W. Enders, 2014, Applied Econometric Time Series, 4th Edition, Wiley.
Upon completion of the course the student will be able to read most of the empirical papers in macroeconomics and will be able to apply the standard econometric techniques in time series analysis.
An introductory course in econometrics, statistical inference
Additional material on the Moodle platform.
Type of Assessment
A written test with questions similar to what appears at the end fo the textbook's chapters.
If a student attends and participates to at least 80% of the lectures He/She has the possibility to skip the exam and do an empirical application.
Time-Series Models, Difference Equations and Their Solutions, Lag Operators. Stochastic Difference Equation Models, ARMA Models, Stationarity, Stationarity Restrictions for an ARMA (p, q) Model , The Autocorrelation Function, The Partial Autocorrelation Function, Sample Autocorrelations of Stationary Series, Box–Jenkins Model Selection, Properties of Forecasts, Seasonality, Structural Change, Combining Forecasts. Deterministic and Stochastic Trends, Removing the Trend, Unit Roots and Regression Residuals, The Monte Carlo Method, Dickey–Fuller Tests and extensions, Power and the Deterministic Regressors, Panel Unit Root Tests, Trends and Univariate Decompositions, Intervention Analysis, ADLs and Transfer Functions, Limits to Structural Multivariate Estimation, Introduction to VAR Analysis, Estimation and Identifcation, The Impulse Response Function, Structural VARs, Examples of Structural Decompositions, Overidentifed Systems, The Blanchard–Quah Decomposition. Linear Combinations of Integrated Variables, Cointegration and Common Trends, Cointegration and Error Correction, Testing for Cointegration: The Engle–Granger Methodology, Cointegration and Purchasing Power Parity, Characteristic Roots, Rank, and Cointegration,