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9781334433986: Finite Sample Properties of Some Alternative Gmm Estimators (Classic Reprint)

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The digital edition of all books may be viewed on our website before purchase. Excerpt from Finite Sample Properties of Some Alternative Gmm Estimators



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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. This text has been digitally restored from a historical edition. Some errors may persist, however we consider it worth publishing due to the work's historical value.The digital edition of all books may be viewed on our website before purchase.

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  • ÉditeurForgotten Books
  • Date d'édition2024
  • ISBN 10 1334433984
  • ISBN 13 9781334433986
  • ReliureBroché
  • Langueanglais
  • Nombre de pages65

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Lars Peter Hansen
Edité par Forgotten Books, 2018
ISBN 10 : 1334433984 ISBN 13 : 9781334433986
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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur LW-9781334433986

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Lars Peter Hansen
Edité par Forgotten Books, 2018
ISBN 10 : 1334433984 ISBN 13 : 9781334433986
Neuf PAP

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PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur LW-9781334433986

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Lars Peter Hansen, John Heaton
Edité par Forgotten Books, 2024
ISBN 10 : 1334433984 ISBN 13 : 9781334433986
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Paperback. Etat : New. Print on Demand. This book dissects the limitations of traditional econometric methods commonly used in the study of asset pricing models. The author proposes alternative estimators that are asymptotically efficient. These methods are categorized into two-step, iterative, and continuous-updating estimators. The author then compares the finite sample properties of each, including bias, efficiency, coverage accuracy, and power. Using simulations calibrated to monthly and annual time series data, the author demonstrates that two-step and iterative estimators often suffer from severe finite sample biases and exhibit substantial size distortions in tests of overidentifying restrictions. In contrast, the continuous-updating estimator performs well, even in small samples, and often outperforms the other estimators. Notably, the continuous-updating estimator is invariant to how the moment conditions are scaled. The author's findings suggest that researchers should reconsider their traditional reliance on two-step and iterative GMM estimators in favor of continuous-updating GMM, especially when sample sizes are small or when the moment conditions are nonlinear in the parameters of interest. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. N° de réf. du vendeur 9781334433986_0

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