Applied Econometric Time Series, 4th Edition
November 2014, ©2015
Chapter 1: Difference Equations
Chapter 2: Stationary Time-Series Models
Chapter 3: Modeling Volatility
Chapter 4: Models with Trend
Chapter 5: Multiequation Time-Series Models
Chapter 6: Cointegration and Error-Correction Models
Chapter 7: Nonlinear Models and Breaks
- Chapter 2 discusses the important issue of combining multiple univariate forecasts so as to reduce overall forecast error variance.
- Chapter 3 expands the discussion of multivariate GARCH models by illustrating volatility impulse response functions.
- Chapter 5 has been rewritten to show the appropriate ways to properly identify and estimate autoregressive distributed lags (ADLs).
- Chapter 7 now discusses the so-called Davies’ problem involving unidentified nuisance parameters under the null hypothesis.
- Learn by Doing through exposure to procedures appearing in econometric software packages, such as EVIEWS, MICROSIT, PC-GIVE, RATS, SAS, SHAZAM, and STATA, and assistance in matrix programming (MATLAB and GAUSS).
- Real-world, timely data and detailed examples from macroeconomics, agricultural economics, international finance, transnational terrorism, and current international finance literature.
- Step-by-step approach to time-series estimation and procedural stages with detailed examples of each procedure and summary of the stages.
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