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Applied Econometric Time Series Third Edition. Walter Enders, University of Alabama. Copyright © 2010 John Wiley & Sons, Inc. Chapter 2 STATIONARY TIME-SERIES MODELS. 1. STOCHASTIC DIFFERENCE EQUATION MODELS 2. ARMA MODELS. 3. STATIONARITY. Stationarity Restrictions for an AR(1) Process.
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Applied Econometric Time SeriesThird Edition Walter Enders, University of Alabama Copyright © 2010 John Wiley & Sons, Inc.
3. STATIONARITY • Stationarity Restrictions for an AR(1) Process
4. STATIONARITY RESTRICTIONSFOR AN ARMA(p, q) MODEL • Stationarity Restrictions for the Autoregressive Coefficients
5. THE AUTOCORRELATION FUNCTION • The Autocorrelation Function of an AR(2) Process • The Autocorrelation Function of an MA(1) Process • The Autocorrelation Function of an ARMA(1, 1) Process
7. SAMPLE AUTOCORRELATIONSOF STATIONARY SERIES • Model Selection Criteria • Estimation of an AR(1) Model • Estimation of an ARMA(1, 1) Model • Estimation of an AR(2) Model
8. BOX–JENKINS MODEL SELECTION • Parsimony • Stationarity and Invertibility • Goodness of Fit • Post-Estimation Evaluation
9. PROPERTIES OF FORECASTS • Higher-Order Models • Forecast Evaluation • The Granger–Newbold Test • The Diebold-Mariano Test
10. A MODEL OF THE INTEREST RATE SPREAD • Out-of-Sample Forecasts
11. SEASONALITY • Models of Seasonal Data • Seasonal Differencing
12. PARAMETER INSTABILITY AND STRUCTURAL CHANGE • Testing for Structural Change • Endogenous Breaks • Parameter Instability • An Example of a Break
APPENDIX 2.2: MODEL SELECTION CRITERIA • The Finite Prediction Error (FPE) Criterion • The AIC and the SBC