Download or read book Adaptive GMM Shrinkage Estimation with Consistent Moment Selection written by Zhipeng Liao and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a GMM shrinkage method to efficiently estimate the unknown parameters identified by some moment restrictions, when there is another set of possibly misspecified moment conditions. We show that our method enjoys oracle-like properties, i.e. it consistently selects the correct moment conditions in the second set and at the same time, its estimator achieves the semi-parametric efficiency bound implied by all correct moment conditions. For empirical implementation, we provide a simple data-driven procedure for selecting the tuning parameters of the penalty function. We also establish oracle properties of the GMM shrinkage method in the practically important scenario where the moment conditions in the first set fail to strongly identify the structural parameters. The simulation results show that the method works well in terms of correct moment selection and the finite sample properties of its estimators. As an empirical illustration, we apply our method to estimate the life-cycle labor supply equation studied in MaCurdy (1981) and Altonji (1986). Our empirical findings support the validity of the IVs used in both papers and confirm that wage is an endogenous variable in the labor supply equation.

Download or read book Select the Valid and Relevant Moments written by Xu Cheng and published by . This book was released on 2013 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper studies the selection of valid and relevant moments for the generalized method of moments (GMM) estimation. For applications with many candidate moments, our asymptotic analysis accommodates a diverging number of moments as the sample size increases. The proposed procedure achieves three objectives in one-step: (i) the valid and relevant moments are distinguished from the invalid or irrelevant ones; (ii) all desired moments are selected in one step instead of in a stepwise manner; (iii) the parameters of interest are automatically estimated with all selected moments as opposed to a post-selection estimation. The new method performs moment selection and efficient estimation simultaneously via an information-based adaptive GMM shrinkage estimation, where an appropriate penalty is attached to the standard GMM criterion to link moment selection to shrinkage estimation. The penalty is designed to signal both moment validity and relevance for consistent moment selection. We develop asymptotic results for the high-dimensional GMM shrinkage estimator, allowing for non-smooth sample moments and weakly dependent observations. For practical implementation, this one-step procedure is computationally attractive.

Download or read book Select the Valid and Relevant Moments written by Xu Cheng and published by . This book was released on 2016 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper considers the selection of valid and relevant moments for the generalized method of moments (GMM) estimation. For applications with many candidate moments, our asymptotic analysis accommodates a diverging number of moments as the sample size increases. The proposed procedure achieves three objectives in one-step: (i) the valid and relevant moments are selected simultaneously rather than sequentially; (ii) all desired moments are selected together instead of in a stepwise manner; (iii) the parameter of interest is automatically estimated with all selected moments as opposed to a post-selection estimation. The new moment selection method is achieved via an information-based adaptive GMM shrinkage estimation, where an appropriate penalty is attached to the standard GMM criterion to link moment selection to shrinkage estimation. The penalty is designed to signal both moment validity and relevance for consistent moment selection and efficient estimation. The asymptotic analysis allows for non-smooth sample moments and weakly dependent observations, making it generally applicable. For practical implementation, this one-step procedure is computationally attractive.

Download or read book Adaptive Elastic Net GMM Estimation with Many Invalid Moment Conditions written by Mehmet Caner and published by . This book was released on 2016 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper develops the adaptive elastic net GMM estimator in large dimensional models with potentially (locally) invalid moment conditions, where both the number of structural parameters and the number of moment conditions may increase with the sample size. The basic idea is to conduct the standard GMM estimation combined with two penalty terms: the adaptively weighted lasso shrinkage and the quadratic regularization. It is a one-step procedure of valid moment condition selection, nonzero structural parameter selection (i.e., model selection), and consistent estimation of the nonzero parameters. The procedure achieves the standard GMM efficiency bound as if we know the valid moment conditions ex ante, for which the quadratic regularization is important. We also study the tuning parameter choice, with which we show that selection consistency still holds without assuming Gaussianity. We apply the new estimation procedure to dynamic panel data models, where both the time and cross section dimensions are large. The new estimator is robust to possible serial correlations in the regression error terms.

Download or read book The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics written by Jeffrey Racine and published by Oxford University Press. This book was released on 2014-04 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures.

Download or read book Consistent Model and Moment Selection Criteria for GMM Estimation with Application to Dynamic Panel Data Models written by Donald W. K. Andrews and published by . This book was released on 1999 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Consistent Model and Moment Selection Procedures for GMM Estimation with Application to Dynamic Panel Data Models written by Donald W. K. Andrews and published by . This book was released on 2001 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Generalized Method of Moments Estimation written by Laszlo Matyas and published by Cambridge University Press. This book was released on 1999-04-13 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book CONSISTENT MODEL AND MOMENT SELECTION CRITERIA FOR GMM ESTIMATION WITH APPLICATION TO DYNAMIC PANEL DATA MODLES written by Donald W.K. ANDREWS and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Rate adaptive Generalized Method of Moments Estimations for Linear Time Series Models written by Guido Kuersteiner and published by . This book was released on 2002 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we analyze Generalized Method of Moments (GMM) estimators for time series models as advocated by Hansen and Singleton. It is well known that these estimators achieve efficiency bounds if the number of lagged observations in the instrument set goes to infinity. However, to this date no data dependent way of selecting the number of instruments in a finite sample is available. This paper derives an asymptotic mean squared error (MSE) approximation for the GMM estimator. The optimal number of instruments is selected by minimizing a criterion based on the MSE approximation. It is shown that the fully feasible version of the GMM estimator is higher order adaptive. In addition a new version of the GMM estimator based on kernel weighted moment conditions is proposed. The kernel weights are selected in a data-dependent way. Expressions for the asymptotic bias of kernel weighted and standard GMM estimators are obtained. It is shown that standard GMM procedures have a larger asymptotic bias and MSE than optimal kernel weighted GMM. A bias correction for both standard and kernel weighted GMM estimators is proposed. It is shown that the bias corrected version achieves a faster rate of convergence of the higher order terms of the MSE than the uncorrected estimator. Keywords: Time Series, Feasible GMM, Number of Instruments, Rate-adaptive Kernels, Higher Order Adaptive, Bias Correction. JEL Classification: C13, C32.

Download or read book Consistent Moment Selection Procedures for Generalized Method of Moments Estimation written by Donald W. K. Andrews and published by . This book was released on 1996 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book GMM with Many Moment Conditions written by Chirok Han and published by . This book was released on 2005 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Three Essays on Generalized Method of Moments written by Artem B. Prokhorov and published by . This book was released on 2006 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Rate Adapative GMM Estimators for Linear Time Series Models written by Guido M. Kuersteiner and published by . This book was released on 2003 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we analyze Generalized Method of Moments (GMM) estimators for time series models as advocated by Hansen and Singleton. It is well known that these estimators achieve efficiency bounds if the number of lagged observations in the instrument set goes to infinity. However, to this date no data dependent way of selecting the number of instruments in a finite sample is available. This paper derives an asymptotic mean squared error (MSE) approximation for the GMM estimator. The optimal number of instruments is selected by minimizing a criterion based on the MSE approximation. It is shown that the fully feasible version of the GMM estimator is higher order adaptive. In addition a new version of the GMM estimator based on kernel weighted moment conditions is proposed. The kernel weights are selected in a data-dependent way. Expressions for the asymptotic bias of kernel weighted and standard GMM estimators are obtained. It is shown that standard GMM procedures have a larger asymptotic bias and MSE than optimal kernel weighted GMM. A bias correction for both standard and kernel weighted GMM estimators is proposed. It is shown that the bias corrected version achieves a faster rate of convergence of the higher order terms of the MSE than the uncorrected estimator.

Download or read book Model Selection and Model Averaging written by Gerda Claeskens and published by . This book was released on 2008-07-28 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: First book to synthesize the research and practice from the active field of model selection.

Download or read book Statistical Foundations of Data Science written by Jianqing Fan and published by CRC Press. This book was released on 2020-09-21 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.

Download or read book Econometric Analysis of Panel Data written by Badi Baltagi and published by John Wiley & Sons. This book was released on 2008-06-30 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by one of the world's leading researchers and writers in the field, Econometric Analysis of Panel Data has become established as the leading textbook for postgraduate courses in panel data. This new edition reflects the rapid developments in the field covering the vast research that has been conducted on panel data since its initial publication. Featuring the most recent empirical examples from panel data literature, data sets are also provided as well as the programs to implement the estimation and testing procedures described in the book. These programs will be made available via an accompanying website which will also contain solutions to end of chapter exercises that will appear in the book. The text has been fully updated with new material on dynamic panel data models and recent results on non-linear panel models and in particular work on limited dependent variables panel data models.