Essays On Non Normality Nonparametrics And Cross Sectional Dependence In Panel Data

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Essays On Non Normality Nonparametrics And Cross Sectional Dependence In Panel Data

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Author : Xiao Huang
language : en
Publisher:
Release Date : 2005

Essays On Non Normality Nonparametrics And Cross Sectional Dependence In Panel Data written by Xiao Huang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Econometric models categories.

Essays On Identification Estimation And Testing Using Nonparametric Methods

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Author : Liquan Huang
language : en
Publisher:
Release Date : 2015

Essays On Identification Estimation And Testing Using Nonparametric Methods written by Liquan Huang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Econometric models categories.

"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.

Dissertation Abstracts International

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Author :
language : en
Publisher:
Release Date : 2007-10

Dissertation Abstracts International written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10 with Dissertations, Academic categories.

A New Diagnostic Test For Cross Section Independence In Nonparametric Panel Data Model

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Author : Jia Chen
language : en
Publisher:
Release Date : 2009

A New Diagnostic Test For Cross Section Independence In Nonparametric Panel Data Model written by Jia Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Econometrics categories.

In this paper, we propose a new diagnostic test for residual cross-section independence in a nonparametric panel data model. The proposed nonparametric cross-section dependence (CD) test is a nonparametric counterpart of an existing parametric CD test proposed in Pesaren (2004) for the parametric case. We establish an asymptotic distribution of the proposed test statistic under the null hypothesis. As in the parametric case, the proposed test has an asymptotically normal distribution. We then analyze the power function of the proposed test under an alternative hypothesis that involves a nonlinear multi-factor model. We also provide several numerical examples. The small sample studies show that the nonparametric CD test associated with an asymptotic critical value works well numerically in each individual case. An empirical analysis of a set of CPI data in Australian capital cities is given to examine the applicability of the proposed nonparametric CD test.

Essays In Honor Of Aman Ullah

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Author : R. Carter Hill
language : en
Publisher: Emerald Group Publishing
Release Date : 2016-06-29

Essays In Honor Of Aman Ullah written by R. Carter Hill and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-29 with Business & Economics categories.

Volume 36 of Advances in Econometrics recognizes Aman Ullah's significant contributions in many areas of econometrics and celebrates his long productive career.

Econometric Analysis Of Cross Section And Panel Data Second Edition

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Author : Jeffrey M. Wooldridge
language : en
Publisher: MIT Press
Release Date : 2010-10-01

Econometric Analysis Of Cross Section And Panel Data Second Edition written by Jeffrey M. Wooldridge and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-01 with Business & Economics categories.

The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.

Tests Of No Cross Sectional Error Dependence In Panel Quantile Regressions

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Author : Matei Demetrescu
language : en
Publisher:
Release Date : 2023

Tests Of No Cross Sectional Error Dependence In Panel Quantile Regressions written by Matei Demetrescu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.

This paper argues that cross-sectional dependence (CSD) is an indicator of misspecification in panel quantile regression (QR) rather than just a nuisance that may be accounted for with panel-robust standard errors. This motivates the development of a novel test for panel QR misspecification based on detecting CSD. The test possesses a standard normal limiting distribution under joint N, T asymptotics with restrictions on the relative rate at which N and T go to infinity. A finitesample correction improves the applicability of the test for panels with larger N. An empirical application to housing markets illustrates the use of the proposed cross-sectional dependence test.

Journal Of Economic Literature

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Author :
language : en
Publisher:
Release Date : 2005-12

Journal Of Economic Literature written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12 with Economics categories.

Three Essays On Panel Data Analysis

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Author : Minyu Han
language : en
Publisher:
Release Date : 2021

Three Essays On Panel Data Analysis written by Minyu Han and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Panel analysis categories.

The first chapter, Two-Way Fixed Effects versus Panel Factor Augmented Estimators: Asymptotic Comparison among Pre-testing Procedures, provides asymptotic analyses of pretesting procedures when the slope coefficients are heterogeneous across cross-sectional units. Empirical researchers may wonder whether or not a two-way fixed effects estimator (with individual and time fixed effects) is sufficiently sophisticated to isolate the influence of common shocks on the estimation of slope coefficients. If it is not, practitioners need to run the so-called panel factor augmented regression instead. There are two pre-testing procedures available in the literature: the use of the estimated number of factors and the direct test of estimated factor loading coefficients. This chapter compares the two pre-testing methods asymptotically. Under the presence of the heterogeneous factor loadings, both pre-testing procedures suggest using the Common Correlated Effects (CCE) estimator. By comparing asymptotic variances, this chapter finds that when the slope coefficients are heterogeneous with homogeneous factor loadings, the CCE estimation is, surprisingly, more efficient than the two-way fixed effects estimation. The second chapter, A New Test for Slope Homogeneity in a Panel Regression with Interactive Fixed Effects, proposes a new test for slope homogeneity in a panel regression with interactive fixed effects without any restriction on the relative expansion rate of n, the number of cross-sectional units, and T, the number of periods.This test is based on a comparison of the estimated number of common factors from two regression residuals. The first regression is an unconstrained regression with heterogeneous slope parameters. The second regression is a pooled regression based on the principal components mean group method. Under the slope heterogeneity, this chapter shows that the estimated number of common factors from the first regression residuals is asymptotically smaller than that of the second regression residuals. In the third chapter, Identification of Outliers for Testing Weak ϳ-Convergence, the authors suggest three novel procedures for separating the divergent series from a convergent club. Weak ϳ8́2convergence test is designed to detect whether cross-sectional variances of a panel data of interest show consistent diminution over time. When the panel data of interest includes divergent series, the cross-sectional variances become contaminated, which results in a seemingly divergent behavior. This chapter deals with this problem. We propose three novel detection procedures for identifying divergence series and provide the asymptotic justification. Utilizing Monte Carlo simulations, the finite sample properties are examined. We demonstrate the effectiveness of the newly proposed methods by using infant mortality rates in 42 countries. Even though all infant mortality rates have shown a downward trending behavior over time, the cross-sectional variance of log infant mortality rates is diverging over time. By using the proposed sieving methods, we identify six outliers. After excluding these outliers, the rest of the infant mortality rates are weakly ϳ-converging over time. Altogether, this dissertation provides methods for a better understanding of the source and nature of the cross-sectional dependence in panel data models.

The Oxford Handbook Of Panel Data

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Author : Badi Hani Baltagi
language : en
Publisher: Oxford Handbooks
Release Date : 2015

The Oxford Handbook Of Panel Data written by Badi Hani Baltagi and has been published by Oxford Handbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Business & Economics categories.

Panel data econometrics has evolved rapidly over the past three decades. The field is of both theoretical and practical importance, and methods to deal with micro- and macroeconomic panel data are in high demand from practitioners. Applications in finance, development, trade, marketing, health, labor, and consumer economics attest to the usefulness of these methods in applied economics. THis book is a comprehensive source on panel data. It contains 20 chapters edited by Professor Badi Baltagi--one of the leading econometricians in the area of panel data econometrics--and authored by renowned experts in the field. The chapters are divided into two sections. Part I examines new developments in theory. It includes panel cointegration, dynamic panel data models, incidental parameters and dynamic panel modeling, and panel data models for discrete choice. The chapters in Part II target applications of panel data, including health, labor, marketing, trade, productivity and macro applications in panels.