Three Essays On Panel Data Analysis
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Three Essays On Panel Data Analysis
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Author : Jihun Kwak
language : en
Publisher:
Release Date : 2020
Three Essays On Panel Data Analysis written by Jihun Kwak and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Convergence (Economics) categories.
Three Essays On The Panel Data Approach To An Analysis Of Economics And Financial Data
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Author : Laura Serlenga
language : en
Publisher:
Release Date : 2005
Three Essays On The Panel Data Approach To An Analysis Of Economics And Financial Data written by Laura Serlenga and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Three Essays On The Panel Data Approach To An Analysis Of Economics And Finance Data
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Author : L. Serlenga
language : en
Publisher:
Release Date : 2005
Three Essays On The Panel Data Approach To An Analysis Of Economics And Finance Data written by L. Serlenga and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
Three Essays On Dynamic Panel Data Estimation
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Author :
language : en
Publisher:
Release Date : 2004
Three Essays On Dynamic Panel Data Estimation written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
This dissertation consists of three essays, first two of which consider a new estimation method of dynamic panel data models and the last one considers an application of these models. The first essay (Chapter 1) offers empirical likelihood (EL) estimation of dynamic panel data models, which provide great flexibility to empirical researchers. EL estimation method is shown to have great advantages in usual settings, however little is known on the relative merits of these estimators in panel data models. With this essay, we try to fill that gap by establishing the asymptotic properties of the EL estimator for a dynamic panel model with individual effects when both the time and the cross-section dimensions tend to infinity. We give the conditions under which this estimator is consistent and asymptotically normal. In the second essay (Chapter 2), via a Monte Carlo study, we assess the relative finite sample performances of EL, generalized method of moments, and limited information maximum likelihood estimators for an autoregressive panel data model when there are many moment conditions. We also extend our results to the many weak moments settings. Our results suggest that when the overall performances are concerned, in terms of median, interquartile range and median absolute error of the estimators, in both strong and weak moments settings, EL is more reliable. In the final essay (Chapter 3) we consider an application of dynamic panel data models to examine the determinants of the allocation of state highway funds using panel data for North Carolina's 100 counties for the years 1990 to 2005. We make two main contributions with this essay. First, although there have been numerous studies of highway funding at the state level, to our knowledge, there is no analysis at the sub-state or county levels. Second, by using dynamic panel data models and sophisticated methods to estimate them, we account for any potential persistence in the process of adjustment toward an equilibri.
Three Essays On Nonlinear Panel Data Models And Quantile Regression Analysis
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Author : Iván Fernández-Val
language : en
Publisher:
Release Date : 2005
Three Essays On Nonlinear Panel Data Models And Quantile Regression Analysis written by Iván Fernández-Val and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.
This dissertation is a collection of three independent essays in theoretical and applied econometrics, organized in the form of three chapters. In the first two chapters, I investigate the properties of parametric and semiparametric fixed effects estimators for nonlinear panel data models. The first chapter focuses on fixed effects maximum likelihood estimators for binary choice models, such as probit, logit, and linear probability model. These models are widely used in economics to analyze decisions such as labor force participation, union membership, migration, purchase of durable goods, marital status, or fertility. The second chapter looks at generalized method of moments estimation in panel data models with individual-specific parameters. An important example of these models is a random coefficients linear model with endogenous regressors. The third chapter (co-authored with Joshua Angrist and Victor Chernozhukov) studies the interpretation of quantile regression estimators when the linear model for the underlying conditional quantile function is possibly misspecified.
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.
Three Essays In Applied Economics With Panel Data
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Author : Pierre-Emmanuel Darpeix
language : en
Publisher:
Release Date : 2018
Three Essays In Applied Economics With Panel Data written by Pierre-Emmanuel Darpeix and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
This dissertation is composed of three empirical articles resorting to econometric methods in panel data analysis to address various research questions. The main article investigates the evolution of the level of price transmission for the three major cereals (wheat, maize and rice) from the international commodity markets down to the local producers for 52 countries between 1970 and 2013 while attempting to identify the main drivers of the heterogeneity in pass-through. The second article measures the elasticity of air-traffic to GDP around the world and demonstrates that the relationship is very stable across régions and through time. Eventually, the third article models the mechanisms through which French life-insurers set the rate of return they pay annually to their policyholders.
Three Essays On Panel Data Models With Interactive And Unobserved Effects
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Author : Nicholas Lynn Brown
language : en
Publisher:
Release Date : 2022
Three Essays On Panel Data Models With Interactive And Unobserved Effects written by Nicholas Lynn Brown and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Electronic dissertations categories.
Chapter 1: More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation (with Jeffrey Wooldridge)We provide a systematic approach in obtaining an estimator asymptotically more efficient than the popular fixed effects Poisson (FEP) estimator for panel data models with multiplicative heterogeneity in the conditional mean. In particular, we derive the optimal instrumental variables under appealing `working' second moment assumptions that allow underdispersion, overdispersion, and general patterns of serial correlation. Because parameters in the optimal instruments must be estimated, we argue for combining our new moment conditions with those that define the FEP estimator to obtain a generalized method of moments (GMM) estimator no less efficient than the FEP estimator and the estimator using the new instruments. A simulation study shows that the GMM estimator behaves well in terms of bias, and it often delivers nontrivial efficiency gains -- even when the working second-moment assumptions fail.Chapter 2: Information equivalence among transformations of semiparametric nonlinear panel data modelsI consider transformations of nonlinear semiparametric mean functions which yield moment conditions for estimation. Such transformations are said to be information equivalent if they yield the same asymptotic efficiency bound. I first derive a unified theory of algebraic equivalence for moment conditions created by a given linear transformation. The main equivalence result states that under standard regularity conditions, transformations which create conditional moment restrictions in a given empirical setting need only to have an equal rank to reach the same efficiency bound. Example applications are considered, including nonlinear models with multiplicative heterogeneity and linear models with arbitrary unobserved factor structures.Chapter 3: Moment-based Estimation of Linear Panel Data Models with Factor-augmented ErrorsI consider linear panel data models with unobserved factor structures when the number of time periods is small relative to the number of cross-sectional units. I examine two popular methods of estimation: the first eliminates the factors with a parameterized quasi-long-differencing (QLD) transformation. The other, referred to as common correlated effects (CCE), uses the cross-sectional averages of the independent and response variables to project out the space spanned by the factors. I show that the classical CCE assumptions imply unused moment conditions which can be exploited by the QLD transformation to derive new linear estimators which weaken identifying assumptions and have desirable theoretical properties. I prove asymptotic normality of the linear QLD estimators under a heterogeneous slope model which allows for a tradeoff between identifying conditions. These estimators do not require the number of cross-sectional variables to be less than T-1, a strong restriction in fixed-$T$ CCE analysis. Finally, I investigate the effects of per-student expenditure on standardized test performance using data from the state of Michigan.
On The Limits Of Data
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Author : Jonathan Neil Katz
language : en
Publisher:
Release Date : 1995
On The Limits Of Data written by Jonathan Neil Katz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Elections categories.
Three Essays In The Economics Of Suburban Water Demand
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Author : Mahesh Ramachandran
language : en
Publisher:
Release Date : 2010
Three Essays In The Economics Of Suburban Water Demand written by Mahesh Ramachandran and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Suburbs categories.