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Germany’s economy is so bad even sausage factories are closingIWHThe Economist, January 15, 2026
The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) for the staggered treatment adoption design and a Stata tool that implements the approach. This flexible conditional difference-in-differences approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations. Introducing more flexibility enables the user to consider individual treatment periods for the treated observations and thus circumventing problems arising in canonical difference-in-differences approaches. The open-source flexpaneldid toolbox for Stata implements the developed approach and allows comprehensive robustness checks and quality tests. The core of the paper gives comprehensive examples to explain the use of the commands and its options on the basis of a publicly accessible data set.
>>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.
The aim of this paper is to analyze the technological activities of Central and Eastern European (CEE) economies and to compare them with the technological activities of other world regions. Using data from the EPO World Wide Statistical Database for the period 1980-2009 the analysis is based on counts of priority patent applications over time. In terms of priority patent applications, CEE reduced its technological activities drastically in absolute and per capita terms after 1990. The level of priority patent applications in this world region maintained more recently a stable level below the performance of EU15, South EU and the former USSR. In what concerns technological specialization, the results suggest a division of labor in technological activities among world regions where Europe, Latin America and the former USSR are mainly specializing in sectors losing technological dynamism in the global patent activities (Chemicals and/or Mechanical Engineering) while North America, the Middle East (especially Israel) and Asia Pacific are increasingly specializing in Electrical Engineering, a sector with strong technological opportunities.
