Social Networks, Reputation and Commitment: Evidence from a Savings Monitors Experiment / Emily Breza, Arun G. Chandrasekhar.
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- D14 - Household Saving • Personal Finance
- D83 - Search • Learning • Information and Knowledge • Communication • Belief • Unawareness
- L14 - Transactional Relationships • Contracts and Reputation • Networks
- O16 - Financial Markets • Saving and Capital Investment • Corporate Finance and Governance
- Z13 - Economic Sociology • Economic Anthropology • Language • Social and Economic Stratification
- Hardcopy version available to institutional subscribers
Item type | Home library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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Working Paper | Biblioteca Digital | Colección NBER | nber w21169 (Browse shelf(Opens below)) | Not For Loan |
May 2015.
We conduct a field experiment with 1,300 participants in India to measure whether individuals save more when information about their savings is regularly shared with another member of their village (a "monitor"). We focus on whether the monitor's effectiveness depends on her social network position, as central monitors may be better able to disseminate information, and more proximate monitors may be more likely to pass information to individuals who interact with the saver most frequently.
In 30 villages, we randomly assign monitors to a subset of savers. An average monitor increases total savings by 35%. Increasing the monitor's network centrality by one standard deviation increases savings by 14%, and increasing proximity from social distance three to two increases savings by 16%.
Supporting the information-based mechanism, 63% of monitors report telling others about the saver's progress. Further, over a year later, villagers are more likely to know if the saver exceeded her goal and to think that the saver is responsible if the saver was randomly assigned to a more central monitor. We also provide evidence that the increase in savings persists over a year after the intervention's end, and that monitored savers can better respond to shocks.
In the remaining 30 villages, savers choose their own monitors. We find that savers choose monitors who are both proximate and central in the network. Finally, we find evidence of spillovers from monitored savers onto their non-monitored friends, suggesting another channel through which social networks influence savings decisions.
Hardcopy version available to institutional subscribers
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