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Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets

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  • Debopam Bhattacharya
  • Pascaline Dupas
  • Shin Kanaya

Abstract

Regular use of effective health-products such as insecticide-treated mosquito nets (ITN) by a household benefits its neighbors by (a) reducing chances of infection and (b) raising awareness about product-effectiveness, thereby increasing product-use. Due to their potential social benefits and high purchase price, causing free-riding and sub-optimal private procurement, such products may be subsidized in developing countries through means-testing. Owing to associated spillover effects, cost-benefit analysis of such subsidies requires modelling behavioral responses of both the subsidized household and its neighbors. Using experimental data from Kenya where subsidies were randomized, coupled with GPS-based location information, we show how to estimate aggregate ITN use resulting from means-tested subsidies in the presence of such spatial spillovers. Accounting for spillovers introduces infinite-dimensional estimated regressors corresponding to continuously distributed location coordinates and makes the inference problem novel. We show that even if individual ITN use unambiguously increases with increasing incidence of subsidy in the neighborhood, ignoring spillovers may over- or under-predict overall ITN use resulting from a specific targeting rule, depending on the resulting aggregate incidence of subsidy. Applying our method to the Kenyan data, we find that (i) individual ITN use rises with neighborhood subsidy-rates, (ii) under means-testing, predicted ITN use is a convex increasing function of the subsidy incidence and (iii) ignoring spillovers implies a nearly-linear increasing relationship leading to over-estimation of ITN use at lower and under-estimation at higher subsidy rates.

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  • Debopam Bhattacharya & Pascaline Dupas & Shin Kanaya, 2013. "Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets," NBER Working Papers 18833, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:18833
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    Cited by:

    1. Rokhaya Dieye & Habiba Djebbari & Felipe Barrera-Osorio, 2014. "Accounting for Peer Effects in Treatment Response," AMSE Working Papers 1435, Aix-Marseille School of Economics, France, revised Jul 2014.
    2. Debopam Bhattacharya, 2015. "Nonparametric Welfare Analysis for Discrete Choice," Econometrica, Econometric Society, vol. 83, pages 617-649, March.
    3. Pascaline Dupas & Edward Miguel, 2016. "Impacts and Determinants of Health Levels in Low-Income Countries," NBER Working Papers 22235, National Bureau of Economic Research, Inc.
    4. Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised Dec 2023.
    5. Bhattacharya, D. & Dupas, P. & Kanaya, S., 2018. "Demand and Welfare Analysis in Discrete Choice Models under Social Interactions," Cambridge Working Papers in Economics 1885, Faculty of Economics, University of Cambridge.
    6. Michael P. Leung, 2020. "Treatment and Spillover Effects Under Network Interference," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 368-380, May.

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    More about this item

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • H4 - Public Economics - - Publicly Provided Goods
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development

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