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An analysis of the distributive effects of public policies and their spillovers

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  • Alan Andre Borges da Costa
  • Sergio Pinheiro Firpo

Abstract

The purpose of this work is to define and identify the effects of treatment saturation on the several quantiles of the outcome variable in the presence of treatment spillover. Exploring the variation resulting from two stage randomization, we propose and estimator that depends on the proportion of treated individuals allowing estimate quantile direct, indirect and saturation treatment effects. In addition we also defined and identified que unconditional quantile private and spillover effects which is similar to the average effects of Phillipson (2000).

Suggested Citation

  • Alan Andre Borges da Costa & Sergio Pinheiro Firpo, 2018. "An analysis of the distributive effects of public policies and their spillovers," Working Papers, Department of Economics 2018_06, University of São Paulo (FEA-USP).
    • Handle: RePEc:spa:wpaper:2018wpecon06
    as

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    File URL: http://www.repec.eae.fea.usp.br/documentos/Costa_Firpo_06WP.pdf
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    References listed on IDEAS

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    1. Jinyong Hahn & Keisuke Hirano & Dean Karlan, 2011. "Adaptive Experimental Design Using the Propensity Score," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 96-108, January.
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    4. Sarah Baird & Aislinn Bohren & Berk Ozler & Craig McIntosh, 2014. "Designing Experiments to Measure Spillover Effects," Working Papers 2014-11, The George Washington University, Institute for International Economic Policy.
    5. 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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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Quantile; Saturation; Spillover;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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