Encouraging Farmers to Use Organic Fertilizers: Evidence from Field Experiment among Tea Farmers.

Last registered on June 27, 2018

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Pre-Trial

Trial Information

General Information

Title

Encouraging Farmers to Use Organic Fertilizers: Evidence from Field Experiment among Tea Farmers.

RCT ID

AEARCTR-0003084

Initial registration date

June 18, 2018

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

June 20, 2018, 1:06 PM EDT

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

Last updated

June 27, 2018, 6:42 AM EDT

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

Locations

Country

Viet Nam

Region

Thai Nguyen province

Primary Investigator

Name

THU VU

Affiliation

HIROSHIMA UNIVERSITY-idec

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

KAWATA KEISUKE

PI Affiliation

Institute of Social Science, the University of Tokyo

Contact Investigator

PI Name

GOTO DAISAKU

PI Affiliation

Hiroshima University

Contact Investigator

PI Name

DUC TRAN

PI Affiliation

Hiroshima University

Contact Investigator

Additional Trial Information

Status

In development

Start date

2018-07-02

End date

2018-07-31

Keywords

Agriculture

Additional Keywords

organic fertilizer, tea farmers, technology adoption

JEL code(s)

Secondary IDs

Abstract

Agricultural innovation is considered as an important factor in the development of agricultural activities. Fertilizer plays a critical role to improve agricultural productivity. However, the overuse of chemical fertilizer causes groundwater contamination, soil acidification and increase in greenhouse gases. Bio-compost is a type of organic fertilizer using microorganisms to break down organic and inorganic substances, which enriches soil quality and reduces environmental pollution. Nevertheless, the usage of organic fertilizer in general and the usage of bio-compost, in particular, are still low. This study aims to evaluate the impact of subsidy and information on the usage of bio-compost among tea farmers.

External Link(s)

Registration Citation

Citation

DAISAKU, GOTO et al. 2018. "Encouraging Farmers to Use Organic Fertilizers: Evidence from Field Experiment among Tea Farmers. ." AEA RCT Registry. June 27. https://doi.org/10.1257/rct.3084-2.0

Former Citation

DAISAKU, GOTO et al. 2018. "Encouraging Farmers to Use Organic Fertilizers: Evidence from Field Experiment among Tea Farmers. ." AEA RCT Registry. June 27. https://www.socialscienceregistry.org/trials/3084/history/31239

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Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2018-07-02

Intervention End Date

2018-07-31

Primary Outcomes

Primary Outcomes (end points)

Take-up decision: whether farmers decide to purchase bio-compost or not;
Usage of bio-compost (amount): quantity of bio-compost used

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Usage of bio-compost (area): the ratio of the area in which bio-compost is applied;
Usage of chemical fertilizer: quantity of chemical fertilizer used

Secondary Outcomes (explanation)

Experimental Design

Target farmer households in each village will be randomly divided into 3 groups: comparison group, treatment group 1 and treatment group 2. Treatment group 1 will receive the subsidy while treatment group 2 will receive information. In the follow-up survey, we will collect the data about actual usage of bio-compost.

Experimental Design Details

We evaluate the impact of subsidy scheme and information provision on the take-up decision and the usage of bio-compost. The reference population of the experiment is made by those tea farmer households in Thai Nguyen province, a largest green tea area in Vietnam. Target farmer households in each village will be randomly divided into 3 groups: comparison group, treatment group 1 and treatment group 2.
Households in comparison group will receive free shipping (up to 200kg) and general information about bio-compost. General information is provided through 2-minute video.
The household in treatment group 1 will receive the same general information and free shipping to households in the comparison group. Moreover, they will get 50% subsidy in price (up to 200kg).
The household in treatment group 2 will receive free shipping (up to 200kg) and information treatment (a 5-minute video). Information treatment has general information about bio-compost and information about successful farmers who used bio-compost. The former is as same as the information provided to households in comparison group and treatment group 1. The latter is the additional information.
Investigators will visit each targeted household and conduct the lottery. After assigning the treatment status, the household has to make the decision to purchase bio-compost or not. If they agree to buy, a contract will be given to them. The bio-compost will be delivered to village center within 1-3 days. On delivery date, the household will receive bio-compost after showing the contract and making full payment. In order to eliminate information leaking, we will complete the field experiment in each village within a day.
In the follow-up survey, we will collect the data about actual usage of bio-compost in each household. From that, we can evaluate the persistent impact of our treatments.

Randomization Method

Households are randomly selected from lists provided by village leaders. Subsequently, treatment assignment is done in each respondent's house by lottery.

Randomization Unit

Household

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

1134 households

Sample size: planned number of observations

1134 households

Sample size (or number of clusters) by treatment arms

378 households in the comparison group
378 household in the treatment group 1
378 household in the treatment group 2

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

According to previous studies ( Duflo et al., 2011; Carter et al., 2014), we set up standard deviation of 0.49 and expected treatment effect of 0.1. We would have 80% power.

Supporting Documents and Materials

IRB