Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Pdynmc An R Package For Estimating Linear Dynamic Panel Data Models Based On Linear And Nonlinear Moment Conditions
Download Pdynmc An R Package For Estimating Linear Dynamic Panel Data Models Based On Linear And Nonlinear Moment Conditions full books in PDF, epub, and Kindle. Read online Pdynmc An R Package For Estimating Linear Dynamic Panel Data Models Based On Linear And Nonlinear Moment Conditions ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Pdynmc - an R-package for Estimating Linear Dynamic Panel Data Models Based on Linear and Nonlinear Moment Conditions by : Markus Fritsch
Download or read book Pdynmc - an R-package for Estimating Linear Dynamic Panel Data Models Based on Linear and Nonlinear Moment Conditions written by Markus Fritsch and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Applied Econometric Analysis Using Cross Section and Panel Data by : Deep Mukherjee
Download or read book Applied Econometric Analysis Using Cross Section and Panel Data written by Deep Mukherjee and published by Springer Nature. This book was released on 2024-01-03 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of 20 chapters on chosen topics from cross-section and panel data econometrics. It explores both theoretical and practical aspects of selected cutting-edge techniques which are gaining popularity among applied econometricians, while following the motto of “keeping things simple”. Each chapter gives a basic introduction to one such method, directs readers to supplementary references, and shows an application. The book takes into account that—A: The field of econometrics is evolving very fast and leading textbooks are trying to cover some of the recent developments in revised editions. This book offers basic introduction to state-of-the-art techniques and recent advances in econometric models with detailed applications from various developing and developed countries. B: An applied researcher or practitioner may prefer reference books with a simple introduction to an advanced econometric method or model with no theorems but with a longer discussion on empirical application. Thus, an applied econometrics textbook covering these cutting-edge methods is highly warranted; a void this book attempts to fills.The book does not aim at providing a comprehensive coverage of econometric methods. The 20 chapters in this book represent only a sample of the important topics in modern econometrics, with special focus on econometrics of cross-section and panel data, while also recognizing that it is not possible to accommodate all types of models and methods even in these two categories. The book is unique as authors have also provided the theoretical background (if any) and brief literature review behind the empirical applications. It is a must-have resource for students and practitioners of modern econometrics.
Book Synopsis Initial Conditions and Moment Restrictions in Dynamic Panel Data Models by : Richard Blundell
Download or read book Initial Conditions and Moment Restrictions in Dynamic Panel Data Models written by Richard Blundell and published by . This book was released on 1995 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Consistent Estimation of Linear Panel Data Models with Measurement Error by : Erik Meijer
Download or read book Consistent Estimation of Linear Panel Data Models with Measurement Error written by Erik Meijer and published by . This book was released on 2015 with total page 53 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measurement error causes a downward bias when estimating a panel data linear regression model. The panel data context offers various opportunities to derive moment conditions that result in consistent GMM estimators. We consider three sources of moment conditions: (i) restrictions on the intertemporal covariance matrix of the errors in the equations, (ii) heteroskedasticity and nonlinearity in the relation between the error-ridden covariate and another, error-free, covariate in the equation, and (iii) nonzero third moments of the covariates. In a simulation study we show that these approaches work well.
Book Synopsis Maximum Likelihood and GMM Estimation of Dynamic Panel Data Models with Fixed Effects by : Hugo Kruiniger
Download or read book Maximum Likelihood and GMM Estimation of Dynamic Panel Data Models with Fixed Effects written by Hugo Kruiniger and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper considers inference procedures for two types of dynamic linear panel data models with fixed effects (FE). First, it shows that the closures of stationary ARMAFE models can be consistently estimated by Conditional Maximum Likelihood Estimators and it derives their asymptotic distributions. Then it presents an asymptotically equivalent Minimum Distance Estimator which permits an analytic comparison between the CMLE for the ARFE (1) model and the GMM estimators that have been considered in the literature. The CMLE is shown to be asymptotically less efficient than the most efficient GMM estimator when N approaches the limit infinity but T is fixed. Under normality some of the moment conditions become asymptotically redundant and the CMLE attains the Cramer-Rao lowerbound when T approaches the limit infinity as well. The paper also presents likelihood based unit root tests. Finally, the properties of CML, GMM, and Modified ML estimators for dynamic panel data models that condition on the initial observations are studied and compared. It is shown that for finite T the MMLE is less efficient than the most efficient GMM estimator.
Book Synopsis Estimation and Testing in Dynamic, Nonlinear Panel Data Models by : Margaret Susan Loudermilk
Download or read book Estimation and Testing in Dynamic, Nonlinear Panel Data Models written by Margaret Susan Loudermilk and published by . This book was released on 2006 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Estimation and Moment Selection in Dynamic Fixed-effects Panel Data Models by : Pavel Čížek
Download or read book Robust Estimation and Moment Selection in Dynamic Fixed-effects Panel Data Models written by Pavel Čížek and published by . This book was released on 2015 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Moment-based Estimation of Linear Panel Data Models with Factor-augmented Errors by : Nicholas Brown
Download or read book Moment-based Estimation of Linear Panel Data Models with Factor-augmented Errors written by Nicholas Brown and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: I 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 that 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 that allows for a tradeoff between identifying conditions. These estimators do not require the number of independent variables to be less than one minus the number of time periods, a strong restriction when the number of time periods is fixed in the asymptotic analysis. Finally, I investigate the effects of per-student expenditure on standardized test performance using data from the state of Michigan.
Book Synopsis Estimation of Linear Dynamic Panel Data Models with Time-Invariant Regressors by : Sebastian Kripfganz
Download or read book Estimation of Linear Dynamic Panel Data Models with Time-Invariant Regressors written by Sebastian Kripfganz and published by . This book was released on 2015 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a two-stage estimation procedure to identify the effects of time-invariant regressors in a dynamic version of the Hausman-Taylor model. We first estimate the coefficients of the time-varying regressors and subsequently regress the first-stage residuals on the time-invariant regressors providing analytical standard error adjustments for the second-stage coefficients. The two-stage approach is more robust against misspecification than GMM estimators that obtain all parameter estimates simultaneously. In addition, it allows exploiting advantages of estimators relying on transformations to eliminate the unit-specific heterogeneity. We analytically demonstrate under which conditions the one-stage and two-stage GMM estimators are equivalent. Monte Carlo results highlight the advantages of the two-stage approach infinite samples. Finally, the approach is illustrated with the estimation of a dynamic gravity equation for U.S. outward foreign direct investment.
Book Synopsis Three Essays on Dynamic Panel Data Estimation by :
Download or read book Three Essays on Dynamic Panel Data Estimation written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Instrumental Variable Estimation with Many Moment Conditions with Applications to Dynamic Panel Data Models by : Ryo Okui
Download or read book Instrumental Variable Estimation with Many Moment Conditions with Applications to Dynamic Panel Data Models written by Ryo Okui and published by . This book was released on 2005 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimating Panel Data Models with Endogeneity and Selection by : Anastasia Semykina
Download or read book Estimating Panel Data Models with Endogeneity and Selection written by Anastasia Semykina and published by . This book was released on 2006 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis On GMM Estimation of Linear Dynamic Panel Data Models by : Markus Fritsch
Download or read book On GMM Estimation of Linear Dynamic Panel Data Models written by Markus Fritsch and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimation of Linear Dynamic Panel Data Models with Timeinvariant Regressors by :
Download or read book Estimation of Linear Dynamic Panel Data Models with Timeinvariant Regressors written by and published by . This book was released on 2015 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a two-stage estimation procedure to identify the effects of time-invariant regressors in a dynamic version of the Hausman-Taylor model. We first estimate the coefficients of the time-varying regressors and subsequently regress the first-stage residuals on the time-invariant regressors providing analytical standard error adjustments for the second-stage coefficients . The two-stage approach is more robust against misspecification than GMM estimators that obtain all parameter estimates simultaneously. In addition, it allows exploiting advantages of estimators relying on transformations to eliminate the unit specific heterogeneity. We analytically demonstrate under which conditions the one-stage and two-stage GMM estimators are equivalent. Monte Carlo results highlight the advantages of the two-stage approach infinite samples. Finally, the approach is illustrated with the estimation of a dynamic gravity equation for U.S. outward foreign direct investment.
Book Synopsis Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors and a Multifactor Error Structure by : Milda Norkute
Download or read book Instrumental Variable Estimation of Dynamic Linear Panel Data Models with Defactored Regressors and a Multifactor Error Structure written by Milda Norkute and published by . This book was released on 2019 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper develops two instrumental variable (IV) estimators for dynamic panel data models with exogenous covariates and a multifactor error structure when both crosssectional and time series dimensions, N and T respectively, are large. Our approach initially projects out the common factors from the exogenous covariates of the model, and constructs instruments based on this defactored covariates. For models with homogeneous slope coe_cients, we propose a two-step IV estimator: the _rst step IV estimator is obtained using the defactored covariates as instruments. In the second step, the entire model is defactored by the extracted factors from the residuals of the _rst step estimation and subsequently obtain the _nal IV estimator. For models with heterogeneous slope coe _cients, we propose a mean-group type estimator, which is the cross-sectional average of _rst-step IV estimators of cross-section speci_c slopes. It is noteworthy that our estimators do not require us to seek for instrumental variables outside the model. Furthermore, our estimators are linear hence computationally robust and inexpensive. Moreover, they require no bias correction, and they are not subject to the small sample bias of least squares type estimators. The _nite sample performances of the proposed estimators and associated statistical tests are investigated, and the results show that the estimators and the tests perform well even for small N and T.
Book Synopsis Initial conditions and efficient estimation in dynamic panel data models by : Richard Blundell
Download or read book Initial conditions and efficient estimation in dynamic panel data models written by Richard Blundell and published by . This book was released on 1991 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimating Dynamic Panel Data Models by : Jörg Breitung
Download or read book Estimating Dynamic Panel Data Models written by Jörg Breitung and published by . This book was released on 1993 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
