Intro; Contents; List of Figures; List of Tables; Chapter 1: Introduction to EViews; 1.1 Introduction; 1.2 Importing Data into EViews; 1.2.1 Reading Excel/IBM SPSS Data Variables; 1.2.2 Saving and Opening an EViews Data File; Chapter 2: A Guideline for Running Regression; 2.1 EViews Regression; 2.1.1 Saving the Regression Equation; 2.1.2 Editing and Saving Regression Graphics; 2.2 The Cobb-Douglas Function; 2.2.1 Estimation of the Cobb-Douglas Model; 2.2.2 Interpret the Regression Equation; 2.2.3 Testing the Coefficients; 2.2.4 Comment on the Value of the R2 and Testing the R2

2.2.5 Multicollinearity and Residual Analysis2.2.5.1 Examine the Multicollinearity Problem in EViews; 2.2.5.2 Examine the Normality Problem in EViews; 2.2.5.3 Examine the Heteroscedasticity Problem in EViews; 2.2.5.4 Examine the Autocorrelation Problem in EViews; Chapter 3: Time Series Analysis; 3.1 Time Series One: The Real Money Demand (RMD); 3.1.1 Informal Method: Plot the Time Series and Generate a Correlogram; 3.1.2 Formal Method: Run the Augmented Dickey-Fuller (ADF) Test; 3.2 Time Series Two: The Real GDP (RGDP); 3.2.1 Informal Method: Plot the Time Series and Generate a Correlogram

3.2.2 Formal Method: Run the Augmented Dickey-Fuller (ADF) Test3.3 Time Series Three: Interest Rates (INT); 3.3.1 Informal Method: Plot the Time Series and Generate a Correlogram; 3.3.2 Formal Method: Run the Augmented Dickey-Fuller (ADF) Test; 3.4 Time Series Four: The First Difference of the RMD-DRMD; 3.4.1 Informal Method: Plot the Time Series and Generate a Correlogram; 3.4.2 Formal Method: Run the Augmented Dickey-Fuller (ADF) Test; 3.5 Time Series Five: The First Difference of the RGDP-DRGDP; 3.5.1 Informal Method: Plot the Time Series and Generate a Correlogram

3.5.2 Formal Method: Run the Augmented Dickey-Fuller (ADF) Test3.6 Time Series Six: The First Difference of INT-DINT; 3.6.1 Informal Method: Plot the Time Series and Generate a Correlogram; 3.6.2 Formal Method: Run the Augmented Dickey-Fuller (ADF) Test; Chapter 4: Time Series Modelling; 4.1 The Property of Stationarity; 4.1.1 Trend Differencing; 4.1.2 Seasonal Differencing; 4.1.3 Homoscedasticity of the Data; 4.2 Time Series in Practice; Chapter 5: Further Properties of Time Series; 5.1 Stochastic and Deterministic Trends; 5.2 The Lag Operator and Invertibility

5.3 The Characteristic Equation and Stationarity5.4 Unit Root Tests; Appendix 5.1: The Binomial Theorem; Appendix 5.2: The Quadratic Equation; Chapter 6: Economic Forecasting Using Regression; 6.1 Forecasting with Regression Models; 6.2 Step One: Checking the Stationarity of the Series; 6.3 Step Two: Making Series Stationary; 6.4 Step Three: The Cointegration Test; 6.5 Step Four: Model Forecasting; 6.6 Step Five: Making a Joint Graph of the Dependent Variable and Its Forecast; 6.7 Step Six: Adding Autocorrelation of the Error Term; Chapter 7: Economic Forecasting using ARIMA Modelling