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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PART ONE SAMPLING THEORY AND BAYESIAN
J Goodness of Fit Measures
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2SLS algorithm alternative Amemiya American Statistical Association Analysis approximate assume assumption asymptotic distribution autocorrelation Autoregressive Bayesian Chapter choice components compute consider consistent estimator correlation covariance matrix criterion dependent variable derived diagonal discussed distributed lag disturbance Econometrica efficient EGLS elements endogenous variables example Exercise exogenous explanatory variables finite sample forecasting given heteroscedasticity identified inequality inference instrumental variable iteration Journal of Econometrics least squares estimator likelihood function linear model maximum likelihood estimator mean square error methods minimizing ML estimator Monte Carlo multivariate nonlinear normally distributed Note null hypothesis observations obtained optimal parameter space parameter vector polynomial pretest estimator prior information problem procedure random variable random vector reduced form Regression Models regressors residuals risk function sample properties Section Seemingly Unrelated Regression Series specification squared error loss statistical model Stein stochastic structure sum of squares test statistic tion transformation unbiased estimator unknown parameters values variance Zellner zero
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Regression Models for Categorical and Limited Dependent Variables
J. Scott Long
Limited preview - 1997