Economics and finance modelling with Eviews : a guide for students and professionals / Abdulkader Aljandali, Motasam Tatahi.

Includes bibliographical references and index.

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.

This practical guide in Eviews is aimed at practitioners and students in business, economics, econometrics, and finance. It uses a step-by-step approach to equip readers with a toolkit that enables them to make the most of this widely used econometric analysis software. Statistical and econometric concepts are explained visually with examples, problems, and solutions. Developed by economists, the Eviews statistical software package is used most commonly for time series-oriented econometric analysis. It allows users to quickly develop statistical relations from data and then use those relations to forecast future values of the data. The package provides convenient ways to enter or upload data series, create new series from existing ones, display and print series, carry out statistical analyses of relationships among series, and manipulate results and output. This highly hands-on resource includes more than 200 illustrative graphs and tables and tutorials throughout. Abdulkader Aljandali is Senior Lecturer at Coventry University in London. He is currently leading the Stochastic Finance Module taught as part of the Global Financial Trading MSc. His previously published work includes Exchange Rate Volatility in Emerging Economies, Quantitative Analysis and IBM® SPSS® Statistics, and Multivariate Methods and Forecasting with IBM® SPSS® Statistics. Dr. Aljandali is an established member of the British Accounting and Finance Association and the Higher Education Academy. Motasam Tatahi is a specialist in the areas of Macroeconomics, Financial Economics, and Financial Econometrics at the European Business School, Regent's University London, where he serves as Principal Lecturer and Dissertation Coordinator for the MSc in Global Banking and Finance.