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Social Networks and the Decision to Insure in China
Last registered on November 06, 2016

Pre-Trial

Trial Information
General Information
Title
Social Networks and the Decision to Insure in China
RCT ID
AEARCTR-0001747
Initial registration date
November 06, 2016
Last updated
November 06, 2016 10:43 AM EST
Location(s)
Region
Primary Investigator
Affiliation
University of Michigan
Other Primary Investigator(s)
PI Affiliation
University of California, Berkeley
PI Affiliation
University of California, Berkeley
Additional Trial Information
Status
Completed
Start date
2010-01-01
End date
2013-12-31
Secondary IDs
Abstract
Using data from a randomized experiment in rural China, we study the influence of social networks on weather insurance adoption and the mechanisms through which they operate. To quantify network effects, the experiment provides intensive information sessions about the product to a random subset of farmers. For untreated farmers, the effect of having an additional treated friend on take-up is equivalent to granting a 13 percent reduction in the insurance premium. By varying the information available about peers' decisions and randomizing default options, we show that the network effect is driven by the diffusion of insurance knowledge rather than purchase decisions.
External Link(s)
Registration Citation
Citation
Cai, Jing, Alain de Janvry and Elisabeth Sadoulet. 2016. "Social Networks and the Decision to Insure in China." AEA RCT Registry. November 06. https://doi.org/10.1257/rct.1747-1.0
Former Citation
Cai, Jing, Alain de Janvry and Elisabeth Sadoulet. 2016. "Social Networks and the Decision to Insure in China." AEA RCT Registry. November 06. https://www.socialscienceregistry.org/trials/1747/history/11663
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Experimental Details
Interventions
Intervention(s)
The intervention was an informational session about weather insurance. The intervention included different specifications implemented at the village level (price and default variation) and within the village level through rounds (time and information variation).

Village I: All households face the same price for insurance.
Village II: Households face 1 of 7 different price options for purchasing insurance.

Within Village I:
Village I - Buy default: Households must opt-out of purchasing insurance.
Village I - No buy default: Households must opt-in to purchasing insurance.

At the village level, for both Villages I and II, information sessions took place in two rounds with two types of sessions being offered simultaneously in each round. In the second round of informational sessions, three types of further information were offered.

Round 1:
Simple1: A 20 minute informational session with information provided solely on the insurance contract. This was followed by the option to take-up insurance.
Intensive1: A 45 minute informational session with information provided on the insurance contract, along with an explanation on how insurance works and its benefits. This was followed by the option to take-up insurance.

Round 2 sessions were the same as Round 1 sessions, with a variety of additional information included.
Simple2/Intensive2 - No Info: No additional information was offered.
Simple2/Intensive2 - Overall: Participants were told how many participants had attended the first round of sessions, and how many households had taken up the insurance. They were then offered the option to take-up the insurance.
Simple2/Intensive2 - Individual: Participants were provided with a nominal list of all individuals who had taken up the insurance in the first round. They were then offered the option to take-up the insurance.
Intervention Start Date
2010-01-01
Intervention End Date
2010-12-31
Primary Outcomes
Primary Outcomes (end points)
Information spillovers, Insurance take-up, Knowledge about insurance, Knowledge of others' purchase decisions
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We designed a randomized experiment based on the introduction of a new weather insurance policy for rice farmers offered by the People's Insurance Company of China (PICC), China’s largest insurance provider. Our experimental design allows us to not only identify the causal effect of social networks on product adoption, but also test for the role of various channels through which social networks operate. Furthermore, using a household level price randomization, we calculate the price equivalence of the social network effect on insurance take-up. Finally, taking advantage of the substantial variation in network structure across households, we measure the effect of network characteristics on the strength of social network effects.
Experimental Design Details
Randomization Method
STATA
Randomization Unit
Village
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
185 villages
Sample size: planned number of observations
5,335 households
Sample size (or number of clusters) by treatment arms
Village I - Buy default: 85 villages
Village I - No buy default: 88 villages
Village II: 12 villages

Simple1: 1,079 households
Intensive1: 1,096 households
Simple2 - No Info: 657 households
Intensive2 - No Info: 660 households
Simple2 - Overall: 355 households
Intensive2 - Overall: 350 households
Simple2 - Individual: 362 households
Intensive2 - Individual: 343 households
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Study has received IRB approval. Details not available.
IRB Approval Date
Details not available
IRB Approval Number
Details not available
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Yes
Data Collection Completion Date
Final Sample Size: Number of Clusters (Unit of Randomization)
185 villages
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
All rice producing households in each village were invited to attend one of the information sessions, and about 90% did attend (5,335 households).
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication
Data Publication
Is public data available?
Yes
Program Files
Program Files
Reports and Papers
Preliminary Reports
Relevant Papers
Abstract
Social Networks and the Decision to Insure
Citation
Cai, Jing, Alain De Janvry and Elisabeth Sadoulet. 2015. "Social Networks and the Decision to Insure." American Economic Journal: Applied Economics, 7(2): 81-108.