Aims and Objectives. The finding that most macroeconomic time series are non-stationary has profoundly changed the econometric methodology. This development in the methodology has proven to be an important tool to understand and analyze the structure of the dynamic econometric models. The purpose of this course is to give a theoretical as well as empirical understanding for the econometric analysis of long-run and short-run structures of macroeconomic models based on a system of equations approach. In particular the course will focus on the properties of the non-stationary time series data in the framework of Cointegrated Vector AutoRegressive (CVAR) models.
The purpose of this course is twofold, first to develop the necessary theoretical tools to illustrate the econometric methodology of non-stationary time series in a system of equations approach, and second to show, using empirical examples, the importance of methodological changes in relation to the empirical modelling.
The program generally includes: modelling dynamic systems and methodology; the probability approach in econometrics; theory of reduction; deriving the VAR and its dynamic properties; misspecification tests; cointegrated VAR and derivation of the Maximum Likelihood estimator; determination of cointegration rank; formal, empirical, and economic identification; adjustment dynamics and exogeneity. Applications may include consumption, demand-supply models, money demand, financial and labour markets.
Intended Learning Outcomes. Acquire knowledge of recent changes in the methodology of ec-onometric analysis of time series. Understand and analyze the short and long run structure of the dynamic econometric models. Understanding the importance of methodological changes in relation to the empirical modelling in the macroeconomic field.