Download or read book Efficient Estimation in the Generalized Semilinear Model written by Mary Jane Emond and published by . This book was released on 1993 with total page 178 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 Journal of the American Statistical Association written by and published by . This book was released on 2005 with total page 1526 pages. Available in PDF, EPUB and Kindle. Book excerpt: A scientific and educational journal not only for professional statisticians but also for economists, business executives, research directors, government officials, university professors, and others who are seriously interested in the application of statistical methods to practical problems, in the development of more useful methods, and in the improvement of basic statistical data.
Download or read book Efficient Estimation with Missing Values in Cross Section and Panel Data written by Bhavna Rai and published by . This book was released on 2021 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter 1: Efficient Estimation with Missing Data and EndogeneityI study the problem of missing values in both the outcome and the covariates in linear models with endogenous covariates. I propose an estimator that improves efficiency relative to a Two Stage Least Squares (2SLS) based only on the complete cases. My framework also unifies the literature on missing data and combining data sets, and includes the "Two-Sample 2SLS" as a special case. The method is an extension of Abrevaya and Donald (2017), who provide methods of improving efficiency over complete cases estimators in linear models with cross-section data and missing covariates. I also provide guidance on dealing with missing values in the instruments and in commonly used nonlinear functions of the endogenous covariates, likes squares and interactions, without introducing inconsistency in the estimates.Chapter 2: Imputing Missing Covariate Values in Nonlinear ModelsI study the problem of missing covariate values in nonlinear models with continuous or discrete covariates. In order to use the information in the incomplete cases, I propose an inverse probability weighted one-step imputation estimator that provides gains in efficiency relative to the complete cases estimator using a reduced form for the outcome in terms of the always-observed covariates. Unlike the two-step imputation and dummy variable methods commonly used in empirical work ,my estimator is consistent for a wide class of nonlinear models. It relies only on the commonly used "missing at random" assumption, and provides a specification test for the resulting restrictions. I show how the results apply to nonlinear models for fractional and nonnegative responses.Chapter 3: Efficient Estimation of Linear Panel Data Models with Missing CovariatesWe study the problem of missing covariates in the context of linear, unobserved effects panel data models. In order to use information on incomplete cases, we propose generalized method of moments (GMM) estimation. By using information on the incomplete cases from all time periods, the proposed estimators provide gains in efficiency relative to the fixed effects (and Mundlak) estimator that use only the complete cases. The method is an extension of Abrevaya and Donald(2017), who consider a linear model with cross-sectional data and incorporate the linear imputation method in the set of moment conditions to obtain gains in efficiency. Our first proposed estimator uses the assumption of strict exogeneity of the covariates as well as the selection, while allowing the selection to be correlated with the observed covariates and unobserved heterogeneity in both the outcome equation and the imputation equation. We also consider the case in which the covariates are only sequentially exogenous and propose an estimator based on the method of forward orthogonal deviations introduced by Arellano and Bover (1995). Our framework suggests a simple test for whether selection is correlated with unobserved shocks, both contemporaneous and those in other time periods.
Download or read book Efficient and Adaptive Estimation for Semiparametric Models written by Peter J. Bickel and published by Springer. This book was released on 1998-06-01 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with estimation in situations in which there is believed to be enough information to model parametrically some, but not all of the features of a data set. Such models have arisen in a wide context in recent years, and involve new nonlinear estimation procedures. Statistical models of this type are directly applicable to fields such as economics, epidemiology, and astronomy.
Download or read book A Simple and Efficient Estimation Method for Models with Nonignorable Missing Data written by Chunrong Ai and published by . This book was released on 2018 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a simple and efficient estimation procedure for the model with non-ignorable missing data studied by Morikawa and Kim (2016). Their semiparametrically efficient estimator requires explicit nonparametric estimation and so suffers from the curse of dimensionality and requires a bandwidth selection. We propose an estimation method based on the Generalized Method of Moments (hereafter GMM). Our method is consistent and asymptotically normal regardless of the number of moments chosen. Furthermore, if the number of moments increases appropriately our estimator can achieve the semiparametric efficiency bound derived in Morikawa and Kim (2016), but under weaker regularity conditions. Moreover, our proposed estimator and its consistent covariance matrix are easily computed with the widely available GMM package. We propose two data-based methods for selection of the number of moments. A small scale simulation study reveals that the proposed estimation indeed out-performs the existing alternatives in finite samples.
Download or read book Efficient Estimation in the Two sample Semiparametric Location scale Model and the Orientation Shift Model written by Byeong Uk Park and published by . This book was released on 1987 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Investigating Efficiency of Estimation in the Generalized Analysis of Variance Model written by Erkki P. Liski and published by . This book was released on 1986 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Efficient Estimation in Semiparametric GARCH Models written by Feike C. Drost and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is well-knownthat financial data sets exhibit conditional heteroskedasticity. GARCH type models are often used to model this phenomenon. Since the distribution of the rescaled innovations is generally far froma normal distribution, a semiparametric approach is advisable. Several publications observed that adaptive estimation of the Euclidean parameters is not possible in the usual parametrization when the distribution of the rescaled innovations is the unknown nuisance parameter. However, there exists a reparametrization such that the efficient score functions in the parametric model of the autoregression parameters are orthogonal to the tangent space generated by the nuisance parameter, thus suggesting that adaptive estimation of the autoregression parameters is possible. Indeed, we construct adaptive and hence efficient estimators in a general GARCH in mean type context including integrated GARCH models. Our analysis is based on a general LAN Theorem for time-series models, published elsewhere. In contrast to recent literature about ARCH models we do not need any moment condition.
Download or read book Generalized Estimating Equations written by James W. Hardin and published by CRC Press. This book was released on 2012-12-10 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generalized Estimating Equations, Second Edition updates the best-selling previous edition, which has been the standard text on the subject since it was published a decade ago. Combining theory and application, the text provides readers with a comprehensive discussion of GEE and related models. Numerous examples are employed throughout the text, al
Download or read book Efficient Estimation of Additive Partially Linear Models written by Qi Li and published by . This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: I consider the problem of estimating an additive partially linear model using general series estimation methods with polynomial and splines as two leading cases. I show that the finite-dimensional parameter is identified under weak conditions. I establish the root-n-normality result for the finite-dimensional parameter in the linear part of the model and show that it is asymptotically more efficient than a semiparametric estimator that ignores the additive structure. When the error is conditional homoskedastic, my finite-dimensional parameter estimator reaches the semiparametric efficiency bound. Efficient estimation when the error is conditional heteroskedastic is also discussed.
Download or read book Efficient Estimation of a Semiparametric Partially Linear Smooth Coefficient Model written by Sittisak Leelahanon and published by . This book was released on 2002 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Efficient Estimation in Marginal Partially Linear Models for Longitudinal clustered Data Using Splines written by Liangyue Zhang and published by . This book was released on 2004 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Efficient Estimation in Semiparametric Models written by Thomas Alan Severini and published by . This book was released on 1987 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Efficient Estimation with a Priori Information written by Thomas J. Rothenberg and published by . This book was released on 1973 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book System Identification written by Rik Pintelon and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electrical Engineering System Identification A Frequency Domain Approach How does one model a linear dynamic system from noisy data? This book presents a general approach to this problem, with both practical examples and theoretical discussions that give the reader a sound understanding of the subject and of the pitfalls that might occur on the road from raw data to validated model. The emphasis is on robust methods that can be used with a minimum of user interaction. Readers in many fields of engineering will gain knowledge about: * Choice of experimental setup and experiment design * Automatic characterization of disturbing noise * Generation of a good plant model * Detection, qualification, and quantification of nonlinear distortions * Identification of continuous- and discrete-time models * Improved model validation tools and from the theoretical side about: * System identification * Interrelations between time- and frequency-domain approaches * Stochastic properties of the estimators * Stochastic analysis System Identification: A Frequency Domain Approach is written for practicing engineers and scientists who do not want to delve into mathematical details of proofs. Also, it is written for researchers who wish to learn more about the theoretical aspects of the proofs. Several of the introductory chapters are suitable for undergraduates. Each chapter begins with an abstract and ends with exercises, and examples are given throughout.
Download or read book On Efficient Estimation and Correct Inference in Models with Generated Regressors written by C. R. McKenzie and published by . This book was released on 1990 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
