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Treatment Effects with Heterogeneous Externalities

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  • Patacchini, Eleonora
  • Rainone, Edoardo

Abstract

This paper proposes a new method for estimating heterogeneous externalities in policy analysis when social interactions take the linear-in-means form. We establish that the parameters of interest can be identified and consistently estimated using specific functions of the share of the eligible population. We also study the finite sample performance of the proposed estimators using Monte Carlo simulations. The method is illustrated using data on the PROGRESA program. We find that more than 50 percent of the effects of the program on schooling attendance are due to externalities, which are heterogeneous within and between poor and nonpoor households.

Suggested Citation

  • Patacchini, Eleonora & Rainone, Edoardo, 2019. "Treatment Effects with Heterogeneous Externalities," CEPR Discussion Papers 13781, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:13781
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    Cited by:

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    4. Patacchini, Eleonora & Hsieh, Chih-Sheng & Lin, Xu, 2019. "Social Interaction Methods," CEPR Discussion Papers 14141, C.E.P.R. Discussion Papers.
    5. Giulio Grossi & Marco Mariani & Alessandra Mattei & Patrizia Lattarulo & Ozge Oner, 2020. "Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach," Papers 2004.05027, arXiv.org, revised Nov 2023.

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    More about this item

    Keywords

    Program evaluation; Two-stage least squares; Indirect treatment effec;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D62 - Microeconomics - - Welfare Economics - - - Externalities

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