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The Impact of Uncertainty on Take-Up and Subsequent Investment in New Technologies Among Farmers in Zambia
Last registered on December 11, 2016

Pre-Trial

Trial Information
General Information
Title
The Impact of Uncertainty on Take-Up and Subsequent Investment in New Technologies Among Farmers in Zambia
RCT ID
AEARCTR-0001659
Initial registration date
December 11, 2016
Last updated
December 11, 2016 9:43 PM EST
Location(s)
Primary Investigator
Affiliation
UC Santa Barbara
Other Primary Investigator(s)
PI Affiliation
NERA Consulting
PI Affiliation
Shared Value Africa
PI Affiliation
University of California Santa Barbara
PI Affiliation
University of California Santa Barbara; NBER
Additional Trial Information
Status
Completed
Start date
2011-11-01
End date
2015-06-23
Secondary IDs
Abstract
Technology adoption often requires investments over time. As new information about the costs and benefits of investment is realized, agents may prefer to abandon a technology that appeared profitable at the time of take-up. This re-optimization can reduce the cost-effectiveness of adoption subsidies. We use a field experiment with two stages of randomization to generate exogenous variation in the payoffs associated with take-up and subsequent investment in a new technology: a tree species that provides private fertilizer benefits to adopting farmers. Our empirical results show high rates of abandoning the technology, even after paying a positive price to take it up. The experimental variation offers a novel source of identification for a structural model of intertemporal decision making under uncertainty. Estimation results indicate that the farmers experience idiosyncratic shocks to net payoffs after take-up, which increase take-up but lower average per farmer tree survival. We simulate counterfactual outcomes under different levels of uncertainty and observe that farmers with high returns are able to self-select at take-up only when the level of uncertainty is relatively low. Thus, uncertainty provides an additional explanation for why many subsidized technologies may not be utilized even when take-up is high.
External Link(s)
Registration Citation
Citation
Bell, Samuel et al. 2016. "The Impact of Uncertainty on Take-Up and Subsequent Investment in New Technologies Among Farmers in Zambia." AEA RCT Registry. December 11. https://doi.org/10.1257/rct.1659-1.0.
Former Citation
Bell, Samuel et al. 2016. "The Impact of Uncertainty on Take-Up and Subsequent Investment in New Technologies Among Farmers in Zambia." AEA RCT Registry. December 11. http://www.socialscienceregistry.org/trials/1659/history/12364.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2011-11-01
Intervention End Date
2012-12-31
Primary Outcomes
Primary Outcomes (end points)
Take-up (measured as purchase of the seedlings);
Follow-through (measured as keeping 35 or more trees alive);
Tree survival greater than 0;
No tree survival
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The researchers conducted a two-period randomized field experiment. In the first stage, groups of 10-15 Zambian farmers were offered a package of tree seedlings which provide private fertilization benefits 7-10 years after planting. The groups are randomly assigned to receive 1 of 4 subsidy amounts to help purchase the seedlings and to introduce exogenous variation in payoff at the take-up decision. The subsidy amounts are 0 ZMK (no subsidy), 4000 ZMK, 8000 ZMK, and 12000 ZMK (fully subsidized).

In the second stage of the experiment, individual farmers drew lots to receive a reward conditional on the survival of at least 35 trees one year after purchase of the seedlings. The rewards ranged from 0 ZMK (no reward) to 150,000 ZMK in increments of 1000 ZMK. This introduced exogenous variation in payoff at the follow-through decision. Data was collected from a baseline survey, an endline survey, and from a mid-experiment survey from a subsample of the farmers.

The multi-period experimental treatment of statistically independent samples offered an alternative to panel data, allowed the researchers to identify a structural model of intertemporal decisions that can distinguish between static and dynamic explanations for the outcomes.
Experimental Design Details
Randomization Method
For the first stage of randomization, groups of 10-15 farmers are randomly assigned to receive 1 of 4 subsidies for seedling purchase: No subsidy, 4000 ZMK, 8000 ZMK, or 12,000 ZMK.
For the second stage, individuals drew lots from a bucket for a reward ranging from no reward to 150,000 ZMK, contingent on keeping a minimum number of trees alive for one year
Randomization Unit
First stage of randomization: groups of farmers
Second stage of randomization: individual farmers
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
125 farmer groups
Sample size: planned number of observations
1314 farmers
Sample size (or number of clusters) by treatment arms
Subsidy treatment: 1092 farmers, randomly assigned to receive 1 of 4 subsidies: 0 ZMK, 4000 ZMK, 8000 ZMK, 12000 ZMK
Reward treatment: 1092 farmers, randomly assigned to receive a reward ranging from 0 ZMK to 150,000 ZMK contingent on keeping at least 35 trees alive after one year
Surprise treatment: 690 farmers, randomly selected to be told of the reward after the take-up decision
Monitoring treatment: 173 farmers, randomly selected to a mid-year survey detailing tree-care activities
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Zambia ERES
IRB Approval Date
2011-10-13
IRB Approval Number
Ref. 2011-July-005
IRB Name
Tufts University
IRB Approval Date
2011-07-29
IRB Approval Number
1107031
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
Yes
Intervention Completion Date
December 31, 2012, 12:00 AM +00:00
Is data collection complete?
Yes
Data Collection Completion Date
December 31, 2012, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
125 farmer groups
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
1314 farmers
Final Sample Size (or Number of Clusters) by Treatment Arms
Subsidy treatment: 1092 farmers, randomly assigned to receive 1 of 4 subsidies: 0 ZMK, 4000 ZMK, 8000 ZMK, 12000 ZMK Reward treatment: 1092 farmers, randomly assigned to receive a reward ranging from 0 ZMK to 150,000 ZMK contingent on keeping at least 35 trees alive after one year Surprise treatment: 690 farmers, randomly selected to be told of the reward after the take-up decision Monitoring treatment: 173 farmers, randomly selected to a mid-year survey detailing tree-care activities
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
Abstract
Technology adoption often requires investments over time. As new information about the costs and benefits of investment is realized, agents may prefer to abandon a technology that appeared profitable at the time of take-up. This re-optimization can reduce the cost-effectiveness of adoption subsidies. We use a field experiment with two stages of randomization to generate exogenous variation in the payoffs associated with take-up and subsequent investment in a new technology: a tree species that provides private fertilizer benefits to adopting farmers. Our empirical results show high rates of abandoning the technology, even after paying a positive price to take it up. The experimental variation offers a novel source of identification for a structural model of intertemporal decision making under uncertainty. Estimation results indicate that the farmers experience idiosyncratic shocks to net payoffs after take-up, which increase take-up but lower average per farmer tree survival. We simulate counterfactual outcomes under different levels of uncertainty and observe that farmers with high returns are able to self-select at take-up only when the level of uncertainty is relatively low. Thus, uncertainty provides an additional explanation for why many subsidized technologies may not be utilized even when take-up is high.
Citation
Jack, B. Kelsey, Paulina Oliva, Christopher Severen, Elizabeth Walker, and Samuel Bell. "Technology Adoption Under Uncertainty: Take-Up and Subsequent Investment in Zambia." NBER Working Paper No. 21414, July 2015
REPORTS & OTHER MATERIALS