liberalization, led to an interactivesequencing problem with respect to fiscal policy, and this has been an important cause of macroeconomicinstability, the drying up of investment and the slowdown in growth.

19 In historical terms, the exchange control system inherited at independence in 1947 was modified by two majorexternal developments in the initial years (1947-55): the devaluation of the British pound, and consequently of a number ofsterling area currencies, in 1949; and the Korean War boom and following slump of the early 1950s. Pakistan first devaluedthe rupee in 1955, and following setbacks in exchange and trade liberalization (pursued during 1959-65) once again in 1972.

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Trade and exchange rate liberalization

The second area where the government undertook reforms, pending meaningful action on the budget, wasthat of external finances. These involved exchange rate depreciation, trade liberalization (i.e. reduction ofnon-tariff barriers) and tariff reforms (i.e. reduction - and the lowering of dispersion – of import duties).These matters need to be assessed separately.

Exchange Rate Reforms (1982- )

In February 1982, as part of the first Extended Fund Facility (EFF), Pakistan de-linked the rupee from theUS dollar, and initiated the current regime of the managed float.19 The immediate motivation fordevaluation or depreciation of the rupee has always been to shore up foreign exchange reserves, eventhough of late the action is sometimes justified as having a beneficial long-term impact on resourceallocation.

There is, however, some controversy about the efficacy of exchange rate action in Pakistan’scircumstances. First, it can be argued that unless there is prior action to curtail excess demand arising fromthe budget – demand for debt service or military expenditures which are insensitive to the exchange rate– a lowering of the exchange rate merely exacerbates budgetary pressures without alleviating the root causeof macroeconomic instability. Second, given that the demand for Pakistan’s major exports (cotton andcotton-based textiles and garments) is relatively price-inelastic, a depreciation of the rupee does not leadto a rise in export receipts. Finally, and more generally, structural rigidities in factor markets inhibit areallocation of resources (from non-tradeables to tradeables), which are necessary to realize the fullerefficiency gains from currency depreciation. Figure 4 presents the basic data on nominal and real(consumer price index deflated) exchange rates and the trade and current account deficits on the balanceof payments (as ratios of GDP).

Despite the heavy nominal depreciation of the rupee, in real terms the rate of exchange has remained fairlyconstant. On the “before-and-after” assessment, it would seem on balance that exchange rate depreciationhas not had any appreciable impact on external deficits. On a “counterfactual” reading, however, it can bemaintained that had the nominal value of the rupee been maintained at a higher level the deficits would havebeen larger. There is probably some positive impact of currency devalution on the the deficit.

Basically, the argument for devaluation resulting in a feedback mechanism for an export boom has notmaterialized. This argument assumes a structure of exports which is essentially different from Pakistan’s.Clearly, exchange rate reforms were not sufficiently drastic to alter the structure of incentives in productionand ensure a smooth transition between tradeable and non-tradeable production in the economy. Thebudgetary effect of exchange rates has been adverse and is mainly felt through price-insensitive items suchas defense and debt repayments.

20 The restricted list was a revised version of the tied list and sought to protect Pakistan’s trade commitments undera variety of bilateral agreements.

21 The bulk of the reduction took place in 1987-88 and the next three years, respectively: 136, 169, 70 and 97 itemswere removed from the negative list, and 10, 51, 20 and 43 items, from the restricted list.

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Figure 4. Exchange Rate (Rs/US$) & External Deficits (% of GDP)

0

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1981

1982

1983

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% o

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Trade Deficit Current Account DeficitNominal Exchange Rate Real Exchange RateLinear (Current Account Deficit)

Trade liberalization (1983- )

Non-tariff barriers

Traditionally, non-tariff barriers (NTBs) were used in Pakistan to curb imports in the face of acuteshortages of foreign exchange. In time, they were justified on grounds of industrial promotion, even thoughtheir adverse impact on government revenues (and efficiency of resource use) was recognized. Until 1982-83, only those goods could be imported which were on the “free” list (for which imports were allowed,subject to quantitative restrictions (QRs), after obtaining an import license) or the “tied” list (whichregulated mainly public-sector imports from specified sources).

Under the first EFF, the government agreed to a radical change in its import policy. In 1980, 406 of 435products on the free list were subject to QRs. As part of its agreement with the IMF, by 1983 thegovernment had reduced these QRs to 5, and by 1985 no product was subject to QRs. Even moresignificantly, the 1983 import policy replaced the free and tied lists with a “negative” list (and atransitional, “restricted” or “conditional” list),20 leaving all items not on the two lists to be freelyimportable. Initially, the negative (and the conditional) list was quite large. Over the years, however, andespecially since 1988, these lists have been narrowed parallel with successive IMF agreements.21 In recentyears, the import licensing requirement has also been removed so that an importer can open a letter of creditwith a bank and import any of the importable goods.

22 Data up to 1996 are from Arshad Zaman Associates (Pvt.) Ltd. (1997, p. 63), data for 1998 are estimated fromGovernment of Pakistan, Import Policy Order 1997-98, Ministry of Commerce, 1997.

23 John Williamson (1991, p. 74). (Williamson is now the Chief Economist, South Asia Region, World Bank.)writes: “Every economist knows that for a country with monopoly power in world trade, equalization of domestic resource costswould require an ‘optimum tariff,’ but the relevance of this principle for developing countries is denied on the grounds thatthey do not possess any significant monopoly power. Although that is true for individual countries, it is not true for developingcountries collectively (most notably beverages). A common export tax on those commodities, by enabling low-income countries

84

What has been the impact of the removal of NTBs? While increased efficiency of resource use is hard todocument, trade liberalization has certainly led to an increase in government revenues from importduties on previously banned imports. This gain however, has been at the expense of increased imports, andthe loss of an instrument of strategic intervention in trade policy.

Tariff reforms (1990- )

One major thrust of the adjustment programmes in the second period has been the reduction of importtariffs and the elimination of export duties. The purported objective is a reduction in effective protectionrates (EPRs), and in the dispersion of EPRs.

Figure 5 is a visual representation of the share of customs tariff line items in the (most favored nation,MFN) statutory tariff rates in (fiscal years ending June 30) 1982, 1990, 1993, 1996 and 1998.22 In additionto the tariff slabs represented in Figure 7.5, the coverage of specific tariffs fell from 4.1 per cent in 1982,to 2.3 per cent in 1990, but rose to 2.6 per cent in 1993 (to meet revenue needs), before falling again to 1.3per cent in 1996 and 1.2 per cent in 1998. As a result of these changes, in the same four years, the averagerate of import tariffs fell from 79.2 per cent, to 59.8 per cent, to 58.2 per cent, to 44.3 per cent, while thedispersion in these rates was reduced from 49.8 per cent, to 33.9 per cent, to 24.6 per cent, to 23.1 per cent(and the coefficient of variation from 62.9 per cent in 1982 to 51.3 per cent in 1996). In addition to tariffreductions, adjustment programmes have sought to reduce (and eliminate) the numerous exemptions andconcessions provided to specific commodities, plants, industries, and even importers.

0

20

40

60

% o

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Free 15 25 35 45 60 75 85 120 160 200 300

1998

1993

1982

MFN Statutory Import Tariffs (%)

Figure 5. Tariff Reform, 1982-98

On the export side and unlike the matter of reduction of import tariffs, there is greater unanimity of viewsamong economists that a good case exists for imposing export duties where the exporting country enjoyssome degree of monopoly power in the export market. Even when this is not so, there is a case for collectiveaction by developing countries. This is a fairly credible position to take.23

to redistribute income toward themselves at the expense of the rich, seems to me worthy of encouragement rather than thereverse.”

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The government has eliminated all export duties, despite the fact that Pakistan enjoys considerablemonopoly power in 8 export items (at the Standard International Trade Classification, SITC, 3-digit level)which account for 52.6 per cent of its 1990-91 merchandise exports (see Table 7.3 below). Clearly, thereis a case on both revenue and trade policy grounds for reconsidering the government’s policy of eliminatingexport taxes on these items.

Table 3: Pakistan’s major exports, among 70 leading commodity exports of developingCountries at the SITC revision 2, group (3-digit) level

SITC (Revision 2) Code World1990-91Value

As percentage of

Country Developing World

Commodity Group Rank (US$ ‘000) Total Countries Total

263 Cotton 1 560,626 8.17 13.25 6.58

611 Leather 6 244,339 3.56 7.30 2.71

651 Textile yarn 2 1,222,853 17.81 13.57 4.99

653 Woven man-made FIB fabric 7 429,189 6.25 3.93 1.75

655 Knitted or crochetted fabric 9 50,357 0.73 1.39 0.69

658 Textile articles NES 2 632,691 9.22 12.96 6.83

848 Headgear non-texti leclothing

8 340,379 4.96 5.07 3.40

894 Toys, sporting goods, etc. 10 132,111 1.92 1.27 0.58

Source: United Nations, Handbook of International Trade Statistics, 1994, New York: United Nations.See ILO-SAAT/Arshad Zaman Associates (1997).

What has been the overall impact of trade liberalization and tariff reforms on growth and employment?First, there has been a fall in government revenues – even though it has been compensated by adiversification of the structure of government revenues. Second, there has been a rise in import paymentsdue to cheaper imports. Third, a reduction in protection to industry has affected industrial output andemployment adversely. On the exports side, there is a case to be made for an unnecessary loss of dutieson certain critical items, which are a much needed source of revenue.

9. UPSHOT

Whereas international circumstances of resource flows (a critical correlate of growth phases in Pakistan)have changed over time, macro policies remain an important consideration in the present period ofeconomic reform, precisely because the adoption of these policies have become a correlate of the timing

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of the resource flows themselves. This is apparent especially in the successive reform that the country hasgone through.

First, there is a question to be raised on the appropriateness of some reform policies to Pakistaniconditions. This is especially so for those pertaining to the trade regime. Second, there has also been a clearsequencing problem in the implementation of some reform policies that have adversely affected the stabilityof the macroeconomic environment and, therefore, growth. This adverse impact on the economy has workedlargely through the budget itself, from its direct and indirect impact on macroeconomic stability, to theinvestment climate and then ultimately to growth and employment. With budget reforms politicallyinfeasible, what happened in Pakistan in practice was that, in return for balance of payments support, such“reforms” as could be carried out were carried out. The sequence in which some of these policies wereimplemented was insensitive to the institutional and structural realities of the country’s political economy.

We can also demarcate the basic differences in the policies of the two sub-periods of reform, the secondof which was the more difficult one as by that time Pakistan was arguably weakened in its geo-strategicposition due to changed international circumstances.

In the first instance (which began with EFF 1980-83) the major movement was on exchange rates andimport liberalization, along with disinvestment, deregulation, and privatization. Clearly, as stated, thesewere also times when resources flowed into Pakistan easily. It can nevertheless be argued thatdisinvestment, deregulation and privatization had an initial beneficial effect on the private sector and theindustrial growth climate of the time.

Over time, and by the second phase of reforms not only did the direct effect of fiscal contraction inproductive public investment lead to a decline in capital formation, but the government’s revenue basepersisted in remaining very narrow. Its continued non-revenue-based financing of expenditure in thechanged, financially liberated internal capital market environment, led to a very serious crisis of domesticdebt in this second reform period. This crisis, apart from starving the private sector for resources, hascontributed to the macroeconomic instability facing the country today.

On the monetary policy front, it is again the interaction of the liberated financial sector’s soaring interestrates and government’s propensity to borrow which has been the most explosive.

Exchange rate reforms, due to the structure of exportable items produced in Pakistan, may also not havehad the desired effect of substantially boosting Pakistani exports, for which demand in general is relativelyprice inelastic. On the other hand, the devaluations have put serious pressures on the budget, owing to theprice-insensitive ‘necessary’ expenditures embedded in it.

Trade reform has increased government revenues on import duties, but imports have also increased, andexports have not picked up. There is a gradual loss of revenue, associated with the removal of tariffs. Theremoval of all export duties, on the other hand, may not have been necessary, and has been done in somehaste.

With hindsight, it seems that in the absence of prior budget reforms, both tariff reform and financial sectorliberalization may have been premature, but in particular it was the financial-sector reforms in the secondreform sub-period which are likely to have significantly contributed to the present crisis of growth.

What can be said about the macroeconomic policies and employment? Clearly, some links have beenestablished between the macroeconomic policies adopted and the slowdown of growth in the 1990s. It has

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also been argued separately in this report that the employment problem can best be addressed with a growthrevival strategy. This is the subject of the rest of the rest of the report.

There are a few policy lessons that need to be further explored and constitute areas in which follow-upwork is urgent.

• First an attempt must be made to minimize sources of macroeconomic instability that arise from theactions of government itself.

• Second, trade policy has to be reassessed in the light of maximizing gains for the country given itsproduction structure, as opposed to hoping that market signals on their own will transform anddiversify the production structure. There is obvious room here for expanding the revenue base forgovernment without adversely impacting output.

• The focus of government expenditure should be on growth-enhancing and demand-generatingactivities that have a strong re-distributive side.

• Lastly and most critically, a central aim of the government should be to produce and develop a newbreed of employment-friendly alternative adjustment programmes. These must examine thefeasibility of expansionary macroeconomic policies in Pakistan and be used as working documentsfor negotiation with donors, carrying explicit improvements on social indicators as part of their shortand medium-run goals.

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ANNEXES

89

CHAPTER ONE

ANNEX 1.1: SOURCES OF DATA ON LABOUR AND HUMAN RESOURCES

Agencies Type of Data

Federal Bureau ofStatistics (FBS)

Labour force surveys, censuses of manufacturing industries, household incomeand expenditure surveys, Inquiry on Labour Welfare, EstablishmentsInquiry, wage rates of unskilled agricultural workers, labour productivityindices in selected industries, wage rate survey of manufacturingestablishments, wage rates of construction workers in cities, and many adhocinquiries, surveys, etc.

Population CensusOrganization (Decennial)

Conducted in 1951, 1961, 1972 and 1981.

Agriculture Census Org. (Decennial)

Agriculture Census: 1962, 1972, 1980, 1990. Mostly data on family Org. (Decennial) : members and use of hired labour family workers.

Provincial Bureau ofStatistics (Punjab & Sindh)

Employment and wages in manufacturing sector, teaching staff, healthpersonnel, number of posts by Basic Scales in the Budget, number of personsmigrated abroad.

Ministry of Industries Category-wise employment, salaries and wages Annual Report of PublicSector Industries.

Management ServicesDivision

Census of Federal Government Civil Servants (Triennial).

Year Book of Information(Railways)

Annual data on persons employed by Departments and total cost ofemployment.

Registrar Pakistan MedicalCouncil

Data on medical and para-medical personnel registered.

Registrar PakistanEngineering council

Data on engineers registered with the council.

Annual Reports of Corporate Bodies

These reports provide information on employment, wages and salaries andsocial security benefits etc.

Economic Advisers Wing,Ministry of Finance

Economic Survey and Annual Reports (now discontinued) of Public SectorCorporations.

Research Institutions Data generated through research, and special surveys and studies onemployment, poverty alleviation, human resource development and wages.

PC-I of Projects PC-I of Development Projects(Part-C)contains information on labourrequirements by major occupation groups.

A cursory glance of the list of agencies and the types of data generated by them would give an impressionthat labour market information system in Pakistan is well developed and integrated and that most of theinformation required for policy formulation and research is available. However, this is not the case and thereal problem emerges when one attempts to use and analyze the data. Official statistics suffer from seriousdefinitional and measurement problems and also render the inter-temporal comparison difficult. Specialized

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studies exist but are usually too limited in coverage to be representative. Some comments on the availabledata are given below:

• Decennial population censuses constitute a major source of information on population and civilianlabour force. An inter-temporal comparison of the censuses data can neither be made betweencensuses themselves nor with other surveys, as surveys are not undertaken in the census year. Forexample, unlike the 1961 census where total enumeration was used to obtain data on employment,in subsequent censuses data on employment was obtained through sample surveys. The last censuswas conducted in 1981.

• Agriculture censuses conducted every ten years, provide data on the use of hired labour, familyworkers, and economically inactive family members. The coverage of data is confined toemployment in agriculture and livestock activities. The rural agriculture employment estimated onthe basis of agriculture census differ widely from data obtained through other sources in numberas well as in concept. The characteristics of employed persons are restricted to the total numberof hired labour and family members sub-divided in full time and part time workers.

• Labour force surveys carried out by the Federal Bureau of Statistics since July, 1963, constitutethe most commonly used major source of information on labour force and employment. Thesurvey is based on a representative sample. However, the labour force participation andunemployment rates obtained through these surveys do not show any significant changes over theperiod.

Pakistan has been using the “labour force approach” recommended by the ILO to define economicallyactive, employment and unemployment. The sample size and inadequacy of the concepts used, may haveinfluenced the quality and size of data generated through these surveys. Moreover, the Federal Bureau ofStatistics have also been changing the concepts. The 1990-91 round is based on new questionnairedeveloped in the light of ILO recommendations made at 13th International conference of LabourStatisticians in 1982. A comparative picture of old and new definition of labour force concepts is givenin table A1.2.

For example, the share of agriculture, animal husbandry, forestry and fishing in employed work-forcejumped from 14.2 per cent in 1987-88 to 46.6 per cent in 1990-91, while that of production and relatedworkers dropped from 58.4 per cent to 26 percent. Similarly the crude participation rate in 1990-91improved to 27.97 (both sexes) under new concept from 27.19 under the old concept, of female increasedfrom 7.61 to 8.23, while that of male increased to 46.36 from 45.45. Similarly the age specific activityrate derived from new concepts were also higher than derived from old concept. Usually the data has a timelag of 3 years. The summary results of LFS(1994-95) were released in April 1997. The data for miningand manufacturing (both large and small-scale) is reported in combined form and as such can not be crosschecked with CMIs data.

The Census of Manufacturing Industries (CMI) conducted annually, provides information on employmentand employment cost by major groups of industries in large scale. The data is reported in aggregate formand is usually available three to four years after the collection. Similarly the data collected by otheragencies shown in the annex, is restricted to a particular activity or profession and are collected for meetingthe internal requirements of the management concerned. Except the LFS, the coverage of statistics collectedby other agencies is restricted to aggregate number and wage bill and that too in areas of vested interest.The national requirement is best served by the LFS(s), though LFS also need improvement in concept, size,and timely releases.

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Comparative statement showing old and new definition of labour force concepts

Contents Old definition New Definition

1. Labour Force It includes all non-institutional civilian population10 years of age and above who are found employed orunemployed during thereference week preceding thedate of inter view.

The “Labour Force” or “currently Activepopulation” consists of all persons 10 years ofage: and above who are either “employed” or“unemployed” during the reference period i.e. oneweek preceding the date of interview.

2. EmployedPersons

It includes all persons: who,during the reference week,were either working for pay orprofit in cash or kind, includingunpaid family helpers (whohad worked for any period oftime during the referenceweek)or had a job but did notwork

The “employed” comprises all persons of 10 yearsage & above who worked at least one hour duringthe reference week in the followingcategories:(i) Paid employment (1) “at work” persons who

during the reference week, performed some work for wage or salary, in cash or in kind;(2)”with a job but not at work”: personswho, having already worked in their presentjob, were temporarily not at work duringreference week due to some reasons such asabsence, leave, illness: and strike etc. but hada formal attachment to their job;

(ii) Self-employment (1) “at work”: personswho, during the reference week, performed some work for profit or family again, in cashor in kind (2) “with an enterprise but not atwork” persons with an enterprise, which maybe a business enterprise, a farm or a serviceundertaking, who temporarily not at workduring reference week for some specificreasons such as absence, leave, illness &strike etc.

3. UnemployedPersons

Include all persons who, duringthe reference week were eitherlooking for work, or notlooking for work because ofillness, or not looking for workbelieving job not avail- able ortemporarily or indefinitely laidoff, or waiting to report to newjob or willing to work if job isprovided, or apprentice with noguaranteed job or have someusual occupation but weredoing nothing during thereference period.

The “unemployed” comprises all persons of 10 years of age and above who during the referenceweek were either:(i) “available for work” i.e. were available

for paid employment or self-employment; or(ii) “seeking work “ had taken specific steps in a

specified recent period to seek paid employment or self-employment. It alsoincludes persons who were not available forwork during the reference week due to certainreasons such as illness, will take a job withina month, temporary laid off and apprenticeand not will to work.

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Annex 1.2: Youth employment and child labour

The exploitation of child labour is one of the most odious aspects of global labour markets. In mostdeveloping countries, it has not been possible to put an end to child labour (including child prostitutioninspired by the tourist industry) despite the fact that almost all these countries have satisfactory legislationin this respect. The abolition of child labour and more generally the protection of children and youngpersons against work of a character or condition unsuitable to their age have been a serious concern to thegovernment and social activists in Pakistan, especially during the last decade or so.

The Census of Population and Labour Force Surveys are the two main sources of manpower statistics butthey do not provide information about child labour. In the absence of information, there are variousguesstimates of varying credibility. According to the summary results of 1994-95 LFS, 1.7 million childrenin the age group of 10-14 years constituted 5.07 per cent of the employed persons. The total population inthe age group 10-14 was 16.5 million or 12.9 per cent of total population.

The Child Labour Survey (CLS) conducted in 1996 by the Federal Bureau of Statistics in collaborationwith the Ministry of Manpower & Overseas Pakistanis and under the auspices of the InternationalProgramme on Elimination of Child Labour (IPEC), revealed that among 40 million children aged 5-14years, 3.3 million (8.3 per cent) were economically active. Out of the total, 2.4 million (73 per cent) wereboys and 0.9 million (27 per cent) were girls. The absolute size of male child labour in the age group of10-14 years was 2.1 millions while that of female child labour in the same age group was found to be 0.6million. Child labour in rural areas was about eight times higher than in urban areas, due mainly to a largeproportion of unpaid family helpers.

The data also revealed that about 33.2 per cent of the total children employed in the labour market, wereliterate from the formal system of education. Of the boys workers about 40.3 per cent were pre-matricwhile only 11.2 per cent of the female child workers were pre-matric. Similarly about 41 per cent of thetotal child workers in urban areas as against 32 per cent in rural areas were pre-matric.

As regard the major industrial groups, about 67 per cent of the children were engaged in agriculture,followed by 11 per cent in manufacturing. The wholesale and retail trade and services (community, socialand personal services) sectors absorbed 9 per cent and 8 per cent of the employed children, respectively.

By occupation, the survey revealed that about 71 per cent of 3.3 million employed children were engagedin unskilled occupations relating to agriculture, fisheries, sales and services. Craft and related tradeactivities were the next major occupational groups which absorbed about 19 per cent of the workingchildren. Only 0.31 per cent child workers were found working as plant and machine operators. Childrenas service and sales workers constituted 9.24 per cent of the working community.

Besides the Child Labour Survey and Labour Force Surveys, studies on the pattern of child labour in a fewcities have also been conducted. According to these studies most of the children are working inmanufacturing, transport and services sectors. In the manufacturing sector they are generally found in foodprocessing, textiles, footwear, printing, publishing, brick-making, carpet-weaving and sports goods.

The Labour Force Surveys show that the age-specific activity rate for the age group 10-14 years isdeclining as shown below:

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Table 1: Percentage share of children age 10-14 years

1982-83 1987-88 1990-91 1994-95

Total

Share in population 18.8 18.7 18.1 19.3

Share in Labour Force 4.0 3.1 2.5 2.2

Participation rate 21.5 16.6 13.6 11.6

Share in employed force 8.4 6.7 5.5 5.1

Males

Share in population 10.0 9.9 9.9 10.4

Share in Labour Force 3.3 2.6 1.9 1.7

Participation rate 33.0 26.6 19.3 16.6

Share in employed force 7.6 6.4 5.0 4.4

Females

Share in population 8.8 8.8 8.2 8.9

Share in Labour Force 0.7 0.5 0.6 0.5

Participation rate 8.3 5.5 6.8 5.7

Share in employed force 14.1 9.6 9.4 9.7

Source: Labour Force Surveys.

Both the age-specific participation rate and the share of children in total employed force are declining,mainly due to higher enrolment at primary and high schools level. Children constitute 6.2 per cent of workforce in rural areas compared to 2.9 per cent in urban areas. The size of child labour revealed by CLS andLFS (1994-95) is compared below:

Table 2: Child labour (million)

Age group (10-14) Total Male Female

CLS (1996) 2.7 2.1 0.6

LFS (1994-95) 1.9 1.5 0.5

Source: CLS and LFS.

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There is not much detailed work done which explores the relationship between the level of family incomeand the incidence of child labour, or on other social-economic compulsions that force children to work inhazardous environments. Although it can be argued that part of the problem certainly derives frominsufficient enforcement of legislation. The major causes for the existence of child labour include poverty,lack of proper educational facilities, large size of informal economy and the socio-economic backgroundof the parents. As such it is a complex issue which does not yield to simplistic analyses. Employers in theinformal sector prefer to hire child workers because there is no law specifying the rights of child workerswith respect to minimum wages, maximum work hours and social security benefits. Children also help asunpaid workers in family-owned and managed business.

The existence of child labour is a worrisome aspect of the condition of the poor in Pakistan. All countrieshave enacted suitable legislation for the protection of children against exploitation, abolition of child labourand against work unsuitable to their age or sex. Articles 11 (3) of the Constitution of the Islamic Republicof Pakistan states that “no child below the age of fourteen years shall be engaged in any factory or mineor any other hazardous employment.” Article 37(a) provides that the state shall “remove illiteracy andprovide free and compulsory secondary education within a minimum period.” Article 37(c) says that thestate shall “ensure that children and women are not employed in vocations unsuitable to their age or sex.”

The above provisions of Pakistan Constitution clearly show the concern of Pakistan regarding child labour.Pakistan is a signatory to the Declaration of the Rights of the Child adopted by the UN General Assemblyin 1959. The legislation enacted and enforced in the country for the protection of children include:

• The Mines Act, 1923.

• Factories Act, 1934.

• The Employment of Children Act, 1938.

• West Pakistan Shops and Establishment Ordinance, 1969.

Most recently the government has set up a National Commission on child welfare in response to UNConvention on the Rights of Children. As a consequence, the Employment of Children Act, 1991 has alsobeen enacted to promote the cause of working children. The government has also enacted the BondedLabour System (Abolition) Act, 1992, Pakistan, through a Memorandum of Understanding signed in 1994with the ILO, has joined the International Programme for Elimination of Child Labour (IPEC), which aimsat gradual elimination of child labour. A National Steering Committee has been set up to supervise theprogramme and a child labour unit has been established in the Ministry of Labour and Manpower tomonitor the administration of IPEC.

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ANNEX 1.3: TABLES

Table A1.1: Growth of population and labour force (% per annum)

PeriodGrowth ofpopulation

Growth of labour force

Total Rural Urban

1972-75 3.2 2.9 3.1 2.2

1975-79 3.0 4.4 3.9 6.3

1979-83 3.1 2.4 2.0 3.6

1983-88 3.1 2.1 1.7 3.3

1988-91 3.1 2.1 0.9 5.1

1991-95 3.0 2.6 3.4 0.5

Average(1972-95) 3.1 2.7 2.5 3.5

Source: Population censuses and labour force surveys.

Table A1.2: Census data on population, labour force and employment

Numbers (in ‘000 or %) Growth rate (% p.a.)b

1951 1961a 1972 19811951-1961

1961-1972

1972-1981

Population (‘000) 33,817 42,978 a 65,321 84,254 2.4a 3.7a 3.1

Urban 6,019 9,654 16,594 23,841 4.8 4.8 4.4

Under 10 Years of Age .. 2,956 4,942 7,131 .. 4.5 4.4

Over 10 Years of Age .. 6,698 11,652 16,710 .. 4.9 4.4

Rural 27,797 33,324 48,727 60,413 1.8 3.3 2.6

Under 10 Years of Age .. 11,156 17,462 19,274 .. 3.9 1.2

Over 10 Years of Age .. 22,168 31,265 41,139 .. 3 3.3

Labour Force (‘000) 10,370 13,880 19,520 25,780 3 3 3.3

Urban .. 2,872 5,128 7,254 .. 5.1 4.2

Rural .. 11,008 14,392 18,526 .. 2.3 3

Employment (‘000) .. 13,640 18,550 24,700 .. 2.7 3.4

Urban .. 2,790 4,814 7,009 .. 4.8 4.5

Rural .. 10,850 13,736 17,691 .. 2.1 3

Unemployment Rate (%) .. 1.73 4.97 4.19

Urban .. 3.06 6.12 3.37

Rural .. 1.63 4.56 3.37

Notes: a Official figures for 1961 are adjusted by 7.5 per cent, for under enumeration. This gives a 1961population of 46.2 million, and hence inter-censal growth rates of 3.21 per cent for 1951-61 and 3.02 percent for 1961-72.b In calculating average annual population growth rates, the month in which the census was carried outis taken into account (February 1951, March 1961, October 1972, and March 1981).

c Civilian labour force only.

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Table A1.3: Population, labour force and employment, 1990-97

Fiscal Years Ending June30:

1990 1991 1992 1993 1994 1995 1996 1997

Population (‘000) 110.4 113.8 117.3 120.8 124.5 128 131.6 135.3

Urban 32.7 35.8 37.0 36.9 36.2 36.9 37.9 39.0

Under 10 Years of Age 10.1 11.6 12.6 11.5 11.0 10.8 11.3 11.5

Over 10 Years of Age 22.6 24.2 24.4 25.4 25.2 26.1 26.8 27.5

Rural 77.7 77.9 80.4 83.9 88.3 91.1 93.7 96.3

Under 10 Years of Age 26.7 28.4 27.9 29.9 30.9 32.0 32.9 63.8

Over 10 Years of Age 51.0 49.5 52.4 54.1 57.4 59.2 60.8 62.5

Labour Force (‘000) 31.8 31.8 33.0 33.7 34.7 35.2 36.1 37.2

Urban 8.6 9.5 9.7 9.5 9.3 9.6 9.9 10.2

Rural 23.2 22.4 23.3 24.1 25.4 25.5 26.2 27.0

Employment (‘000) 30.8 29.8 31.0 32.1 33.0 33.3 34.2 35.2

Urban 8.2 8.7 9.0 9.0 8.7 9.0 9.2 9.5

Rural 22.6 21.2 22.0 23.1 24.3 24.3 25.0 25.7

Unemployment Rate (%) 3.1 6.3 5.9 4.7 4.8 5.4 5.4 5.4

Urban 4.6 8.2 7.0 5.9 6.5 6.9 6.9 6.9

Rural 2.6 5.5 5.4 4.3 4.2 4.8 4.8 4.8

Source: Labour Force Surveys, cited in Government of Pakistan (1997, Statistical Appendix, pp. 19-20). Figuresfor 1996 and 1997 are estimates by the Economic Adviser’s Wing, Ministry of Finance, based on the1994-95 labour force survey. (See Annex 4, Table 1.3.)

98

Table A1.4: Crude labour force participation rates

Year

Total labour force Rural labour force Urban labour force

Total Male Female Total Male Female Total Male Female

1971-72 29.9 51.9 5.3 31.0 53.3 5.6 26.5 53.2 2.6

1974-75 29.5 52.1 4.3 30.8 52.1 5.1 26.5 48.0 2.4

1978-79 31.0 52.3 7.9 32.6 53.1 9.7 27.1 47.3 3.7

1982-83 30.2 51.5 7.2 31.8 53.1 8.9 26.3 47.7 3

1984-85 29.6 51.7 5.8 30.7 52.7 7.1 27.1 49.4 2.8

1985-86 28.7 50.0 6.0 29.9 51.2 7.5 25.8 47.1 2.4

1986-87 29.4 49.5 7.9 30.8 50.7 9.8 26.3 47.0 3.5

1987-88 28.8 49.4 6.8 29.9 50.2 8.2 26.3 47.5 3.4

1990-91 28 46.4 8.2 28.7 46.9 9.4 26.4 45.1 5.8

1991-92 28.1 46.1 9.2 29.0 46.5 10.7 26.1 45.1 5.5

1992-93 27.9 45.9 8.6 28.8 46.3 10.1 25.8 45.0 5.0

1993-94 27.9 45.7 8.9 28.7 45.9 10.5 25.8 45.4 4.9

1994-95 27.5 45.9 7.6 28.0 46.0 8.7 26.1 45.7 4.9

Source: Labour Force Surveys.

Table A1.5: Age specific participation rates

Age group 1982-83 1987-88 1994-95

36446 21.5 16.6 11.5

15-19 40.3 36.4 32.3

20-24 50.8 48.3 47.9

25 & above 52.0 53.0 52.8

Source: Labour Force Surveys.

99

Table A1.6: Out and return migration for different years

PeriodEmigration

BOIPer Year

(000)Return

MigrationPer Year

(000)Net Out

MigrationPer Year

(000)

1977-81 659715 132 98176 19 561539 112

1982-87 59227998642

44810750169-9

98 642448 107 -50169 -9

1988-92 642494 128 450000 90 192494 60

1993-95 394633 131 213008 71 181625 60

Sources: ILO-SAAT/ M. Irfan , 1997. 1 1977-81 (Iqbal & Khan) 1981 2 1982-87 and 1993-95 (Bureau of Emigration) based on Airport Surveys. 3 1988-92 (M. Irfan’s ,estimation on the basis of the estimated flows of preceding and the following periods.

Table A1.7: Persons included and excluded from the labour force, 1994-95 (million)

Total Male Female

Population 128.3 66.3 61.8

Age 10 years and above 85.4 44.2 41.2

Labour Force 35.2 30.5 4.7

Fully Employed 29.3 27 2.4

Underemployed 4 2.3 1.7

Unemployed 1.9 1.2 0.7

Outside Labour Force 50.2 13.7 36.5

Students 17.4 11.0 6.4

Others 32.8 2.7 30.1

Source: Labour Force Survey, 1994-95.

100

Table A1.8: Composition of labour force by sex and level of education

1990-91 1994-95 Growth (% p.a.)

Total M F Total M F Total M F

Total 31.8 27.30 4.5 35.20 30.5 4.7 2.6 2.8 1.1

Illiterate 19.11 15.43 3.68 19.86 16.10 3.76 1.0 1.1 0.5

Literate 12.69 11.87 0.82 15.34 14.40 0.94 4.8 4.9 3.5

Literate 100 100 100 100 100 100 4.8 4.9 3.6

No formal education 3.95 3.60 9.01 2.89 2.67 6.31 -3.0 -2.6 -5.2

Pre-Matriculate 60.68 61.70 45.95 57.37 58.60 37.84 3.4 3.6 -1.1

Matriculate 20.91 20.61 24.32 22.59 22.36 25.23 6.9 7.1 4.7

Intermediate 7.20 7.08 9.01 8.51 8.24 12.61 9.3 9.0 12.6

Engineering Degree 1.05 1.06 0.90 1.06 1.01 1.80 5.2 3.6 24.8

Medical Degree 0.52 0.43 0.90 0.39 0.36 0.90 -2.4 -2.7 0

Agriculture Degree 0.06 0.06 - 0.11 0.12 0.00 20.7 20.7 0

Other Degree 4.30 4.10 7.21 5.17 4.80 10.81 9.7 9.1 14.7

Post-Graduate 1.39 1.30 2.70 1.89 1.78 3.60 13.3 13.5 11.5

Source: Based on Labour Force Surveys.

101

Table A1.9: Percentage Distribution of Employed by Sex and Level of Literacy

1987-88 1990-91 1994-95

Total M F Total M F Total M F

Total 100 88.35 11.65 100 87.40 12.60 100 87.85 12.15

Illiterate 64.67 54.51 10.16 60.40 49.90 10.50 56.80 46.98 9.82

Literate 35.3 33.8 1.49 39.6 37.5 2.1 43.2 40.9 2.33

No Formal education - - - 1.54 1.36 0.18 1.28 1.11 0.17

Formal education 35.33 33.84 1.49 38.06 36.13 1.92 31.92 39.76 2.16

K.G Nursery 0.06 0.06 - 0.41 0.39 0.02 0.18 0.17 0.01

K.G but below Prim. 3.49 3.36 0.10 3.54 3.38 0.16 3.01 2.92 0.10

Primary but belowmiddle

12.26 11.81 0.46 12.81 12.29 0.52 13.30 12.72 0.58

Middle but belowMatric

7.39 7.24 0.15 7.50 7.24 0.26 8.50 8.31 0.18

Matric but below inter 7.14 6.80 0.34 8.09 7.60 0.49 9.60 9.03 0.57

Inter but below degree 2.20 2.06 0.14 2.81 2.63 0.18 3.63 3.35 0.28

Degree in Engineering - - - 0.41 0.40 0.02 0.43 0.39 0.04

Degree in Medicine 1.84 1.64 0.20 0.20 0.17 0.03 0.17 0.15 0.02

Degree in Agriculture - - - 0.03 0.03 - 0.04 0.04 -

Degree in other subj. 0.80 0.69 0.11 1.70 1.53 0.17 2.25 1.96 0.29

Post Graduate 0.19 0.18 0.01 0.56 0.48 0.08 0.81 0.71 0.09

Source: Labour Force Surveys.

102

Table A1.10: Rural-urban share of self-employed (%)

1982-83 1987-88 1994-95 Average

Total 40.3 47.9 42.3 43.6

Rural 41.7 51 45.2 46.1

Urban 36.1 39.5 34.3 36.6

Table A1.11: Distribution of self-employed by sectors

Sectors1982-83 1987-88

T R U T R U

Agriculture 54.3 67.5 7.6 53.6 66.6 7.2

Manufacturing 13.6 11.1 22.1 10.9 8.7 19.1

Trade 19.6 12.4 45.1 16.8 9.8 41.8

Transport 3.3 2.2 6.8 8.3 3.4 8.2

Services 6.6 4.8 12.8 6.0 4.1 12.8

Others 2.6 2.0 5.6 4.4 7.4 10.9

Total 100.0 100.0 100.0 100.0 100.0 100

Source: Labour Force Surveys.

Table A1.12: Share of full-time (over 35 hours) and educated workersamong the self-employed, 1994-95

Share of full-time workers(%)

Share of educated workers(%)

Pakistan Rural UrbanMiddle

and belowMatric but

below DegreeDegree and

above

National

Total 87.8 86.0 92.9 62.6 28.5 8.9

Male 92 90.8 95.0

Female 57.7 55.8 67.5

Self-employed

Total 91.9 90.9 95.1 74.4 22.1 3.5

Male 93.2 92.4 95.9

Female 59.4 51.1 71.0

Source: Labour Force Surveys.

103

Table A1.13: Underemployment among the employed (%)

Status

1982-83 1987-88 1993-94

Total Rural Urban Total Rural Urban Total Rural Urban

Employer 0.2 0.3 0 0.2 0.2 0.1 0.1 0.1 0.2

Self-Employed 3.8 4.2 2.8 3.5 4.1 1.9 3.4 4.1 1.7

Unpaid FamilyHelpers

7.4 9.2 1.7 6.1 7.9 1.2 5.7 7.2 1.3

Employees 2.6 2.6 2.5 1.3 1.2 1.6 3.0 2.6 3.9

Total 14 16.3 7 11.1 13.4 4.8 12.2 14 7.1

Source: Labour Force Surveys

Table A1.14: Underemployment rates in rural and urban areas

1982-83 1987-88 1993-94

T R U T R U T R U

Labour Force (mill.) 26.9 20.0 6.9 29.9 21.9 8.1 35.2 25.6 9.6

Employed (mill.) 25.8 19.3 6.5 29.0 21.3 7.7 33.3 24.4 8.9

Underemployed 3.6 3.1 0.5 3.2 2.9 0.4 4.1 3.4 0.6

Underemployment Rate 13.4 15.5 7.2 10.7 13.2 4.9 11.6 13.3 6.3

Source: Calculated from Labour Force Survey Data.

104

Table A1.15: Number of unemployed and unemployment rates

YearUnemployed labour force (million) Unemployment rate

Total Rural Urban Total Rural Urban

1986-87 0.90 0.55 0.35 3.05 2.50 4.51

1987-88 0.94 0.57 0.37 3.13 2.60 4.58

1988-89 0.97 0.59 0.38 3.13 2.60 4.58

1989-90 1.00 0.60 0.40 3.13 2.60 4.58

1990-91 2.00 1.23 0.77 6.28 5.48 8.19

1991-92 1.93 1.26 0.67 5.85 5.40 6.97

1992-93 1.60 1.03 0.57 4.74 4.29 5.88

1993-94 1.68 1.04 0.64 4.84 4.22 6.31

1994-95(E) 1.73 1.06 0.68 4.84 4.22 6.51

Source: Federal Bureau of Statistics.

Table A1.16: Duration of unemployment

YearNature ofexperience

Duration of unemployment

TotalLess than 1

month1-6 months

6 months andover

1984-85 Total 100.0 46.4 18.5 35.1

w.past.exp. 41.9 14.7 11.6 15.6

without p.exp. 58.1 31.7 6.9 19.5

1985-86 Total 100.0 23.0 37.2 39.8

w.p.exp. 41.4 16.4 12.6 12.5

without p.exp. 58.6 6.7 24.6 27.3

1986-87 Total 100.0 28.7 35.9 35.5

w.p.exp. 43.6 15.0 12.7 15.9

without p.exp. 56.4 13.6 23.1 19.6

1987-88 Total 100.0 22.7 36.9 40.4

w.p.exp. 44.3 14.9 16.9 12.5

without p.exp. 55.7 7.7 20.1 28.0

Source: LFS.FBS Economic Survey of Pakistan 1995-96Note: w.p.exp= with past experience; without p.exp.= without past experience.

105

Table A1.17: Percentage distribution of educated unemployed

1982-83 1987-88 1993-94

Total M F Total M F Total M F

Total 100 - - 100 96.7 3.3 100 68.1 31.9

Illiterate 57.2 - - 51.0 48.9 2.1 51.2 27.1 24.2

Literate 42.8 - - 49.0 47.8 1.3 48.8 41.0 7.7

Pre-matric 27.9 - - 29.6 29.3 0.3 24.1 21.3 2.7

Matric 10.5 - - 12.6 12.1 0.5 14.2 11.5 2.7

Inter 2.4 - - 4.2 4.1 0 4.6 3.5 1.1

Degree. Of which 1.2 - - 2.1 1.8 0.4 3.4 3.0 0.4

Professional - - - - - - 0.6 0.6 0.1

Post Graduates 0.5 - - 0.5 0.5 0.1 0.9 0.7 0.2

No formal education - - - - - - 1.6 1.0 0.6

Source: Labour Force Surveys.

106

CHAPTER TWO

ANNEX 2: TABLES

Table A2.1a: Growth rates of population labour force and employed labour force in Pakistan

Year Growth (Pop) Growth (LF) Growth (Emp)

1973 3.01 1.28 0.98

1974 4.03 3.54 3.72

1975 3.05 2.60 2.70

1976 3.06 2.58 2.73

1977 3.06 4.36 3.84

1978 3.06 4.36 3.84

1979 3.05 4.36 3.84

1980 3.05 4.39 3.92

1981 3.07 2.37 2.24

1982 3.05 2.31 2.28

1983 3.10 2.42 2.31

1984 3.10 2.44 2.30

1985 3.10 2.01 2.13

1986 3.10 2.00 2.12

1987 3.10 0.18 0.22

1988 3.10 5.53 6.22

1989 3.10 1.11 1.01

1990 3.10 3.14 3.14

1991 3.10 3.08 3.08

1992 3.10 0.03 -3.21

1993 3.10 3.58 4.06

1994 3.00 2.12 3.35

1995 3.00 3.03 2.90

1996 2.86 1.33 0.76

1997 2.83 2.82 2.83

1998 2.77 2.79 2.78

107

Table A2.1b: Levels of population, labour force and employed labour force in Pakistan

Year Population Labour forceEmployed labour

force

1971 61.49 18.70 18.37

1972 63.34 18.94 18.55

1973 65.89 19.61 19.24

1974 67.90 20.12 19.76

1975 69.98 20.64 20.30

1976 72.12 21.54 21.08

1977 74.33 22.48 21.89

1978 76.60 23.46 22.73

1979 78.94 24.49 23.62

1980 81.36 25.07 24.15

1981 83.84 25.65 24.70

1982 86.44 26.27 25.27

1983 89.12 26.91 25.85

1984 91.88 27.45 26.40

1985 94.73 28.00 26.96

1986 97.67 28.05 27.02

1987 100.70 29.60 28.70

1988 103.82 29.93 28.99

1989 107.04 30.87 29.90

1990 110.36 31.82 30.82

1991 113.78 31.83 29.83

1992 117.31 32.97 31.04

1993 120.83 33.67 32.08

1994 124.45 34.69 33.01

1995 128.01 35.15 33.26

1996 131.63 36.14 34.20

1997 135.28 37.15 35.15

108

Tab

le A

2.2:

GD

P (

at

fact

or c

ost)

sec

tora

l sha

res

Yea

rA

gric

ultu

reM

inin

g an

dm

anuf

actu

ring

Min

ing

Man

ufac

turi

ngM

aunf

actu

ring

larg

e sc

ale

Con

stru

ctio

n

Ele

ctic

ity

and

gas

Tra

nspo

rtT

rade

1971

39.0

414

.55

0.39

14.1

611

.15

3.57

1.67

8.55

14.7

019

7239

.48

14.4

00.

3914

.01

10.8

52.

921.

728.

5614

.69

1973

37.5

814

.63

0.37

14.2

611

.09

3.16

1.87

9.31

14.5

419

7436

.44

14.5

00.

3814

.12

10.9

43.

252.

059.

0715

.42

1975

34.3

314

.03

0.37

13.6

610

.37

3.69

1.76

9.12

15.3

019

7634

.74

13.7

60.

3513

.42

9.99

4.26

1.77

8.93

15.0

719

7734

.63

13.6

80.

4013

.28

9.71

4.11

1.99

8.84

14.6

119

7833

.03

13.9

90.

3813

.61

9.97

4.13

2.01

9.36

14.9

019

7932

.26

14.3

40.

3713

.96

10.1

94.

132.

099.

5815

.03

1980

32.0

214

.76

0.39

14.3

710

.53

4.28

2.18

9.53

15.0

519

8130

.83

15.5

30.

4215

.11

11.0

84.

672.

399.

6515

.06

1982

30.0

116

.42

0.44

15.9

811

.91

4.59

2.26

9.72

15.3

619

8329

.34

16.4

20.

4116

.02

11.8

94.

182.

269.

8315

.60

1984

26.8

617

.02

0.40

16.6

212

.32

4.06

2.46

10.2

315

.69

1985

27.4

116

.94

0.42

16.5

212

.23

4.09

2.33

10.1

616

.12

1986

27.3

017

.19

0.48

16.7

112

.34

4.10

2.44

10.0

216

.18

1987

26.6

417

.47

0.49

16.9

812

.50

4.36

2.54

10.1

616

.20

1988

25.7

118

.07

0.53

17.5

512

.98

4.30

2.78

10.1

916

.59

1989

26.2

217

.92

0.51

17.4

012

.69

4.19

3.00

9.34

16.6

619

9025

.83

18.1

30.

5417

.59

12.7

04.

133.

299.

5116

.49

1991

25.6

818

.27

0.56

17.7

112

.69

4.14

3.46

9.58

16.4

519

9226

.11

18.2

90.

5317

.76

12.7

14.

073.

509.

8216

.39

1993

24.1

818

.83

0.54

18.3

012

.94

4.21

3.64

10.2

416

.50

1994

24.3

418

.98

0.54

18.4

412

.89

4.10

3.59

10.1

616

.23

1995

24.6

518

.66

0.49

18.1

712

.45

3.93

3.99

10.0

516

.14

1996

24.8

118

.64

0.50

18.1

412

.21

3.88

3.82

9.67

16.3

819

9724

.24

18.4

10.

5017

.92

11.6

83.

864.

149.

8616

.32

109

Table A2.3: Distribution of the employed by sector

Period AgricultureManufacturing

and miningConstructiondistribution

Electricityand gas

Transport Trade Others

1969-70 57.03 15.57 3.93 0.41 4.73 9.89 8.44

1970-71 57.58 15.25 3.60 0.25 4.88 10.89 7.56

1971-72 57.32 12.92 3.41 0.37 4.84 9.89 11.25

1972-73 56.47 13.20 3.66 0.41 4.85 10.27 11.15

1973-74 55.62 13.49 3.92 0.45 4.86 10.67 10.99

1974-75 54.80 13.78 4.20 0.49 4.87 11.09 10.77

1975-76 54.25 13.99 4.37 0.54 4.83 11.09 10.92

1976-77 53.71 14.21 4.55 0.60 4.80 11.09 11.04

1977-78 53.71 14.44 4.73 0.67 4.76 11.08 11.15

1978-79 52.65 14.66 4.92 0.74 4.73 11.08 11.22

1979-80 52.67 14.37 4.89 0.82 4.69 11.29 11.26

1980-81 52.69 14.09 4.86 0.91 4.66 11.50 11.28

1981-82 52.71 13.81 4.83 1.02 4.62 11.72 11.29

1982-83 52.73 13.54 4.80 1.13 4.59 11.94 11.27

1983-84 51.63 13.69 5.18 0.88 4.89 11.74 11.99

1984-85 50.56 13.84 5.60 0.69 5.20 11.54 12.57

1985-86 54.01 13.40 5.24 0.52 4.42 11.40 11.01

1986-87 49.24 14.23 6.01 0.73 5.25 12.05 12.50

1987-88 51.15 12.84 6.38 0.59 4.89 11.93 12.22

1988-89 51.15 12.84 6.38 0.59 4.89 11.93 12.22

1989-90 51.15 12.84 6.38 0.59 4.89 11.93 12.22

1990-91 47.45 12.38 6.62 0.83 5.24 13.24 15.22

1991-92 48.27 12.53 6.33 0.79 5.51 13.10 13.48

1992-93 47.54 10.89 6.94 0.85 5.52 13.31 14.95

1993-94 50.04 10.12 6.50 0.87 4.95 12.78 15.56

Source: Labour Force Surveys.

110

Table A2.4: Decomposing output growth, productivity and employment effects

Nto (DP)DY

ProductivityEffect

Pto (DN) DY

EmploymentEffect

DP (DN) DY

Multiple Effect

1969/70 – 1980/81AgricultureManufacturingConstructionTransportTradeOtherTOTAL

1980/81-1990/92AgricultureManufacturingConstructionTransportTradeOtherTOTAL

1991/92 – 1994/95AgricultureManufacturingConstructionTransportTradeOtherTOTAL

0.0630.4600.1780.4160.0450.1450.292

0.6640.8160.0410.3340.4250.3390.578

0.3611.868

-1.2501.090

-0.599-0.0890.400

0.9180.4190.6950.4310.9270.7310.615

0.2360.0890.9320.5010.3900.4910.273

0.623-0.6802.522

-0.0771.7101.1070.571

0.0180.1200.1270.1530.0280.1240.118

0.1000.0940.0260.1630.1840.1700.148

0.0140-0.188-0.272-0.013-0.110-0.0180.028

Source: National Income Accounts and Labour Force Survey (various years).Note: P = Productivity; N = Employment; Y = Output; D = Change; to = original time period.

111

Table A2.5: Employment, output and productivity growth rates (OLS estimates)

1970s 1980s 1990s

Productivity

Total (GDP) 1.50 3.90 1.80

Agriculture -0.10 2.00 1.70

Manufacturing 1.30 7.00 4.60

Construction 0.90 -0.30 -2.20

Transport 2.50 3.40 3.20

Trade 0.50 4.70 -0.90

Employment

Total 3.20 2.40 2.40

Agriculture 2.10 1.90 1.60

Manufacturing 3.00 1.40 -0.40

Construction 7.00 6.00 4.90

Electricity and gas 12.80 -3.90 2.40

Transport 3.00 3.20 0.50

Trade 4.40 2.80 5.00

Others 6.40 3.50 4.30

Output

Total (GDP) 4.70 6.30 4.20

Agriculture 2.00 3.90 3.30

Manufacturing 4.30 8.40 4.20

Construction 7.90 5.70 2.70

Electricity and gas 8.50 9.90 7.40

Transport 5.50 6.60 3.70

Trade 4.90 7.50 4.10

Others 6.40 3.50 4.30

Elasticity

Total (GDP) 0.68 0.38 0.57

Agriculture 1.05 0.49 0.48

Manufacturing 0.70 0.17 -0.10

Construction 0.89 1.05 1.81

Electricity and gas 1.51 -0.39 0.32

Transport 0.55 0.48 0.14

Trade 0.90 0.37 1.22

Note: The estimates are based on Ordinary Least Squares Regression Coefficients.

112

Table A2.6: Corelation coefficents productivity and employment growth

Sectors cor (1970-96) cor (1970s) cor (1980s) cor (1990s)

All -0.71 -0.25 -0.81 -0.43

Agriculture -0.72 -0.13 -0.49 -0.66

Manufacturing and mining -0.89 -0.86 -0.93 -0.96

Construction -0.41 0.42 -0.72 -0.95

Electricity and gas -0.91 -0.61 -0.95 -0.87

Transport -0.84 0.041 -0.93 -0.83

Trade -0.80 -0.67 -0.86 -0.92

Table A2.7:

(i) Correlation matrix between sectoral employment growth rates 1971-97

All Agriculture Manufacturing ConstructionElectricity

and gasTransport Trade

All 1

Agriculture 0.42 1

Manufacturing 0.62 -0.07 1

Construction 0.49 -0.37 0.56 1

Electricity and gas

0.14 -0.46 0.04 0.12 1

Transport 0.50 -0.49 0.59 0.69 0.46 1

Trade 0.17 -0.53 0.61 0.63 0.27 0.50 1

(ii) Correlation matrix between sectoral productivity growth rates 1971-97

All Agriculture Manufacturing ConstructionElectricity

and gasTransport Trade

All 1

Agriculture 0.56 1

Manufacturing 0.45 -0.08 1

Construction 0.35 -0.04 0.06 1

Electricity andgas

0.28 -0.20 0.16 0.04 1

Transport 0.44 -0.33 0.56 0.43 0.43 1

Trade 0.39 -0.13 0.56 0.07 0.32 0.41 1

113

(iii) Correlation matrix between sectoral output growth rates 1971-97

All Agriculture Manufacturing ConstructionElectricity

and gasTransport Trade

All 1

Agriculture 0.58 1

Manufacturing 0.76 0.17 1

Construction 0.34 -0.04 0.25 1

Electricity and gas

0.15 0.04 0.26 -0.10 1

Transport 0.54 -0.13 0.62 0.28 0.14 1

Trade 0.88 0.40 0.63 0.22 0.12 0.39 1

Table A2.8: Poverty GAP (P1) & Foster-Greer-Thorbecke index (P2)1984-85, 1987-88,1990-91

All Pakistan Gazdar et.al (1994) Basket of Basic Needs

(P1) (P2)

1984-85

1987-88

1990-91

0.111 0.077

0.071

0.038

0.023

0.022

Source: Gazdar, et.al. (1994) and Malik, S. (1996).

114

Table A2.9: Growth rates of output productivity and employment

YearOutputgrowth

Productivitygrowth

Employmentgrowth

1971 - - -

1972 2.3 1.3 1.0

1973 6.8 3.0 3.7

1974 7.5 4.6 2.7

1975 3.9 1.1 2.7

1976 3.3 -0.6 3.8

1977 2.8 -1.0 3.8

1978 7.8 3.8 3.8

1979 5.6 1.6 3.9

1980 7.4 5.0 2.2

1981 6.0 3.7 2.3

1982 7.6 5.1 2.3

1983 6.8 4.4 2.3

1984 4.0 1.8 2.1

1985 8.7 6.5 2.1

1986 6.4 6.1 0.2

1987 5.8 -0.4 6.2

1988 6.4 5.4 1.0

1989 4.8 1.6 3.1

1990 4.6 1.5 3.1

1991 5.6 9.1 -3.2

1992 7.7 3.5 4.1

1993 2.3 -1.0 3.4

1994 4.5 1.6 2.9

1995 5.2 4.4 0.8

1996 4.6 1.7 2.8

1997 3.1 0.3 2.8

115

Table A2. 10: Real Wage Trends in Selected Sectors 1971 to 1996 (Index base year 1984)

Year

Manufacturing Constructionc1

Agriculturerural casual

workersdl Rabi KharifLargescaleal

Smallscale and

householdblLabour Carpenters Masons

1971

1972

19731974

1975

1976

19771978

1979

1980

19811982

1983

1984

19851986

1987

1988

19891990

1991

1992

19931994

1995

1996

58

--

----

--

58

6872

78

81

8183

95

100

104113

123

132

----

138

--

----

--

--

--

--

----

--

161

----

--

--

----

--

100

----

--

138

----

--

--

----

--

--

--

--

--84

83

91

9498

115

111

116104

103

100

97100

103

107

103104

101

104

10399

99

96

--

--

--85

86

92

10098

114

113

113104

104

100

9798

101

104

103103

100

98

10097

96

96

--

--

--91

90

103

108105

111

110

110104

105

100

110111

114

116

116118

121

117

124119

121

127

--

--

----

--

--

----

--

--

----

--

100

102107

110

110

108111

110

116

105121

113

114

--

--

----

--

--

----

--

--

----

--

100

104108

118

109

117129

118

118

107116

--

--

--

--

----

--

--

----

--

--

----

--

100

102104

105

114

115127

118

116

112111

--

--

Note: Money wages deflated by the consumer price index.al – Economic survey 1986-87, 1990-91, 1996-97.bl – Census of Small & Household Manufacturing Industries 1976-77, 1983-84, 1988.cl – Economic survey 1986-87, 1996-97, average of Karachi, Lahore, Quetta, Peshawar wages. Datapertains to month of November each year.dl – Monthly Statistical Bullein Jan. 1997, Jan.1992 & Nov. 1988.

116

CHAPTER THREE

ANNEX 3: TABLES

Table A3.1: Selected indicators of employment and output for the economy and agriculture

Year GDP GDP(AG)

POP L F EMPForce

Emp (AG)PRDY (AG)

1971 14.80 5.80 61.49 18.70 18.37 10.58 0.54

1972 15.1 6.0 63.34 18.94 18.55 10.63 0.57

1973 16.1 6.1 65.89 19.61 19.24 10.82 0.57

1974 17.3 6.3 67.90 20.12 19.76 10.99 0.58

1975 18.0 6.2 69.98 20.64 20.30 11.12 0.55

1976 18.6 6.5 72.12 21.54 21.08 11.44 0.57

1977 19.1 6.6 74.33 22.48 21.89 11.76 0.57

1978 20.6 6.8 76.60 23.46 22.73 12.09 0.57

1979 21.8 7.0 78.94 24.49 23.62 12.43 0.57

1980 23.4 7.5 81.36 25.07 24.15 12.72 0.59

1981 24.8 7.6 83.84 25.65 24.70 13.01 0.59

1982 26.7 8.0 86.44 26.27 25.27 13.32 0.60

1983 28.5 8.4 89.12 26.91 25.85 13.63 0.61

1984 29.6 8.0 91.88 27.45 26.40 13.63 0.59

1985 32.2 8.8 94.73 28.00 26.96 13.63 0.64

1986 34.2 9.3 97.67 28.05 27.02 14.60 0.63

1987 36.2 9.6 100.70 29.60 28.70 14.13 0.69

1988 38.5 9.9 103.82 29.93 28.99 14.83 0.67

1989 40.4 10.6 107.04 30.87 29.90 15.29 0.70

1990 42.20 10.9 110.36 31.82 30.82 15.77 0.70

1991 44.60 11.5 113.78 31.83 29.83 14.15 0.80

1992 48.00 12.5 117.31 32.97 31.04 14.98 0.83

1993 49.10 11.9 120.83 33.67 32.08 15.25 0.78

1994 51.40 12.5 124.45 34.69 33.01 16.52 0.75

1995 54.1 13.3 128.01 35.15 33.26 15.56 0.85

1996 56.5 14.0 131.63 36.14 34.20 16.00 0.88

1997 58.3 14.1 135.28 37.15 35.15 16.45 0.85

Note: GDP = Gross domestic product; VA = Value added; POP = Population; LF = Labour force;EMP = Employment; PRDY = Productivity

Source: Labour Force Survey and Natural Income Accounts, various years.

117

Table A3.2: Selected growth indicators of employment and outputfor the economy and agriculture

YEAR VA EMP EMP(AG)

1973 1.67 3.72 1.79

1974 4.18 2.70 1.57

1975 - 2.12 2.73 1.18

1976 4.47 3.84 2.88

1977 2.53 3.84 2.80

1978 2.82 3.84 2.81

1979 3.10 3.92 2.81

1980 6.61 2.24 2.33

1981 2.06 2.28 2.28

1982 4.72 2.31 2.38

1983 4.40 2.30 2.33

1984 -4.82 2.13 0.00

1985 10.92 2.12 0.00

1986 5.95 0.22 7.12

1987 3.25 6.22 -3.22

1988 2.73 1.01 4.95

1989 6.87 3.14 3.10

1990 3.03 3.08 3.14

1991 4.96 - 3.21 - 10.27

1992 9.50 4.06 5.87

1993 - 5.29 3.35 1.80

1994 5.23 2.90 8.33

1995 6.57 0.76 - 5.81

1996 5.27 2.83 2.83

VA = Value added; EMP = EmploymentSource: Labour Force Survey and Natural Income Accounts, various years.

118

Table A3.3a: Output levels and trends in agriculture from 1979-80 to 1994-95

Description 1979-80 1984-85 1989-90 1994-95

A. Value added at constant factor cost of 1959-60 (Rs. billion) for:

(vii) Agricultural sector 15.83 18.60 23.26 28.21

(viii) Crop sector 11.20 12.75 15.29 17.74

(ix) Livestock sector 4.42 5.85 7.51 9.41

B. Output (mil tonnes) of:

• Wheat 10.59 11.70 14.72 17.00

• Cotton 0.73 1.01 1.46 1.48

• Sugarcane 27.50 32.14 35.49 47.12

C. Annual growth rates (% ) over preceeding five years

1. Agricultural sector - 3.28 4.57 3.93

2. Crop sector - 2.63 3.70 3.02

3. Livestock sector - 4.77 6.12 5.70

4. Wheat output - 2.01 4.12 3.49

5. Cotton output - 6.71 7.65 0.27

6. Sugarcane output - 3.12 2.00 12.89

7. Rice output - 1.19 -0.61 1.39

Source: Calculation based on data in Pakistan (1997).

Table A3.3b: Use of Agricultural Inputs for Cultivated Acre 1969-70,1979-80,1984-85, 1989-90 and 1994-95

Year

Acreage input (kgs) per cultivated acre of:

Fertilizer nutrients

Improvedseed

distributedPesticides

Number oftractors per100 Acres

(1) (2) (3) (4) (5)

1969-70 16.00 0.83 0.10 0.17 -

1979-80 51.62 3.01 0.22 0.48 -

1984-85 - 60.81 4.19 0.77 0.76

1989-90 - 90.26 2.90 0.50 -

1994-95 101.53 3.57 1.01 1.17 -

Source: Columns 2-4 from Pakistan (1996 and 1997) and Col. 5 from United Consultants (Private) Limited (1989)and Agricultural Census Organization (1997) Pakistan 1994 Census of Agricultural Machinery. Lahore:Statistics Division, Government of Pakistan

119

Table A3.4: Growth rates of employment in agriculture from alternative sources at mid and endpoints of the decades since 1969-70

Source and descriptionAnnual growth rate during:

1969-70 to 1979-80 1979-80 to 1989-90 1989-90 to 1994-95

A. Agricultural Census Data

1. Family labour 3.14 0.59 -

2. Permanent hired labour -3.44 2.33 -

3. Total permanent labour 2.94 0.62 -

B. Labour Force Surveys*

1. Labour force employed inagriculture

2.30 2.17(2.96)

2.40

C. Labour input changes due to:

1. Cropping pattern change 0.75 0.34 0.74

2. Crop land increase 1.70 1.11 0.62

3. Per acre labour input increase 0.13 0.75 0.19

4. Total 2.58 2.20(2.61)

1.55

Note: Figures in parentheses refer to growth rates during 1984-85 to 1989-90.* Growth rates based on labour force survey data reported in Pakistan (1997) Table 1.10.

Source: For A. Pakistan (1975, 1983 and 1993, for B, C-1 and C-2 Pakistan 1984 and 1997) and for C-3 PERI(n.d.).

Table A3.5: Farms using casual labour and number of permanent hired workers as percentage oftotal permanent labour working in agriculture during 1972, 1980 and 1990

Description

Number (‘000) during the agriculturalcensus of:

1972 1980 1990

A. Total number of farms 3,762 4,070 5,071

1. Farms using casual labour 1,102 1,753 2,557

2. Percentage using casual labour 29.29 43.07 50.42

3. Growth rate of farms using casual labour 5.64 3.85

4. Percentage change of farms using casual labour 59.10 95.90

B. Total permanent labour (family + permanentlabour)

13,366 16,853 17,943

C. Permanent hired labour 512 387 487

D. C as percentage of B 3.83 2.30 2.71

Source: Pakistan (1975, 1983 and 1993).

120

Table A3.6: Population and labour force estimates and trends accordingto Labour Force Survey Data

Areas and year

PopulationCrude

activity rate(%)

Labour force

Number(mn)

Growthrate (%)

Number(mn)

Growthrate (%)

A. Rural areas

1979-80 58.34 - 31.03 18.10 -

1984-85 68.30 3.20 30.65 20.93 2.98

1989-90 77.71 2.62 29.90 23.23 2.08

1994-95 91.12 3.24 28.00 25.51 1.89

B. Urban areas

1979-80 23.02 - 27.17 6.25 -

1984-85 26.43 2.80 27.07 7.16 2.58

1989-90 32.66 4.32 26.28 8.59 3.88

1994-95 36.89 2.47 26.12 9.64 2.33

C. All Areas

1979-80 81.36 - 29.95 24.35 -

1984-85 94.73 3.09 29.59 28.09 2.89

1989-90 110.36 3.10 28.99 31.82 2.52

1994-95 128.01 3.01 27.35 35.15 2.01

Source: Labour Force Survey data given in Pakistan (1997).

121

Table A3.7a: Use of agricultural inputs per cultivated acre 1969-70, 1979-80,1984-85, 1989-90 and 1994-95

Year

Acreage input (kgs) per cultivated acre of:

Fertilizernutrients

Improved seeddistributed Pesticides

Number oftractors per 100

Acres

(1) (2) (3) (4) (5)

1969-70 16.00 0.83 0.10 0.166

1979-80 51.62 3.01 0.22 0.476

1984-85 60.81 4.19 0.77 0.763

1989-90 90.26 2.90 0.50 -

1994-95 101.53 3.57 1.01 1.173

Source: Columns 2-4 from Pakistan (1996 and 1997) and Col. 5 from United Consultants (Private) Limited (1989)and Agricultural Census Organization (1997) Pakistan 1994 Census of Agricultural Machinery. Lahore:Statistics Division, Government of Pakistan.

Table A3.7b: Area under high yielding varieties (HYVs) of wheat, rice and cottonsince 1979-80

Agriculturalcrops and area

Area (million acres) under the crop during:

1979-80 1984-85 1989-90 1994-95

A. Total area under:

Wheat 17.11 17.94 19.38 20.19

Rice 5.03 4.94 5.21 5.25

Cotton 4.99 5.54 6.42 6.56

B. Area under HYV’s of:

Wheat 13.81 16.18 17.99 18.93

Rice 4.31 4.33 4.81 4.97

Cotton 4.61 5.22 6.20 6.35

C. HYV areas as % of total area

Wheat 71.30 90.19 92.83 93.76

Rice 85.69 87.65 92.32 94.67

Cotton 92.38 94.22 96.57 96.80

Source: Pakistan (1996).

122

Table A3.8: Rates of rural unemployment and underemployment in Pakistan and provinces

PeriodPercentage of labour force (%)

Pakistan Baluchistan NWPF Punjab Sindh

A. Rate of unemployment

1979-80 2.33 2.96 2.00 2.54 1.64

1982-83 3.19 3.07 7.53 3.43 0.40

1984-85 2.95 1.03 3.53 3.43 1.28

1985-86 3.12 3.19 5.71 3.27 0.80

1986-87 2.50 0.64 3.83 2.82 0.63

1987-88 2.60 0.44 4.57 2.80 0.67

1990-91 5.47 4.09 5.48 6.46 2.19

1991-92 5.40 2.73 5.51 6.21 2.85

1992-93 4.28 2.24 5.50 4.82 1.98

1993-94 4.22 1.58 5.23 4.61 2.36

1994-95 4.80 4.09 7.10 4.86 2.28

B. Underemployment (working less than 35 hours per week)

1982-83 16.24 4.96 9.28 17.65 17.51

1984-85 11.64 8.64 10.76 11.68 12.92

1985-86 12.00 6.46 12.33 11.90 13.49

1986-87 12.68 1.19 15.23 13.80 9.44

1987-88 13.27 3.62 20.41 14.58 4.96

1990-91 14.83 11.63 19.43 18.45 9.90

1991-92 16.51 11.39 18.78 18.62 7.75

1992-93 15.02 14.12 21.05 15.91 7.75

1993-94 15.26 13.87 20.29 14.69 10.94

Note: Underemployment rates for 1979-80 and 1994-95 are not available.Source: Pakistan (1984, n.d. and 1997).

123

Table A3.9: Cropping pattern and average labour input per crop acre for various years andprovinces

Geographical areaand year

Percentage (%) area under:

Wheat Rice Cotton SugarcaneFruits andvegetables

Othercrops

A. Pakistan

Labour input(Man-days per acres)

40.7 34.7 47.1 169.5 74.6 20.0

1979-80 36.0 10.6 10.8 3.7 2.3 36.6

1984-85 36.6 10.0 11.2 4.6 3.1 34.5

1989-90 36.5 9.8 12.1 4.0 3.4 34.2

1994-95 36.9 9.6 12.0 4.6 4.1 33.8

B. Punjab

1979-80 38.1 9.1 11.4 3.8 2.0 35.6

1984-85 37.9 8.2 11.5 4.6 2.9 34.9

1989-90 37.9 8.5 13.6 3.3 3.1 33.6

1994-95 37.7 8.6 14.3 4.2 3.4 31.8

C. Sindh

1979-80 26.3 19.2 15.3 3.3 2.3 33.6

1984-85 22.7 18.5 18.0 4.8 2.7 28.3

1989-90 27.7 17.6 14.9 6.7 3.2 29.9

1994-95 30.3 17.1 11.7 7.1 3.7 30.1

D. NWFP

1979-80 39.8 3.7 - 4.7 2.6 49.2

1984-85 40.7 3.6 - 5.2 2.1 48.4

1989-90 41.4 3.0 - 4.9 3.5 47.2

1994-95 41.0 2.9 - 4.8 3.8 47.5

E. Baluchistan

1979-80 45.2 9.5 - - 9.5 35.8

1984-85 43.8 18.8 - - 10.9 26.5

1989-90 42.9 15.7 - - 12.9 28.5

1994-95 37.4 13.3 - - 17.6 31.8

Source: Pakistan (1996) for crop shares and Chaudhry (1982) for labour input.

124

Table A3.10: Rate of profit in Pakistan's agriculture: 1982-83 to 1991-92

Commodity andprovince

Rate of profit (percentage) during:

1982-83 1983-84 1984-85 1985-86 1986-87 1987-88 1988-89 1989-90 1990-91 1991-92

1. Wheat

Punjab -1.70 -12.57 -3.71 6.67 0.38 0.98 7.46 15.11 16.55 10.32

Sindh -1.70 8.29 5.74 17.47 11.11 11.79 6.38 16.08 15.70 11.71

2. Rice coarse

Punjab - -11.23 -14.39 -8.01 -11.49 -12.59 -8.84 -5.96 -4.76 -18.11

Sindh - -11.23 27.60 26.13 31.56 22.22 8.70 12.82 5.01 0.00

3. Sugarcane

Punjab - - 14.20 13.26 26.77 24.11 23.43 23.87 15.53 10.20

Sindh - - 16.09 15.14 35.80 32.78 35.37 35.92 32.35 25.95

4. Seed cotton

Punjab - 9.77 5.43 4.43 19.58 11.56 10.11 13.47 13.11 11.69

Sindh - - - - 65.50 16.30 15.50 18.30 14.30 11.40

5. Rice basmati

Punjab - -5.51 2.35 2.38 6.92 31.45 21.18 22.75 7.99 7.90

Source: Afzal et al (1992 and 1993).

Table A3.11: Relative shares of agricultural and non-agricultural sectors in rural employment since 1979-80

YearsEmployment rural

labour force

Percentage ofemployment in

agriculture

Share of non-agricultural

sector

1979-80 100.00 68.76 31.24

1982-83 100.00 67.69 32.31

1984-85 100.00 66.69 33.31

1985-86 100.00 70.94 29.06

1986-87 100.00 65.24 34.76

1987-88 100.00 67.49 32.51

1990-91 100.00 63.74 36.26

1991-92 100.00 63.26 36.74

1992-93 100.00 63.76 36.24

1993-94 100.00 64.76 35.24

1994-95 100.00 61.94 38.06

Source: Population Census 1981, Pakistan (1997) and Various Labour Force Surveys.

125

Table A3.12: Area and permanent (hired and family) labour input per acre by farm size for 1979-80 and 1989-90

Farm size

Area and permanent labour input during:

1979-80 1989-90

Area(%)

Labour (man-years)

Area(%)

Labour(man-years)

All sizes 100.00 0.2820 100.00 0.2898

Under 1.0 acre 0.19 4.2559 0.39 3.9914

1.0 - 2.5 acres 1.75 1.5215 3.28 1.3842

2.5 - 5.0 acres 5.10 0.5941 7.56 0.7128

5.0 - 7.5 acres 8.54 0.5342 10.31 0.4654

7.5 - 12.5 acres 18.76 0.3619 17.32 0.3097

12.5 - 25.0 acres 24.67 0.2477 21.58 0.2007

25.0 - 50.0 acres 17.81 0.1528 15.83 0.1200

50.0 - 150.0 acres 14.68 0.0786 13.64 0.0633

150.0 acres and above 8.50 0.0309 10.09 0.2610

Source: Pakistan (1983 and 1993).

Table A3.13: Proportionate area and labour input (man-hours per crop acre)under various technological packages

DescriptionBullocks

onlyBullock-cum-

tractorTractor

only

A. Percentage area

1979-80 57.67 29.45 12.88

1989-90 17.69 30.33 52.98

B. Labour input

Family and permanently hired 184 141 110

Casual labour 42 85 70

Source: Pakistan (1983 and 1993) and United Consultants (1989).

126

Table A3.14: Changing patterns of land tenure between 1979-80 and 1989-90

Census years andtenurial classes

Number of farms (‘000) andoperational farm area (million acres)

Number of farms Operational farm area

Number Percentage Area Percentage

A. 1980 Agricultural Census

1. All farms 4,070 100.00 47.09 100.00

2. Owner farms 2,227 54.72 24.53 52.09

3. Owner cum tenant 789 19.38 12.40 26.33

4. Tenant fars 1,054 25.90 10.16 21.58

B. 1990 Agricultural Census

1. All farms 5,071 100.00 47.32 100.00

2. Owner farms 3,491 68.84 30.73 64.94

3. Owner cum tenant 626 12.35 8.98 18.98

4. Tenant farms 954 18.81 7.61 16.08

Source: Pakistan (1983 and 1993).

1 The table is based on data from the 1991 Pakistan Integrated Household Survey. The identification of householdswas sequential, with priority given to the identification of agricultural households in rural areas, followed by wage earnersoutside agriculture and self-employed outside agriculture. Agricultural households were identified from their land ownershipor operation status, ownership of other agricultural assets such as livestock, and reporting of earnings from agricultural labour.Of the remainder, if the household head reported any positive wage income and his/her occupation as employment, thehousehold was classified as a non-agricultural wage earner. The residual households were classified as self-employed if thehousehold head reported any positive income from self-employment, and as “other” if they could not be classified under anyof the above categories, or were non-earners or unemployed. The category “other agriculture” includes those who did not reportland ownership or operation, but did own other agricultural assets such as livestock. The poverty line used is Rs 296 per capitaper month in 1991/92 rural prices.

127

Table A3.15: Employment profile of household heads and incidence of poverty, 1991

Urban Rural

Proportionof sample

(%)

Incidenceof poverty

(%)

Poor(%)

Proportionof sample

(%)

Incidenceof poverty

(%)

Poor(%)

Agriculture 63.60 35.10 64.70

By land ownership

Tenant 36.60 30.20 32.00

Agricultural Labourer 13.60 43.80 17.30

Other Agriculture 7.00 56.00 11.40

Non-Agriculture Wage Earners 43.80 28.40 39.60 17.90 29.80 15.50

By type of job

White collar 14.20 22.1 10.00 6.50 26.30 5.00

Skilled/Semi-skilled 20.10 28.1 18.00 6.60 22.10 4.20

Casual/Manual 9.50 38.3 11.60 4.80 45.10 6.30

Self-EmployedOut-side Agriculture

36.30 34.00 39.30 15.20 36.30 16.00

By value of assets

Rs. 1,000 or less 9.30 51.20 15.20 4.30 46.30 5.80

Rs. 1,000 – 10,000 12.40 34.5 13.60 6.00 39.20 6.80

Rs. 10,000 or more 14.60 22.2 10.30 4.80 24.50 3.40

Other 19.90 33.7 21.40 3.40 41.10 4.10

Overall 100.00 31.40 100.00 100.00 34.50 100.00

Source: Gazdar, Howe and Zaidi (1994).1

128

Tab

le A

3.16

:R

eal w

ages

for

agr

icul

ture

wor

kers

(av

erag

e in

Rs.

per

day

)

1984

-85

1985

-86

1986

-87

1987

-88

1988

-89

1989

-90

1990

-91

1991

-92

1992

-93

1993

-94

1994

-95

Kha

rif

15.0

015

.28

15.8

517

.38

15.9

717

.21

18.8

517

.35

17.2

615

.68

17.0

1

Rab

i15

.00

15.5

615

.85

16.0

717

.46

17.6

319

.32

18.0

117

.69

17.1

017

.01

CPI

131.

8313

7.57

142.

5215

1.49

167.

2317

7.33

199.

7822

0.69

242.

7326

9.98

305.

12

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), ci

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mpl

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vide

nce,

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CHAPTER FOUR

ANNEX 4: TABLES

Table A4.1: Capital stock ratios in large-scale manufacturing, 1990-91 (Rs million or %)

Gross output Capitalper

worker

Netoutput

perworker

Net output% of

Per unitPer

workerGrossoutput

Capitalstock

Consumer goods 77.80 0.49 0.158 0.130 34.2 82

Food, geverages and tobacco 80.20 0.78 0.182 0.224 28.9 123

Of which: Sugar 423.30 0.50 0.256 0.203 40.7 7

Textiles, garments and footwear 76.90 0.38 0.156 0.100 25.3 62

Of which: Cotton yarn and cloth 236.70 0.39 0.188 0.109 28.0 58

Other consumer goods 73.40 0.58 0.104 0.126 21.8 121

Intermediate goods (cons.) 104.60 1.30 0.228 0.239 18.4 105

Cotton ginning 57.80 1.88 0.066 0.108 5.8 164

Industrial chemicals 168.20 1.13 0.477 0.379 33.4 79

Of which: Fertilizers 902.50 1.13 0.605 0.431 38.3 71

Petroleum refining 10122.30 13.50 0.809 0.960 7.1 119

Other cons-related inter. goods 63.80 0.68 0.146 0.184 26.8 125

Intermediate goods (invest.) 72.20 0.49 0.437 0.166 34.0 38

Non-metallic mineral products 99.60 0.57 0.436 0.261 46.2 60

Of which: Cement 582.90 0.86 0.655 0.428 49.8 65

Gross output Capitalper

worker

Netoutput

perworker

Net output% of

Per unitPer

workerGrossoutput

Capitalstock

130

Iron and steel 116.90 0.50 0.537 0.134 27.0 25

Other inv-related inter. goods 15.40 0.28 0.084 0.062 22.3 75

Capital goods 49.70 0.53 0.125 0.131 24.7 105

Machinery (including electrical) 44.20 0.49 0.128 0.143 29.4 112

Transport equipment 111.80 0.78 0.141 0.142 18.3 101

Other capital goods 15.40 0.25 0.084 0.056 22.0 67

Total or average 78.20 0.60 0.202 0.149 24.8 74

Memo: “Big Four” a 307.40 0.47 0.249 0.160 34.2 64

Note: a “Big Four” refers to sugar, textiles (cotton yarn and cloth), cement and fertilizers.Source: Censuses of Manufacturing Industries.

Table A4.2: Ratio of fixed assets to employment

Major IndustryK/L ratio

1988-87 1990-91

Food 183,045 177,905

Beverages 132,167 228,000

Tobacco 32,333 85,833

Textiles 93,327 151,172

Wearing apparels 39,417 46,050

Leather and products 49,833 104,733

Ginning, pressing and bailing - -

Wood and products 303,000 203,333

Furniture and fixture - -

Paper and products 153,222 207,875

Printing and publishing 60,583 121,000

Drugs and pharmaceutical products 86,267 120,889

Industrial chemicals 453,000 449,000

Other chemical products 80,364 110,889

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Petroleum refining 1,176,500 984,000

Petroleum and coal products 77,000 92,500

Rubber products 94,875 103,875

Plastic products 95,000 133,200

Non-metallic mineral products 331,036 443,000

Iron and steel basic industries 612,667 546,614

Fabricated metal products 67,000 76,417

Non-electrical goods 101,947 95,960

Electrical machinery 74,250 152,684

Transport equipment 70,913 135,947

Measuring, photographic, optical goods 62,000 43,500

Sports and athletic goods 86,319,000 14,962,250

Others - -

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Table A4.3: Capital output ratios wage – value added ratios

Capital output ratios Wage – value added ratios

1980-81

1984-85

1987-88

1990-91

1980-81

1984-85

1987-88

1990-91

All industries 1.7 1.89 1.421 1.350 0.417 0.355 0.253 0.285

Food manufacturing 1.3 1.34 0.746 1.169 0.229 0.273 0.207 0.251

Beverage industries 1.4 2.13 0.776 1.103 0.374 0.510 0.159 0.184

Tobacco manufacturing 0.4 0.75 0.056 0.079 0.325 0.313 0.031 0.032

Textile 1.8 1.70 1.538 1.576 0.551 0.373 0.290 0.322

Wearing apparel 0.8 1.14 0.665 1.086 0.313 0.694 0.398 0.754

Leather and leather products 0.7 0.53 4.203 1.891 0.181 0.217 0.991 0.452

Foot-wear except rubber or plastic 0.3 0.88 0.633 1.404 0.338 0.323 0.480 0.870

Ginning and bailing of fibres 0.5 0.76 0.623 0.435 0.183 0.266 0.347 0.325

Furniture and fixtures, not metal 0.8 5.12 3.192 1.022 0.387 0.373 0.449 0.347

Other paper products 1.6 2.11 1.959 1.491 0.535 0.440 0.319 0.229

Printing and publishing 2.1 1.57 1.388 0.420 0.558 0.506 0.606 0.166

Drugs and pharmaceutical products 0.4 1.14 0.875 0.798 0.236 0.385 0.478 0.479

Industrial chemicals 4.2 2.10 1.725 1.259 0.332 0.269 0.224 0.220

Other chemical products 1.0 0.55 0.501 0.497 0.395 0.233 0.194 0.217

Petroleum refining na 4.59 0.508 0.843 na 0.183 0.043 0.116

Rubber products 0.6 1.66 1.558 0.972 0.345 0.489 0.433 0.388

Plastic products 2.4 1.43 1.484 0.095 0.784 0.362 0.424 0.376

Pottery, china and earthenware 2.2 2.42 1.415 3.011 0.538 0.478 0.411 0.424

Other non-metallic mineral products 7.9 1.81 1.492 na 0.938 0.303 0.156 7.622

Glass and glass products 2.3 4.49 2.010 1.609 na 0.604 0.344 5.740

Iron and steel 1.0 1.40 5.784 4.019 0.863 na 0.422 0.543

Non-ferrous metal basic industries 1.4 1.12 0.470 2.662 0.756 0.403 0.722 0.676

Metal products, machinery, equipment

1.8 1.10 1.036 0.955 0.595 0.419 0.418 0.381

Non-electrical machinery 1.0 1.09 1.888 1.049 0.458 0.518 0.538 0.530

Transport-equipment 2.3 1.17 1.730 0.988 -na 0.319 0.676 0.414

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Table A3.4: Determinants of labour productivity and employment in PakistanOLS Regression results

log V/L = 0.89 + 0.85 log K/L + 0.05t(0.41) (3.84) (12.32)

R2 = 0.99 D.W. 1.20

log V/L = -0.48 + 0.81 log K/L + 1.74 log V+ 0.040t(0.16) (3.41) (0.69) (2.56)

R2 = .99 D.W. = 1.09

log V/L = -6.68 + 0.78 log K/L + 0.79 log V(3.30) (2.79) (10.02)

R2 = .98 D.W. = 0.53

log V/L = -1.15 + 0.99 log v(2.50) (23.85)

R2 = .97 D.W. 1.15

log L = 6.99 - 0.58 log K/L - 0.01 t(2.41) (-1.96) (1.80)

R2 = 0.22 D.W. 0.49

log L = 0.48 + 0.83 log V - 0.81 log K/L - 0.04 t(-.20) (3.30) (3.41) (2.l56)

R2 = .57 D.W. 1.09

Log L = 6.68 + 0.21 log V - 0.78 log K/L(3.30) (2.67) (2.78)

R2 = .36 D.W. = 1.5

Log L = 1.15 + 0.013Log V(2.50) (0.31)

R2 = 0.06 D.W. = 1.15

where: V = Value added in manufacturingK = Capital stock in manufacturingL = Labour in manufacturingt = time trend

Table A4.5: Productivity in different manufacturing industries in 1990-91 (Base=1982-83)

Labour productivity Capital productivityTotal factorproductivity

Food 84.3 76.7 98.3

Textiles 257.1 151.3 103.1

Leather 57.2 53.2 94.9

Drugs and pharmaceutical 124.7 70.0 97.6

Industrial chemicals 139.4 196.0 104.2

Plastic products 109.1 106.0 100.2

Electrical machinery 175.0 103.9 100.7

Transport equipment 145.0 72.9 99.3

Cement 72.6 61.3 96.6

Source: DRI/PIDE Technology Study (1977).

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Table A4.6: Labour productivity and capital intensity manufacturing (Rs. Mn)

1984-85 1985-86 1986-87 1987-88 1990-91

Labour productivity (Value added/employment)

0.104 0.109 0.127 0.144 0.178

Capital intensity(Value of fixed assets /employment)

0.099 0.123 0.166 0.168 0.192

Source: Economic Survey 1995-96.

Table A4.7: Investment in manufacturing industries

Investment in manufacturing as percentage of GDP Share of private

investment in totalmanufacturing

Private Public Total

1982-83 1.7 1.3 3.0 57.0

1983-84 2.9 1.2 3.1 60.0

1984-85 2.0 0.8 2.7 72.1

1985-86 2.2 0.8 3.0 72.6

1986-87 2.6 0.4 2.9 87.1

1987-88 2.5 0.4 2.9 86.5

1988-89 2.9 0.4 3.4 87.2

1989-90 3.3 0.5 3.7 88.0

1990-91 3.3 0.5 3.8 87.6

1991-92 4.3 0.5 4.8 89.8

1992-93 4.2 0.5 4.7 89.1

1993-94 4.2 0.5 4.7 87.7

1994-95 2.2 0.5 2.7 80.8

1995-96 2.3 0.6 2.9 80.9

1996-97 2.1 0.6 2.7 77.4

Source: Based on data obtained from Economic Survey, 1996-97 and previous issues.

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Table A4.8: Composition of total investment in the manufacturing sector

Percentage share in investment

1982-83 1988-89 1992-93

Food, tobacco and beverages 14.30 18.90 26.40

Textiles 16.09 41.00 29.30

Leather, footwear and leather goods 1.50 3.70 2.30

Rubber and rubber products 3.60 0.80 1.20

Pulp and paper 5.50 4.30 4.60

Chemicals, pharmaceuticals and fertilizers 27.60 7.30 10.10

Cement and other non-metallic minerals products

12.80 4.90 2.90

Basic metals 2.30 1.20 1.80

Metal products other than machinery and transport equipment

2.50 1.10 1.30

Machinery other than electrical 2.40 1.10 1.30

Electrical machinery, appliances and fittings 3.20 3.20 2.70

Transport equipment 2.20 2.50 3.40

Services and miscellaneous industries 5.10 9.10 13.60

Source: National Accounts, 1988/89, and unpublished data from Federal Bureau of Statistics.

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Table A4.9: Composition of industrial output in Pakistan

Industries

Percentage share in value addedat factor cost

1980-81 1985-86 1987-88 1990-91

1 Food Industries 24.21 15.69 15.49 14.24

2 Beverage Industries 0.90 1.52 0.61 1.27

3 Tobacco Manufacturing 3.00 2.87 5.38 7.49

4 Manufacturing of textiles 24.32 19.85 21.43 25.97

5 Manufacturing of wearing apparel except footwear 1.42 1.55 1.96 1.03

6 Manufacturing of leather and leather products, leather substitutes and fur except wearing apparel

1.62 2.34 1.60 0.73

7 Manufacturing of footwear except vulcanizedmolded rubber of plastic footwear

1.29 0.29 0.99 0.38

8 Ginning, pressing and baling of fibres 4.65 2.60 1.25 1.23

9 Manufacturing of wood and cork products except furniture

0.43 0.48 0.61 0.26

10 Manufacturing of paper and paper products 2.06 1.26 1.32 1.69

11 Printing publishing and allied industries 1.15 1.54 1.33 2.57

12 Manufacturing of drugs and pharmaceutical products

5.35 5.72 3.46 3.46

13 Manufacturing of Industrial chemicals 5.88 14.18 8.35 7.25

14 Manufacturing of other chemical products 1.99 3.62 3.11 2.31

15 Manufacturing of rubber products 1.26 1.86 0.70 0.86

16 Manufacturing of plastic products n.e.c. 0.24 0.75 0.51 0.55

17 Manufacturing of pottery, china and earthenware 0.32 0.32 0.42 0.25

18 Manufacturing of non-metallic mineral products 2.36 4.86 6.02 7.69

19 Iron and steel basic industries 6.61 5.32 8.26 6.34

20 Non-ferrous metal basic industries 0.06 0.02 0.02 0.03

21 Manufacturing of fabricated metal products except machinery and equipment

1.30 1.10 0.93 0.80

22 Manufacturing of machinery except electrical 2.59 3.26 2.09 2.46

23 Manufacturing of electrical machinery apparatus, appliances and supplies

4.25 4.06 3.53 4.21

24 Manufacturing of transport equipment 2.49 3.36 4.62 2.86

25 Manufacturing of scientific, precision and measuring instruments and equipment

0.29 0.17 0.40 0.14

26 Manufacturing of photographic and optical goods 0.04 0.03 - -

27 Manufacturing of sports and athletic goods 0.10 0.17 0.25 0.32

28 Other manufacturing industries 0.36 0.29 5.00 1.27

Source: Census of Manufacturing Industries, 1980-81, 1985-86, 1987-88 and 1990-91.

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Table A4.10: Industrial production – large-scale (percentage share)

Item 1988-89 1989-90 1990-91 1991-92 1992-93 1994-95 1995-96 1996-97

Food, beverage and tobacco

26.14 25.58 24.25 25.52 27.06 28.65 28.53 26.10

Food 18.89 18.76 18.83 19.57 19.59 21.68 20.73 18.34

Beverages 5.55 2.18 4.03 4.68 6.15 5.60 6.62 6.10

Cigarettes 1.70 1.64 1.30 1.27 1.32 1.37 1.18 1.66

Textile, apparel and leather

24.75 26.46 26.03 27.48 26.78 26.05 26.07 28.32

Textiles 16.13 18.11 17.17 17.50 19.62 19.93 20.03 21.39

Jute goods 1.36 1.22 1.22 1.16 1.04 0.79 0.67 0.69

Leather 1.84 1.83 1.73 1.58 1.39 1.29 1.23 1.15

Cotton (ginned) 5.41 5.30 5.91 7.24 4.73 4.04 4.14 5.09

Paper and board 2.29 2.16 1.87 1.99 2.75 2.69 2.99 2.84

Pharmaceuticals, chemicals and rubber

19.16 18.52 18.79 17.70 17.88 18.57 17.22 18.67

Pharmaceuticals 7.04 7.16 7.52 7.60 7.56 7.07 6.32 6.50

Chemicals 11.26 10.54 10.39 9.41 9.74 10.88 10.24 11.44

Rubber 0.86 0.82 0.88 0.69 0.59 0.62 0.66 0.74

Petroleum products 7.13 7.17 8.02 7.40 6.56 6.43 5.60 6.02

Non-metallic mineral products

2.70 2.72 2.82 2.71 2.59 2.42 2.37 2.68

Basic metal industries 6.78 6.49 7.22 6.65 6.44 7.02 5.73 5.60

Metal products, machinery

11.06 10.90 11.00 10.54 9.94 8.18 11.50 9.77

Metal products 0.29 0.29 0.25 0.28 0.29 0.23 0.24 0.27

Machinery 1.33 1.05 0.78 0.56 0.84 0.52 0.47 0.44

Electrical machinery 4.98 4.85 5.15 4.85 4.57 4.55 4.75 5.02

Transport equipment 4.46 4.75 4.82 4.85 4.24 2.88 6.04 4.04

TOTAL 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00

Source: Unpublished National Accounts Data.

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Table A4.11: Capacity utilization in major industries

1992-93 1993-94 1994-95 1995-96

Spinning 80.30 71.90 72.10 61.50

Weaving 42.90 42.90 35.70 42.90

Jute Goods - 50.70 44.70 47.30

Fertilizer 87.70 93.50 92.40 100.60

Cement 104.80 99.60 95.40 96.60

Sugar 99.10 102.20 95.40 69.50

Source: Planning and Development Division.

2 See ILO-SAAT, Mahmood, M., 1997, mimeo for details.

3 This is sometimes attributed to the effect of the first PPP governments’ nationalization of some large-scaleindustries.

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CHAPTER FIVE

ANNEX 5.12: THE SMALL-SCALE ENTERPRISE SECTOR IN MAIN DATA SOURCES

The data sources include National Income Accounts, Labour Force Surveys, the Economic Survey as wellas major surveys done for this sector in Pakistan. These major surveys are: the Small Household andManufacturing Industries (SHMI) 1983-84, 1988; the Census of Establishments 1987-88, the HouseholdIntegrated Economic Survey (HIES) 1987-88, 1990-91; the Integrated Survey of Service and ManufacturingIndustries-Small, (ISSMI-Small), 1992.

Partial estimates of the output of the sector based on National Income Accounts (NIA) (table A5.1), suggestthat its output share in manufacturing is around 30 per cent while its employment share is nearly 83 per cent(table A2). NIA, however calculate the size of the small-scale sector as a residual. In short, according toNIA we have a disproportionately high share of employment within manufacturing which goes to the SSE.Another characteristic of the SSE sector is its allegedly high growth rate. The combination of highemployment absorption capacities and its supposedly high growth rate make this sector a focus of attentionfrom an employment perspective.

Rates of growth

It is therefore important to estimate the growth rate of the sector as correctly as is possible, even if it is onlyin manufacturing. However, serious problems arise. Of the two methods of calculating growth rates of theSSE in Pakistan, one is based on National Income Accounts (NIA) and the other on inter-survey data onthe SSE. National Income Accounts essentially calculate the growth rate between two residual categories(the estimate of the sector’s size is itself based on a residual); these calculations give a high growth rate forthe sector. Inter-survey data on the other hand give a much lower rate of growth, although they have someproblems of definition and comparability.

On NIA data, during the period 1980-81 to 1992-93, the manufacturing sector as a whole grew by 7.3 percent, the large-scale sector is supposed to have grown by 7.1 per cent. This gives a residual growth rate ofthe SSE of 8.1 per cent (see table A5.3). If the period is extended up to 1996-97, the growth rate of the SSEbecome even higher at nearly 10 per cent. NIA data over the long run show, that during the 1950s and 1960sthe large-scale sector was the leading sector in manufacturing. In the 1970s a reversal took place when thegrowth of the large-scale sector dropped (to around 4 per cent) and that of the small sector increased (tonearly 8 per cent)3. Over the 1980s , the period of high growth of the economy both sectors registered agrowth of around 8 per cent. Since 1987-88, the trend in large-scale manufacturing growth is one of decline.However, a constant rate of growth of 8.4 per cent is estimated for the SSE for each subsequent year, upto 1997. This suggests that the estimate is likely to be ‘projection based’ and does not have a directempirical basis (see table A5.4).

The growth of the SSE in manufacturing from the alternative survey sources give different growth figures.There are two sources here. First we have the Survey of Small Household-based Manufacturing Industries

4 The differences between the SHMI surveys and ISSMI-Small in definitions and coverage are the following: SHMI1976/77: (a) Surveyed establishments; (b) With an investment of less than Rs. 2 million; (c) In urban areas only. SHMI1983/84: (a) Surveyed establishments; (b) Which were not registered; (c) In both urban and rural areas. SHMI 1988: (a)Conducted a census of establishments; (b) Employing less than 10 workers; (c) In both urban and rural areas. ISSMI-Small1992/93: (a) Surveyed establishments; (b) Which were neither listed on the stock exchange, nor registered with theGovernment, nor Government sponsored; (c) In both urban and rural areas.

5 To make the SHMIs for 1976/77 and 1983/84 comparable and to calculate the growth rate, Table A5.5 carries outa procedure detailed in Input Output Table for Pakistan, 1993. In essence the procedure is the following: for the SHMI 1983/84,it takes the Gross Value Added (GVA) revised downwards for 6 industries with estimation errors, per urban labourer. It thenestimates the labour force in manufacturing for 1983/84 and subtracts the large-scale sectors share given in the Census ofManufacturing industries (CMI) for 1983/84. This gives an SSE labour force for both rural and urban areas. Then SSEemployment multiplied by SSE GVA per labourer gives a total SSE GVA of Rs 12.8 billion. For the SHMI 1976/77 it followsa similar procedure to give a total SSE GVA of Rs 5.6 billion. These values for 1976/77 and 1983/84 are then indexed bywholesale prices. This procedure gives a growth rate for the inter-survey period of 1976/77 - 1983/84 of 4.4 per cent in TableA5.5. We have followed an additional procedure given in SHMI 1988, which makes urban SHMI 1983/84 comparable to urbanSHMI 1988 [SHMI, 1988]. This involves subtracting units employing more than 10 workers from urban SHMI 1983/84. Thisprocedure gives a growth rate for the inter-survey period of 1983/84 and 1988 of 4.7 per cent in Table A5.6.

The growth rates for value added per unit of labour are given in Table A5.7. Finally in Table A5.8 we have calculatedgrowth rates for value added in the SSE sector for the most recent period possible, 1983/84 to 1992/93. This involves acomparison between the SHMI 1983/84, and the most recently conducted Integrated Survey of Service and ManufacturingIndustries Small (ISSMI-Small) for 1992/93. There is some justification for making this comparison because, as the abovedefinitions show, both the SHMI 1983/84 and ISSMI Small 1992/93 surveyed the unregistered sector. In Table A5.8 we havecompared SHMI 1983/84 which is for manufacturing only, with ISSMI-Small 1992/93 for manufacturing. This gives an evenlower growth rate for the SSE sector between 1983/84 and 1992/93 of 2.6 per cent p.a.

140

(SHMI) surveys for 1976-77, 1983-84 and 1988. Growth rates can be calculated from these, subject tomodifications, due to differences in definitions and coverage of the SSEs in the three surveys, in order tomake the basis of calculations consistent. There is also a fourth Integrated Survey of Service andManufacturing Industries –Small (ISSMI-Small) for 1992-934 .

An input-output table for Pakistan has been used to make the SHMIs of 1976-77 and 1983-84 comparable(table A5.5) . This gives a growth rate of SSE between 1976-77 and 1983-84 of 4.4 per cent. Makingthe SHMIs of 1983-84 and 1988 comparable, a growth rate of 4.7 per cent is estimated. The finalcomparison is between the SHMI 1983-84 and ISSMI-Small 1992-93.5 This gives an even lower growthrate of 2.6 per cent.

Thus, NIA-based growth rates for the SSE sector in manufacturing are high, at around 8 per cent for the1970s, 1980s and the 1990s. In contrast inter-survey growth rates for the 1970s and 1980s are much lowerat 4.5 per cent and, for the last decade, up to 1992-93, even lower at 2.6 per cent. Even if we take anequivocal view on the data sources for the calculation of growth rates the SSE sector in manufacturingcannot be considered to have had unambiguously high growth rates during the 1970s, 1980s and 1990s.The likelihood is that growth rates were considerably lower, especially in the past decade. We now examinethe profile of SSEs as it is revealed in the major surveys.

Broad characteristics

The SHMI

In 1988 there were 258,000 SSE units in manufacturing. They had fixed assets of Rs.5.6 billion; employed.6 million persons and produced a value added of Rs 9.9 billion.

141

The value added per worker (labour productivity) of the sector was Rs. 18,000 in urban areas andRs. 11,000 in rural areas (table A5.7). In contrast, large-scale sector labour productivity is 10 timesgreater on average. The capital-labour ratio, i.e. the capital intensity, for the SSE is around Rs. 9,000. Thelarge-scale sectors value of capital per worker is Rs. 202,000 (not provided in a table here), which is greaterby a factor of 22 in comparison to the SSE (table A5.9). The capital output ratio of the SSE is 1.8, whichis also lower than 3.0 for large-scale sector. Clearly, both in terms of capital intensity and labourproductivity the SSE sector is much lower than the large-scale sector.

In terms of value of assets the predominant SSE sub-sectors are food (31 per cent); followed by textiles (24per cent); wood products (17 per cent) and fabricated metals (15 per cent). In employment, textiles have thelargest share (42 per cent) followed by food (16 per cent); wood products (15 per cent) and fabricated metals(14 per cent). Textile again have the highest share in value added at 36 per cent, followed by food (18 percent) and fabricated metals and wood with a 15 per cent share.

The significant industries within each major sub-sector can be determined on the basis of value added. Intextiles, the largest industries are weaving (11 per cent share in total SSE manufacturing value added(TVA)) and carpets (7 per cent of TVA). In the second largest sub-sector, which is food products, thelargest industry is wheat milling (8 per cent of TVA) and rice (2 per cent of TVA). In the third largest sub-sector of fabricated metals, the major industry is metal products (8 per cent of TVA) followed by non-electrical machines (3 per cent of TVA). In the fourth largest sub-sector, wood products, the mostsignificant industry is furniture (6 per cent of TVA).

If we rank the industries on their own, weaving is the largest, followed by metal products, wheat milling,jewelry (a category on its own), furniture and non-electrical machinery.

The Census of Establishments (CE) 1987-88 and the Household IntegratedEconomic Survey 1990-91 (HIES)

The SHMI of an SSE employment of .63 million workers and 258,000 units is also partial as it excludesnon-manufacturing sector. This SHMI estimate, however, is complemented well by a survey of income forthe same year, the Census of Establishments (CE) 1987-88. The two together allow an estimate of the entireSSE sector.

The CE estimates of non-farm establishments using less than 10 workers are around 1.8 million, whichemploy 3.1 million workers. The share of manufacturing in employment from this data source is 0.65 millionwhich is consistent with the SHMI data set, this is also the case with the sectoral compositions.

The total picture therefore gives an employment size of 2.45 million workers in non-manufacturingemployment in 1987-88 (table A5.10). The largest share of employment is in trade (42 per cent of SSEemployment), followed by services (28 per cent), textiles (9 per cent), catering (7 per cent), finance (2 percent), transport (1 per cent), and fabricated metals and wood (around 3 per cent) each. The urban-ruralemployment split of the SSE is 69 per cent and 31 per cent respectively, although the ranking of the sub-sectors within them is the same.

The rural urban split is 31 to 69 per cent in favour of rural and the ranking of sub-sectors is the same forboth.

6 LFS 4.1 million in the manufacturing sector should be equaled by [CMI Large-scale = 0.6m] + [SHMI Small-scale ] in 1988 but is not. Therefore, as a second-best estimate we can take SSE as a residue = [(4.1m) - (CMI's 0.6m)] = 3.7m.But this may be on the high side since CMI 0.6m is underestimated due to non-registration.

7 The density of units per 1,000 population is 55 for urban, 33 for rural areas and 40 for the whole sector. Thissuggests that the proliferation of the SSE sector is some function of population, even if it is not strictly proportional.

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Serious discrepancy in the manufacturing sector estimates

We need to note a very significant discrepancy between the employment estimates based on the SHMI andCE of 1987-88 and the Labour Force Surveys( LFS). The SHMI and CE data estimate the SSE employmentin manufacturing to be roughly around 0.7 million. The LFS estimates the total employment inmanufacturing in 1987-88 to be 4.1 million, of which the SSE’s share is 3 million and the large-scalemanufacturing sectors share is .6 million.6 In other words the lower bound for SSE manufacturingemployment is .7 million (SHMI and CE data) and the upper bound is 3 million (LFS data) for the year1987-88. This poses a serious problem and we need to have some alternative estimates, to achieveperspective on the size of employment in the sector.

The Household Integrated Economic Survey (HIES) 1987–88 and 1990-91

The HIES 1990-91 gives a fairly good and recent estimate of the entire SSE (tables A5.10 an A5.11). Thevariable in the HIES is the number of units, 4.5 million in 1990-91. Trade is still the largest sub-sector (2.1million units) followed by services (1.3 million), manufacturing (0.8 million) and catering (0.2 million). Forall the units in the sector taken together and applying a constant ratio of employment per unit (1.72) the totalemployment for 1991 comes to 7.7 million persons. On the same assumption, manufacturing employmentcomes to 1.37 million, somewhere between the SHMI/CE estimate and the LFS estimate.

A striking characteristic brought out by the HIES 1990-91 is that of the 4.5 million units, 1.1 million aremobile, 0.5 from trade and another 0.5 from services.

A third important characteristic is that rural units are greater than urban ones. Of the 4.5 million, 2.5 millionare in rural areas and 2 million in urban areas7. This is in contrast to the SHMI/CE estimates whichsuggest that the number of urban units to be higher in 1987-88, some three year prior to the date of theHIES.

Fourthly, mean income is clearly lower than that in the large-scale sector.

Our estimates of the SSE from the above discussion suggest that this sector could be employing between3.1 and 7.7 million persons. Its mean income is lower than that in the large-scale sector and to that extentit is to a refuge sector. Manufacturing is a quarter of this sector in terms of value added, while trade andservices account for around 70 per cent. Manufacturing in the SSE has a low capital-labour ratio andtherefore a much lower labour productivity compared to the large-scale sector.

ISSMI-Small 1992-93

We have a wide range of size of employment in the sector, which we need to narrow down. Estimates basedon Integrated Survey of Service an Manufacturing Industries-Small 1992-93 (ISSMI) allow for thispossibility (tables A5.12-15). In 1992-93 the SSE comprised 1.9 million units which is consistent with the1.8 units figure of the CE 1990-91 and much lower than the HIES 1990-91 figure of 4.5 million.Employment according to ISSMI is 4.4 million which lies between the lower bound given by CE of 3.1

143

million and the upper bound of 7.7 million projected with HIES 1990-91. Of the value added contributionof Rs. 226 billion, the share of manufacturing is 26 billion, which is 17 per cent of the value added in theentire manufacturing sector according to ISSMI –Small and ISSMI- Large. The mean wage in the SSE isRs 4000, which lies between that of a semiskilled and skilled worker. Capital stock data for ISSMI-Smallare comparable to SHMI 1988 estimates shown above. Trade is ranked as the largest sub-sector on assetvalues, employment and value added. This is followed by services, textiles, food, hotels and metalfabrication. This is also in keeping with the SHMI 1988 data.

Therefore ISSMI-Small is not only consistent in many respects with other major surveys, it also arrives ata plausible middling figure for employment in the SSE sector which lies between the wide range of figureswe get from different sources.

144

ANNEX 5.2: TABLES

Table A5.1: Estimated share of the small-scale sector in manufacturing 1992/93

GDP at currentfactor cost

Totalmanufacturing

Large-scale Small-scale

1990/91 (Rs. Million)

908,374 158,840 112,204 46,636

% 100.00 17.49 12.35 5.13

% 100.00 70.64 29.36

1991/92(Rs. Million)

1,077,943 186,832 130,252 56,580

% 100.00 17.33 12.08 5.25

% 100.00 69.72 30.28

1992/93 (Rs. Million)

1,200,129 207,273 142,206 65,267

% 100.00 17.27 1185.00 5.44

% 100.00 68.61 31.49

1996/97(Rs. Million)

2,245,904 378,647 256,164 122,483

% 100.00 16.86 11.40 5.45

% 100.00 67.65 32.36

Source: Calculated from the Economic Survey 1996-97.

145

Tab

le A

5.2:

Em

ploy

men

t in

the

man

ufac

turi

ng s

ecto

r

1960

% o

fM

anu-

fact

urin

g19

71-7

2%

of

Man

u-fa

ctur

ing

1977

-78

% o

fM

anu-

fact

urin

g19

82-8

3%

of

Man

u-fa

ctur

ing

1987

-88

% o

fM

anu-

fact

urin

g19

90-9

1%

of

Man

u-fa

ctur

ing

% o

f M

anu-

fact

urin

g

Lar

ge-S

cale

Man

ufac

turi

ng33

7,00

0(2

.49)

18.3

048

0,00

0(2

.63)

21.0

058

0,00

0(2

.66)

19.5

069

0,00

0(2

.74)

20.4

072

0,00

0c(2

.43)

17.4

062

3,38

02.

0917

.10

Smal

l-Sc

ale

(a)

Man

ufac

turi

ng

1,50

1,00

0(1

1.10

)81

.70

1,80

6,15

0

(9.8

9)

79.0

02,

398,

928

(10.

98)

80.5

02,

699,

044

(10.

70)

79.6

03,

423,

900

(11.

57)

82.6

03,

024,

584

10.1

482

.90

Tot

al

Man

ufac

turi

ng

1,83

8,00

0

(13.

60)

100.

002,

286,

150

(12.

51)

100.

002,

978,

928

(13.

640)

100.

003,

389,

044

(13.

44)

100.

004,

143,

900a

(14.

00)

100.

003,

647,

964

12.2

310

0.00

Tot

al la

bour

13,5

17,0

0018

,270

,000

21,8

40,0

0025

,220

,000

29,6

00,0

0029

,828

,000

100.

00

Not

e:(a

) R

esid

ual o

f to

tal a

nd la

rge-

scal

e m

anuf

actu

ring

sec

tor.

(b)

Dom

estic

em

ploy

ed la

bour

for

ce.

(c)

For

198

7-88

bas

ed o

n C

MI

and

NM

C S

urve

y of

larg

e-sc

ale

man

ufac

turi

ng.

Sour

ce:

ILO

/AR

TE

P, e

mpl

oym

ent a

nd s

truc

tura

l cha

nge

in P

akis

tan,

Ban

gkok

, 19

83 a

nd la

bour

for

ce s

urve

ys,

CM

I 19

90-9

1.

146

Tab

le A

5.2b

:E

mpl

oym

ent

in m

anuf

actu

ring

, ur

ban/

rura

l

1971

-72

1977

-78

1987

-88

1990

-91

Tot

al m

anuf

actu

ring

2,28

6,15

0(1

00.0

0)2,

978,

928

(100

.00)

4,14

3,90

0(1

00.0

0)3,

647,

964

(100

.00)

Lar

ge-s

cale

480,

000

(21.

00)

580,

000

(19.

47)

720,

000

(17.

37)

623,

380

(17.

10)

Smal

l-sc

ale

rura

l1,

295,

814

(56.

68)

1,50

1,45

2(5

0.40

)1,

950,

275

(47.

06)

1709

,144

(46.

90)

Smal

l-sc

ale

urba

n51

,366

(22.

32)

897,

476

(30.

13)

1,47

3,62

5(3

5.56

)1,

315,

440

(36.

10)

Not

e:(I

)B

reak

dow

n of

Sm

all-

scal

e ba

sed

on la

bour

for

ce s

urve

y.(I

I)A

ll L

arge

-sca

le a

ssum

ed in

urb

an a

reas

.%

in b

rack

ets.

Sour

ce:

ILO

/AR

TE

P, e

mpl

oym

ent a

nd s

truc

tura

l cha

nge

in P

akis

tan,

Ban

gkok

, 19

83 a

nd la

bour

for

ce s

urve

ys,

CM

I 19

90-9

1.

147

Table A5.3: Growth rates in manufacturing (constant factor cost 1980/81, Rs million)

Value added

Totalmanufacturing

Large-scale Small-scaleSmall-scale(%) share

1980-81 37,446 27,451 9,995 26.70

1992-93 89,889 63,577 26,312 29.10

Growth rate (%)1980/81-1992/93

7.30 7.10 8.10 -

1996-97 104,381 68,051 33,330 31.90

Growth rate (%)1980/81-1996-97

8.50 7.60 10.00 -

Source: Calculated from the Economic Survey 1996-97.

Table A5.4: Real growth in the manufacturing sector (% per annum)

PeriodSmall-scale

manufacturingLarge-scale

manufacturingTotal manufacturing

sector

1950-60 2.30 15.40 7.70

1960-70 2.90 13.90 9.90

1970-80 7.90 3.90 4.80

1980-89 8.40 8.30 8.40

1950-86 5.00 10.00 7.50

1986-87 8.40 7.20 7.50

1987-88 8.40 10.60 10.00

1988-89 8.40 2.40 4.00

1989-90 8.40 4.70 5.70

1990-91 8.40 5.40 6.30

1991-92 8.40 7.90 8.10

1992-93 8.40 4.10 5.40

1993-94 8.40 4.30 5.50

1994-95 8.40 1.50 3.60

1995-96 8.40 2.60 4.40

1996-97 8.40 -1.40 1.80

Source: Economic Surveys.

148

Table A5.5: Growth of SSE based on inter survey 1976/77 - 1983/84 growth rates

(Rs. million)

I. 1983/84

SHMI - Urban GVA (published) 8377.4 million

Correction for 6 industries 1518.0 million

SHMI Urban GVA revised 6895.4 million

Employment SHMI Urban 555,497

Urban SHMI GVA/L Rs. 12,413

II. 1983/84 Estimates

Employed labour force in manufacturing Pakistan Urban Rural

by Pop. Census 1981 1.996 1.041 0.955

LFS % PA 1980/81-1983/84 1.23%

Manuf. est. labour force 1983/84 2.071 1.08 0.991

Manuf. LSE (cm1 1983/84) -0.665 -0.484 -0.181

Manuf. SSE 1.406 million 0.596 0.81

GVA/L in SSE Rs. 12,413 Rs. 6,669

SSE GVA 1983/84 Rs. 12,808 million 7,410 million 5,398 million

III. 1976/77 Estimates

Employed labour force in manuf. Pakistan Urban Rural

by pop. Census 1981 1.996 million 1.041 0.955

LFS % PA 1976/77 - 1980/81 2.85%

Manuf. Est. L Force 1976/77 1.784 0.931 0.853

Manuf. LSE (CM1 1976/77) -0.616 -0.462 -0.154

Manuf. SSE 1168 0.469 0.699

GVA/L in SSE Rs. 6,629 Rs. 3,561

SSE GVA 1976/77 Rs. 5,594 million 3104 2,490

IV. WPI 1976/77 (1975/76 = 100) = 112.4

WPI 1983/84 (1975/76 = 100) = 190.8

V. GVA SSE ave. PA growth rate 1976/77 -1983/84 = 4.4%

Source: Input Output Table 1993.

149

Table A5.6: Inter survey growth in value added: Pakistan, 1976/77-1988Value added (Rs.million)

Current (Rs. 1975/76) Constant % Growth Rate

1976-77 5,594 4,977

4.3a

1983-84 12,808 6,713

(URBAN)

1983-84 5,250 2,752

4.7b

1988 7,736 326

Notes: a From the Input Output Table 1993. SHMI 1976/77 made comparable to 1983/84.b From the SHMI 1988. SHMI 1983/84 made comparable to 1988.

Table A5.7: Inter survey growth in value added/labourer Value added/labourer (Rs.)

Years

URBAN RURAL

(Rs.)Current

(Rs.1975/76)Constant

GrowthRate

(Rs.)Current

(Rs.1975/76)Constant

GrowthRate

1976-77 6,629 5,898 3,561 3,168

1.40 1.40

1983-84 12,413 6,506 6,669 3,495

4.80 6.60

1988 18,359 7,893 10,566 4,543

Source: Calculated from Input Output Table 1993, SHMI 1988.

Table A5.8: SSE manufacturing: Inter survey growth rates in value added 1983-84 - 1992/93

YearCurrent

GVA(Rs. Million)

WPIConstant

GVA(Rs. Million)

RealGrowthRate in GVA

1983/84 12,808.00 100.00 12,808.00

2.6% PA1992/93 25,768.00 159.41 16,206.00

Source: Calculated from SMM1 1983/84 and ISSMI 1992/93.

150

Tab

le A

5.9:

SSE

sec

tora

l sha

res

1976

/77

UR

BA

N19

83/8

4R

UR

AL

AN

D U

RB

AN

1988

RU

RA

L A

ND

UR

BA

N

No

ofU

nits

Fix

edA

sset

s(R

s.m

)

Em

ploy

men

t(0

00)

Val

ueA

dded

(Rs.

m)

No

of U

nits

Fix

edA

sset

s(R

s.m

)

Em

ploy

men

t(0

00)

Val

ueA

dded

(Rs.

m)

No

of U

nits

Fix

edA

sset

s(R

s.m

)

Em

ploy

men

t(0

00)

Val

ue A

dded

(Rs.

m)

Tot

al v

alue

108,

642

955

380

1042

6,45

76,

736

946

9,36

925

7,55

75,

597

627

9,90

3T

otal

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

100.

010

0.0

1Fo

od, b

ever

ages

toba

cco

9.2

22.4

11.1

11.4

20.3

44.5

22.0

20.2

18.9

30.8

15

.918

.0

Whe

at m

illin

g3.

59.

32.

43.

09.

45.

57.

57.

913

.419

.78.

98.

0R

ice

mill

ing

0.2

3.1

0.

30.

4

0.9

18.9

1.7

3.2

0.5

1.4

0.

51.

6

Oil

extr

actio

n1.

2

3.5

1.

1 2.

4

0.9

1.0

0.6

0.9

0.6

1.2

0.5

1.0

2

Tex

tiles

, lea

ther

43.0

29

.6

41.6

41.4

35

.017

.335

.332

.039

.224

.4

41.6

35.6

W

eavi

ng6.

4 8.

5

5.5

7.8

2.9

5.9

4.4

7.0

6.2

12.5

8.8

11.3

Car

pets

9.1

2.5

19.2

7.3

9.3

1.2

10.7

1.8

13.5

1.5

14.2

6.8

3W

ood

& p

rodu

cts

13

.511

.510

.010

.413

.912

.512

.912

.715

.117

.215

.014

.6Fu

rnitu

re6.

72.

44.

24.

45.

92.

45.

24.

87.

04.

06.

55.

94

Che

mic

als,

rubb

er2.

82.

7 2.

9 3.

6 1.

01.

31.

31.

91.

72.

5 2.

2 3.

6 Pl

astic

pro

duct

s1.

6 0.

9 1.

6 2.

00.

40.

40.

50.

80.

91.

01.

3 1.

6 5

Min

eral

s (n

on-i

ron)

3.5

4.4

10.0

7.4

4.1

4.0

6.7

8.7

2.7

2.8

3.2

3.7

Potte

ry2.

00.

71.

61.

02.

40.

41.

91.

11.

40.

51.

30.

7B

rick

s0.

52.

07.

45.

10.

71.

32.

44.

70.

30.

50.

61.

2Fa

bric

ated

met

al16

.922

.616

.117

.915

9.0

14.2

14.5

15.4

12.4

14.7

13.7

14.9

Met

al p

rodu

cts

8.3

8.4

7.9

8.2

12.1

6.6

10.1

8.8

7.7

7.1

8.0

8.2

Non

ele

ctri

c m

achi

nes

4.9

9.3

4.5

5.0

3.1

5.9

3.2

4.2

2.2

4.4

2.6

3.3

Agr

icul

tura

l0.

71.

10.

50.

91.

22.

41.

21.

80.

81.

50.

81.

4M

achi

ning

3.0

5.2

2.6

2.7

1.1

1.8

1.1

1.3

0.6

1.0

0.6

0.8

Tex

tiles

--

--

0.1

0.3

0.2

0.2

0.2

0.4

0.3

0.3

7B

asic

met

als

0.8

2.0

0.8

0.9

0.2

0.5

0.3

0.4

0.3

0.7

0.5

0.7

Iron

foun

drie

s0.

61.

30.

80.

80.

10.

30.

20.

30.

10.

30.

30.

38

Oth

er10

.24.

87.

47.

19.

45.

67.

18.

79.

76.

97.

88.

9Je

wel

ry8.

83.

65.

85.

77.

74.

35.

36.

77.

15.

85.

36.

7Sp

orts

goo

ds

0.4

0.8

0.8

0.9

0.5

0.4

0.5

0.6

1.3

0.3

1.3

0.9

Sour

ce:

Cal

cula

ted

from

SH

MI:

197

6/77

, 198

3/84

, 198

8.

151

Tab

le A

5.10

:H

IES

87/8

7 i.

e. S

SE in

man

ufac

turi

ng a

nd o

ther

sec

tors

-es

tim

ate

of e

stab

lishm

ents

wit

h le

ss t

han

10 w

orke

rs (

‘000

)

Tot

alU

rban

Rur

alT

otal

Urb

anR

ural

No.

Uni

tsE

mpl

oy-

men

tN

o.U

nits

E

mpl

oy-

men

tN

o. U

nits

Em

ploy

-m

ent

No.

Uni

tsE

mpl

oy-

men

tN

o. U

nits

Em

ploy

-m

ent

No.

Uni

tsE

mpl

oy-

men

t

Tot

al1,

845.

03,

068.

71,

132.

82,

119.

671

2.2

949.

110

0.0

100.

061

.469

.138

.630

.9

Man

ufac

turi

ng26

8.0

650.

616

0.7

434.

210

7.2

216.

414

.521

.28.

714

.15.

87.

1

Foo

d be

vera

ge52

.610

7.9

16.2

45.9

36.5

62.0

2.9

3.5

0.9

1.5

2.0

2.0

Tex

tiles

, le

athe

r10

2.0

262.

859

.316

6.9

42.3

95.9

5.5

8.6

3.2

5.4

2.3

3.1

Woo

d pr

oduc

ts41

.999

.729

.074

.413

.725

.32.

33.

21.

62.

40.

70.

8

Che

mic

als

5.1

16.7

4.7

15.8

0.4

1.0

0.3

0.5

0.3

0.5

0.0

0.0

Min

eral

s7.

822

.94.

312

.33.

510

.70.

40.

70.

20.

40.

20.

3

Met

als

1.3

4.1

1.2

3.9

0.1

0.2

0.1

0.1

0.1

0.1

0.0

0.0

Fab

ric

met

als

31.6

86.1

26.7

76.2

4.9

9.8

1.7

2.8

1.4

2.5

0.3

0.3

Oth

ers

indu

stri

es26

.050

.319

.338

.96.

711

.51.

41.

61.

01.

30.

40.

4

Util

ities

0.9

1.3

0.9

1.3

--

0.0

0.0

0.0

0.0

--

Con

stru

ctio

n0.

51.

70.

41.

60.

10.

10.

00.

00.

00.

00.

00.

0

Tra

de89

9.0

1,28

5.6

555.

788

2.9

343.

140

2.9

48.7

41.9

30.1

28.8

18.6

13.1

Cat

erin

g99

.420

6.4

68.0

152.

031

.454

.45.

46.

73.

75.

01.

71.

8

Tra

nspo

rt,

stor

age

com

mun

icat

ion

10.4

20.2

9.6

18.7

0.8

1.4

0.6

0.7

0.5

0.6

0.0

0.0

Fin

ance

24.5

57.8

23.5

55.8

1.0

2.0

1.3

1.9

1.3

1.8

0.1

0.1

Serv

ices

543.

084

4.8

314.

057

3.0

228.

527

1.9

29.4

27.5

17.0

18.7

12.4

8.9

Sour

ce:

HIE

S 19

87/8

8.

152

Table A5.11: HIES, Non agricultural micro enterprises, 1990/91 (number and %)

Total Manuf. Trade Hotels Servicesand others Total Manuf. Trade Hotels Services

No. All Units 4,475 818 2,134 207 1,316 100.0 18.2 47.6 4.6 29.4

Fixed 3,367 777 1,610 166 814 75.2 17.3 35.9 3.7 18.1

Mobile 1,108 41 524 40 502 24.7 0.9 11.7 0.9 11.2

Urban 1,962 321 925 123 593 43.8 7.1 20.6 2.7 13.2

Rural 2,513 496 1,209 84 723 56.1 11.0 27.0 1.8 16.1

Average monthly income (Rs)

All Units 2,025 1,706 2,254 2,213 1,821

Urban 2,481 2,243 2,743 2,416 2,214

Rural 1,668 1,358 1,881 1,916 1,498

Density (Units/1000 Pop)

All Units 39.6 7.2 18.9 1.8 11.6

Urban 54.5 8.9 25.7 3.4 16.5

Rural 32.6 6.5 15.7 1.1 9.4

% Income share from SSE:

All Units 61 54.4 63.8 79.7 57.6

Urban 63 55.9 65.9 78.7 59.6

Rural 58.8 52.8 61.5 81.6 55.4

% Share of SSE's with all loans

All Loans 26.0 34.7 22.4 18.9 27.4

Urban 22.6 26.2 19.6 23.5 25.1

Rural 28.7 40.2 24.6 12.1 29.4

% Share of SSE's with commercial loans only

All Units 1.5 0.9 2.4 0.0 0.7

Urban 1.6 0.6 2.1 0.0 1.6

Rural 1.5 1.1 2.6 0.0 0.0

Average outstanding loan (Rs) Commercial only

All Units 74,046 200,000 64,510 54,323

Urban 51,711 18,937 18,987 12,007 16,474

Rural 90,967 200,000 73,051

Total Manuf. Trade Hotels Servicesand others Total Manuf. Trade Hotels Services

153

Average outstanding loan (Rs) Non-commercial only

All Units 12,953 12,340 14,233 9,725 12,269

Urban 17,611 18,937 18,987 12,007 16,474

Rural 10,129 9,432 11,425 3,572 9,467

Average income of (Rs/pm) SSE without any loans

All Units 2,086 1,738 2,326 2,238 1,837

Urban 2,567 2,327 2,854 2,443 2,243

Rural 1,677 1,268 1,895 1,979 1,484

Average income of (Rs/pm) SSE with only commercial loans

All Units 2,627 3,067 2,435 3,240

Urban 2,537 1,406 2,279 3,240

Rural 2,724 3,725 2,559

Average income of (Rs/pm) SSE with only non-commercial loans

All Units 1,796 1,607 1,950 2,103 1,724

Urban 2,148 2,022 2,288 2,330 2,026

Rural 1,588 1,432 1,752 1,461 1,531

Average employment of SSE without any loan

All Units 1.5 1.9 1.4 2.0 1.4

Urban 1.8 2.4 1.6 2.5 1.5

Rural 1.3 1.6 1.3 1.3 1.4

Average employment of SSE with only commercial loan

All Units 2.1 5.4 1.8 0.0 1.3

Urban 1.9 6.0 1.9 0.0 1.3

Rural 2.2 5.2 1.7 0.0 0.0

Average employment of SSE with only non commercial loan

All Units 1.5 2.1 1.3 1.5 1.3

Urban 1.5 2.0 1.4 1.6 1.3

Rural 1.5 2.1 1.2 1.2 1.3

Source: HIES (1990/91).

152

153

Tab

le A

5.12

:Sm

all a

nd m

ediu

m s

ecto

r ch

arac

teri

stic

s (I

SSM

I) 1

992-

93

No

Uni

ts(0

00)

(K)

Ass

etV

alue

(M.R

s)

(L)

Em

ploy

men

t

Mea

nW

age

(Rs)

(Y)

Pro

fits

or

Val

ueA

dded

(Mrs

)

K/L

(Rs)

Y/L

(Rs)

Y/K

Per

cent

age

No

Uni

tsA

sset

Val

ueE

mpl

oy-

men

tV

alue

Add

ed

Man

ufac

turi

ng36

929

,159

1,14

3,60

26,

171

25,8

2925

,510

22,5

970.

8919

.75

24.7

026

.18

11.4

3

Food

546,

041

149,

634

4,17

03,

195

40,5

4321

,442

0.53

2.89

5.12

3.42

1.41

Tex

tiles

158

8,63

752

0,53

06,

782

9,77

716

,592

18,8

011.

138.

467.

3211

.92

4.33

Woo

d49

4,90

613

1,50

44,

905

2,89

737

,306

28,4

770.

592.

624.

163.

011.

28

Pape

r9

973

31,4

298,

304

809

31,3

8710

,124

0.83

0.48

0.82

0.71

0.36

Che

mic

als

61,

030

22,5

898,

455

692

46,8

1820

,726

0.67

0.32

0.87

0.52

0.31

Min

eral

s13

1,04

762

,541

10,5

212,

586

16,8

8727

,001

2.47

0.70

0.89

1.43

1.14

Met

als

114

24,

039

8,66

696

35,5

0024

,000

0.68

0.05

0.12

0.09

0.04

Met

al P

rodu

cts

454,

989

147,

278

6,68

83,

605

33,9

3824

,523

0.72

2.41

4.23

3.37

1.60

Oth

er35

1,39

174

,055

1,70

12,

168

18,7

9729

,297

1.56

1.87

1.18

1.70

0.96

Tra

de77

847

,108

1,52

3,85

52,

694

171,

246

30,9

3111

2,43

93.

6441

.65

39.9

134

.89

75.7

7

Hot

els

134

2,49

647

7,14

62,

808

6,38

45,

232

13,3

832.

567.

332.

1110

.92

2.82

Tra

nspo

rt2

195

8,42

43,

561

168

23,2

1420

,000

0.86

0.10

0.17

0.19

0.07

Fin

ance

393,

561

99,8

479,

925

3,25

735

,664

32,6

190.

912.

093.

022.

291.

44

Serv

ices

546

35,5

181,

115,

040

3,91

219

,126

31,8

5417

,153

0.54

29.2

330

.09

25.5

28.

46

All

Sect

ors

1,86

811

8,03

74,

368

(Mill

ion)

4,09

522

6,01

027

,023

51,7

421.

9110

0.00

100.

0010

0.00

100.

00

Sour

ce:

ISSM

1, 1

992/

93.

154

Tab

le A

5.13

:E

stim

ates

of

the

med

ium

and

sm

all-

scal

e no

n-ag

ricu

ltur

al s

ecto

r 1

992-

93, (

ISSM

1) (

000)

No.

of

Uni

tsT

ype

of F

irm

No.

of

Em

ploy

ees

Tot

al

%U

rban

%

Rur

al

%

Indi

vi-

dual

prop

rie-

tors

hip

%P

artn

er-

ship

% 1

2

3-4

5-9

> 1

0

All

sect

ors

1,82

910

01,

279

100

550

100

1,71

994

112

675

064

735

410

117

Man

ufac

turi

ng36

920

188

1518

133

339

9230

810

111

595

518

Food

543

191

346

Tex

tiles

158

866

592

17

Woo

d49

329

220

4

Pape

r9

09

10

0

Che

mic

als

60

50

10

Min

eral

s13

15

09

2

Met

als

10

10

00

Met

al p

rodu

cts

452

343

112

Oth

er35

220

215

3

Tra

de77

842

618

4816

93

687

8842

12

Hot

els

134

793

741

712

795

75

Tra

nspo

rt2

02

00

02

100

00

Fina

nce

00

00

00

00

00

Serv

ices

546

2937

729

169

3148

689

234

Sour

ce:

ISSM

1 (1

992-

93).

155

Table A5.14: SSE Sector characteristics (ISSMI, 1992/93) (000)

Characteristics All sectors Manufacturing

Vintage 551

90's 205

Late 80's 113

Early 80's 93

Late 70's 58

Early 70's 21

60's 45

50's 12

Pre 1947 4

Period Worked 1,279

Full Year 1,264

Type of Work 1,868

Subcontracting Only 0

Asset Size (Rs.) 369

> 1000 85

1 - < 10,000 106

10,000 - < 50,000 73

50,000 - < 100,000 44

100,000 - <500,000 51

>500,000 11

Obtaining loans 23

Outstanding Value Rs.2,286M

Sources: Private 32

Landlord/Shopkeeper 22

Commercial Bank/Institution 18

Provincial Government 6

Source: ISSM1 (1992-93).

156

Tab

le A

5.15

:Sm

all a

nd m

ediu

m s

ecto

r ch

arac

teri

stic

s by

siz

e, (

ISSM

1), 1

992/

93

Em

ploy

men

t si

ze(p

erso

ns e

ngag

ed)

No

of.

Uni

ts(0

00)

Ass

et V

alue

(M

. Rs.

)E

mpl

oym

ent

Mea

nW

age

(Rs.

)

Pro

fit

orV

alue

Add

ed(M

.Rs.

)

Pro

fit/

Uni

t(M

.Rs.

)

Pro

fit/

Cap

ital

Pro

fit/

Lab

our

(M.R

s.)

K/l

(rs.

)

All

Man

ufac

turi

ng36

929

,159

1,14

3,60

26,

170

25,7

680.

060

0.88

00.

023

25,5

10

110

11,

996

112,

167

723

2,48

10.

020

1.24

00.

022

17,8

21

211

55,

183

238,

328

1,81

93,

789

0.03

00.

730

0.01

621

,777

3-4

956,

252

325,

640

5,02

56,

453

0.07

01.

030

0.02

019

,178

5-9

5111

,299

331,

414

10,0

428,

889

0.20

00.

790

0.02

734

,135

3645

67

3,73

488

,201

13,4

092,

960

0.40

00.

790

0.03

442

,432

>25

169

247

,850

8,33

31,

194

1.80

01.

730

0.02

514

,416

<10

362

24,7

331,

007,

551

5,43

321

,614

0.06

00.

874

0.02

124

,536

Sour

ce:

ISSM

1 (1

992/

93).

157

Tab

le A

5.16

:C

redi

t fo

r th

e SS

E s

ecto

r

Tot

alIn

vest

men

t(R

s. M

)

Fro

mSa

ving

s

Loa

ns f

rom

fin

anci

al in

stit

utio

ns

Indi

vidu

als

Tot

alP

akis

tani

Ban

ksF

orei

gnB

anks

Coo

p B

anks

Non

-Ban

ksIn

stit

utio

nsJo

int

Inve

stm

ent

All

indu

stri

es1,

697.

31,

536.

414

4.7

16.1

12.5

0.1

0.6

2.6

0.3

Lan

d19

1.7

182.

58.

21.

10.

70.

4

Bui

ldin

gs26

9.8

259.

59.

91.

51.

20.

3

Plan

t56

6.5

539.

424

.12.

91.

90.

40.

5

Tra

nspo

rt9.

08.

60.

40.

0

Oth

er f

ixed

ass

ets

30.6

28.3

1.3

1.0

1.0

Wea

ving

62

9.8

519.

410

0.8

9.7

7.7

0.1

0.2

1.5

0.3

Food

, Bev

erag

e,to

bacc

o36

4.8

335.

318

.710

.79.

80.

30.

50.

1

Tex

tiles

, lea

ther

569.

248

6.3

80.5

2.4

0.9

0.1

1.3

0.1

Woo

d an

d pr

oduc

ts24

7.1

234.

111

.21.

50.

80.

60.

1

Che

mic

als,

rub

ber

55.5

52.7

2.6

0.1

0.1

Min

eral

s (n

on ir

on)

88.5

84.6

3.9

0.0

Bas

ic m

etal

s11

.010

.60.

40.

0

Fabr

icat

ed m

etal

s25

2.9

235.

416

.70.

80.

50.

10.

10.

1

Oth

ers

108.

397

.510

.40.

50.

30.

2

Tot

al I

nves

tmen

tSh

ares

All

indu

stri

es10

0.0

90.5

8.5

1.

0

158

Table A5.17: Vintage of industries

Totalunits

No. of Units (000)

Totalunits

% of Units

Pre-1970

1970-1979

1980-1988

Pre-1970

1970-1979

1980-1988

Total 1,844.9 263.1 256.4 1,325.4 100 14.3 13.9 71.8

Manufacturing 267.9 27.1 37.9 202.9 100 10.1 14.1 75.7

Food, beverages 52.6 6.4 10.5 35.7 100 12.2 20.0 67.9

Textile, leather 101.6 9.7 14.0 77.9 100 9.5 13.8 76.7

Wood 41.9 3.4 5.3 33.2 100 8.1 12.6 79.2

Chemicals 5.1 0.2 0.4 4.5 100 3.9 7.8 88.2

Minerals 7.8 2.2 1.4 4.2 100 28.2 17.9 53.8

Metals 1.3 0.1 0.1 1.1 100 7.7 7.7 84.6

Fabric metals 31.6 2.2 2.9 26.5 100 7.0 9.2 83.9

Other industries 26.0 2.9 3.3 19.8 100 11.2 12.7 76.2

Utilities 0.9 0.1 0.2 0.6 100 11.1 22.2 66.7

Constructions 0.5 0.0 0.1 0.4 100 0.0 0.2 0.8

Trade 898.7 80.5 134.2 684.0 100 9.0 14.9 76.1

Catering 99.4 7.7 12.5 79.2 100 7.7 12.5 79.2

Transport, storage 10.4 0.8 1.5 8.1 100 7.7 14.4 77.9

Finance 24.5 2.1 4.4 18.0 100 8.6 18.0 73.5

Services 542.5 144.7 65.5 332.3 100 26.7 12.1 61.3

Source: HIES (1987/88).

159

Tab

le A

5.18

:SH

MI

Pak

ista

n (r

ural

and

urb

an)

1976

/77

1983

/198

419

87/1

988

No.

Uni

tsF

ixed

Ass

ets

(Rs.

M.)

Em

ploy

men

t(0

00)

Val

ueA

dded

(Rs.

M.)

No.

Uni

tsF

ixed

Ass

ets

(Rs.

M.)

Em

ploy

men

t(0

00)

Val

ueA

dded

(Rs.

M.)

No.

Uni

tsF

ixed

Ass

ets

(Rs.

M.)

Em

ploy

men

t(0

00)

Val

ueA

dded

(Rs.

m)

Tot

al v

alue

108.

695

5.2

380.

02,

599.

642

6,45

7.0

6,73

6.2

946.

09,

368.

925

7.6

5,59

7.0

627.

09,

902.

81

Food

, bev

erag

e, to

bacc

o10

,042

.0

213.

642

.0

296.

5 86

,774

.03,

000.

520

8.0

1,89

4.2

48.8

1,72

8.2

100.

0 1,

784.

6W

heat

mill

ing

3,79

3.0

88.8

9.0

76

.740

,149

.037

2.9

71.0

73

9.1

34,3

89.0

1,10

0.6

56.0

78

9.2

Ric

e m

illin

g20

1.0

29.6

1.0

9.5

39

.81,

271.

416

7.0

308.

41,

169.

079

.0

3.5

155.

4 O

il ex

pelli

ng1,

317.

0 33

.9

4.0

62

.43,

751.

067

.16.

682

.31,

444.

068

.13.

596

.3

2T

extil

es, l

eath

er46

,709

.028

2.4

1,58

6.0

10,7

66.0

149,

088.

01,

165.

533

4.0

2,99

3.8

100,

867.

01,

363.

726

1.0

3,52

3.4

Wea

ving

stan

6,96

5.0

81.6

21

.0

202.

812

,466

.039

8.3

42.0

659.

616

,082

.070

0.7

55.0

1,

118.

3C

arpe

ts9,

833.

023

.673

.0

190.

039

,861

.081

.810

1.0

171.

634

,705

.085

.989

.0

676.

93

Woo

d an

d pr

oduc

ts

14,6

43.0

110.

238

.0

269.

159

,186

.084

1.8

122.

0 1,

187.

838

,897

.096

2.9

94.0

1,

445.

6Fu

rnitu

re7,

284.

022

.616

2.0

113.

625

.016

0.8

492.

044

6.2

17,9

57.0

224.

741

5.0

583.

34

Che

mic

als,

rubb

er3,

070.

026

.111

.094

.04,

450.

088

.012

.017

9.5

4,28

2.0

139.

514

.0

355.

5Pl

astic

pro

duct

s1,

688.

08.

76.

0 51

.21,

844.

026

.75.

074

.52,

228.

057

.88.

0 16

0.1

5M

iner

als

(non

-met

al)

3,83

2.0

41.8

38.0

19

1.5

17,8

07.0

272.

563

.0

813.

57,

012.

015

5.0

20.

0 36

9.5

Potte

ry2,

123.

06.

66.

0

25.4

10,4

32.0

29.9

18.0

10

7.5

3,71

3.0

27.8

8.3

64.7

Bri

cks

589.

019

.228

.0

131.

33,

022.

085

.823

.044

1.5

673.

026

.14.

0

119.

66

Fabr

icat

ed m

etal

18,3

95.0

216.

261

.0

465.

367

,927

.095

8.2

137.

0 1,

440.

231

,903

.082

2.8

86.0

1,

477.

9M

etal

pro

duct

s9,

060.

080

.730

.0

212.

451

,530

.044

1.7

96.0

82

3.7

19,8

48.0

397.

650

.081

5.9

Non

ele

ctri

c m

achi

nes

5,30

5.0

17.0

13,2

22.0

30.0

5,75

8.0

16.0

324.

724

8.0

391.

440

0.6

131.

288

.5A

gric

ultu

ral

771.

010

.82.

0

24.4

5,19

6.0

161.

911

.016

5.1

2,05

7.0

81.2

5.0

13

4.2

Mac

hini

ng3,

312.

049

.410

.069

.54,

913.

012

1.6

10.0

11

7.5

1,52

8.0

54.1

4.0

75

.1T

extil

es-

--

-57

5.0

18.3

2.0

21

.356

9.0

20.6

2.0

27

.67

Bas

ic m

etal

s85

1.0

19.3

3.0

23

.192

8.0

35.2

3.0

41

.381

3.0

37.6

3.0

69

.0Ir

on fo

und-

arie

s62

8.0

12.2

3.0

19

.750

0.0

17.0

2.0

23

.538

4.0

18.4

2.0

32

.88

Oth

er11

,100

.045

.628

.018

3.3

40,2

97.0

374.

467

.0

818.

725

,015

.038

7.4

49.0

87

7.4

Jew

elry

9,61

1.0

34.1

22.0

148.

432

,830

.028

7.5

50.0

62

7.0

18,1

59.0

324.

933

.0

662.

8Sp

orts

goo

ds s

hare

480.

07.

33.

0

24.0

229.

430

.25.

0

53.1

3,35

9.0

17.7

8.0

85

.7

Not

e:T

he a

bsol

ute

valu

es o

f th

e 3

surv

eys

are

not c

ompa

rabl

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