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Module Content
  • Univariate Time Series Models (Basic Concepts in Time Series Analysis). Approximating the Wold Representation.Data Transformations.Parametric Analysis of Time Series: Estimating AR, MA, and ARMA Processes.Nonparametric Analysis of Time Series.Unobserved Components Models. Measuring Volatility (ARCH, GARCH, ARCH-in-Models, Other Models of Conditional Heteroskedasticity).Measuring Risk.)
  • Unit Roots, Spurious Regressions and Cointegration(Testing the Unit Root Hypothesis. Robust Inference in the Presence of Possible Autoregressive Unit Roots.The Quantitative Importance of Unit Roots.Unit Root Regressions.Cointegration).
  • Multivariate Time Series Models (Nonparametric Methods for Multivariate Time Series. Reduced-Form Vector Autoregressions.AR and VAR Lag Order Selection.Structural VAR Models: Lessons from the Money-Income Causality Debate.)
  • Other Forecasting Methods(Forecasting a Scalar Time Series. Forecasting a Scalar Time Series with Large Cross-Sections.Predictability Tests.Pseudo Out-of-Sample Tests of Equal Predictive Accuracy.Tests of Forecast Encompassing.In-Sample versus Pseudo Out-of-Sample Tests of Predictability.Testing Forecastability.Direction-of-Change Tests. Data minining (What is data mining. Cures for data mining)).
  • Bootstrapping(Bootstrapping Stationary Time Series Models)
  • Nonrecursive Structural VAR Models(Identification. Structural VAR Critiques.Selected Alternative Structural VAR Approaches)/li>
  • Market failure, property rights and public goods
  • Nonlinear Time Series Models
  • Large data sets: Dynamic Factor Models, FAVAR, Combinations, Bayesian Model Averaging, BVARs(Motivation and application. Econometric Method).