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Identify More, Observe Less: Mediation Analysis Synthetic Control

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Abstract

The synthetic control method (SCM) allows estimation of the causal effect of an intervention in settings where panel data on just a few treated units and control units are available. We show that the existing SCM as well as its extensions can be easily modified to estimate how much of the “total” effect goes through observed causal channels. The additional assumptions needed are arguably very mild in many settings. Furthermore, in an illustrative empirical application we estimate the effects of adopting the euro on labor productivity in several countries and show that a reduction in the Economic Complexity Index helped to mitigate the negative short run effects of adopting the new currency in some countries and boosted the positive effects in others.

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  • Giovanni Mellace & Alessandra Pasquini, 2019. "Identify More, Observe Less: Mediation Analysis Synthetic Control," CEIS Research Paper 474, Tor Vergata University, CEIS, revised 20 Nov 2019.
    • Handle: RePEc:rtv:ceisrp:474
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    Cited by:

    1. Roberta Di Stefano & Giovanni Mellace, 2020. "The inclusive synthetic control method," Working Papers 21/20, Sapienza University of Rome, DISS.
    2. Viviana Celli, 2022. "Causal mediation analysis in economics: Objectives, assumptions, models," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 214-234, February.

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    More about this item

    Keywords

    MASC; Synthetic Control Method; Mediation Analysis; Causal Channels; Causal Mechanisms; Direct and Indirect Effects.;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal 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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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