05.16.2013 - Dilip Mookherjee

Asymmetric Information and Middleman Margins:An Experiment with Potato Farmers in India

Sandip MitraIndian Statistical Institute, Kolkata

Dilip MookherjeeBoston University

Maximo ToreroInternational Food Policy Research Institute

Sujata VisariaHong Kong Univ of Science & Technology

May 2013S. Mitra, D. Mookherjee, M. Torero, S. Visaria

Asymmetric Info & Middleman Margins in Potato Markets

Questions

How large are middleman margins relative to pricesreceived by farmers in LDCs?To what extent do benefits of market growth trickle down tofarmers?How are these affected by improvements in externalmarket price information available to farmers owing toadvances in IT?More broadly, what role do middlemen play in agriculturalmarketing

S. Mitra, D. Mookherjee, M. Torero, S. Visaria


Existing Evidence

Considerable evidence of large gaps between retail pricesof LDC exports and prices received by original producers(Feenstra (1998), Morisset (1998))Difficult to evaluate how much of these are accounted bytransport and distribution costs of intermediariesKey problem: difficult to obtain data concerning costs andmarkups of intermediaries



Existing Evidence, contd.

Micro-level evidence of limited pass-through (less than50%) of commodity export price increases to farmers:

Ugandan coffee 2002-03 (Fafchamps-Hill (2008))Mozambique cashews in 1990s (McMillan, Rodrik andWelch (2002))

Fafchamps-Hill show rising middleman margins were notaccompanied by rise in transport or storage costs



Broad Questions

Possible reasons for high margins and limitedpass-through to farmers:

(a) trader market power, owing to collusion, limited entry(capital requirements, network/reputational barriers), scaleeconomies in transport, storage etc.(b) risk premium for insurance provided by traders tofarmers(c) asymmetric information between traders and farmersconcerning price movements in wholesale or retail marketswhere traders re-sell

Relative importance of (a,b,c)? If (c) is important, scope forlow-cost policy interventions using new IT



Recent Evidence Concerning Price Effects ofCellphones

Jensen (2007), Aker (2010), Goyal (2010): increased useof IT products reduce price dispersion across locations,raise average returns for farmers (Kerala/Niger/MP)Contrast: Fafchamps-Minten (2012) find no significanttreament effects on prices received by Maharashtrafarmers of offer of free SMS service providingprice/weather informationAll of the above contexts: farmers sell directly in wholesalemarkets rather than at farmgate



Effect on Farmgate prices?

Focus on contexts where most sales are at the farmgate:bilateral contracting between farmer and customary trader(Ugandan coffee, Mozambique cashews, West Bengalpotatoes)IT services provide each farmer with informationconcerning prices at which their middleman re-sells thegood in marketsPrimary advantage to farmer: reduce informationaldisadvantage vis-a-vis middlemen (rather than who orwhere to sell)Farmer could negotiate a better farmgate price, or reduceinformational distortions in ex ante bilateral contract



This Paper

Context: potato farmers in West BengalCalculate (lower bound to) average margins earned bylocal intermediaries, estimate pass-throughConduct a field experiment providing farmers withinformation about the intermediaries’ resale price inwholesale and retail marketsUse observed impacts on farmgate prices and tradevolumes to test alternative models ofcontracting/bargaining



Preview of Main Findings

Large middleman margins in WB potato (≥ 50-90% offarmgate prices); low (6-20%) pass-through fromwholesale to farmgate pricesResults of providing price information to farmers: noaverage effects, increased volatility

(consistent with poolingequilibria of bargaining model, inconsistent with ex antecontracting model)Hence neither risk-sharing nor asymmetric information playa significant roleKey cause of high margins: hierarchical marketingarrangements, market power of middlemen



Preview of Main Findings

Large middleman margins in WB potato (≥ 50-90% offarmgate prices); low (6-20%) pass-through fromwholesale to farmgate pricesResults of providing price information to farmers: noaverage effects, increased volatility (consistent with poolingequilibria of bargaining model, inconsistent with ex antecontracting model)Hence neither risk-sharing nor asymmetric information playa significant roleKey cause of high margins: hierarchical marketingarrangements, market power of middlemen



Presentation Outline

1. Context: WB Potato Supply Chain, Markets andPrices2. Alternative Theories: ex ante contracting, expost bargaining3. Experiment Details4. Testing Different Theories5. Implications



1. Context: Potato Supply Chain

We study two main potato growing districts of W Bengal:Hugli, W MedinipurFarmers harvest potatoes once a year (Feb-April), sell halfat harvest time, store the rest and sell later (May-Dec)Sell mostly to local traders (phorias) who resell inneighboring wholesale markets (mandi) to wholesalersWho in turn sell to traders in city markets (Kolkata forHugli, Bhubaneswar for Medinipur) and in neighboringstates (Assam/AP)



Supply Chain

City Markets/Kolkata,

BhubneshwarOther States

WholesaleMarkets / Mandis

Farmers

Village Traders

Local Markets

92% 8%

Table: West Bengal Potato Supply Chain



Supply Chain: Distances




Farmers

Village Traders

Local Markets

80-400 km

3 km

0 km

5 km

Table: Distances



Gross/Net Prices at Various Layers




Farmers

Village Traders

Wholesale(Local) Markets

Rs. 6.38

Rs. 4.85

Rs. 4.52

Rs. 2.24/2.15 Rs. 2.55/2.22

Table: Prices



Average Margins

Key Fact: Less than 1% farmers sell to wholesalers inmandi directly, so almost invariably farmers must gothrough a local middleman (phoria)When farmers sell in a local market or the mandi, they sellto some other phoria located therePrices farmers receive are significantly below resale pricesphorias receive at the mandi



Average Margins, contd.

In 2008 (year of the experiment), average farmgate (gross)price was Rs 2.24/kg; farmer sold at Rs 2.55 in localmarket/haatWhereas phorias received average price of Rs 4.85 in themandiFor farmers that sell directly to a local market, we knowtheir selling costs (transport, handling, storage), whichprovides an upper bound estimate of these costs incurredby traders



Average Margins, contd.

Per Kg: transport costs Rs 0.24, handling & other costs Rs0.35, storage costs (only for potatoes sold after June) Rs0.89Using these as upper bound for corresponding costsincurred by traders, obtain a lower bound for net phoriamargin of Rs 2.02/1.13 for harvest/post-harvest salesEquals 42/23% of wholesale price, and 90/50% offarmgate prices for harvest/post-harvest sales



Hierarchical Marketing System

What prevents farmers from selling directly to awholesaler?Wholesaler does not want to negotiate with small farmers:‘not worth my time’Wholesaler transacts with 7-8 phorias per village, who are‘aggregators’ in a classical hierarchical manner (a la CalvoWellisz):

deliver ‘reliable’ supply: stable quantity, good quality (80%phorias inspect potatoes supplied by farmers)can accept delayed payment from wholesalermaintain ‘good relations’ with farmers (risk-sharing role?)



Phoria Market Concentration

Not particularly concentrated: number of phorias in avillage ranges from 2–20, with mode 6 and mean 9.5,number of farmers selling is 150-200Median village market share of a phoria is 5%58% (resp. 28%) selling to same phoria for more than 2(resp. 5) years; no exclusive dealing or contractualcommitmentsSome interlinkage: one out of three farmers borrow and/orpurchase from same phoriaNo difference in price between old and new suppliers (butsome difference in non-price services)



Resale Price Information

Farmers say they would like to know price at which phoriaresells the crop at the mandiLatter decided by private negotiation between phoria andwholesaler: they don’t like to publicize these pricesFarmers access to phones does not help: ‘we don’t knowwho to call’We paid ‘insider’ market vendors at the mandi to provideus with this information daily74% farmers say phoria is their primary source ofinformation about the resale price



Price Shocks

Predicting prices on the basis of past price information forfarmers is difficult owing to huge fluctuations over time:both across and within yearsAnnual average mandi (resale) price: Rs 7.60 in 2007,4.85 in 2008, 10.72 in 2011, 12.37 in 2012High co-movement with city prices: within-yearpass-through of weekly city price to mandi price exceeds65%Compared with insignificant (6%) pass through to farmgateprices in 2008 (making it even harder to predict mandiprices on the basis of farmgate prices)



Wholesale Potato Prices for Different Years, Agmarkdata, deflated by WB food price index

05

1015

Mod

al p

rice

per

kg

2005w26 2006w26 2007w26 2008w26 2009w26 2010w26 2011w26Week

Mandi prices adjusted for inflation in food article prices in West Bengal.

2005−2011Mandi prices for jyoti potatoes, Agmark data



Analysis of Variance of Mandi Prices

Table 3: Analysis of Variance of Mandi PricesSource MSE F

Year 6382.05 2980.75***Period 1756.82 820.53***Year x Period 731.69 341.74***Mandi 165.92 77.49***Mandi x Year 54.61 25.50***

ObservationsR-squared

27170.87

Notes: Based on weekly averages of mandi prices for the months June-November in 2007, January - November in 2008 and 2011, and January-April in 2012. Periods refer to three "seasons" when potato sales occur: harvest (weeks 1-12), post-harvest early (weeks 13-26) and post-harvest late (weeks 27-52). A mandi is defined as a variety-year combination.

Table: Mandi Price ANOVA



Intra-year Pass-through of City Prices

Table 2: Within-year Pass-through of Weekly City Prices to Farmgate and Mandi Prices

Farmgate Mandi Mandiprice price price

2008 2008 2011

City price 0.06 0.67*** 0.74***(1.07) (16.85) (13.82)

Constant 2.11*** 0.65 -0.72(4.66) (1.38) (-1.54)

R-squared 0.50 0.91 0.95Observations 689 949 1,031Notes: Observations are market-variety-week combinations. City is Kolkata for Hugli andBhubaneswar for Medinipur. Week and mandi dummies are included. t-statistics in parentheses.*** p<0.01, ** p<0.05, * p<0.1

Table: Mandi Price Variations



Explaining Across-Year Variations in Mandi Prices

Table 1: Explaining Varia1ons in Mandi PricesPooling data across 2007, 2008, 2011, 2012

(1) (2)

Local area yield (tonnes/acre) -0.37 -0.42***(-1.44) (-7.11)

Distance ('00 km) -0.21(-0.86)

% households with landline 1.31(0.25)

% villages with pucca road 1.14(1.00)

% villages with factory/mill -1.50(-1.33)

adult male wage rate 0.01(0.18)

2008 -1.81** -1.13***(-2.11) (-5.79)

2011 4.52*** 5.68***(4.10) (22.53)

2012 5.73*** 8.98***(6.59) (37.99)

Constant 10.62*** 0.81(3.69) (1.31)

R-squared 0.78 0.81Observations 86 2,717Notes: Column 1 observations are mandi-year;Column 2 observations are mandi-week;Mandi denotes market-variety combination;Distance measures distance to nearest city;t-statistics in parentheses

Table: Mandi Price Variations



Ranking of Mandis by Price: 2008 versus other years

05

1015

20

0 5 10 15 20Mandi’s rank before 2008

after 2008 2008

Mandis’ relative price rank

Table: Price RankingsS. Mitra, D. Mookherjee, M. Torero, S. Visaria


Summary: Farmers’ Price Information

Farmers have no access to direct information regardingmandi prices at which phoria will be able to re-sell potatoesPredicting this on the basis of past price information offarmers is difficult (esp in 2008) because:

farmgate prices co-move little with mandi or city priceshuge year-to-year fluctuations in mandi prices, of whichsmall part explained by local potato yields2008 intra-year and across-mandi price patterns were sodifferent from other years



2.Theoretical Predictions

When farmers sell to middlemen rather than to marketsdirectly, effects of information provision depend crucially onwhether trade is governed by ex ante contracts or ex postbargaining



Theoretical Predictions: Implications of Ex AnteContracting

With ex ante contracts (necessary for risk-sharing),asymmetric information results in screening distortionsTraders tempted to claim resale price is low in order to paylow farmgate price; counteracted by lowering tradevolumes below efficient levelProviding information to farmers should reduce thesedistortions: hence information provision should raiseaverage and reduce volatility of trade volumes

(assuming competition among middlemen)If traders have monopoly power, information provision willhave no effect



Theoretical Predictions: Implications of Ex AnteContracting

With ex ante contracts (necessary for risk-sharing),asymmetric information results in screening distortionsTraders tempted to claim resale price is low in order to paylow farmgate price; counteracted by lowering tradevolumes below efficient levelProviding information to farmers should reduce thesedistortions: hence information provision should raiseaverage and reduce volatility of trade volumes(assuming competition among middlemen)If traders have monopoly power, information provision willhave no effect



EAC Prediction

!" !" !" !"

#" $"

#%!&"

$'%!&"

$%!&"

#'%!&"

Figure: Bertrand competition among traders, risk neutrality



EAC Prediction

!" !" !" !"

#" $"

#%!&"

$'%!&"

$%!&"

#'%!&"

Figure: Bertrand competition among traders, risk aversion



Testable Predictions of EAC

Robust prediction of EAC: reducing asymmetricinformation should increase volume tradedInformation treatment should expand average quantitytradedExtent of increase typically larger, lower the mandi priceExpect heterogenous treatment effect: quantity expansionshould be larger, lower the realized mandi price



Alternative Theory: Ex Post Bargaining

Field interviews confirm absence of any ex anteagreements: stress the role of ex post bargainingMiddlemen make price offers (after observing v ): signalingrather than screeningOutside option: farmer can take his potatoes to the localmarket/mandi and sell to another trader there (who re-sellsto a wholesaler at same v ); 11% of farmer transactions(4.5% of annual output) were in local markets in 2008Collusion amongst village traders, and amongst markettraders, but no collusion between village and markettraders: sequential duopolySunk transport cost at the local market: scope for hold-upby market trader



Separating Equilibrium: Graphical Illustration

v

p(v) m(v)



Partially Pooling Equilibrium: Graphical Illustration

v

p(v) m(v)

v1 v2

r1

r2



Comparative Statics of Partially Pooling Equilibrium

v

p(v) m(v)

v1 v2

r1

r2



Pooling Equilibria: Testable Predictions

Starting with a pooling equilibrium, improving the farmersinformation lowers p,q for low v and raises p,q for high vAverage treatment effect will be zero, since m(v) isunaffected and price offers made so that farmers areindifferent between selling to VT or MTHigher transport costs: lowers price offers and probabilityof farmer accepting village trader’s offerHigher v raises offer and lowers probability of farmeraccepting



4. Information Provision Experiment

Experiment involving 72 villages and 25 farmers per villagein Hugli and MedinipurTwo information treatments in 24 villages each:

Public (noticeboards)Private (‘blocked’ cell phones for 4 farmers/village)

24 villages served as controlVillages at least 8 km from each other



Experiment, contd.

Control-treatment villages paired to ensure balance withineach local areaExpect no effect on mandi prices: less than 1% supply tomandi came from treated villagesStarted experiment June-Nov 2007 but many problemswith cell-phones needed to be sorted outSorted out by end-2007, so we use data for one full year:Jan-Nov 2008



Table 4: Descriptive Statistics, by intervention group (baseline survey, 2007)

(1) (2) (3)Village-levelDistance to mandi (km) 8.07 8.56 8.93

(1.01) (1.65) (0.88)

Has a PCO box (2007) 0.46 0.42* 0.67(0.10) (0.10) (0.09)

Household-levelOwned land (2008) (acres) 1.19 1.09 1.09

(0.05) (0.05) (0.05)

Fraction land planted with potatoes (2007) 0.51 0.51* 0.53(0.01) (0.01) (0.02)

Has a landline phone (2007) 0.24 0.23 0.25(0.02) (0.02) (0.02)

Has a cell phone (2007) 0.34 0.31 0.34(0.02) (0.02) (0.02)

ControlPrivate InfoPublic Info

Notes:***, ** and * denote difference from control is significant at 1%, 5%, 10% resp.

Table: Descriptive Statistics, by Intervention Group: Panel A



Effects of Interventions on Source of Farmer PriceInformation

Table 5: Effect of Interventions on Farmers Price InformationProbability of

tracking Days since

tracked

Friends/Nbrs Other(1) (2) (3) (5)

Private info 0.80 0.71*** 1.12 0.50 1.82(0.47) (2.88) (0.19) (1.05) (0.79)

Phone recipient 1.71* 0.86*** 1.43 2.31 20.33***(1.65) (2.78) (0.82) (1.47) (4.42)

Public info 8.00*** 0.80** 1.03 0.49 30.19***(3.03) (2.20) (0.04) (1.10) (4.72)

Observations 10771 10771Prob > χ2 0.00 0.00Notes: In the fortnightly trading surveys (March — December 2008) a randomly selected 50% sample (stratified by village) was asked if they kept track of retail or wholesale potato prices, and if they answered yes, were asked to list up to 3 markets (2 varieties per market) where they tracked prices, how long ago they last tracked the price, the price when they last tracked it and the source of their information. Each observation is a household-variety-market combination. Column (1) reports odds ratios from a logit regression. Column (2) reports incidence-rate ratios from a Poisson regression. Columns (3), (4) and (5) report relative-risk ratios from a single multinomial logit regression. Dummies for month, variety and district are included.

0.00

Information source

(4)

9302

Trader



5. Treatment Effects on Quantity and Prices

Predicted average effects:contracting model predicts traded volumes should risebargaining model predicts zero average effect on pricesand quantities

Also examine heterogeneity of treatment effects w.r.t.realized mandi price:

contract model predicts treatment will raise trade volumesmore in low v statesbargaining model predicts trade volumes will fall in low vstates, and rise in high v states



Table 6: Average Effects of Intervention on Total Quantity Sold and Net Price Received

(1) (2) (3) (4)

Private info 484.65 16.09 -0.07 0.02(0.88) (0.03) (-0.55) (0.15)

Phone 524.55 454.09 0.10 0.08(1.18) (0.99) (1.05) (0.98)

Public info 229.40 -275.17 -0.10 -0.05(0.44) (0.54) (-0.82) (0.47)

Land 2252.24*** 2218.82*** -0.09*** -0.07***(12.89) (12.42) (-5.03) (4.82)

Constant 2844.90*** 3022.93*** 2.21*** 2.37***(5.16) (6.69) (18.28) (26.40)

Mandi fixed effects No Yes No Yes

R-squared 0.35 0.39 0.37 0.44Observations 2318 2318 2318 2318Notes: The unit of observation is a farmer-variety-quality. A mandi is defined as a market-variety combination. In columns (1) and (3) a variety dummy for chandramukhi potatoes, a dummy for low-quality potatoes and a dummy for Medinipur district are included; therefore the constant refers to high-quality jyoti potatoes in Hugli district. All columns control for the farmer's landholding. Columns (1) and (3) include controls for variety and quality of potatoes, and a dummy for Medinipur district. Columns (2) and (4) include mandi dummies. t-statistics are in parentheses. Standard errors are clustered at the village level.

Total Quantity Sold (kg)Net Price Received

(Rs/kg)

Table: Average Treatment Effects



Table 7: Heterogeneous Effects of Intervention on Total Quantity Sold and Net Price Received

(1) (2) (3) (4)

Private info -3027.18* -3066.96** -0.75** -0.61**-1.67 (2.22) (2.11) (2.03)

Private info x Mandi price 782.06* 695.64** 0.15* 0.14**(1.85) (2.15) (1.95) (2.02)

Phone 1221.77 1715.92 0.06 0.05(0.94) (1.23) (0.18) (0.18)

Phone x Mandi price -159.73 -293.64 0.01 0.00(0.50) (0.87) (0.09) (0.05)

Public info -2064.80 -2845.59** -0.21 0.02(1.30) (2.26) (0.62) (0.08)

Public info x Mandi price 496.83 581.60** 0.02 -0.01(1.33) (2.04) (0.28) (0.17)

Mandi price (annual average) -519.22*** 65.40 0.18** 0.18**(2.93) (0.27) (2.38) (2.60)

Land 2249.33*** 2184.05*** -0.09*** -0.07***(12.72) (11.96) (5.05) (5.55)

Constant 5197.65*** 2837.50** 1.73*** 1.58***(5.37) (2.63) (5.63) (5.34)


R-squared 0.36 0.39 0.41 0.46Observations 2299 2299 2299 2299

Quantity sold (kg) Net price received (Rs/kg)

Notes: The unit of observation is a farmer-variety-quality. A mandi is defined as a market-variety combination. All columns include the farmer's landholding. In columns (1) and (3) a variety dummy for chandramukhi potatoes, a dummy for low-quality potatoes and a dummy for Medinipur district are included; therefore the constant refers to high-quality jyoti potatoes in Hugli district. Columns (2) and (4) include mandi dummies. The average mandi price for each individual farmer-variety is calculated as the average price of potatoes in the relevant mandi, averaged over the weeks in which the farmer made a potato sale. Thus the average mandi price varies at the farmer-variety level. t-statistics are in parentheses. Standard errors are clustered at the village level.

Table: Heterogeneity of Treatment Effects



Predicted Treatment Effects at 10th/90th percentile

Table 8: Total Effects of the Intervention on Quantity Sold and Net Price Received, 10th and 90th Percentile

(1) (2) (3) (4)Private information, no phone

10th percentile -746.16 -1038.01* -0.32* -0.20(1.04) (1.70) (1.98) (1.57)

90th percentile1736.71* 1170.48 0.14 0.25(1.80) (1.37) (0.86) (1.46)

Private information, with phone10th percentile 9.72 -178.55 -0.25 -0.13

(0.01) (0.21) (1.30) (0.77)

90th percentile1985.47* 1097.70 0.23 0.33(1.76) (1.04) (1.06) (1.47)

Public information10th percentile -615.73 -1149.27* -0.15 -0.01

(0.97) (1.97) (0.98) (0.08)

90th percentile 961.58 697.16 -0.08 -0.04(1.09) (0.94) (0.45) (0.26)

Mandi fixed effects No Yes No YesNotes: Total effects are computed at the 10th percentile and 90th percentile of mandi prices using results from the heteregenous effects regressions.

Net price received (Rs/kg)Quantity sold (kg)

Table: Predicted Treatment Effects at 10th, 90th percentiles



Predicted Treatment Effects at 10th/90th percentile,Using Deviation from ‘Expected’ Price

Quantity Quantity Net Price Net PricePrivate information, no phone

10th percentile -2449.89 *** -2955.29 *** -0.25 -0.09(3.08) (3.26) (1.03) (0.53)

90th percentile 2777.22 *** 2123.19 *** 0.06 0.11(3.79) (3.20) (0.41) (0.73)

Private information, with phone10th percentile -1808.98 * -2621.14 ** -0.14 0.01

(1.94) (2.50) (0.52) (0.05)

90th percentile 3542.95 *** 3039.67 ** 0.19 0.20(2.82) (2.60) (1.10) (1.13)

Public information10th percentile -1830.98 ** -2465.10 *** -0.14 -0.09

(2.39) (2.90) (0.60) (0.58)

90th percentile 1679.93 ** 1037.57 -0.06 0.07(2.19) (1.56) (0.39) (0.42)




Summary of Treatment Effects

Absence of any significant average treatment effects(analogous to Fafchamps-Minten (2011))Masked significant heterogeneous impactsReject contracting model, results consistent with poolingequilibria of bargaining model



Additional Predictions of Partial Pooling in Ex PostBargaining Model

1. Farmers exposed to information treatments track localmarket prices with less error2. Farmgate (gross) price is lower than gross pricereceived by a farmer in a mandi sale (p(v) < m(v))3. More market sales when v is higher (α(v) decreasing)4. More market sales where transport costs are higher



Testing Additional Prediction no. 1 of Bargaining Model

Table 9: Effect of Intervention on Normalized Error Variance in Tracked Price relative to Actual Local Market Price

Public info Private info Control(1) (2) (3)

Standard deviation of normalized error 0.33 0.32 0.40

Observations 2957 1335 1802

(3)/(1) (3)/(2) (2)/(3)1.541*** 1.418*** 0.920*

__________________________________________________ ___________________________ ______________________

is defined as (tracked price - actual market price)/actual market price.

Variance-comparison test F-statistic

Note: Half the farmers in the sample were asked each fornight if they tracked the prices in local markets, and if so which markets, and what the pricewhen they last checked. The date when they checked was matched to the actualwas average price in that market in that fortnight. The normalized error



Testing Additional Prediction no. 2 of Bargaining Model

Table 10: Farmers Gross Price Difference between Farmgate and Local-Market SalesOverall Hugli Medinipur

(1) (2) (3)

Sold to market 0.36*** 0.56*** 0.36*(2.78) (2.99) (1.99)

Mandi price 0.23*** 0.47*** 0.19***(5.07) (6.92) (4.65)

Constant 1.44*** 0.73*** 1.30***(9.06) (3.11) (5.78)

R-squared 0.37 0.48 0.29Observations 3919 2002 1917Notes: The unit of observation is a farmer-quality-variety-week when a transaction occurred. Landholding, a variety dummy for chandramukhi potatoes, a quality dummy for low quality potatoes and a district dummy for Medinipur are included; therefore the constant term is the coefficient on high-quality jyoti potatoes in Hugli. t-statistics are in parentheses. Standard errors are clustered at the village level.



Testing Additional Predictions no. 3,4 of BargainingModel

Table 11: Likelihood of Market Sales Regressed on Mandi PriceOverall Hugli Medinipur West

(1) (2) (3)

Mandi price 1.61*** 0.85 1.68***(3.55) (0.45) (3.37)

Land owned 0.93 0.86 0.96(1.10) (0.76) (0.58)

Medinipur dummy 4.72**(2.41)

Prob > χ2 0.00 0.58 0.00Observations 3919 2002 1917Notes: The unit of observation is a farmer-variety-quality combination in a week when a positive quantity is sold. The results show odds-ratios and z-statistics for logit regressions. Landholding, a variety dummy for chandramukhi potatoes and a dummy for low-quality potatoes are included. Standard errors are clustered at the village level.



Implications

Failure of information treatments to help farmers securehigher prices reflect weaknesses of both formal andinformal institutionsWeakness of formal institutions: no centralized wholesalemarkets permitting farmers to sell directlyWeaknesses of informal trading relationships: no long termcontracts or insurance; ex post bargaining with highlyrestricted competition between tradersPolicy makers need to focus on ways of enhancingcompetition (eg encouraging entry of modern retailers thatcontract directly with farmers)



05.16.2013 - Dilip Mookherjee

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Transcript of 05.16.2013 - Dilip Mookherjee