TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 194

SAS/Ets User's Guide 194. Provides detailed reference material for using SAS/ETS software and guides you through the analysis and forecasting of features such as univariate and multivariate time series, cross-sectional time series, seasonal adjustments, multiequational nonlinear models, discrete choice models, limited dependent variable models, portfolio analysis, and generation of financial reports, with introductory and advanced examples for each procedure. You can also find complete information about two easy-to-use point-and-click applications: the Time Series Forecasting System, for automatic and interactive time series modeling and forecasting, and the Investment Analysis System, for time-value of money analysis of a variety of investments | 1922 F Chapter 30 The TSCSREG Procedure proportion of the transformed sum of squares of the dependent variable that is attributable to the influence of the independent variables. In the case of OLS estimation the Buse R-square measure is equivalent to the usual R-square measure. Estimation Techniques If the effects are fixed the models are essentially regression models with dummy variables that correspond to the specified effects. For fixed-effects models ordinary least squares OLS estimation is equivalent to best linear unbiased estimation. The output from TSCSREG is identical to what one would obtain from creating dummy variables to represent the cross-sectional and time fixed effects. The output is presented in this manner to facilitate comparisons to the least squares dummy variables estimator LSDV . As such the inclusion of a intercept term implies that one dummy variable must be dropped. The actual estimation of the fixed-effects models is not LSDV. LSDV is much too cumbersome to implement. Instead TSCSREG operates in a two step fashion. In the first step the following occurs One-way fixed-effects model In the one-way fixed-effects model the data is transformed by removing the cross-sectional means from the dependent and independent variables. The following is true yit yit - yi- Xt Xit - x Two-way fixed-effects model In the two-way fixed-effects model the data is transformed by removing the cross-sectional and time means and adding back the overall means yn yit - yi- - y-t y Xit Xit - Xi- - X-t x where the symbols yit and Xit are the dependent variable a scalar and the explanatory variables a vector whose columns are the explanatory variables not including a constant respectively yi- and Xi are cross section means y-t and X-t are time means y and X are the overall means The second step consists of running OLS on the properly demeaned series provided that the data are balanced. The unbalanced case is slightly more difficult because the structure of the missing

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