Technology Upgrading in Agricultural Export Supply Chains: A Field Experiment in Vietnam
Last registered on August 21, 2018

Pre-Trial

Trial Information
General Information
Title
Technology Upgrading in Agricultural Export Supply Chains: A Field Experiment in Vietnam
RCT ID
AEARCTR-0003237
Initial registration date
August 15, 2018
Last updated
August 21, 2018 12:30 AM EDT
Location(s)

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Primary Investigator
Affiliation
University of Hong Kong
Other Primary Investigator(s)
Additional Trial Information
Status
On going
Start date
2017-08-01
End date
2020-08-31
Secondary IDs
Abstract
This proposed project studies technology upgrading in an export supply chain of the dragon fruit industry of Vietnam. Despite demand for high-quality fruits from overseas markets, the supply of dragon fruits that meet export standards is surprisingly low. Observations on agricultural practices show persistent use of low technology along the supply chain. I hypothesize that a key reason for the lack of supply of export-quality dragon fruits is that farmers and intermediaries lack the information and technological resources that are necessary to produce and trade high-quality agricultural products. I plan to test this hypothesis through a randomized control trial that generates exogenous variation in access to information and training on an export-oriented agricultural technology for dragon fruit farmers and intermediaries in Vietnam.
External Link(s)
Registration Citation
Citation
Park, Sangyoon. 2018. "Technology Upgrading in Agricultural Export Supply Chains: A Field Experiment in Vietnam." AEA RCT Registry. August 21. https://www.socialscienceregistry.org/trials/3237/history/33296
Experimental Details
Interventions
Intervention(s)
The intervention will offer farmers and intermediaries the opportunity to receive information and training on applying new export-oriented technology for growing and processing dragon fruits. I use this variation to understand whether and how technology upgrading in the supply chain occurs as a response to the intervention.
Intervention Start Date
2018-09-01
Intervention End Date
2019-01-31
Primary Outcomes
Primary Outcomes (end points)
Primary outcome: Agricultural technology as measured by percentage of practices that meet GAP standards; Export volume; Profits
Primary Outcomes (explanation)
I will measure each farmer’s or intermediary’s technology as the frequency of practices that meet or exceed the standards fully recognized by GLOBAL GAP. The advantages of using this method are twofold. One, it is practical from the farmer’s and intermediary’s points of view since GLOBAL GAP certification is the primary requirement for entering most export markets in the world (UNCTD, 2007). Two, GLOBAL GAP provides a list of standardized practices that can be verified by outsiders, such as our survey team. Under this metric, technology level upgrading refers to an increase in the number of practices that satisfy the standards and practices approved by GLOBAL GAP. Profits will be constructed using revenue and costs collected through surveys.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
I will conduct a randomized control trial (RCT) on dragon fruit farmers and intermediaries to examine the effect of information and technology transfers on the adoption of export-oriented agricultural technologies and trading practices. Specifically, I will randomly provide a subset of farmers and intermediaries with the opportunity to participate in information and training sessions on the farming and trading of export-quality dragon fruits.
Experimental Design Details
Not available
Randomization Method
Using a computer in my office I will implement stratified random sampling based on data collected from a baseline survey.
Randomization Unit
Sub-commune level
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
100 villages
Sample size: planned number of observations
800 farmers and 300 intermediaries
Sample size (or number of clusters) by treatment arms
75 villages (approximately 600 farmers and 240 intermediaries) to one of three treatment groups, 25 villages (approximately 200 farmers and 60 intermediaries) to control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Holding the sample size of each treatment group at 150 farmers and 70 intermediaries and significance level at 0.05, the statistical power for detecting a 40 percentage point increase in agricultural technology is about 0.97 with farmers and 0.76 with intermediaries, respectively.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
University of Hong Kong
IRB Approval Date
2017-07-19
IRB Approval Number
EA1703013