Panel Data Analysis of Microdata
Dr Mark Bryan, University of Essex
13 - 24 July (two week course / 35 hrs)
Mark Bryan is a Senior Research Fellow, Institute for Social and Economic Research, University of Essex. He has published on the economics of training, the effects of the National Minimum Wage, the wage impact of trade unions, the effects of housework on wages, and the size of the gender wage gap over the wage distribution. Recent research focuses on the impact of flexible work on informal care, the reaction of couples to job loss, and methods for making cross-country comparisons using survey data.
- Micro panel data contain information on many cross-sectional units (usually individual people) observed at regular time points (e.g. every year). This module will introduce micro panel data and the main techniques required for micro panel data analysis. The module will begin by discussing the advantages (and limitations) of panel data, and will show how to handle and describe a panel dataset. We will then cover linear regression techniques: fixed and random effects models, instrumental variables methods and simple dynamic regression models. Next we will look at non-linear models, such as the random effects probit and fixed effects logit, which are used to deal with discrete variables. Finally, we will examine issues of panel attrition and selection. Following each lecture, participants will work through practical examples in the computer lab using the Stata statistical package and the British Household Panel Survey. The focus of the module is applied, but some maths will be used to formalise theoretical concepts. Note that the module does not cover specific techniques for macro panels (e.g. data on countries over time) or panels with small numbers of cross-sectional units but many time points. The module does not cover survival (event history or duration) analysis.
- To develop the skills necessary to understand and assess the applications of micro panel data analysis reported in the applied economics literature; and to enable participants to apply micro panel data techniques to their own research questions.
- Essential requirements for the module are:
- (a) Final year undergraduate level knowledge of linear regression methods (OLS regression) and some familiarity with issues like sample selection and endogeneity. Some experience of non-linear methods like probit and logit would also be useful. Remedial reading for these topics is Verbeek, chapters 1–3, 5 and 7 (see below).
- (b) Intermediate level proficiency in Stata: familiarity with basic commands and experience of writing Stata do files.
- There is no single text which covers all the module topics in a way that is accessible to applied researchers (dedicated panel data texts tend to be quite technical). The following recommended books contain useful material (* indicates preferred):
- Andreß, Hans-Jürgen, Golsch, Katrin, and Schmidt, Alexander W. 2013. Applied Panel Data Analysis for Economic and Social Surveys. Springer.
- Baltagi Badi H. 2008. Econometric Analysis of Panel Data, (4th ed.) Wiley.
- *Cameron, A. C., and Trivedi, P.K. 2005. Microeconometrics: Methods and Applications. Cambridge University Press.
- Cameron, A. C., and Trivedi, P.K. 2010. Microeconometrics Using Stata, Stata Press.
- Hsiao, C. 2003. Analysis of Panel Data (Econometric Society Monographs). (2nd ed.) Cambridge University Press.
- Jones Andrew M, Rice Nigel, Bago d'Uva Teresa and Balia Silvia, 2002, Applied Health Economics, Routledge 2007.
- *Verbeek, M. 2012. A Guide to Modern Econometrics. (4th ed.). Wiley. Participants should be comfortable with the material in ch. 1–3, 5 and 7 before the course. Ch. 10 covers panel data.
- Wooldridge, Jeffrey, 2010, Econometric Analysis of Cross Section and Panel Data (2nd ed.) MIT Press.
- Andreß et al is an intuitive and fairly non-technical guide. It contains a very good treatment of descriptive techniques and key modelling concepts, but does not cover more advanced dynamic models, instrumental variables, or more sophisticated non-linear models. Verbeek, chapter 10, is more formal, but still accessible, introduction to both basic and more advanced models. Students are advised to acquire both books.