User’s Guide : Basic Single Equation Analysis : Basic Regression Analysis
Basic Regression Analysis
Single equation regression is one of the most versatile and widely used statistical techniques. Here, we describe the use of basic regression techniques in EViews: specifying and estimating a regression model, performing simple diagnostic analysis, and using your estimation results in further analysis.
Subsequent chapters discuss testing and forecasting, as well as advanced and specialized techniques such as weighted least squares, nonlinear least squares, ARIMA/ARIMAX models, two-stage least squares (TSLS), generalized method of moments (GMM), GARCH models, and qualitative and limited dependent variable models. These techniques and models all build upon the basic ideas presented in this chapter.
You will probably find it useful to own an econometrics textbook as a reference for the techniques discussed in this and subsequent documentation. Standard textbooks that we have found to be useful are listed below (in generally increasing order of difficulty):
Pindyck and Rubinfeld (1998), Econometric Models and Economic Forecasts, 4th edition.
Johnston and DiNardo (1997), Econometric Methods, 4th Edition.
Wooldridge (2013), Introductory Econometrics: A Modern Approach, 5th Edition.
Greene (2008), Econometric Analysis, 6th Edition.
Davidson and MacKinnon (1993), Estimation and Inference in Econometrics.
Where appropriate, we will also provide you with specialized references for specific topics.