flexpaneldid: A Stata Command for Causal Analysis with Varying Treatment Time and Duration
Eva Dettmann, Alexander Giebler, Antje Weyh
Abstract
>>A completely revised version of this paper has been published as: Dettmann, Eva; Giebler, Alexander; Weyh, Antje: flexpaneldid. A Stata Toolbox for Causal Analysis with Varying Treatment Time and Duration. IWH Discussion Paper 3/2020. Halle (Saale) 2020.<<
The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) and its Stata implementation, the command flexpaneldid. The approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations (like investment grants or other subsidy schemes). Introducing more flexibility enables the user to consider individual treatment and outcome periods for the treated observations. The flexpaneldid command for panel data implements the developed flexible difference-in-differences approach and commonly used alternatives like CEM Matching and difference-in-differences models. The novelty of this tool is an extensive data preprocessing to include time information into the matching approach and the treatment effect estimation. The core of the paper gives two comprehensive examples to explain the use of flexpaneldid and its options on the basis of a publicly accessible data set.
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Public Investment Subsidies and Firm Performance – Evidence from Germany
Matthias Brachert, Eva Dettmann, Mirko Titze
Jahrbücher für Nationalökonomie und Statistik,
No. 2,
2018
Abstract
This paper assesses firm-level effects of the single largest investment subsidy programme in Germany. The analysis considers grants allocated to firms in East German regions over the period 2007 to 2013 under the regional policy scheme Joint Task ‘Improving Regional Economic Structures’ (GRW). We apply a coarsened exact matching (CEM) in combination with a fixed effects difference-in-differences (FEDiD) estimator to identify the effects of programme participation on the treated firms. For the assessment, we use administrative data from the Federal Statistical Office and the Offices of the Länder to demonstrate that this administrative database offers a huge potential for evidence-based policy advice. The results suggest that investment subsidies have a positive impact on different dimensions of firm development, but do not affect overall firm competitiveness. We find positive short- and medium-run effects on firm employment. The effects on firm turnover remain significant and positive only in the medium-run. Gross fixed capital formation responses positively to GRW funding only during the mean implementation period of the projects but becomes insignificant afterwards. Finally, the effect of GRW-funding on labour productivity remains insignificant throughout the whole period of analysis.
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