Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/173223
Authors: 
Vandenberghe, Vincent
Year of Publication: 
2018
Series/Report no.: 
GLO Discussion Paper 172
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.
Subjects: 
Treatment-Effect Analysis
Differences-in-Differences Models
Correction for trend differences
JEL: 
C21
C4
C5
Document Type: 
Working Paper

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