Muutke küpsiste eelistusi

Advanced Econometric Theory [Pehme köide]

4.00/5 (2 hinnangut Goodreads-ist)
(University of Minnesota, USA)
  • Formaat: Paperback / softback, 394 pages, kõrgus x laius: 234x156 mm, kaal: 750 g, 1 Tables, black and white; 9 Line drawings, black and white
  • Sari: Routledge Advanced Texts in Economics and Finance
  • Ilmumisaeg: 21-Apr-2011
  • Kirjastus: Routledge
  • ISBN-10: 0415326303
  • ISBN-13: 9780415326308
Teised raamatud teemal:
Advanced Econometric TheorySuurem pilt
  • Formaat: Paperback / softback, 394 pages, kõrgus x laius: 234x156 mm, kaal: 750 g, 1 Tables, black and white; 9 Line drawings, black and white
  • Sari: Routledge Advanced Texts in Economics and Finance
  • Ilmumisaeg: 21-Apr-2011
  • Kirjastus: Routledge
  • ISBN-10: 0415326303
  • ISBN-13: 9780415326308
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780415326308.html
Märksõnad:
When learning econometrics, what better way than to be taught by one of its masters. In this significant new volume, John Chipman, the eminence grise of econometrics, presents his classic lectures in econometric theory.

Starting with the linear regression model, least squares, Gauss-Markov theory and the first principals of econometrics, this book guides the introductory student to an advanced stage of ability. The text covers multicollinearity and reduced-rank estimation, the treatment of linear restrictions and minimax estimation. Also included are chapters on the autocorrelation of residuals and simultaneous-equation estimation. By the end of the text, students will have a solid grounding in econometrics.

Despite the frequent complexity of the subject matter, Chipman's clear explanations, concise prose and sharp analysis make this book stand out from others in the field. With mathematical rigor sharpened by a lifetime of econometric analysis, this significant volume is sure to become a seminal and indispensable text in this area.
List of figures and tables
xii
Preface xiii
1 Multivariate analysis and the linear regression model
1(29)
1.1 Introduction
1(6)
1.2 Existence of a solution to the normal equation
7(3)
1.3 The concept of wide-sense conditional expectation
10(4)
1.4 Conditional expectation with normal variables
14(1)
1.5 The relation between wide-sense and strict-sense conditional expectation
15(2)
1.6 Conditional means and minimum mean-square error
17(3)
1.7 Bayes estimation
20(3)
1.8 The relation between Bayes and Gauss---Markov estimation in the case of a single independent variable
23(4)
1.9 Exercises
27(3)
2 Least-squares and Gauss---Markov theory
30(35)
2.1 Least-squares theory
30(1)
2.2 Principles of estimation
31(2)
2.3 The concept of a generalized inverse of a matrix
33(2)
2.4 The matrix Cauchy---Schwarz inequality and an extension
35(2)
2.5 Gauss---Markov theory
37(4)
2.6 The relation between Gauss---Markov and least-squares estimators
41(8)
2.7 Minimum-bias estimation
49(2)
2.8 Multicollinearity and the imposition of dummy linear restrictions
51(4)
2.9 Specification error
55(5)
2.10 Exercises
60(5)
3 Multicollinearity and reduced-rank estimation
65(23)
3.1 Introduction
65(1)
3.2 Singular-value decomposition of a matrix
65(3)
3.3 The condition number of a matrix
68(2)
3.4 The Eckart---Young theorem
70(11)
3.5 Reduced-rank estimation
81(5)
3.6 Exercises
86(2)
4 The treatment of linear restrictions
88(38)
4.1 Estimation subject to linear restrictions
88(4)
4.2 Linear aggregation and duality
92(9)
4.3 Testing linear restrictions
101(5)
4.4 Reduction of mean-square error by imposition of linear restrictions
106(2)
4.5 Uncertain linear restrictions
108(1)
4.6 Properties of the generalized ridge estimator
109(3)
4.7 Comparison of restricted and generalized ridge estimators
112(3)
4A Appendix (to Section 4.4): Guide to the computation of percentage points of the noncentral F distribution
115(7)
4.8 Exercises
122(4)
5 Stein estimation
126(17)
5.1 Stein's theorem and the regression model
126(6)
5.2 Lemmas underlying the James---Stein theorem
132(6)
5.3 Some further developments of Stein estimation
138(3)
5.4 Exercises
141(2)
6 Autocorrelation of residuals - 1
143(24)
6.1 The first-order autoregressive model
143(4)
6.2 Efficiency of trend estimation: the ordinary least-squares estimator
147(7)
6.3 Efficiency of trend estimation: the Cochrane---Orcutt estimator
154(3)
6.4 Efficiency of trend estimation: the Prais---Winsten weighted-difference estimator
157(4)
6.5 Efficiency of trend estimation: the Prais---Winsten first-difference estimator
161(1)
6.6 Discussion of the literature
162(3)
6.7 Exercises
165(2)
7 Autocorrelation of residuals - 2
167(35)
7.1 Anderson models
167(10)
7.2 Testing for autocorrelation: Anderson's theorem and the Durbin---Watson test
177(12)
7.3 Distribution and beta approximation of the Durbin---Watson statistic
189(7)
7.4 Bias in estimation of sampling variances
196(4)
7.5 Exercises
200(2)
8 Simultaneous-equations estimation
202(85)
8.1 The identification problem
202(8)
8.2 Anderson and Rubin's "limited-information maximum-likelihood" (LIML) method, 1: the handling of linear restrictions
210(5)
8.3 Anderson and Rubin's "limited-information maximum-likelihood" method, 2: constrained maximization of the likelihood function
215(8)
8.4 The contributions of Basmann and Theil
223(15)
8.5 Exact properties of simultaneous-equations estimators
238(13)
8.6 Approximations to finite-sample distributions
251(17)
8.7 Recursive models
268(15)
8.8 Exercises
283(4)
9 Solutions to the exercises
287(62)
9.1
Chapter 1
287(7)
9.2
Chapter 2
294(10)
9.3
Chapter 3
304(5)
9.4
Chapter 4
309(9)
9.5
Chapter 5
318(5)
9.6
Chapter 6
323(6)
9.7
Chapter 7
329(5)
9.8
Chapter 8
334(15)
Notes 349(8)
Bibliography 357(28)
Index 385
John S. Chipman is Regents' Professor of Economics Emeritus at the University of Minnesota. He taught in the areas of Econometrics, International Trade, and Welfare Economics. His is currently involved in theoretical and econometric research into international trade and the history of utility theory. He has published a number of key journal articles and his paper Homothetic Preferences and Aggregation - is one of the most significant papers in economic theory ever published.