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21- Time Series Econometrics I: Stationarity, Unit Roots, and Cointegration

Approaches to Econometrics Forecasting AR, MA, and ARIMA Modeling of Time Series Data The Box-Jenkins (BJ) Methodology Identification Estimation of the ARIMA Model Diagnostic Checking Forecasting Further Aspects of the BJ Methodology Summary and Conclusions . 22- Time Series Econometrics F

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21- Time Series Econometrics I: Stationarity, Unit Roots, and Cointegration

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    1. A Look at Selected U.S. Economic Time Series Stationary Stochastic Process Test of Stationarity Based on Correlogram The Unit Root Test of Stationarity Trend-Stationary (TS) and Difference-Stationary (DS) Stochastic Process Spurious Regression Cointegration Cointegration and Error Correction Mechanism (ECM) Summary and Conclusions 21- Time Series Econometrics I: Stationarity, Unit Roots, and Cointegration

    2. Approaches to Econometrics Forecasting AR, MA, and ARIMA Modeling of Time Series Data The Box-Jenkins (BJ) Methodology Identification Estimation of the ARIMA Model Diagnostic Checking Forecasting Further Aspects of the BJ Methodology Summary and Conclusions 22- Time Series Econometrics Forecasting with ARIMA and VAR Models

    3. A- A Review of Some Statistical Concepts B- Rudiments of Matrix Algebra C- A List of Statistical Computer Packages D- Statistical Tables Selected Bibliography Indexes - Name Index - Subject Appendixes

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