Finite Sample Properties of Some Alternative Gmm Estimators

Finite Sample Properties of Some Alternative Gmm Estimators
Author: Lars Peter Hansen
Publisher: Franklin Classics
Total Pages: 64
Release: 2018-10-15
Genre:
ISBN: 9780343206994

This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

Finite Sample Properties of Some Alternative Gmm Estimators (Classic Reprint)

Finite Sample Properties of Some Alternative Gmm Estimators (Classic Reprint)
Author: Lars Peter Hansen
Publisher: Forgotten Books
Total Pages: 64
Release: 2017-11-26
Genre: Mathematics
ISBN: 9780331971491

Excerpt from Finite Sample Properties of Some Alternative Gmm Estimators Let vtw) denote (an infeasible) consistent estimator of this covariance matrix. This latter estimator is typically made operational by substituting a consistent estimator for (3. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

Finite Sample Properties of Some Alternative Gmm Estimators...

Finite Sample Properties of Some Alternative Gmm Estimators...
Author: Hansen Peter
Publisher: Hardpress Publishing
Total Pages: 72
Release: 2013-12
Genre:
ISBN: 9781314823356

Unlike some other reproductions of classic texts (1) We have not used OCR(Optical Character Recognition), as this leads to bad quality books with introduced typos. (2) In books where there are images such as portraits, maps, sketches etc We have endeavoured to keep the quality of these images, so they represent accurately the original artefact. Although occasionally there may be certain imperfections with these old texts, we feel they deserve to be made available for future generations to enjoy.

Finite Sample Properties of Some Alternative Gmm Estimators - Scholar's Choice Edition

Finite Sample Properties of Some Alternative Gmm Estimators - Scholar's Choice Edition
Author: Lars Peter Hansen
Publisher: Scholar's Choice
Total Pages: 66
Release: 2015-02-15
Genre:
ISBN: 9781297030888

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

Reliable Inference for GMM Estimators? Finite Sample Properties of Alternative Test Procedures in Linear Panel Data Models

Reliable Inference for GMM Estimators? Finite Sample Properties of Alternative Test Procedures in Linear Panel Data Models
Author: Stephen R. Bond
Publisher:
Total Pages: 0
Release: 2005
Genre:
ISBN:

We compare the finite sample performance of a range of tests of linear restrictions for linear panel data models estimated using Generalised Method of Moments (GMM). These include standard asymptotic Wald tests based on one-step and two-step GMM estimators; two bootstrapped versions of these Wald tests; a version of the two-step Wald test that uses a finite sample corrected estimate of the variance of the two-step GMM estimator; the LM test; and three criterion-based tests that have recently been proposed. We consider both the AR(1) panel model, and a design with predetermined regressors. The corrected two-step Wald test performs similarly to the standard one-step Wald test, whilst the bootstrapped one-step Wald test, the LM test, and a simple criterion-difference test can provide more reliable finite sample inference in some cases.

Generalized Method of Moments Estimation

Generalized Method of Moments Estimation
Author: Laszlo Matyas
Publisher: Cambridge University Press
Total Pages: 332
Release: 1999-04-13
Genre: Business & Economics
ISBN: 9780521669672

The generalized method of moments (GMM) estimation has emerged as providing a ready to use, flexible tool of application to a large number of econometric and economic models by relying on mild, plausible assumptions. The principal objective of this volume is to offer a complete presentation of the theory of GMM estimation as well as insights into the use of these methods in empirical studies. It is also designed to serve as a unified framework for teaching estimation theory in econometrics. Contributors to the volume include well-known authorities in the field based in North America, the UK/Europe, and Australia. The work is likely to become a standard reference for graduate students and professionals in economics, statistics, financial modeling, and applied mathematics.

Asymptotics for GMM Estimators with Weak Instruments

Asymptotics for GMM Estimators with Weak Instruments
Author: James H. Stock
Publisher:
Total Pages: 60
Release: 1996
Genre: Asymptotic distribution (Probability theory)
ISBN:

This paper develops asymptotic distribution theory for generalized method of moments (GMM) estimators and test statistics when some of the parameters are well identified, but others are poorly identified because of weak instruments. The asymptotic theory entails applying empirical process theory to obtain a limiting representation of the (concentrated) objective function as a stochastic process. The general results are specialized to two leading cases, linear instrumental variables regression and GMM estimation of Euler equations obtained from the consumption-based capital asset pricing model with power utility. Numerical results of the latter model confirm that finite sample distributions can deviate substantially from normality, and indicate that these deviations are captured by the weak instrument asymptotic approximations.

A Finite Sample Correction for the Variance of Linear Efficient Two-Step GMM Estimators

A Finite Sample Correction for the Variance of Linear Efficient Two-Step GMM Estimators
Author: Frank Windmeijer
Publisher:
Total Pages: 0
Release: 2005
Genre:
ISBN:

Monte Carlo studies have shown that estimated asymptotic standard errors of the efficient two-step generalised method of moments (GMM) estimator can be severely downward biased in small samples. The weight matrix used in the calculation of the efficient two-step GMM estimator is based on initial consistent parameter estimates. In this paper it is shown that the extra variation due to the presence of these estimated parameters in the weight matrix accounts for much of the difference between the finite sample and the usual asymptotic variance of the two-step GMM estimator, when the moment conditions used are linear in the parameters. This difference can be estimated, resulting in a finite sample corrected estimate of the variance. In a Monte Carlo study of a panel data model it is shown that the corrected variance estimate approximates the finite sample variance well, leading to more accurate inference.