Applied Macroeconometrics

3 credits · Graduate credit

The aim of this course is to equip students with a working knowledge of important econometric techniques used in monetary economics, financial economics, international economics, and econometric theory. The centerpiece of this course is the vector auto-regressive model. The course is divided into six parts: (1) a review of the foundations of time series econometrics; (2) detrending models: restricted and unrestricted estimation of stationary vector auto-regressive and moving-average methods: asymptotic, bootstrap and Bayesian inference; model selection and specification tests, forecasting; exogeneity and Granger causality; tests of forecast encompassing and tests of equal forecast accuracy; impulse response analysis, variance decompositions and historical decompositions; (3) estimation and inference in the presence of trends, structural change and unit roots in univariate models; (4) spurious regressions, unbalance regressions and cointegration; (5) identification problems and the relationship between structural and reduced form models; and (6) estimation and inference for structural dynamic macroeconomic models and their relationship to vector auto-regressive models.