Introduction to the Mathematical and Statistical Foundations of Econometrics

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Cambridge University Press, Dec 20, 2004 - Business & Economics - 323 pages
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This book is intended for use in a rigorous introductory PhD level course in econometrics.
 

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Contents

Probability and Measure
1
Borel Measurability Integration and Mathematical
37
Conditional Expectations
66
A Proof of Theorem 3 12
83
The Multivariate Normal Distribution and Its Application
110
A Proof of Theorem 5 8
134
Numbers
143
A Proof of the Uniform Weak Law
164
Dependent Laws of Large Numbers and Central Limit
179
Maximum Likelihood Theory
205
Review of Linear Algebra
229
of a Matrix
253
Miscellaneous Mathematics
283
A Brief Review of Complex Analysis
298
Tables of Critical Values
306
References 315

C Convergence of Characteristic Functions
174

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About the author (2004)

Herman J. Bierens is Professor of Economics at the Pennsylvania State University and part-time Professor of Econometrics at Tilburg University, The Netherlands. He is Associate Editor of the Journal of Econometrics and Econometric Reviews, and has been an Associate Editor of Econometrica. Professor Bierens has written two monographs, Robust Methods and Asymptotic Theory in Nonlinear Econometrics and Topics in Advanced Econometrics Cambridge University Press 1994), as well as numerous journal articles. His current research interests are model (mis)specification analysis in econometrics and its application in empirical research, time series econometrics, and the econometric analysis of dynamic stochastic general equilibrium models.

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