Panel data econometrics / Manuel Arellano.

Format:

Book

Author/Creator:

Arellano.

Contributor:

Manuel..

Series:

Advanced texts in econometrics.

Advanced texts in econometrics

Language:

English

Subjects (All):

Econometrics.

Panel analysis.

Physical Description:

1 online resource (244 p.)

Place of Publication:

Oxford ; New York : Oxford University Press, c2003.

Language Note:

English

Summary:

This book is intended for researchers and graduate students of econometrics.

Contents:

Contents; Preface; 1 Introduction; I: Static Models; 2 Unobserved Heterogeneity; 2.1 Overview; 2.2 Fixed Effects Models; 2.2.1 Assumptions; 2.2.2 Within-Group Estimation; 2.3 Heteroskedasticity and Serial Correlation; 2.3.1 Robust Standard Errors for Within-Group Estimators; 2.3.2 Optimal GLS with Heteroskedasticity and Autocorrelation of Unknown Form; 2.3.3 Improved GMM and Minimum Distance Estimation under Heteroskedasticity and Autocorrelation of Unknown Form; 2.4 Likelihood Approaches; 2.4.1 Joint Likelihood; 2.4.2 Conditional Likelihood; 2.4.3 Marginal (or Integrated) Likelihood

2.5 Nonlinear Models with Additive Effects2.5.1 Nonlinear Regression; 2.5.2 Linear Structural Equation; 2.5.3 Nonlinear Simultaneous Equations; 3 Error Components; 3.1 A Variance Decomposition; 3.2 Error-Components Regression; 3.2.1 The Model; 3.2.2 GLS and ML Estimation; 3.2.3 GLS,Within-Groups,and Between-Groups; 3.3 Testing for Correlated Unobserved Heterogeneity; 3.3.1 Specification Tests; 3.3.2 Robust Alternatives; 3.4 Models with Information in Levels; 3.5 Estimating the Error Component Distributions; 4 Error in Variables

4.1 An Introduction to the Standard Regression Model with Errors in Variables4.2 Measurement Error Bias and Unobserved Heterogeneity Bias; 4.3 Instrumental Variable Estimation with Panel Data; 4.4 Illustration: Measuring Economies of Scale in Firm Money Demand; II: Time Series Models with Error Components; 5 Covariance Structures for Dynamic Error Components; 5.1 Introduction; 5.2 Time Effects; 5.3 Moving Average Autocovariances; 5.4 Estimating Covariance Structures; 5.4.1 GMM/MD Estimation; 5.4.2 Using Transformations of the Original Moments; 5.4.3 Relationship between GMM and Pseudo ML

5.4.4 Testing Covariance Restrictions5.5 Illustration: Testing the Permanent Income Hypothesis; 6 Autoregressive Models with Individual Effects; 6.1 Assumptions; 6.2 The Within-Group Estimator; 6.3 Instrumental Variable Estimation; 6.4 Initial Conditions and Heteroskedasticity; 6.4.1 Estimation under Stationarity; 6.4.2 Unrestricted Initial Conditions; 6.4.3 Time Series Heteroskedasticity; 6.4.4 Time Effects in Autoregressive Models; 6.5 Mean Stationarity; 6.6 Unit Roots; 6.7 Estimating and Testing VARs for Firm Employment and Wages; III: Dynamics and Predeterminedness

7 Models with both Strictly Exogenous and Lagged Dependent Variables7.1 The Nature of the Model; 7.2 An Example: Cigarette Addiction; 7.3 GMM Estimation; 7.3.1 2SLS Estimation from a Large T Perspective; 7.3.2 Optimal IV Estimation in a Small T, Large N Context; 7.3.3 GMM with the Number of Moments Increasing with T; 7.3.4 Explanatory Variables Uncorrelated with the Effects; 7.3.5 Enforcing Restrictions in the Covariance Matrix; 7.4 Maximum Likelihood; 7.4.1 Estimation with Unrestricted Covariance Matrix; 7.4.2 MLE with Covariance Restrictions; 7.4.3 MLE with Correlated xs

8 Predetermined Variables

Notes:

Description based upon print version of record.

Includes bibliographical references (p. 215-226) and index.

Description based on print version record.

Description based on publisher supplied metadata and other sources.

ISBN:

0-19-924529-0

0-19-152967-2

1-280-90758-4

1-282-19935-8

9786610907588

9786612199356

OCLC:

320909617