Highly Efficient Water-Saving Irrigation Technology Adoption

Last registered on August 24, 2023

Pre-Trial

Trial Information

General Information

Title
Highly Efficient Water-Saving Irrigation Technology Adoption
RCT ID
AEARCTR-0011935
Initial registration date
August 17, 2023

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
August 24, 2023, 4:58 AM EDT

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
Peking University

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2023-08-26
End date
2024-09-01
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This project aims to use education on technology and market information as a treatment in a randomized controlled trial (RCT) in Hebei Province of China, covering approximately 1500 farm households. The goal is to investigate how technology and market information affect the adoption of HEWIT, and to examine the impacts of these advanced agricultural irrigation technologies on agricultural performance, including operational decisions and farm outputs.
External Link(s)

Registration Citation

Citation
Chao, Wei. 2023. "Highly Efficient Water-Saving Irrigation Technology Adoption." AEA RCT Registry. August 24. https://doi.org/10.1257/rct.11935-1.0
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-08-26
Intervention End Date
2023-09-04

Primary Outcomes

Primary Outcomes (end points)
Education on technology information will increase farmers' willingness to pay (WTP) for adopting the technology.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
There are two focused HEWITs, including Mobile Sprinkler Irrigation and Reel Irrigation Machine. Technology information and market information on them will be our information treatments.
Experimental Design Details
Not available
Randomization Method
randomization done in office by a computer
Randomization Unit
Group level randomization for some treatment, and individual randomization for some treatments.
The RCT will be nested in a large-scale field household survey conducted in Hebei Province in China, designed to evaluate the policy impact of Chinese government’s police intervention for groundwater overexploitation control.
Two types of surveys will be conducted. The first type is “regular farm household survey”, which will be done at villages. 944 households in 148 villages will be surveyed. The second type is “professional farm survey”, which aims to interview the farmer with farm size larger than 50 mu. Around 500 professional large farmers will be surveyed. Randomization will be done in both of the surveys.
Village level randomization for “regular farm household survey”, and individual randomization for “professional farm survey”.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
148 villages (including 944 farmers) and 518 professional large farmers
Sample size: planned number of observations
1462 farmers
Sample size (or number of clusters) by treatment arms
Village level randomization for “regular farm household survey”:49 villages control,33 villages receive information about Mobile Sprinkler Irrigation, 33 villages receive information about Reel Irrigation Machine,33 villages receive information about Mobile Sprinkler Irrigation and Reel Irrigation Machine

individual randomization for “professional farm survey”.:173 professional farmers control, 115 professional farmers receive information about Mobile Sprinkler Irrigation ,115 professional farmers receive information about Reel Irrigation Machine,115 professional farmers receive information about Mobile Sprinkler Irrigation and Reel Irrigation Machine.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
Institutional Review Board of Finance and Economics Experimental Laboratory;The Wang Yanan Institute for Studies in Economics Xiamen University
IRB Approval Date
2023-07-30
IRB Approval Number
FEEL230704