Economic Change in Ghana, 1987-2006

Chris UdryYale University

Goal: • document trends in entrepreneurship and

employment in preparation for Ghana panel survey and associated interventions

• Ghana LSMS 1987 through GLSS 2006; 5 rounds of comparable cross-sections

• 4,000 – 7,000 households

Trends in Ghana

• Significant growth over 2 decades• Marked decline in poverty

– Dramatic increases in education– Urbanization– Health improvements, decline in birth rates

• What changes do we see in economic activity at the micro level?– New enterprises?– Enterprise growth?– Increased specialization?

Gradual Change in Primary Occupation

Gradual fall in Self-employment

Look at Investment patterns:Household Asset Portfolios, 1992

0.2

.4.6

0 2000 4000 6000 8000 10000Household Wealth

Farm Assets DurablesBusiness Assets Gross Financial Savings

Declining share of business assets

0.1

.2.3

.4S

hare

of B

usi

nes

s A

sse

ts

0 2000 4000 6000 8000 10000totalassets

1987-88 19922006

For business owners, as well

0.2

.4.6

.8S

hare

of B

usi

nes

s A

sse

ts

0 2000 4000 6000 8000 10000Household Wealth

1987-88 19922006

Enterprise size over timeMeans Medians

year # of workers # of hh workers # of workers # of hh workers

1987 1.67 1.37 1 11988 1.77 1.33 1 11992 1.64 1.27 1 11998 1.65 1.15 1 12006 1.74 1.34 1 1

Enterprises are not growing

By household, total enterprise employmentMeans Medians

year # of workers # of hh workers # of workers # of hh workers

1987 2.17 1.78 2 11988 2.32 1.75 2 11992 2.03 1.57 1 11998 2.04 1.42 1 12006 2.18 1.68 1 1

• Nor are they growing in terms of capital:Median k Mean Median

wealth

1987-88 143 787 722

2006 128 670 1003

Evidence on Returns to Capital

• Farm profits in new technology• Prices• Enterprise profits

Prices of durable goods

• Prices of goods with varying life expectancies contain information on the discount rate

• Can estimate this with data on prices and t (assuming measurement error in t) – used parts example

• Using this relationship, we estimate r=60%

NFEs earn high returns, particularly at low levels of K.- warning: sensitive to assumptions on w

010

020

030

040

0%

ret

urn

on

K

0 200 400 600 800value of bus. assets/10000

GLSS 5 Return on Assets by Enterprise Capital

Decile of Invested Capital Median Profit/K ^ 100

1 282

2 138

3 76

4 62

5 29

6 31

7 28

8 25

9 15

10 20

n= 1707

• Are business starts dependent on wealth?

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.3.4

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of e

mp

loye

es

hire

d in

to n

ew

bu

sin

esse

s

0 100 200 300 400 500Quantile of Wealth

1987-88 2006

Determinants of Business Starts(probit dependent variable: 1 if new enterprise opened in past year)

Marginal Effect (s.e.)

female head 0.0828(0.0151)

hhsize 0.0697(0.0129)

hhnoschool -0.00746(0.0138)

hhprimary -0.00516(0.00959)

hhjss 0.00959(0.00207)

hhsec -0.00535(0.0101)

real household wealthlevel -0.00101

(0.00224)squared 2.40e-05

(8.17e-05)cubed 8.42e-08

(5.90e-07)bank distance -0.0178

-0.0355wealth-bank distance interactionsrealbank 3.36e-05

(0.000120)real2bank 4.08e-06

(3.92e-06)real3bank -2.42e-07

(2.10e-07)

community characteristicsurban 0.0149

(0.0266)dwater 0.00360

(0.00728)delectric 0.00624

(0.0118)roaddist -0.000669

(0.00127)femwater 0.00294

(0.00748)femelec 0.00372

(0.00886)fembank 0.000236

(0.000468)round5 -0.0197

(0.0364)round3 -0.0149

(0.0284)Observations 6349 .observed p 0.13predicted p 0.11

Are commercial enterprises growing less, or not being started, due to capital constraints and

risk?

• Experimental intervention associated with EGC surveys discussed earlier

• Driven by theory: role of risk and imperfect access to K on investment choice. Goal is to quantify effects of risk/risk aversion and capital market imperfections on investment choice

• Not a policy evaluation; insurance is to be free• Working with MIA to design an insurance

product to address most salient dimension of risk of commercialization. Crop price or rainfall, likely rainfall for intensive maize.

• 2 x 2 design with grant experiment• Sample of 500 farmers in high potential maize

areas

• Combine with data collection on expectations, and prospective uses of additional funds

• Simultaneous orthogonal evaluation of large-scale commercial training program for farmers

Annual Hours Worked

Labor Force Participation by Gender

Net effect, increase in work/capita

Determinants of Annual Hours Worked -- GLSS rounds 1,2,3, 5

variable estimate variable estimatenoschool 18.05 dist to road -0.0997

(30.83) (1.979)primary 66.95 months road passible 0.627

(35.23) (3.256)jss 105.3 bank distance -1.890

(29.81) (0.578)sec 88.71 post distance 1.003

(39.49) (0.668)male = 1 367.7 daily market in community -24.57

(17.26) (23.89)age 48.05 any market in community 11.01

(2.027) (18.65)age squared -0.527 restaurant in community 67.08

(0.0232) (20.21)urban 346.2 y1987 -370.3

(19.26) (21.73)electricty 6.669 y1988 -541.2

(27.88) (22.30)pipe or borehole water -72.91 y1992 61.94

(24.15) (19.76)Male*electricity -27.32 Constant 550.9

(35.78) (55.59)Male*water -11.72

(34.97)

Observations 25880R-squared 0.140

• No increase in specialization: