This course focuses on the econometric analysis of data that contains a temporal component. The concept of a time series will be rigorously defined and some of the main tools to analyse them are discussed. The students are introduced to well-known models for time series data, including autoregressive moving average (ARMA) models, autoregressive distributed lag (ADL) and error correction models (ECM). The course provides both theoretical and practical insights into parameter estimation for time series models and the use of these models for forecasting, testing for Granger causality, and performing policy analysis using impulse response functions. Finally, students become familiar with the fundamental problem of spurious regression in time series analysis. We therefore discuss unit root and cointegration tests, as well as error-correction representation theorems.

Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.