The Theory and practice of econometrics
This broadly based graduate-level textbook covers the major models and statistical tools currently used in the practice of econometrics. It examines the classical, the decision theory, and the Bayesian approaches, and contains material on single equation and simultaneous equation econometric models. Includes an extensive reference list for each topic.
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Estimation and Inference
Combining Sample and Other Information
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algorithm alternative Amemiya American Statistical Association Analysis applied approximate assumed assumption asymptotic autocorrelation autoregressive Bayesian bias Chapter characteristic roots choice Compute considered constraints correlation covariance matrix criterion dependent variable design matrix diagonal discussed distributed lag disturbance Econometrica economic efficient EGLS elements equation explanatory variables finite sample given GLS estimator heteroscedasticity homoscedastic inequality instrumental variable iterative Journal of Econometrics lag length lag model least squares estimator likelihood function linear model maximum likelihood estimator mean square error method minimax minimizing multicollinearity nonlinear normally distributed null hypothesis objective function observations obtained parameter space polynomial posterior pretest estimator prior information Problem random coefficient random variable random vector Regression Models regressors residuals restricted estimator restricted least squares risk function rule sampling properties Section Seemingly Unrelated Regressions specification squared error loss suggested sum of squares Swamy test statistic Theil tion transformation unknown parameters unobservable variables values variance Zellner zero
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Regression Models for Categorical and Limited Dependent Variables
J. Scott Long
Limited preview - 1997