06.21.2012 - Vivian Hoffmann
-
date post
12-Sep-2014 -
Category
Documents
-
view
339 -
download
0
description
Transcript of 06.21.2012 - Vivian Hoffmann
A Market for Lemons: Maize in Kenya
Vivian HoffmannAgricultural and Resource Economics
University of Maryland
Samuel Mutiga Michael Milgroom Rebecca Nelson Plant and Microbe-Biology
Cornell University
Jagger HarveyBiosciences East and Central Africa -
International Livestock Research Institute Hub
With thanks to the Atkinson Center for a Sustainable Future
The Market for Lemons
“Business in underdeveloped countries is difficult” - Akerlof (1970)
• When sellers have information about quality of goods not available to buyers:– Quality is not reflected in the price– Low quality goods are traded, high quality retained– Volume of trade is reduced
• Institutions (guarantees, branding) may arise to solve this problem
Previous empirical tests• Used vehicles
Bond, 1982, 1984; Pratt and Hoffer, 1984; Lacko, 1986; Genesove, 1993; Sultan, 2008; Emons & Sheldon, 2009• Workers
Gibbons and Katz, 1991• Slaves
Greenwald & Glasspiegel, 1983; Pritchett & Chamberlain, 1993• Cattle
Anagol, 2011
• We apply the lemons model to a developing country food market
Maize in Kenya
• Main staple food: estimated 400 grams / day per capita consumption (Muriuki and Siboe, 1995)
• Grown by 92% of farm households (KIHBS)• Not well suited to growing conditions
– Vulnerable to drought– Other crops generally more profitable (Tegemeo
Institute, 1996)– Prone to toxic fungal contamination
“It’s not the same as maize from my farm” – respondent who refused to sell sample
Less typical maize shop in Western KenyaMaize for sale in typical roadside market
Maize market, Rift Valley ProvinceAggregators
Maize market structure
Motivating welfare concerns
Human health• Absence of price incentive for quality leads to
underinvestment in good storage practices / over-supply of toxic contamination
Efficiency• Poor quality of food available for purchase could
lead to self-provisioning, inhibit specialization in more profitable activities (among other factors including price risk, transaction costs)
Aflatoxin• Produced by fungus Aspergillus flavus aflatoxin• Can colonize crop in field or post-harvest• Pre-harvest risk factors: drought, heat stress, pest attack• Post-harvest: high moisture content during storageHealth effects (Strosnider et al. 2006):• One of the most potent known carcinogens• Acute exposure: liver failure, death• Chronic exposure: liver cancer, suppressed immune response,
growth faltering in childrenObservability:• A. flavus not always visible; other, non-toxigenic molds may be
visible visible attributes poor proxy• Mold generally tastes bad aflatoxin likely correlated with taste
(also a noisy signal)
This is your chicken
This is your chicken on aflatoxin
Necessary condition for lemons market: asymmetric information
• Farmers have private information about the quality of food in their possession– Knowledge of growing and storage conditions
(own-produced only)– Observe taste (own produced and purchased)– This information is not available to buyers
Necessary condition for over-supply of contaminant:
• Farmers (and / or others in value chain) can influence the dimension of quality on which information is asymmetric
A model of food marketing behavior
(1)
Subject to:
(2)
(3)
(4)
(5)
(6)
(7)
Utility is derived from food quality and consumption of numeraire good
Budget constraint: Income generated by sale of food, cash crop
Exogenous food requirement
Food quality identity
Cash crop production function
Food crop production function
Food crop quality function
Quality of harvested maize
𝑞𝑚 h,𝑖−𝑀 𝑖
Retained
𝑝 (𝑞<𝑞 𝑗)
Sold
𝑞𝑚 h, 𝑖𝑞0 𝐸 [𝑞¿¿𝑝 ]¿
Quality of harvested maize
𝑞𝑚 h,𝑖−𝑀 𝑖
Retained
𝑝 (𝑞<𝑞 𝑗)
Sold
𝑞𝑚 h, 𝑖𝑞0 𝐸 [𝑞¿¿𝑝 ]¿
1. The quality of retained food is increasing in the quantity of maize harvested, controlling for
the quality of harvested food
Testable predictions
2. The quality of retained food is higher than that which is available for purchase.
Where
3. The proportion of food consumed that is self-produced is increasing household wealth.
Data: Posho mill survey
• When need flour, take kernels to small-scale mill (posho mill)
• Interviewed clients & collected maize samples
Data: Posho mill survey
• 176 mills in 138 market centers• Western, Rift Valley, Nyanza Provinces: 2009• Eastern Province: 2010• Diversity of agro-ecological zones• Collected samples and survey data from at least 10
individuals per mill• Maize samples sent to Nairobi for laboratory analysis
as collected• Observations for which both survey & lab data
available: 2124
Respondent characteristics & maize sorting practices
Urban Rural Overall Mean Ndemographic & assetsfemale 0.75 2082age 36.3 2088completed primary 0.83 0.56 0.63 0.70 2077completed secondary 0.61 0.28 0.35 0.19 2077house: electricity 0.58 0.07 0.19 0.13 1441house: permanent roof 0.92 0.78 0.81 0.95 1429house: permanent walls 0.88 0.51 0.60 0.52 1369own cell phone 0.86 0.53 0.62 0.81 1441sorting practicessort at miller? 0.66 2107 sorted for health 0.68 1833 sorted for taste 0.25 1833
Nationally Representative Data (means)
Sample
Maize origin, use, and observable properties
Mean Nmaize originown farm 0.52 1983posho miller 0.04 1983purchased elsewhere 0.38 1983gift 0.06 1983food aid 0.00 1983intended usehousehold food 0.73 2124brewing 0.23 2124livestock feed 0.01 2124sell 0.03 2124maize characteristics1-10% broken kernels 0.28 1019> 10% 0.05 10191-10% discolored 0.32 1019> 10% 0.08 1019price per kg if purchased (KSH) 14.1 402
Analysis of maize samples
• Enzyme-linked immunosorbent assay (ELISA) for aflatoxin contamination
• Test is sensitive up to 20 ppb – above this, sample must be diluted, precision is lost
• Key thresholds: – 10 ppb (Kenyan regulatory standard)– 20 ppb (test limit and FDA standard)
Aflatoxin by region
Vertical lines indicate limit of test accuracy (20 parts per billion) and Kenyan regulatory standard (10 parts per billion).
Empirical Approach
1) Test assumption of asymmetric information2) Test predictions of the model3) Investigate impact of farmer practices on
quality
1) Test assumption of asymmetric information
• Qualities observable to buyers should affect price• Qualities observable to owners should affect use• Are there any attributes that do not affect price,
but do affect use?
Effect of maize characteristics on priceObservable Unobservable Both
1-10% discolored -1.077** -1.102**(0.502) (0.514)
>10% discolored -1.547** -1.592**(0.736) (0.733)
1-10% broken -0.030 -0.119(0.382) (0.395)
>10% broken -1.959* -2.374*(1.112) (1.259)
0 < ppb afla < 10 -0.426 0.042(0.379) (0.394)
10-20 ppb afla -0.630 0.237(0.573) (0.604)
afla ppb > 20 -0.282 0.989(0.588) (0.969)
Constant 14.540*** 14.388*** 14.324***(0.208) (0.303) (0.345)
Observations 294 390 294Communities 94 94 94R-squared 0.044 0.006 0.057
Notes: Linear model with community fixed effects, clustered errors shown in parentheses. Data are from the Eastern sample only. * p<0.10, ** p<0.05, *** p<0.01
To what extent do observables predict unobservables?
ppb = 0 0 > ppb > 10 10 > ppb > 20 ppb > 201-10% broken kernels -0.043 -0.004 0.015 0.032
(0.035) (0.005) (0.012) (0.027)>10% broken kernels -0.139*** -0.041 0.043*** 0.137*
(0.050) (0.033) (0.012) (0.071)1-10% discolored kernels 0.026 0.001 -0.009 -0.018
(0.039) (0.002) (0.014) (0.026)>10% discolored kernels -0.027 -0.003 0.010 0.020
(0.051) (0.007) (0.018) (0.040)
Proportion with no discolored or broken in aflatoxin category
0.331 0.317 0.176 0.176
ObservationsCommunitiesPseudo R-squared
1014
0.067107
Notes: Marginal effects on the likelihood of observing each outcome, derived from an ordered logit regression, with standard errors clustered at the community level. Data are from Eastern Province only. * p<0.10, ** p<0.05, *** p<0.01
Aflatoxin by intended use
mean min25th
percentile median75th
percentile95th
percentile max NFood for HH 28.7 0.0 0.0 1.4 9.3 83.6 4839.3 1492Brewing 41.5 0.0 0.0 7.2 18.9 172.4 1658.1 494Livestock Feed 48.1 0.0 1.1 2.8 17.6 201.3 288.8 19Sale 64.6 0.0 0.0 7.0 33.9 476.3 806.7 69
0.2
.4.6
.81
Pro
babi
lity
<=
ppb
afla
toxi
n
0 20 40 60 80 100aflatoxin
consume brewinglivestock sell
CDF of contamination by use
Effect of aflatoxin level on use of maize
Marginal effects from multinomial logit regressions, with clustered standard errors in parentheses. Base category is no detectable aflatoxin. Eastern data only. * p<0.10, ** p<0.05, *** p<0.01
HH Food BrewingLivestock
FeedSale HH Food Brewing
Livestock Feed
Sale
(5) (6) (7) (8) (9) (10) (11) (12)0 < ppb < 10 -0.114** 0.090** 0.028 -0.004 -0.112** 0.088** 0.027 -0.002
(0.047) (0.041) (0.030) (0.015) (0.046) (0.040) (0.027) (0.015)10 < ppb < 20 -0.223*** 0.192*** 0.019 0.011 -0.232*** 0.207*** 0.015 0.009
(0.048) (0.049) (0.027) (0.021) (0.048) (0.050) (0.023) (0.020)ppb > 20 -0.256*** 0.151** 0.036 0.069** -0.258*** 0.163*** 0.032 0.064**
(0.058) (0.060) (0.036) (0.031) (0.059) (0.062) (0.032) (0.030)1-10% discolored 0.079* -0.085* 0.007 -0.001
(0.046) (0.044) (0.007) (0.012)>10% discolored 0.160*** -0.135*** -0.002 -0.023**
(0.054) (0.051) (0.007) (0.010)1-10% broken -0.071 0.058 -0.002 0.015
(0.048) (0.046) (0.006) (0.014)>10% broken 0.076 -0.171*** 0.017 0.078
(0.082) (0.049) (0.021) (0.065)Proportion used for X at ppb = 0 0.785 0.189 0.003 0.023 0.785 0.189 0.003 0.023
ObservationsCommunitiesPseudo R-squared
984107
0.000107
0.032
984
2) Test predictions of the model
• Impact of quantity grown on quality of retained maize
• Compare quality of purchased vs. retained maize
• Is self-produced maize a normal good?
Effect of harvest quality (yield) & quantity (area planted) on aflatoxin contamination of retained maize
Notes: Marginal effects from an ordered probit regression, with clustered standard errors shown in parentheses. Controls for post-harvest practices not shown. * p<0.10, ** p<0.05, *** p<0.01
ppb = 0 0 <ppb < 10 10 < ppb < 20 ppb > 20(1) (2) (3) (4)
Quality and quantity of harvestHectares under maize 0.028*** 0.001 -0.009*** -0.020***
(0.009) (0.002) (0.003) (0.006)Yield (100 kg / ha) 0.001** 0.000 -0.000** -0.001**
(0.001) (0.000) (0.000) (0.000)ObservationsCommunities(Pseudo) R-squared
1060.228
761
Contamination by source of maize
Contamination by source of maize
Contamination as a function of source
Marginal effects from multinomial probit regressions, with clustered standard errors in parentheses. Eastern data only. * p<0.10, ** p<0.05, *** p<0.01
ppb = 00 > ppb >
1010 > ppb >
20 ppb > 20 ppb = 00 > ppb >
1010 > ppb >
20 ppb > 20
(5) (6) (7) (8) (9) (10) (11) (12)
Miller -0.010 -0.000 0.003 0.008 0.024 -0.000 -0.007 -0.017(0.103) (0.004) (0.029) (0.078) (0.106) (0.003) (0.032) (0.072)
Other purchase -0.052* -0.002 0.014* 0.039* -0.053* -0.002 0.015* 0.040*(0.029) (0.003) (0.008) (0.023) (0.030) (0.003) (0.009) (0.023)
Gift or aid -0.056 -0.004 0.015 0.044 -0.058 -0.004 0.016 0.047(0.051) (0.007) (0.013) (0.044) (0.051) (0.007) (0.013) (0.045)
1-10% broken -0.056* -0.003 0.016* 0.043(0.034) (0.004) (0.009) (0.027)
>10% broken -0.126** -0.018 0.030*** 0.114(0.063) (0.021) (0.012) (0.072)
1-10% discolored 0.030 0.000 -0.009 -0.021(0.038) (0.001) (0.011) (0.027)
>10% discolored -0.034 -0.002 0.009 0.026(0.057) (0.004) (0.015) (0.045)
Share of Own-Grown Maize in Category
0.377 0.280 0.159 0.185 0.377 0.280 0.159 0.185
ObservationsCommunitiesPseudo R-squared
931106
0.018
931106
0.002
Alternative explanation
Perhaps those who purchase are less concerned with bad taste / toxic contamination, purchase even though fully informed
– Compare quality-usage patterns of own vs. purchased maize
Quality-use relationship similar for own-grown and purchased maize
ppb = 0 0 > ppb > 10 10 > ppb > 20 ppb > 20N 296 262 84 99
% 77.9 76.8 60.9 57.6
N 68 66 47 51
% 17.9 19.4 34.1 29.7
N 2 4 3 4
% 0.5 1.2 2.2 2.3
N 14 9 4 18
% 3.7 2.6 2.9 10.5
% total 100 100 100 100
ppb = 0 0 > ppb > 10 10 > ppb > 20 ppb > 20N 241 206 75 46
% 86.1 79.2 66.4 46.5
N 35 45 36 47
% 12.5 17.3 31.9 47.5
N 1 4 1 1
% 0.4 1.5 0.9 1
N 3 5 1 5
% 1.1 1.9 0.9 5.1
% total 100 100 100 100
Food for HH
Brewing
Livestock Feed
Sale
Panel A: Maize grown on own farm
Food for HH
Brewing
Livestock Feed
Sale
Panel B: Purchased maize
Quality-use relationship similar for own-grown and purchased maize
ppb = 0 0 > ppb > 10 10 > ppb > 20 ppb > 20N 296 262 84 99
% 77.9 76.8 60.9 57.6
N 68 66 47 51
% 17.9 19.4 34.1 29.7
N 2 4 3 4
% 0.5 1.2 2.2 2.3
N 14 9 4 18
% 3.7 2.6 2.9 10.5
% total 100 100 100 100
ppb = 0 0 > ppb > 10 10 > ppb > 20 ppb > 20N 241 206 75 46
% 86.1 79.2 66.4 46.5
N 35 45 36 47
% 12.5 17.3 31.9 47.5
N 1 4 1 1
% 0.4 1.5 0.9 1
N 3 5 1 5
% 1.1 1.9 0.9 5.1
% total 100 100 100 100
Food for HH
Brewing
Livestock Feed
Sale
Panel A: Maize grown on own farm
Food for HH
Brewing
Livestock Feed
Sale
Panel B: Purchased maize
Is self-produced maize a normal good? (REPEAT data)
Harvested maize
(100 kg)(1) (2) (3)
Log asset value 2.502*** 0.025** 0.021*(0.479) (0.011) (0.012)
Agricultural land (ha) 1.873** 0.013 0.013(0.892) (0.009) (0.009)
Land squared (ha sqr) -0.034 -0.000 -0.000(0.043) (0.000) (0.000)
Harvested maize (100kg) 0.001(0.001)
Obsevations 679 695 677Communities 86 86 86R squared 0.144 0.017 0.018Notes: Results are from linear regressions with community fixed effects. Standard errors, shown in parentheses, are clustered at the community level . * p<0.10, ** p<0.05, *** p<0.01
Consumed maize produced on own farm past 7 days
3) Impact of farmer practices on quality
Determinants of visible mold & afla
ppb = 0 0 <ppb < 10 10 < ppb < 20 ppb > 20 0 kernels 0-10% kernels >10% kernels
(1) (2) (3) (4) (5) (6) (7)Quality and quantity of harvestHectares under maize 0.056** 0.007 -0.017** -0.046** 0.026 -0.018 -0.007
(0.025) (0.005) (0.008) (0.022) (0.026) (0.019) (0.007)Yield (100 kg / ha) 0.002** 0.000 -0.000** -0.001** 0.001 -0.001 -0.000
(0.001) (0.000) (0.000) (0.001) (0.001) (0.001) (0.000)Post-harvest practicesDry maize in field 0.042 0.007 -0.012 -0.037 -0.295** 0.244** 0.051**
(0.132) (0.005) (0.035) (0.128) (0.126) (0.114) (0.024)Improved drying 0.020 0.000 -0.006 -0.016 -0.236** 0.175** 0.061**
(0.069) (0.000) (0.020) (0.058) (0.092) (0.071) (0.031)Months since harvest -0.048*** 0.067 0.014*** 0.040*** -0.022 0.016 0.006
(0.013) (0.045) (0.005) (0.010) (0.020) (0.014) (0.006)ObservationsCommunities(Pseudo) R-squared 0.225
Discolored kernelsAflatoxin
36174
0.144
36174
Notes: Marginal effects calculated from ordered probit regressions of the categorical proportion of discolored kernels (1 through 3), and aflatoxin contamination (4 through 7). Yellow shading indicates differences between coefficient values across models at p<0.1. Standard errors, shown in parentheses, are clustered at the community level for all models and tests. * p<0.10, ** p<0.05, *** p<0.01
• Visibly moldy maize is less likely to be sold: farmers appear to respond to price incentives
• Impact of farm practices on visible molds and aflatoxin are not well correlated– Inhibits learning about best practices, implies weak
incentives for aflatoxin control
– Technologies to reduce aflatoxin unlikely to be profitable unless asymmetric information problem can be solved
Aflatoxin and farmer incentives
Overcoming the information asymmetry: prospects & implications
• Technologies in development for rapid and affordable screening, e.g. “e-nose”
• Efforts to develop AflaSafe certification– Would better align farmer, trader incentives with
public health goals
– May also encourage more profitable specialization
– Could adversely impact health of poorest consumers
Summary of Key Findings
• Evidence consistent with asymmetric information– Aflatoxin (or correlate) determines how maize is used
observed by maize holders– No impact on market price not observed by buyers
• Evidence consistent with lemons market– Controlling for quality of harvest (yield), quality of retained
maize is increasing in harvested amount (area planted)– Quality of sold and purchased maize is lower than quality of
retained maize– Consumption of self-produced maize is increasing in
household wealth