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(Ebook) Asymptotic theory for econometrician Revised Edition by Halbert White ISBN 0127466525 9780127466521

  • SKU: EBN-56381884
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Authors:Halbert White
Language:english
File Size:7.47 MB
Format:pdf
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(Ebook) Asymptotic theory for econometrician Revised Edition by Halbert White ISBN 0127466525 9780127466521

(Ebook) Asymptotic theory for econometrician Revised Edition by Halbert White - Ebook PDF Instant Download/Delivery: 0127466525 ,9780127466521
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ISBN 10: 0127466525
ISBN 13: 9780127466521
Author: Halbert White

This book provides the tools and concepts necessary to study the behavior of econometric estimators and test statistics in large samples. An econometric estimator is a solution to an optimization problem; that is, a problem that requires a body of techniques to determine a specific solution in a defined set of possible alternatives that best satisfies a selected object function or set of constraints. Thus, this highly mathematical book investigates situations concerning large numbers, in which the assumptions of the classical linear model fail. Economists, of course, face these situations often. It includes completely revised chapter seven on functional central limit theory and its applications, specifically unit root regression, spurious regression, and regression with cointegrated processes. It includes updated material on: central limit theory; asymptotically efficient instrumental variables estimation; estimation of asymptotic covariance matrices; efficient estimation with estimated error covariance matrices; and efficient IV estimation.

Ebook Asymptotic theory for econometrician Revised Edition Table of contents:

CHAPTER I. The Linear Model and Instrumental Variables Estimators

Text

References

For Further Reading

CHAPTER II. Consistency

II.1 Limits

II.2 Almost Sure Convergence

II.3 Convergence in Probability

II.4 Convergence in rth Mean

References

CHAPTER III. Laws of Large Numbers

III.1 Independent Identically Distributed Observations

III.2 Independent Heterogeneously Distributed Observations

III.3 Dependent Identically Distributed Observations

III.4 Dependent Heterogeneously Distributed Observations

III.5 Martingale Difference Sequences

References

CHAPTER IV. Asymptotic Normality

IV.1 Convergence in Distribution

IV.2 Hypothesis Testing

IV.3 Asymptotic Efficiency

References

CHAPTER V. Central Limit Theory

V.1 Independent Identically Distributed Observations

V.2 Independent Heterogeneously Distributed Observations

V.3 Dependent Identically Distributed Observations

V.4 Dependent Heterogeneously Distributed Observations

V.5 Martingale Difference Sequences

References

CHAPTER VI. Estimating Asymptotic Covariance Matrices

VI.1 General Structure of Vn

VI.2 Case 1: Ωn (Block) Diagonal

VI.3 Case 2: Ωn (Block) Band Diagonal

VI.4 Case 3: General Case

References

CHAPTER VII. Efficient Estimation with Estimated Error Covariance Matrices

VII.1 General Results

VII.2 Case 1: Contemporaneous Covariance

VII.3 Case 2: Heteroskedasticity

VII.4 Case 3: Serial Correlation

References

CHAPTER VIII. Directions For Further Study

VIII.1 Extensions of the Linear Model

VIII.2 Nonlinear Models

VIII.3 Other Estimation Techniques

VIII.4 Model Misspecification

References

Solution Set

Index

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