Teaching Climate-Smart Agricultural Practices through Demonstration in Punjab, Pakistan

Last registered on November 21, 2025

Pre-Trial

Trial Information

General Information

Title
Teaching Climate-Smart Agricultural Practices through Demonstration in Punjab, Pakistan
RCT ID
AEARCTR-0017220
Initial registration date
November 17, 2025

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
November 21, 2025, 7:59 AM EST

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

Locations

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Primary Investigator

Affiliation
Lahore School of Economics

Other Primary Investigator(s)

PI Affiliation
Lahore School of Economics
PI Affiliation
Urban Unit, Government of Punjab, Pakistan
PI Affiliation

Additional Trial Information

Status
In development
Start date
2025-11-17
End date
2026-11-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The agricultural sector plays a crucial role in Pakistan's economy, contributing significantly to the country's GDP. However, it faces several challenges, including low productivity, outdated technology, and slow growth. Additionally, climate change and unpredictable weather patterns exacerbate these issues. While there is substantial evidence that adopting Climate Smart Agriculture (CSA) can boost farm income, particularly in developing countries, the implementation of CSA practices in Pakistan has been minimal. This project aims to implement a CSA package to improve agricultural productivity and income for small farmers in Pakistan. The focus will be on Bhera, a region in the province of Punjab, which experiences lower agricultural productivity compared to the provincial average. The CSA package for one pilot farm in this pilot intervention will include practices such as crop diversification, balanced fertilizer use, water conservation techniques, and the adoption of climate-resilient crop varieties. Additionally, advanced technologies like drone technology and integrated pest management will be incorporated. The project will evaluate the impact of these CSA practices on farm productivity, income, and sustainability throughout a typical cropping year. It will also explore whether informational, financial, or technical constraints are limiting the adoption of sustainable farming practices among small farmers in Pakistan. The project will include an informational intervention with nearby farmers in which information about CSA practices will be shared with farmers and these farmers will be surveyed to determine their knowledge and adoption of CSA practices before and after the intervention on the pilot farm. The results will be shared with policymakers and can be extended to small, rural farmers across Pakistan.
External Link(s)

Registration Citation

Citation
Chaudhry, Azam et al. 2025. "Teaching Climate-Smart Agricultural Practices through Demonstration in Punjab, Pakistan." AEA RCT Registry. November 21. https://doi.org/10.1257/rct.17220-1.0
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Experimental Details

Interventions

Intervention(s)
Small farmers will either i) receive an invitation (T1) or ii) receive an invitation and nudge to visit a demonstration farm currently implementing a variety of climate-smart agricultural practices.

Intervention Start Date
2026-02-01
Intervention End Date
2026-05-01

Primary Outcomes

Primary Outcomes (end points)
CSA Knowledge Index (Index of 15 practices)
Probability of implementing any CSA practice in a future planting season
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Based on a listing of farmers, we developed strata based on each farm's distance quartile from the demonstration farm and whether each farmer was interested in learning more about climate-smart agricultural practices.



Experimental Design Details
Not available
Randomization Method
Randomization done by computer (Python)
Randomization Unit
Unit=individual farm
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
250 farms
8 strata: quartile of distance from demo farm x interest in CSA
Sample size: planned number of observations
250 farms
Sample size (or number of clusters) by treatment arms
The farmers' assignment was as follows: 35 are assigned to T1 (invitation), 65 to T2 (invitation + nudge), and 150 to the control group (T0).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Review Committee, Lahore School of Economics
IRB Approval Date
2025-03-27
IRB Approval Number
n/a