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Credit Constraints and Capital Misallocation in Agriculture: Theory and Evidence from Uganda
Last registered on September 28, 2018

Pre-Trial

Trial Information
General Information
Title
Credit Constraints and Capital Misallocation in Agriculture: Theory and Evidence from Uganda
RCT ID
AEARCTR-0003257
Initial registration date
September 28, 2018
Last updated
September 28, 2018 2:23 PM EDT
Location(s)

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Primary Investigator
Affiliation
Institute for International Economic Studies
Other Primary Investigator(s)
PI Affiliation
Copenhagen Business School
PI Affiliation
Institute for International Economic Studies
PI Affiliation
Institute for International Economic Studies
Additional Trial Information
Status
On going
Start date
2017-01-13
End date
2019-10-31
Secondary IDs
Abstract
A basic requirement for free markets to allocate capital to those with the highest return is that willingness-to-pay for capital is increasing in returns. Credit constraints may interfere with the efficient functioning of markets if they constrain the willingness-to-pay of those with high returns. We investigate these issues in the context of the market for chemical fertilizer in Uganda. Using an incentive-compatible mechanism, we study the relationship between farmers’ willingness-to-pay for fertilizer and their return to fertilizer. We also study how this relationship changes when farmers’ credit constraints are relaxed by receiving a large cash transfer prior to willingness-to-pay elicitation.
External Link(s)
Registration Citation
Citation
Burchardi, Konrad et al. 2018. "Credit Constraints and Capital Misallocation in Agriculture: Theory and Evidence from Uganda." AEA RCT Registry. September 28. https://doi.org/10.1257/rct.3257-1.0.
Former Citation
Burchardi, Konrad et al. 2018. "Credit Constraints and Capital Misallocation in Agriculture: Theory and Evidence from Uganda." AEA RCT Registry. September 28. https://www.socialscienceregistry.org/trials/3257/history/34947.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2017-01-13
Intervention End Date
2018-02-19
Primary Outcomes
Primary Outcomes (end points)
The unit of analysis is the household throughout. Survey and willingness responses are provided by the household head wherever possible, and crop yields are measured by us at the plots. We measure
1. The empirical distribution of willingness-to-pay (WTP) for 1 sack of DAP and 1 sack of CAN fertilizer (worth approximately 200,000 UGX in total), and how this distribution changes when farmers receive a 200,000 UGX cash transfer shortly prior to WTP elicitation.
2. The average return to randomly receiving fertilizer (measured by differences in quantity of maize, value of crop output, or profit, respectively), and how this changes when farmers receive a 200,000 UGX cash transfer shortly prior to WTP elicitation.
3. Linear and nonlinear estimates of the relationship between returns to fertilizer and WTP, and how it changes when farmers receive a 200,000 UGX cash transfer shortly prior to WTP elicitation.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Farmers are given the opportunity to purchase fertilizer (a bundle of one 50 Kilogram sack of DAP and one 50 Kilogram sack of CAN fertilizer) through a Becker-DeGroot-Marschak mechanism. The mechanism elicits their maximum willingness-to-pay (WTP) for the fertilizer (between 0 and 200,000 UGX, in increments of 20,000) and then charges a random price. If WTP exceeds the price, the farmer purchases the fertilizer at the random price, otherwise they do not purchase. This allows us to estimate returns by comparing output or profits of those who do and do not receive the fertilizer. A treatment group receives a cash transfer of 200,000 UGX shortly prior to WTP elicitation (the control group receive a 5,000 UGX consolation prize).

We run the study in two six-month seasons, beginning January 2017 and January 2018 respectively.
Experimental Design Details
Not available
Randomization Method
Assignment to receive the 200,000 UGX cash transfer is randomly assigned by computer, stratified (as closely as possible) by village.
Assignment to fertilizer depends on bidding in the Becker-DeGroot-Marschak WTP elicitation. Respondents receive the fertilizer if their bid exceeds their individual price. Prices are pre-assigned randomly by computer at the individual level, stratified by lottery assignment and (as closely as possible) by village, from a distribution that assigns 41% of the mass each to prices of 0 or 200,000 UGX and the remaining 18% uniformly across the range {20,000, 40,000, …, 180,000}.
Randomization Unit
The unit of randomization is the household
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
1232 households in 154 villages. Of which 412 households in 51 villages in Season 1, and 820 households in 103 villages in Season 2.
Sample size: planned number of observations
1232 households, of which 412 in season 1 and 820 in season 2.
Sample size (or number of clusters) by treatment arms
769 Individuals were assigned to the “consolation” cash transfer (5,000 UGX) and 463 were assigned to the full cash transfer (200,000 UGX). Before Willingness To Pay elicitation survey, individual price assignment was {(501,0); (25, 20,000); (25, 40,000); (25, 60,000); (24, 80,000); (24, 100,000); (24,120,000); (25, 140,000); (24, 160,000); (23, 180,000); (512, 200,000)}, where for each pair, the first number represents the number of individuals assigned to one of the prices, and the second number is the pre-assigned individual price. At the end of the Willingness To Pay elicitation survey, 592 Individuals purchased the fertilizer and 636 did not.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Mildmay Uganda Research Ethics Committee
IRB Approval Date
2017-01-24
IRB Approval Number
0412-2016