Ex Post Impacts of Improved Maize Varieties
on the Poor in Rural Ethiopia
Di Zeng, Jeffrey Alwang, George Norton,
Bekele Shiferaw, Moti Jaleta, Chilot Yirga
Poverty Impact Assessment: Ex Ante vs. Ex Post
Ex ante
Observed income
distribution
Predicted income
distribution
Predicted poverty
impact
Poor
Ex post
Poverty Line
Counterfactual
income distribution
Rich
Observed income
distribution
Estimated poverty
impact
Poor
Poverty Line
Rich
Maize Production in Ethiopia
• A major maize producer in Sub-Saharan Africa
• 19% daily energy contribution (Smale, Byerlee and Jayne, 2011)
• Mainly cropped in central highlands (>93% total yield, Schneider and
Anderson, 2010)
• Over 40 improved varieties released since 1970s (hybrid and OPV)
Data Description
• Four regions surveyed in 2010
• 1,359 households with 2,443 maize plots
• 564 adopters, 535 non-adopters, and 260 partial adopters
• 43.3% of maize area under improved varieties
• Woreda-level monthly precipitation datal for the past 5-10 years from
National Meteorology Agency of Ethiopia
Tigray
Amhara
Oromia
SNNPR
Kernel Density of Yields
Empirical Specification
• Normalize the utility from local varieties to zero, and denote the utility
from improved varieties as
• The decision rule of adoption
• The potential outcomes (Rubin, 1974) in logarithm form are
or
• The generalized Roy model (Heckman et al., 2006)
Treatment Effect Estimation
• Endogenous adoption decision: IV methods
• Homogeneity
•
•
Probit-2SLS (Wooldridge, 2002)
Selection model (Heckman, 1979)
• Heterogeneity
•
Marginal treatment effect via semiparametric local IV estimation (Björklund and
Moffitt,1987; Heckman et al., 2006)
• Obtain estimates of percentage yield increase (treatment effect)
Welfare Changes: the Economic Surplus Model
Welfare Changes: Small Open Economy
• Directly estimated at household level

 

•
Plot level income change: I ik  PYikobs  Cikobs  PYik*  Cik*  PYik  Cik
•
Aggregated to household: I i  k PYik  Cik 
• ΔCik — IV cost function estimation
• Counterfactual income distribution computed
Welfare Changes: Closed Economy
STEP 1: Estimate market-level economic surplus changes
• The k-shift (Alston et al., 1995)
• The counterfactual price level (elasticities synthesized from literature)
• The aggregate surplus changes
Welfare Changes: Closed Economy
STEP 2: Allocate market level surplus changes to households
• Decomposition of ΔPS
PS  PSyield  PS price where PS price  P*Q* Z (1  0.5Z)
•
•
ΔPSprice — allocated to all maize sellers by market shares
ΔPSyield — allocated to all adopters by the yield increases' shares
• ΔCS — allocated to all maize buyers by purchase shares among total supply
• Counterfactual income distribution computed
Poverty Impacts
• Foster-Greer-Thorbecke (FGT, 1984) poverty indices calculated for both
observed and counterfactual income distributions
• The differences are poverty impacts
Instrumental Variables
• Production
•
•
•
•
Rainfall intensity of the sowing month
Local population density
Distance to the nearest agricultural extension office
Temporary seed supply shortage (yes / no)
• Cost
• Rainfall intensity of the sowing month
• Distance to the nearest agricultural extension office
Yield Impact: Mean Estimates
ATT Esimates
Robustness
check
Probit2SLS
Selection
LIV
C-D
.474**
.551***
.662***
Translog
.552***
.584***
.514***
PSM-NN
.419***
PSM-Radius
.442***
PSM-Kernel
.454***
Partial Adopter FD: C-D
.386***
Partial Adopter FD: Translog
.409***
Yield Impact: MTE Estimates
C-D technology
Translog technology
Other Parameter Estimates
• Cost increase due to adoption — 32.5%
• The k-shift — 39.1% cost reduction per kilogram
• Elasticities
• ε — 0.5
• η — -1
• Aggregate impacts
•
•
•
•
ΔPS in small open economy — 135.9 thousand USD
ΔPS in closed economy — 101.3 thousand USD
ΔCS in closed economy — 50.7 thousand million USD
Only 6.37% sold maize is consumed by surveyed households
Poverty Impacts: Small Open Economy
Poverty Line
$1
$1.25
$1.45
Poverty impact
FGT Index
Poverty impact
under Homogeneity
Headcount
.0095
.0088
Depth
.0029
.0032
Severity
.0015
.0017
Headcount
.0103
.0089
Depth
.0042
.0045
Severity
.0023
.0025
Headcount
.0103
.0118
Depth
.0049
.00453
Severity
.0029
.0031
under
Heterogeneity
Poverty Impacts: Closed Economy
Poverty Line
$1
$1.25
$1.45
Poverty impact
FGT Index
Poverty impact
under Homogeneity
Headcount
.0110
.0066
Depth
.0048
.0031
Severity
.0027
.0019
Headcount
.0162
.0089
Depth
.0064
.0040
Severity
.0038
.0025
Headcount
.0147
.0081
Depth
.0073
.0047
Severity
.0046
.0030
under
Heterogeneity
Further Interpretation
• Individual level
• A typical adopter with average maize area (0.39 ha) observe 440.5 kg yield
increase
• Such an adopter observe an income increase of 45.6 - 72.4 USD (evaluated
using average per-capita maize consumption)
• Population level
• Sensitivity analyses lend credence to previous estimates
• 0.7 - 1.2 percentage headcount poverty reduction means 0.48 - 0.83 million
rural people have escaped poverty
• A major achievement
Further Interpretation: Producer Benefits
Concluding Remarks
• Maize research and variety diffusion has had a substantial effect on
poverty in rural Ethiopia
• The poor benefit the least from maize technologies due to resource
constraints: still much room for micro-level policies to work
• Methodological remarks
References
•
•
•
•
•
•
•
•
•
Smale, M., D. Byerlee, and T. Jayne. 2011. Maize revolutions in Sub-Saharan Africa. World Bank Policy
Research working paper. No. WPS 5659.
Schneider, K., and L. Anderson. 2010. Yield Gap and Productivity Potential in Ethiopian Agriculture:
Staple Grains & Pulses. Evans School Policy Analysis and Research (EPAR) Brief No. 98.
Rubin, D. 1974. Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies.
Journal of Educational Psychology 66: 688-701
Wooldridge, J. 2002. Econometric Analysis of Cross Section and Panel Data, MIT Press.
Heckman, J.J., S. Urzua, and E. Vytlacil. 2006. Understanding Instrumental Variables in Models with
Essential Heterogeneity. The Review of Economics and Statistics 88: 389-432.
Heckman, J.J. 1979. Sample Selection Bias as a Specification Error. Econometrica 47: 153-61.
Björklund, A., and R. Moffitt. 1987. The Estimation of Wage and Welfare Gains in SelfSelection Models.
Review of Economics and Statistics 69: 42-49.
Alston, J.M., G.W. Norton, and P.G. Pardey. 1995. Science under Scarcity: Principles and Practice for
Agricultural Research Evaluation and Priority Setting. Ithaca, NY: Cornell University Press.
Foster, J., J. Greer, and E. Thorbecke. 1984. A Class of Decomposable Poverty Measures. Econometrica
52: 761-766.
Thank you.