User’s Guide
The first section of the User’s Guide describes EViews fundamentals and describes using EViews to perform basic data analysis and display results. This material may be divided into three parts:
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Part I. “EViews Fundamentals” introduces you to the basics of using EViews. In addition to a discussion of basic Windows operations, we explain how to use EViews to work with your data.
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Part II. “Basic Data Analysis” describes the use of EViews to perform basic analysis of data and to draw graphs and display tables describing the results of analysis of your data.
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Part III. “Customizing Output” documents the graph object, table and text objects, and the spool object, all of which are used to produce presentation output.
The second section offers a description of EViews’ interactive tools for advanced statistical and econometric analysis. This material may be divided into several parts:
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Part V. “Basic Single Equation Analysis” discusses the use of the equation object to perform standard regression analysis, ordinary least squares, weighted least squares, nonlinear least squares, basic time series regression, specification testing and forecasting.
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Part VI. “Advanced Single Equation Analysis” documents two-stage least squares (TSLS) and generalized method of moments (GMM), autoregressive conditional heteroskedasticity (ARCH) models, single-equation cointegration equation specifications, discrete and limited dependent variable models, generalized linear models (GLM), quantile regression, and user-specified likelihood estimation.
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Part VII. “Advanced Univariate Analysis” describes advanced tools for univariate time series analysis, including unit root tests in both conventional and panel data settings, variance ratio tests, and the BDS test for independence.
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Part VIII. “Multiple Equation Analysis” describes estimation and forecasting with systems of equations (least squares, weighted least squares, SUR, system TSLS, 3SLS, FIML, GMM, multivariate ARCH), vector autoregression and error correction models (VARs and VECs), state space models and model solution.
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Part IX. “Panel and Pooled Data” documents working with and estimating models with time series, cross-sectional data. The analysis may involve small numbers of cross-sections, with series for each cross-section variable (pooled data) or large numbers systems of cross-sections, with stacked data (panel data).