Instructor: Gabriele Fiorentini
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.
Instructor: Alessandro Palandri and Fabrizio Cipollini
Monte Carlo Simulations: Law of Large Numbers, unbiasedness, Central Limit Theorem. Maximum Likelihood. Testing Principles: Wald, Likelihood Ratio, Lagrange Multiplier. Models for binary data: link function, logit, probit, goodness of fit. Models for count data: Poisson and Negative Binomial regressions. Generalized Method of Moments: estimation, optimal weighting matrix, Instrumental Variables, Quasi-Maximum Likelihood. Models for panel data: pooled OLS, Fixed Effects Models, Random Effects Models, Hausman Test.
Computer laboratory. Use of Gretl.