Course Overview
Panel data modelling provides a means to estimate and test relations when there are samples containing a time series of observations for a cross section of individuals, firms, markets, countries, etc. Panel Data analysis has 2 main advantages over cross-sectional or time-series analysis: (1) It utilises more information (i.e. more degrees of freedom) and introduces more variability in the data and hence inference of model parameters can be more accurate; (2) Controlling for omitted / missing / unobserved factors. The growing availability of panel data has stimulated a rapid growth in both methodological approaches and applications during the last 20 years.

The course aims to provide participants with an in-depth background on panel data econometrics. Up-to-date treatment for a selection of major topics will be presented including endogeneity, serial correlation, stationarity and cointegration in addition to more traditional panel data techniques. All topics will be demonstrated with real life data in Stata.

Topics Include:
Introduction to Panel Data Analysis
Fixed Effect vs. Random
Effect Estimator
Dynamic Panel Data Methods
Dynamic Heterogeneous
Panel Methods
Non-Stationary Time-series and Panels
Panel Cointegration
Other Topics in Panel Data Analysis (Limited dependent Variables, Panel Data Instrumental Variables)

Who should attend?
This course targets practitioners and policy makers who are interested in gaining an in-depth knowledge of Panel Data techniques and learning how to use them in their current or future assignments.

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