Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/175360 
Year of Publication: 
2018
Citation: 
[Journal:] Economics: The Open-Access, Open-Assessment E-Journal [ISSN:] 1864-6042 [Volume:] 12 [Issue:] 2018-9 [Publisher:] Kiel Institute for the World Economy (IfW) [Place:] Kiel [Year:] 2018 [Pages:] 1-19
Publisher: 
Kiel Institute for the World Economy (IfW), Kiel
Abstract: 
Imagine a region suffering from a widening income gap that becomes eligible for a generous transfer programme (the treatment). Imagine difference-in-differences analysis (DD) - a before-and-after comparison of the income-level difference - shows that the handicap has risen. Most observers would conclude to the policy's inefficiency. But second thoughts are needed, because DD rests heavily on the validity of a key assumption: parallel paths in the absence of treatment; an assumption that is often violated. To cope with this problem, economists traditionally 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. 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 1994-2006 EU programme that was implemented in the Belgian province of Hainaut.
Subjects: 
treatment-effect analysis
difference-in-differences models
EU convergence policy
JEL: 
C21
R11
R15
O52
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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