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Inferring Welfare Maximizing Treatment Assignment under Budget Constraints

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  • Debopam Bhattacharya
  • Pascaline Dupas

Abstract

This paper concerns the problem of allocating a binary treatment among a target population based on observed covariates. The goal is to (i) maximize the mean social welfare arising from an eventual outcome distribution, when a budget constraint limits what fraction of the population can be treated and (ii) to infer the dual value, i.e. the minimum resources needed to attain a specific level of mean welfare via efficient treatment assignment. We consider a treatment allocation procedure based on sample data from randomized treatment assignment and derive asymptotic frequentist confidence interval for the welfare generated from it. We propose choosing the conditioning covariates through cross-validation. The methodology is applied to the efficient provision of anti-malaria bed net subsidies, using data from a randomized experiment conducted in Western Kenya. We find that subsidy allocation based on wealth, presence of children and possession of bank account can lead to a rise in subsidy use by about 9 percentage points compared to allocation based on wealth only, and by 17 percentage points compared to a purely random allocation.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 14447.

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Date of creation: Oct 2008
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Publication status: published as Bhattacharya, Debopam & Dupas, Pascaline, 2012. "Inferring welfare maximizing treatment assignment under budget constraints," Journal of Econometrics, Elsevier, vol. 167(1), pages 168-196.
Handle: RePEc:nbr:nberwo:14447

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Citations

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Cited by:
  1. Debopam Bhattacharya & Shin Kanaya & Margaret Stevens, 2012. "Are University Admissions Academically Fair?," Economics Series Working Papers 608, University of Oxford, Department of Economics.
  2. Jonas Hjort, 2013. "Ethnic Divisions and Production in Firms," CESifo Working Paper Series 4449, CESifo Group Munich.
  3. John List & Imran Rasul, 2010. "Field experiments in labor economics," Artefactual Field Experiments 00092, The Field Experiments Website.
  4. Bhattacharya, Debopam, 2013. "Evaluating treatment protocols using data combination," Journal of Econometrics, Elsevier, vol. 173(2), pages 160-174.
  5. Debopam Bhattacharya & Pascaline Dupas & Shin Kanaya, 2013. "Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets," CREATES Research Papers 2013-06, School of Economics and Management, University of Aarhus.
  6. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers 1927R, Cowles Foundation for Research in Economics, Yale University, revised Apr 2014.
  7. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers 1927, Cowles Foundation for Research in Economics, Yale University.
  8. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2014. "Can Variation in Subgroups' Average Treatment Effects Explain Treatment Effect Heterogeneity? Evidence from a Social Experiment," NBER Working Papers 20142, National Bureau of Economic Research, Inc.

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