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Alternatives to Polynomial Trend-Corrected Differences-In-Differences Models

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  • Vandenberghe, Vincent

Abstract

A common problem with differences-in-differences (DD) estimates is the failure of the parallel-trend assumption. To cope with this, most authors include polynomial (linear, quadratic…) trends among the regressors, and estimate the treatment effect as a once-in-a-time trend shift. In practice that strategy does not work very well, because inter alia the estimation of the trend uses post-treatment data. An extreme case is when sample covers only one period before treatment and many after. Then the trend's estimate relies almost completely on post-treatment developments, and absorbs most of the treatment effect. What is needed is a method that i) uses pre-treatment observations to capture linear or non-linear trend differences, and ii) extrapolates these to compute the treatment effect. This paper shows how this can be achieved using a fully-flexible version of the canonical DD equation. It also contains an illustration using data on a 1994-2000 EU programme that was implemented in the Belgian province of Hainaut.

Suggested Citation

  • Vandenberghe, Vincent, 2018. "Alternatives to Polynomial Trend-Corrected Differences-In-Differences Models," GLO Discussion Paper Series 172, Global Labor Organization (GLO).
    • Handle: RePEc:zbw:glodps:172
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    More about this item

    Keywords

    Treatment-Effect Analysis; Differences-in-Differences Models; Correction for trend differences;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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