The urban poor in developing countries are tired: noise, heat, pain, and physical discomfort all interfere with their sleep. Low-income adults in Chennai, India, sleep on average just over five hours a night (based on our pilot studies). How does insufficient sleep affect how these individuals think, work, and make decisions? Can simple and scalable interventions improve sleep among the poor in a cost-effective way? We investigate these questions in a field experiment in Chennai. The randomized controlled trial aims to: (i) evaluate three interventions (devices to improve the home sleep environment; incentives to sleep more; naps at work) to improve sleep among the urban poor; (ii) estimate the causal impact of improved sleep on cognitive function, health, and economic outcomes.
This dataset is open access.
When using this dataset, please cite the following:
Zhang GQ, Cui L, Mueller R, Tao S, Kim M, Rueschman M, Mariani S, Mobley D, Redline S. The National Sleep Research Resource: towards a sleep data commons. J Am Med Inform Assoc. 2018 Oct 1;25(10):1351-1358. doi: 10.1093/jamia/ocy064. PMID: 29860441; PMCID: PMC6188513.
Bessone P, Rao G, Schilbach F, Schofield H, Toma M. The Economic Consequences of Increasing Sleep Among the Urban Poor. Q J Econ. 2021 Apr 8;136(3):1887-1941. doi: 10.1093/qje/qjab013. PMID: 34220361; PMCID: PMC8242594.
Please include the following text in the Acknowledgements:
The National Sleep Research Resource was supported by the U.S. National Institutes of Health, National Heart Lung and Blood Institute (R24 HL114473, 75N92019R002).
This package contains replication data for: "The Economic Consequences of Increasing Sleep Among the Urban Poor." It contains analysis data from an RCT conducted in Chennai, India, between 2017 and 2019. It contains cleaned analysis data from seven sources: i) a baseline survey, ii) daily Actigraph sleep data, iii) daily surveys of participants, iv) daily lab experiments, v) daily data collected from a work task, vi) a priors survey of experts, and vii) a larger survey of a representative sample of Chennai. The scripts, produced in Stata and R, contain code to replicate the tables and figures in the paper and its appendix. For further details on the data or how to run the code, please see the readme file.