Advanced Econometric Methods

Thomas B Fomby

ISBN 10: 0387909087 / ISBN 13: 9780387909080

Editore: Springer Nature Aug 1984, 1984

Riguardo questo articolo

Neuware - This book is intended for a two-semester, graduate-level course and is paced to admit more extensive treatment of areas of specific interest to the instructor and students. It is assumed that the reader of the book will have had an econometric methods course. In the final section of each chapter we have provided a guide to further readings that briefly lists and describes useful related works in the area. The exercises provided with each chapter are a blend of proofs and results that replace or extend many of those in the text. Applications are included in the exercises as well. We believe strongly that students must grapple with applied econometric techniques. Of course, this means the development of an appropriate dexterity with computers and relevant software as a requirement for serious students in econometrics.

Codice articolo 9780387909080

Dati bibliografici

• Titolo: Advanced Econometric Methods
• Editore: Springer Nature Aug 1984
• Data di pubblicazione: 1984
• Lingua: Inglese
• ISBN 10: 0387909087
• ISBN 13: 9780387909080
• Rilegatura: Buch
• Condizione: Neu

Descrizione articolo

Riassunto

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.

Product Description

Book by Fomby Thomas B Hill R Carter Johnson Stanley R