Stochastic Limit Theory: An Introduction for Econometricians

Stochastic Limit Theory: An Introduction for Econometricians

by Arnold I. Davidson, James Davidson
     
 

ISBN-10: 0198774036

ISBN-13: 9780198774037

Pub. Date: 12/08/1994

Publisher: Oxford University Press

This major new econometrics text surveys recent developments in the rapidly expanding field of asymptotic distribution theory, with a special emphasis on the problems of time dependence and heterogeneity. Designed for econometricians and advanced students with limited mathematical training, the book clearly lays out the necessary math and probability theory and

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Overview

This major new econometrics text surveys recent developments in the rapidly expanding field of asymptotic distribution theory, with a special emphasis on the problems of time dependence and heterogeneity. Designed for econometricians and advanced students with limited mathematical training, the book clearly lays out the necessary math and probability theory and uses numerous examples to make its data useful and comprehensible. It also includes original new material from Davidson's own research on central limit theorems.

About the Series
Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.

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Product Details

ISBN-13:
9780198774037
Publisher:
Oxford University Press
Publication date:
12/08/1994
Series:
Advanced Texts in Econometrics Series
Edition description:
New Edition
Pages:
568
Product dimensions:
9.19(w) x 6.13(h) x 1.33(d)

Table of Contents

Preface
Mathematical Symbols and Abbreviations
1Sets and Numbers
2Limits and Continuity
3Measure
4Integration
5Metric Spaces
6Topology
7Probability Spaces
8Random Variables
9Expectations
10Conditioning
11Characteristic Functions
12Stochastic Processes
13Dependence
14Mixing
15Martingales
16Mixingales
17Near-Epoch Dependence
18Stochastic Convergence
19Convergence in L[subscript p]-Norm
20The Strong Law of Large Numbers
21Uniform Stochastic Convergence
22Weak Convergence of Distributions
23The Classical Central Limit Theorem
24CLTs for Dependent Processes
25Some Extensions
26Weak Convergence in Metric Spaces
27Weak Convergence in a Function Space
28Cadlag Functions
29FCLTs for Dependent Variables
30Weak Convergence to Stochastic Integrals
Notes
References
Index

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