Oliver Lipps and Ursina Kuhn
Introduction to Panel Data Analysis

Oliver Lipps is head of the methodological research programme at FORS and lecturer in survey methodology and survey research at the University of Bern.

Ursina Kuhn is a Senior researcher at FORS and member of the Swiss Household Panel team.

Workshop contents and objectives

This course introduces the structure, data management, and analysis of panel data in general and the Swiss Household Panel (SHP) in particular. Participants will learn to prepare the data for panel analyses, and to apply descriptive statistics and analytical models. After a detailed presentation of the SHP, we will learn how to organise data for different types of research questions which are specific to that type of data. This includes for example creating longitudinal data files, spells, and transitions. Analysis techniques focus on regression approaches (pooled, fixed effects, random effects, first differences). In the afternoon sessions, participants will work on practical exercises either with the SHP data or with panel data of their own choice. There will be time to solve individual problems.

Bibliography

Introductory texts

• Longitudinal Data / SHP data
• Andress, H. J., Golsch, K., & Schmidt, A. W. (2013). Applied panel data analysis for economic and social surveys. Springer Science & Business Media.
• Ruspini E. (1999) Longitudinal Research and the Analysis of Social Change. Special Issue of Quality & Quantity 33: 219-227. [Springerlink, access requires subscription]
• Voorpostel et al. (2011) Swiss Household Panel User Guide (1999-2010). FORS, Lausanne. [Swiss Household Panel] Specifically chapters 2.1 (p.11), 2.4.1 (p.14-16), 4.1.1 (p.23-25)
• Application examples using SHP data
• Lipps, O. and F. Moreau-Gruet (2010) Change of individual BMI in Switzerland and the USA: a multi-level model for growth." Forthcoming 2010 in International Journal of Public Health, Published online December 2: [SpringerlinkDoes unemployment hurt less if there is more of it around]
• Oesch, D. and O. Lipps (2013). Does unemployment hurt less if there is more of it around? A panel analysis of life satisfaction in Germany and Switzerland. European Sociological Review 29 (5): 955-967.
• Fitzgerald, J., and K. Amber Curtis (2011). Partisan discord in the family and political engagement: A comparative behavioral analysis. The Journal of Politics 74 (3): 783-796.

Books and articles on panel data analysis methods

(Kind of material covered during class)

• Kohler, U. and F. Kreuter (2009). Data Analysis Using Stata, 2nd ed. College Station, Texas: Stata Press.
• Rabe-Hesketh, S. and A. Skrondal (2007). Multilevel and Longitudinal Modeling Using Stata. Second edition. College Station, Texas: Stata Press.
• Singer J. and J. Willett (2003). Applied longitudinal Analysis - Modeling Change and Event Occurrence. Oxford University Press.
• Online resources: Stata Starter Kit, UCLA Academic Technology Services, USA
• Wooldridge, J. (2010). Econometric Analysis of Cross Section and Panel Data, 2nd Edition. MIT Press.
• Angrist, J. and J. Pischke (2009). Mostly harmless econometrics: An Empiricist's Companion. Princeton University Press.
• Morgan, S. and C. Winship (2015). Counterfactuals and Causal Inference. Methods and Principles for Social Research. 2nd ed. Cambridge University Press.
• Bell, A. and K. Jones (2015). Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data. Political Science Research and Methods 3(1): 133-153.

Prerequisites

Experience in statistical analysis of cross-sectional (survey) data is required. This includes experience with statistical software (such as R, SPSS, Stata, SAS) and a basic knowledge of cross tabulations and regressions. In the course, Stata will be used. To accommodate participants who are less familiar with Stata, we will repeat the basics.