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Author : Luke Taylor
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (16 download)
Download or read book Essays in Nonparametric Estimation and Inference written by Luke Taylor and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (953 download)
Download or read book Essays on Nonparametric Inference and Instrument Selection written by and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: My dissertation consists of two chapters on nonparametric inference and model selection in econometric models. First chapter constructs inference methods for nonparametric series regression models and introduces tests based on the infimum of t-statistics over different series terms. First, I provide a uniform asymptotic theory for the t-statistic process indexed by the number of series terms. Using this result, I show that the test based on the infimum of the t-statistics and its asymptotic critical value controls the asymptotic size with the undersmoothing condition. We can construct a valid confidence interval (CI) by test statistic inversion that has correct asymptotic coverage probability. Even when asymptotic bias terms are present without the undersmoothing condition, I show that the CI based on the infimum of the t-statistics bounds the coverage distortions. In an illustrative example, nonparametric estimation of wage elasticity of the expected labor supply from Blomquist and Newey (2002), proposed CI is close to or tighter than those based on existing methods with possibly ad hoc choice of series terms. Second chapter provides instrument selection criteria in instrumental variable (IV) regression model when there is a large set of instruments with potential invalidity. Economic data identified by IV model sometimes involve large sets of potential instruments and debates about their validity. Existing methods for instrument selection are largely based on a priori assumption of an instrument's validity and/or based on the first-order asymptotics, which may lead to a large finite sample bias with many and invalid instruments. First, I derive higher-order mean square error (MSE) approximation for two-stage least squares (2SLS), limited information maximum likelihood (LIML), modified Fuller (FULL) and bias-adjusted 2SLS (B2SLS) estimator allowing locally invalid instruments. Based on the approximation to the higher-order MSE, I propose an invalidity-robust instrument selection criteria (IRC) that capture two sources of finite sample bias at the same time: bias from using many instruments and bias from invalid instruments. I also show optimality result of choice of instruments based on the criteria of Donald and Newey (2001) under certain locally invalid instruments specification.
Author : Dev Basu
Publisher : IMS
ISBN 13 : 9780940600249
Total Pages : 278 pages
Book Rating : 4.6/5 (2 download)
Download or read book Current Issues in Statistical Inference written by Dev Basu and published by IMS. This book was released on 1992 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Benjamin William Deaner
Publisher :
ISBN 13 :
Total Pages : 212 pages
Book Rating : 4.:/5 (133 download)
Download or read book Essays in Econometrics: Nonparametrics and Robustness written by Benjamin William Deaner and published by . This book was released on 2021 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heterogeneity and my key identifying assumptions follow from restrictions on the serial dependence structure.
Author : Seonjin Kim
Publisher :
ISBN 13 :
Total Pages : 103 pages
Book Rating : 4.:/5 (862 download)
Download or read book Three Essays on Nonparametric Inference for Longitudinal Data and Time Series Data written by Seonjin Kim and published by . This book was released on 2013 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Donald W. K. Andrews
Publisher : Cambridge University Press
ISBN 13 : 1139444603
Total Pages : 589 pages
Book Rating : 4.1/5 (394 download)
Download or read book Identification and Inference for Econometric Models written by Donald W. K. Andrews and published by Cambridge University Press. This book was released on 2005-07-04 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 2005 volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose others. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.
Author : Neng-Chieh Chang
Publisher :
ISBN 13 :
Total Pages : 134 pages
Book Rating : 4.:/5 (122 download)
Download or read book Three Essays on Causal Inference with High-dimensional Data and Machine Learning Methods written by Neng-Chieh Chang and published by . This book was released on 2020 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation consists of three chapters that study causal inference when applying machinelearning methods. In Chapter 1, I propose an orthogonal extension of the semiparametric difference-in-differences estimator proposed in Abadie (2005). The proposed estimator enjoys the so-called Neyman-orthogonality (Chernozhukov et al. 2018) and thus it allows researchers to flexibly use a rich set of machine learning (ML) methods in the first-step estimation. It is particularly useful when researchers confront a high-dimensional data set when the number of potential control variables is larger than the sample size and the conventional nonparametric estimation methods, such as kernel and sieve estimators, do not apply. I apply this orthogonal difference-in-differences estimator to evaluate the effect of tariff reduction on corruption. The empirical results show that tariff reduction decreases corruption in large magnitude. In Chapter 2, I study the estimation and inference of the mode treatment effect. Mean,median, and mode are three essential measures of the centrality of probability distributions. In program evaluation, the average treatment effect (mean) and the quantile treatment effect (median) have been intensively studied in the past decades. The mode treatment effect, however, has long been neglected in program evaluation. This paper fills the gap by discussing both the estimation and inference of the mode treatment effect. I propose both traditional kernel and machine learning methods to estimate the mode treatment effect. I also derive the asymptotic properties of the proposed estimators and find that both estimators follow the asymptotic normality but with the rate of convergence slower than the regular rate N^1/2, which is different from the rates of the classical average and quantile treatment effect estimators. In Chapter 3 (joint with Liqiang Shi), we study the estimation and inference of the doublyrobust extension of the semiparametric quantile treatment effect estimation discussed in Firpo (2007). This proposed estimator allows researchers to use a rich set of machine learning methods in the first-step estimation, while still obtaining valid inferences. Researchers can include as many control variables as they consider necessary, without worrying about the over-fitting problem which frequently happens in the traditional estimation methods. This paper complements Belloni et al. (2017), which provided a very general framework to discuss the estimation and inference of many different treatment effects when researchers apply machine learning methods.
Author : Vijay Nair
Publisher : World Scientific
ISBN 13 : 9812708294
Total Pages : 698 pages
Book Rating : 4.8/5 (127 download)
Download or read book Advances in Statistical Modeling and Inference written by Vijay Nair and published by World Scientific. This book was released on 2007 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: There have been major developments in the field of statistics over the last quarter century, spurred by the rapid advances in computing and data-measurement technologies. These developments have revolutionized the field and have greatly influenced research directions in theory and methodology. Increased computing power has spawned entirely new areas of research in computationally-intensive methods, allowing us to move away from narrowly applicable parametric techniques based on restrictive assumptions to much more flexible and realistic models and methods. These computational advances have also led to the extensive use of simulation and Monte Carlo techniques in statistical inference. All of these developments have, in turn, stimulated new research in theoretical statistics. This volume provides an up-to-date overview of recent advances in statistical modeling and inference. Written by renowned researchers from across the world, it discusses flexible models, semi-parametric methods and transformation models, nonparametric regression and mixture models, survival and reliability analysis, and re-sampling techniques. With its coverage of methodology and theory as well as applications, the book is an essential reference for researchers, graduate students, and practitioners.
Author : Liquan Huang
Publisher :
ISBN 13 :
Total Pages : 105 pages
Book Rating : 4.:/5 (1 download)
Download or read book Essays on Identification, Estimation and Testing Using Nonparametric Methods written by Liquan Huang and published by . This book was released on 2015 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This dissertation is a collection of two papers studying the identification, estimation and testing of Econometrics problems using nonparametric methods. In Chapter 1, we study the estimation and testing of structural changes in panel data models with cross-sectional dependence and local stationarity. Instead of focusing on detection of abrupt structural changes, we consider smooth structural changes for which model parameters are unknown deterministic smooth functions of time, except for a finite number of time points. Such smooth alternatives are expected to be more realistic than sudden structural changes. We use nonparametric local smoothing method to consistently estimate the smooth changing parameters and develop two consistent tests for smooth structural changes in panel data models. The first test is to check whether all model parameters are stable over time. The second test is to check potential time-varying interaction while allowing for a common trend. Both tests have an asymptotic N (0, 1) distribution under the null hypothesis of parameter constancy and are consistent against a vast class of smooth structural changes as well as abrupt structural breaks with possibly unknown break points alternatives. Simulation studies show that the tests provide reliable inference in finite samples. Applying our tests to the cross-country growth accounting model using 14 OECD (Organisation for Economic Co-operation and Development) countries, we find instability in the model parameters. In Chapter 2, we study an under-identified triangular system of equations model that has k endogenous variables, but only strictly less than k excluded instrumental variables (k = 1, 2, ...). We consider a partially linear model. The endogenous variables for which excluded instruments are available are allowed to have a non-parametric effect. The linear part contains the endogenous variables (and higher order moments and interactions of these) for which we have no excluded instruments. Without the availability of additional instrumental variables, we exploit the additive separability in the partially linear model to generate additional exogenous variation that allows us to identify the coefficients of the endogenous regressors for which no excluded instruments are available. An easy-to-implement consistent estimator for the parametric part is presented. By applying the empirical process methods, we show that the estimator retains ?n-convergence rate and asymptotic normality even with the presence of generated regressors (when k > 1). The nonparametric part of the model is identified, and can be estimated with the standard nonparametric convergence rate. Monte Carlo simulation demonstrates our estimator performs well in finite samples."--Pages v-vi.
Author : R. Carter Hill
Publisher : Emerald Group Publishing
ISBN 13 : 1785607863
Total Pages : 680 pages
Book Rating : 4.7/5 (856 download)
Download or read book Essays in Honor of Aman Ullah written by R. Carter Hill and published by Emerald Group Publishing. This book was released on 2016-06-29 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume 36 of Advances in Econometrics recognizes Aman Ullah's significant contributions in many areas of econometrics and celebrates his long productive career.
Author : Badi H. Baltagi
Publisher : Emerald Group Publishing
ISBN 13 : 1781903085
Total Pages : 576 pages
Book Rating : 4.7/5 (819 download)
Download or read book Essays in Honor of Jerry Hausman written by Badi H. Baltagi and published by Emerald Group Publishing. This book was released on 2012-12-17 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aims to annually publish original scholarly econometrics papers on designated topics with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business and social science literature.
Author : Yan Liu
Publisher : Springer Nature
ISBN 13 : 9819908035
Total Pages : 591 pages
Book Rating : 4.8/5 (199 download)
Download or read book Research Papers in Statistical Inference for Time Series and Related Models written by Yan Liu and published by Springer Nature. This book was released on 2023-05-31 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book compiles theoretical developments on statistical inference for time series and related models in honor of Masanobu Taniguchi's 70th birthday. It covers models such as long-range dependence models, nonlinear conditionally heteroscedastic time series, locally stationary processes, integer-valued time series, Lévy Processes, complex-valued time series, categorical time series, exclusive topic models, and copula models. Many cutting-edge methods such as empirical likelihood methods, quantile regression, portmanteau tests, rank-based inference, change-point detection, testing for the goodness-of-fit, higher-order asymptotic expansion, minimum contrast estimation, optimal transportation, and topological methods are proposed, considered, or applied to complex data based on the statistical inference for stochastic processes. The performances of these methods are illustrated by a variety of data analyses. This collection of original papers provides the reader with comprehensive and state-of-the-art theoretical works on time series and related models. It contains deep and profound treatments of the asymptotic theory of statistical inference. In addition, many specialized methodologies based on the asymptotic theory are presented in a simple way for a wide variety of statistical models. This Festschrift finds its core audiences in statistics, signal processing, and econometrics.
Author : Byunghoon Kang
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (16 download)
Download or read book Essays on Nonparametric Inference and Instrument Selection written by Byunghoon Kang and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jian Zhang (Ph.D.)
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Essays in Transformation Models written by Jian Zhang (Ph.D.) and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Chapter 1, I study the estimation and inference of transformation models in the presence of a high dimensional set of control variables. In the study, I consider a generalized form of the transformed model, which includes the traditional transformed model, binary choice model, and generalized accelerated failure time model as special cases. I include both low dimensional covariates of interest and high dimensional control variables in this model. The estimation of high dimension nuisance parameters could lead to substantial bias and thus incorrect inference on parameters of interest. I provide a double-machine learning estimator to reduce this substantial bias and obtain a root-n-consistent and asymptotically normal results. According to the simulation study, I compare the performance of our estimator with the classical estimator based on average partial derivatives, it turns out that our estimator has less bias and provides correct inference results. Finally, I use an empirical example to illustrate the performance of our estimator in real data. In Chapter 2, I study the specification test for a generalized additive model (a.k.a. GAM) with an unknown link function. GAM is widely used to reduce the curse of dimensionality in nonparametric estimation. Additive Model is a special case when the link function is known by econometricians to be an identity. Under some regular conditions, I derive a sufficient and necessary condition when a function can be written as a GAM, which turns out to be a partial differential equation. This equation implies countably many restrictions on the coefficients from a simple polynomial series estimation, which forms the base of our test. Therefore, our test doesn't need to run a GAM estimation. Instead, I use an ``unrestricted'' series regression estimation with polynomial basis functions and make a statistical inference on its coefficients. The asymptotic properties of the test statistics are derived. The asymptotic distribution is the Chi-squared distribution with an increasing degree of freedom. A Monte Carlo study is shown for the case with two variables.
Author : Jian Zhang
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Essays in Transformation Models written by Jian Zhang and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Chapter 1, I study the estimation and inference of transformation models in the presence of a high dimensional set of control variables. In the study, I consider a generalized form of the transformed model, which includes the traditional transformed model, binary choice model, and generalized accelerated failure time model as special cases. I include both low dimensional covariates of interest and high dimensional control variables in this model. The estimation of high dimension nuisance parameters could lead to substantial bias and thus incorrect inference on parameters of interest. I provide a double-machine learning estimator to reduce this substantial bias and obtain a root-n-consistent and asymptotically normal results. According to the simulation study, I compare the performance of our estimator with the classical estimator based on average partial derivatives, it turns out that our estimator has less bias and provides correct inference results. Finally, I use an empirical example to illustrate the performance of our estimator in real data. In Chapter 2, I study the specification test for a generalized additive model (a.k.a. GAM) with an unknown link function. GAM is widely used to reduce the curse of dimensionality in nonparametric estimation. Additive Model is a special case when the link function is known by econometricians to be an identity. Under some regular conditions, I derive a sufficient and necessary condition when a function can be written as a GAM, which turns out to be a partial differential equation. This equation implies countably many restrictions on the coefficients from a simple polynomial series estimation, which forms the base of our test. Therefore, our test doesn't need to run a GAM estimation. Instead, I use an ``unrestricted'' series regression estimation with polynomial basis functions and make a statistical inference on its coefficients. The asymptotic properties of the test statistics are derived. The asymptotic distribution is the Chi-squared distribution with an increasing degree of freedom. A Monte Carlo study is shown for the case with two variables.
Author : Thomas B. Fomby
Publisher : Emerald Group Publishing
ISBN 13 : 1784411825
Total Pages : 772 pages
Book Rating : 4.7/5 (844 download)
Download or read book Essays in Honor of Peter C. B. Phillips written by Thomas B. Fomby and published by Emerald Group Publishing. This book was released on 2014-11-21 with total page 772 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume honors Professor Peter C.B. Phillips' many contributions to the field of econometrics. The topics include non-stationary time series, panel models, financial econometrics, predictive tests, IV estimation and inference, difference-in-difference regressions, stochastic dominance techniques, and information matrix testing.
Author : Wang, Xi
Publisher :
ISBN 13 :
Total Pages : 87 pages
Book Rating : 4.:/5 (952 download)
Download or read book Essays on Semiparametric and Nonparametric Estimation of Nonlinear Panel Data Models written by Wang, Xi and published by . This book was released on 2015 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt:
