Within-estimation with panel data (e.g. fixed-effects regression) has the advantage that it automatically controls for all time-constant unit-specific confounders. Therefore, within-estimation is meanwhile widely used in social research. However, available textbooks are largely silent on how to specify a within analysis and therefore it is no wonder that many published studies use problematic specifications that have the potential to spoil the advantages of within-estimation. In this workshop we will discuss several of these specification issues for within-estimation: How to model impact functions? How to model the age effect? Should one use a control group? How to use hybrid models? How to specify interaction effects? Should one use lagged outcome/treatment variables? How to get rid of the parallel trends assumption? How to deal with reverse causality?
The workshop will last two full days (Tuesday and Wednesday, 9:00 to 17:00 each day) and will be hosted at the Mannheim Centre for European Social Research (MZES). The workshop is free of charge, including coffee breaks and lunches. Participants will have to organize and finance accommodation on their own.
Participation and Application
The number of participants is limited. Everyone who wants to participate in the workshop should send an e-mail to cils4eu(at)mzes.uni-mannheim(dot)de until February, 28th 2019, including their full names as well as their affiliation and their position (researcher, postdoc, PhD candidate, etc.).
The workshop is intended for participants who have a basic understanding of and previous experience in carrying out panel data analysis, in particular in doing fixed-effects regression with the statistical package Stata.
Exemplary analyses will be carried out using the ‘Children of Immigrants Longitudinal Survey in Four European Countries (CILS4EU)’. Access to the data will be granted for the time of the workshop. Participants are asked to bring their own laptops equipped with an up-to-date version of the statistical package Stata.
Instructor: Prof. Dr. Josef Brüderl (Ludwig-Maximilians-Universität, Munich)