Economic Change in Ghana, 1987-2006 Chris Udry Yale University.
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Transcript of Economic Change in Ghana, 1987-2006 Chris Udry Yale University.
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?
.1.2
.3.4
.5N
um
ber
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: