This is a course on applied econometrics dealing with ‘panel’ or ‘longitudinal’ data sets which are frequently met in empirical applications in the energy and financial sector. Topics to be studied include specification, estimation, and inference in the context of models that include individual (firm, person, etc.) and/or time effects. The course begins with a review of the standard linear regression model, then apply it to panel data settings involving ‘fixed’, ‘random’, and ‘mixed’ effects. The basic model will be extended to spatial and dynamic models with recently developed GMM and instrumental variables methods. Furthermore, the course will consider numerous applications from the literature, including static and dynamic panel data regression models. Basic understanding of econometric analysis is required. Knowledge of calculus, algebra, probability theory and statistics are essential for this course. Familiar with computer programming and econometric packages will be useful. The programming language and packages in R will be used throughout the course. Optionally, Stata or E-views may be used.