1 Introduction.- 2 Review of Ordinary Least Squares and Generalized Least Squares.- 3 Point Estimation and Tests of Hypotheses in Small Samples.- 4 Large Sample Point Estimation and Tests of Hypotheses.- 5 Stochastic Regressors.- 6 Use of Prior Information.- 7 Preliminary Test and Stein-Rule Estimators.- 8 Feasible Generalized Least Squares Estimation.- 9 Heteroscedasticity.- 10 Autocorrelation.- 11 Lagged Dependent Variables and Autcorrelation.- 12 Unobservable Variables.- 13 Multicollinearity.- 14 Varying Coefficient Models.- 15 Models That Combine Time-Series and Cross-Section Data.- 16 The Analysis of Models with Qualitative or Censored Dependent Variables.- 17 Distributed Lags.- 18 Uncertainty in Model Specification and Selection.- 19 Introduction to Simultaneous Equations Models.- 20 Identification.- 21 Limited Information Estimation.- 22 Full Information Estimation.- 23 Reduced Form Estimation and Prediction in Simultaneous Equations Models.- 24 Properties of Dynamic Simultaneous Equations Models.- 25 Special Topics in Simultaneous Equations.- Appendix Estimation and Inference in Nonlinear Statistical Models.- A.1 Nonlinear Optimization.- A.1.1 Method of Steepest Ascent.- A.1.2 The Method of Newton.- A.1.3 Method of Quadratic Hill Climbing.- A.1.4 Numerical Differentiation.- A.2 Maximum Likelihood Estimation.- A.2.1 Use of the Method of Newton.- A.2.2 Method of Scoring.- A.2.3 The Method of Berndt, Hall, Hall, and Hausman.- A.2.4 Asymptotic Tests Based on the Maximum Likelihood Method.- A.2.4a The Wald Test.- A.2.4b The Lagrange-Multiplier Test.- A.2.4c The Likelihood Ratio Test Statistic.- A.2.4d Concluding Remarks.- A.3 Nonlinear Regression.- A.4 Summary and Guide to Further Readings.- A.5 References.

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Book by Fomby Thomas B Hill R Carter Johnson Stanley R

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