The Last Mile of Agricultural Service System: Irrigation Service

Last registered on August 24, 2023
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Pre-Trial

Trial Information

General Information

Title
The Last Mile of Agricultural Service System: Irrigation Service
RCT ID
AEARCTR-0011944
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, 4:57 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

Name
Lijuan Zhang
Affiliation
Chinese Academy of Social Sciences
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2023-08-26
End date
2024-09-01
Keywords
Agriculture, Behavior, Environment & Energy, Labor, Welfare
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study aims to use technology information provision and market information provision as two orthogonal interventions in a randomized controlled trial (RCT) in Hebei Province of China, covering approximately 1500 farmers, to investigate whether the technology information or market information are barriers of the development of irrigation service market.
External Link(s)

Registration Citation

Citation
Zhang, Lijuan. 2023. "The Last Mile of Agricultural Service System: Irrigation Service." AEA RCT Registry. August 24. https://doi.org/10.1257/rct.11944-1.0
Sponsors & Partners
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 and market information will increase farmers' willingness to pay (WTP) for adopting irrigation service.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Technology information and market information 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”: 82 villages control,66 villages receive technology information. In these 66 villages, 33 villages receive market information. In those 82 villages not receiving technology information, 41 villages receive market information.
Individual randomization for “professional farm survey”:200 professional farmers control, 160 professional farmers receive information about Reel lrrigation Machine. In these 160 professional farmers, 80 farmers receive market information. In those 200 professional farmers, a half receive market information.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
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
2023-07-31
IRB Approval Number
FEEL230706
Analysis Plan