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Recovering the counterfactual as part of ex-ante impact assessments: an application to the PASIDP – II project in Ethiopia

Author

Listed:
  • Manuela Coromaldi

    (Università degli Studi Niccolò Cusano)

  • Alessandra Garbero

    (International Fund for Agricultural Development (IFAD))

  • Marco Letta

    (Sapienza Università di Roma)

Abstract

Real-world ex-ante impact assessments are far from the ideal experimental design, where the eligible population is supposed to be randomly assigned to treatment and control groups. Often, many surveys in developing contexts do not even collect data from a comparison group. We propose a methodology that recovers the counterfactual for ex-ante impact assessments of policy interventions under the conditions of distance decay in the exposure to continuous treatments and lack of control groups. We test this approach on data from a large-scale irrigation project in Ethiopia.

Suggested Citation

  • Manuela Coromaldi & Alessandra Garbero & Marco Letta, 2019. "Recovering the counterfactual as part of ex-ante impact assessments: an application to the PASIDP – II project in Ethiopia," Economics Bulletin, AccessEcon, vol. 39(3), pages 1844-1854.
    • Handle: RePEc:ebl:ecbull:eb-19-00480
    as

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    References listed on IDEAS

    as
    1. Michela Bia & Carlos A. Flores & Alfonso Flores-Lagunes & Alessandra Mattei, 2014. "A Stata package for the application of semiparametric estimators of dose–response functions," Stata Journal, StataCorp LLC, vol. 14(3), pages 580-604, September.
    2. Barbara Guardabascio & Marco Ventura, 2014. "Estimating the dose–response function through a generalized linear model approach," Stata Journal, StataCorp LLC, vol. 14(1), pages 141-158, March.
    3. Michela Bia & Alessandra Mattei, 2008. "A Stata package for the estimation of the dose–response function through adjustment for the generalized propensity score," Stata Journal, StataCorp LLC, vol. 8(3), pages 354-373, September.
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    More about this item

    Keywords

    counterfactual building; impact assessment; generalized propensity score; distance decay;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • H4 - Public Economics - - Publicly Provided Goods

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