NMAA05025U Econometrics 2: Statistical Analysis of Econometric Time Series (StatØ2)

Knowledge: The following topics will be covered in the course. Dependence and correlation, stationary and mixing stochastic processes, the law of large numbers for dependent sequences, martingales, central limit theorem for martingales, Markov processes, asymptotic stability, linear processes, uni- and multivariate autoregressive processes, estimation and asymptotic statistical theory for time series models, tests for misspecification of time series models, non-linear time series models, autoregressive processes with unit roots.


Skills: After the course, the student will be able to apply standard time series models used for the analysis of macro-econometric data, to use statistical software for time series, to apply key concepts and methods from the theory of stochastic processes (including martingales, law of large number and central limit theorem) to statistically analyse time series, and to formulate and apply likelihood-based tests for linear hypotheses and specification tests for time series models.


Competences: After the course, the student will be able to statistically analyse macro-economic time series at an advanced level, to make predictions of future values of the series, to theoretically analyse uni- and multivariate time series,  and to develop statistical methodology for such models.