Pricing and Allocative Efficiency of New Agricultural Technologies: Evidence from Bangladesh

Last registered on April 29, 2022

Pre-Trial

Trial Information

General Information

Title
Pricing and Allocative Efficiency of New Agricultural Technologies: Evidence from Bangladesh
RCT ID
AEARCTR-0008784
Initial registration date
January 07, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
January 10, 2022, 9:38 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
April 29, 2022, 3:56 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

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Primary Investigator

Affiliation
Tufts University

Other Primary Investigator(s)

PI Affiliation
CIMMYT

Additional Trial Information

Status
On going
Start date
2021-10-07
End date
2023-06-01
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Modern agricultural technologies can increase productivity and enhance resilience to climate shocks. However, the low adoption of new technologies in developing countries is puzzling. The efficiency of subsidies to boost technology adoption is debatable. On the one hand, subsidization of agricultural technologies could be justified in the presence of externalities (e.g., environmental or learning externalities) or information market failures. On the other hand, charging full market prices could improve targeting through a screening effect, especially if farmers with higher willingness-to-pay have higher returns to adoption.

This research study aims to analyze the allocative efficiency of higher prices by focusing on a new agricultural technology – improved wheat variety – that has been recently introduced in response to emerging crop diseases in Bangladesh. Using a randomized controlled trial (RCT), we analyze the extent to which higher prices of a new technology could lead to efficient sorting. That is, whether charging higher prices causes farmers with lower actual returns to choose not to adopt. One innovation of the study is that we use a two-step experiment to estimate whether actual returns are lower among farmers that are unwilling to pay higher prices.
External Link(s)

Registration Citation

Citation
Mahmoud, Mai and Khondoker A. Mottaleb. 2022. "Pricing and Allocative Efficiency of New Agricultural Technologies: Evidence from Bangladesh." AEA RCT Registry. April 29. https://doi.org/10.1257/rct.8784
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2021-11-01
Intervention End Date
2021-11-30

Primary Outcomes

Primary Outcomes (end points)
yield (agricultural productivity), agricultural profits, take-up (demand), cropping pattern
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
plot management and input allocation
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The total sample size is 5,500 farmers from 220 villages that span seven districts with different degrees of exposure to a recently emerged crop disease called wheat blast. Sampled villages are split into three sub-samples of control villages, free distribution villages, and two-stage experiment villages. Farmers in the control villages receive no intervention neither at stage one nor at stage two of the experiment. In the free-distribution villages, a random sample of farmers will receive the new, blast-resistant, wheat seed for free at stage one. In the two-stage experiment villages, treatment randomization takes two stages. First, villages are randomized to different price levels for the new seed. Then, the same villages are randomized into stage-two treatment and stage-two control.
Experimental Design Details
Not available
Randomization Method
Random number generator
Randomization Unit
Villages
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
220 villages
Sample size: planned number of observations
5,500 farmers
Sample size (or number of clusters) by treatment arms
40 villages control, 25 villages free seed distribution, 155 villages two-step experiment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Tufts University
IRB Approval Date
2021-11-01
IRB Approval Number
1978
Analysis Plan

Analysis Plan Documents

Pre-analysis plan

MD5: 06e3ecadf7f1587fe27d38d50dadcbd1

SHA1: 96add50916e6aa21cce00ac0812d183742c114a4

Uploaded At: April 29, 2022