A Poverty-Focused Evaluation of

Commodity Tax Options

B. Essama-NssahWorld Bank Poverty Reduction

GroupApril 2007

2

Introduction Context

Poverty Reduction: A fundamental objective of development

(MDGs) Need to design policies and assess

effectiveness in terms of this objective. Importance of Commodity Taxation

Difficult for developing countries to collect direct taxes on individuals and firms, hence reliance on indirect taxes on goods and services. One key reason: Sizable informal sector

Developing countries derive about 40% of tax revenue from indirect taxes and about 25% from income tax (Keen and Simone 2004)

3

Purpose Demonstrate identification of socially desirable

options for commodity taxation in the context of a poverty reduction strategy.

General Approach Embed the concept of price elasticity of poverty

within the logic of social impact evaluation Social Impact Evaluation: assessment of variations in

individual and social welfare attributable to a shock or policy. This entails: Identification of individual outcomes. Aggregation of these outcomes into a social outcome on

the basis of value judgments underlying members of the additively separable class of poverty measures (e.g. FGT, Watts).

Ranking based on the distributional characteristic of each commodity.

4

Specification Focal policy problem

Reform of an indirect tax system to maintain or increase yield, reduce distortions and minimize burden on the poor.

Presentation focuses on the latter. Maintained hypothesis

Observed poverty in a given society depends on individual endowments and behavior , and the socio-political arrangements that govern social interaction.

Consequential evaluation Identification of desirable changes from status quo

based on the computation of consequences of the policy reform and use of explicit value judgments to assess such consequences.

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Focus of the presentation: Evaluation Framework

Individual Outcomes Welfare Impact Poverty Implications

Aggregation Additively Separable Poverty Measures

Price Elasticity of Real Income

Price Elasticity of Poverty

Ranking Social Outcomes Benchmark

Decision Rule

Empirical Illustration A Poverty Profile for South Africa Distributional Characteristic of Household Spending

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Evaluation Framework Individual Outcomes

Welfare Impact Need to link policy instruments to determinants

of individual living standard. Commodity taxes affect the prices at which such

commodities are sold. Represent individual welfare by indirect utility:

maximum attainable level of utility attainable given an exogenous budget, x, and prevailing prices, p.

This envelope function summarizes optimal behavior by consumer.

]);([max),( xqpqupxvq

7

Welfare Impact , continued

Marginal change in the price of commodity k induces adjustment in optimal behavior.

Invoke envelope theorem in the form of Roy’s identity to compute welfare impact as (Deaton and Muellbauer 1980). d*(x,p) = – qk(x,p)dpk , where *(x,p) stands for

indirect utility normalized by the marginal utility of income.

Measure of welfare loss (in monetary terms) induced by a marginal increase in the price of commodity k.

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Poverty Implications

Measure of individual poverty (Kakwani 1990) Let (x|z) be that measure (x is same as above

and z is poverty line)

Assume: (1) indicator is zero when x greater or equal poverty line; (2) a decreasing convex function of x, given z. Hence first-order derivative with respect to x is negative.

.0

)|()|(

x

zxzx

9

Poverty Implications, continued Linking changes in individual welfare and

poverty

Observed demand function is a consequence of optimal behavior (Envelope theorem)

Duality between expenditure function and indirect utility implies x is the minimum expenditure required to attain *(x,p).

Loss in real income associated with tax increase on k is: dx=– qk(x,p)dpk

Poverty impact k

k

qzxp

zx)|(

)|(

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Aggregation Additively Separable Poverty Measures

Aggregate impact of price change

Price elasticity of real income

Price elasticity of poverty

z

dxxfzx0

)()|(

z

kk

dxxfzxqp 0

)()|(

)(xw

x

qp

x

p

p

xk

kkk

k

z

kk dxxfzxxxw0

)()|()(1

)(

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Ranking Social Outcomes Benchmark

An increase (reduction) in price of commodity k (possibly induced by a tax reform) is pro-poor if it leads to an absolute increase (reduction) in poverty smaller (greater) than it would in a benchmark case.

Chosen benchmark: situation of equal relative impact i.e. a one percent change in price of k would have the same relative impact on real income x.

If everybody assigned same proportion of real income, wok, to the purchase of k.

x

x

m

m

k

k

dxxxf

dxxfxxww

0

00

)(

)()(

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Benchmark, continued Benchmark price elasticity of poverty

A one percent increase in the price of commodity k would increase poverty by k under the observed budget shares, and by 0k in the hypothetical case.

Whether the change is pro-poor depends on which term dominates.

z

kk dxxfzxx

w0

00 )()|()(

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Decision Rule Based on a comparison of the poverty impact given the

observed distribution of budget shares and the hypothetical impact

Choice between ratio or additive comparison Focus on ratio comparison

Normalize budget shares

Ratio measure of pro-poorness is a weighted average of normalized budget shares among the poor (i.e. along the distribution of real income up to the poverty line)

Price increase would hurt the poor less than the non-poor if this indicator less than one.

k

kk w

xwx

0

)()(

z

z

k

k

dxxfzxx

dxxfzxxx

0

0

)()|(

)()|()()(

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Decision Rule, continued Indicators associated with some members of

the additively separable class of poverty measures.

Headcount

Watts

FGT

)(

)()(

0

zw

zwH k

k

kk

z

kWk dxxfxH 0

)()(1

)(

dxxfz

x

z

x

dxxfxz

x

z

x

z

k

z

k

)(1

)()(1

)(1

0

1

0

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Empirical Results

A Poverty Profile for South Africa

Data

2000 Income and Expenditure Survey (IES)

[Statistics South Africa]

Sample size: 26, 214 households (Nationally representative)

Poverty line: About US $1.00 per day, or Rand 2,533 per person per year.

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Poverty Profile, continued

Poverty Estimates Incidence: about 37 percent. 5 provinces out of 9 have

rates higher than national average.

A Poverty Profile for South Africa (2000) Headcount Poverty Gap Squared Poverty Gap Watts

Western Cape 11.00 3.22 1.44 4.12 Eastern Cape 57.02 24.95 14.03 39.10 Northern Cape 35.49 14.00 7.34 21.12 Free State 44.52 19.00 10.54 29.75 Kwazulu Natal 46.85 19.76 10.86 30.29 Northwest 38.60 16.51 9.31 24.96 Gauteng 17.20 5.86 2.84 8.51 Mpumalanga 35.98 12.84 6.30 18.85 Northern Province- Limpopo 55.92 23.17 12.53 35.75

South Africa 37.29 15.22 8.23 23.24 Source: Author’s cal calculations (results in percentage)

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Poverty Profile, continued

TIP Representation TIP stands for “three i’s of poverty”, namely:

incidence, intensity and inequality among the poor. Construction: (1) rank individuals from poorest to richest;

(2) form the cumulative sum of poverty gaps divided by population size; (3) plot cumulative sum of poverty gaps as a function cumulative population share (Jenkins and Lambert 1997).

Interpretation Length of non-horizontal section reveals poverty

incidence. Intensity is represented by height of the curve Concavity of non-horizontal section translates degree of

inequality among the poor. Usefulness: An alternative way to test for unanimous

poverty comparisons across time, across regions and across countries based on a wide class of poverty meaures.

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A Normalized TI P Curve for South Af rica (2000)

0

2

4

6

8

10

12

14

16

0 10 20 30 40 50 60 70 80 90 100

Cum

ulat

ive

Pove

rty

Gap

s

Cumulative Percentage of Population

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Distributional Characteristic of Household Spending Recall Decision Rule

Commodities for which the ratio measure of pro-poorness is greater than ones are those with higher budget shares for low-income households. Hence deserve special consideration, ceteris paribus, in

policy design and evaluation. Data from the 2000 Income and Expenditure Survey

reveal: Food Tobacco Clothing Personal Care Fuel

Health and education expenditures are distributed in favor of the non-poor. Given their importance for human development, they too merit special treatment in the context of a poverty reduction strategy.

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Distributional Characteristic of Expenditure Components in South Af rica (2000)

Headcount Poverty Gap Squared Poverty Gap Watts

Food 2.90 2.29 2.35 2.32 Health 0.10 0.22 0.21 0.21 Education 0.27 0.75 0.80 0.81 Non Alcoholic Beverages 0.00 1.01 0.87 0.90 Alcoholic Beverages 0.00 0.90 0.77 0.82 Tobacco NA 1.13 1.06 1.11 Clothing 3.33 1.40 1.33 1.35 Personal Care 1.81 1.61 1.59 1.60 Housing 0.53 1.07 1.10 1.08 Furniture 1.98 0.62 0.49 0.53 House Operation 0.48 0.84 0.87 0.87 Fuel 5.02 4.59 4.78 4.78 Transport 0.13 0.31 0.28 0.30 Communication 0.07 0.32 0.28 0.29 Reading 0.00 0.18 0.18 0.19 Entertainment 0.00 0.21 0.20 0.21 Miscellaneous 0.09 0.22 0.19 0.20

Source: Author’s calculations

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Conclusion Poverty reduction has become a benchmark measure of

performance for development interventions. Many developing countries rely heavily on indirect taxes on

goods and non-factor services to finance such interventions. A rigorous application of the logic of social evaluation

confirms the basic intuition that, ceteris paribus, progressive public policy should protect commodities with higher budget shares for low-income households.

Application to data for South Africa identified food, tobacco, clothing, housing, and fuel. Health effects of tobacco should be taken into consideration Even though expenditure on health and education is

distributed in favor of the non-poor their importance for human capital development means that public policies should aim at making these services affordable by the poor.

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References Bibi Sami and Duclos Jean-Yves. 2007. Poverty-Decreasing Indirect

Tax Reforms: Evidence from Tunisia. International Tax and Public Finance, Vol. 14, No.2:165-190.

Essama-Nssah, B. (2007). A Poverty-Focus Evaluation of Commodity Tax Options. Forthcoming, Journal of International Development.

Essama-Nssah, B. and Lambert P.J. (2006). Measuring the Pro-Poorness of Income Growth within an Elasticity Framework. World Bank Policy Working Paper No. 4035 (October). Washington D.C. The World Bank.

Jenkins, S. and Lambert, Peter J. 1997. Three ‘I’s of Poverty Curves, with Analysis of UK Poverty Trends. Oxford Economic Papers, 49: 317-327.

Son, Hyun H. 2006. Assessing the “Pro-Poorness” of Government Fiscal Policy in Thailand. Public Finance Review, Vol. 34, No.4: 427-449.

____________ and Kakwani, Nanak. 2006. Measuring the Impact of Price Changes on Poverty. Working Paper No. 33, International Poverty Centre, Brazil.

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End.