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Identification And Fast Estimation Of Large Nonlinear Panel Models With Two Way Fixed Effects
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Book Synopsis Identification and (Fast) Estimation of Large Nonlinear Panel Models with Two-Way Fixed Effects by : Martin Mugnier
Download or read book Identification and (Fast) Estimation of Large Nonlinear Panel Models with Two-Way Fixed Effects written by Martin Mugnier and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study a nonlinear two-way fixed effects panel model that allows for unobserved individual heterogeneity in slopes (interacting with covariates) and (unknown) flexibly specified link function. The former is particularly relevant when the researcher is interested in the distributional causal effects of covariates, and the latter mitigates potential misspecification errors due to imposing a known link function. We show that the fixed effects parameters and the (nonparametrically specified) link function can be identified when both individual and time dimensions are large. We propose a novel iterative Gauss-Seidel estimation procedure that overcomes the practical challenge of dimensionality in the number of fixed effects when the dataset is large. We revisit two empirical studies in trade (Helpman et al., 2008) and innovation (Aghion et al., 2013), and find non-negligible unobserved dispersion in trade elasticity (across countries) and the effect of institutional ownership on innovation (across firms). These exercises emphasize the usefulness of our method in capturing flexible (and unobserved) heterogeneity in the causal relationship of interest that may have important implications for the subsequent policy analysis.
Book Synopsis Nonseparable Panel Data Models Identification, Estimation and Testing by : Dalia A. Ghanem
Download or read book Nonseparable Panel Data Models Identification, Estimation and Testing written by Dalia A. Ghanem and published by . This book was released on 2013 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microeconomic panel data, also known as longitudinal data or repeated measures, allow the researcher to observe the same individual across time. One of the advantages of panel data is that they allow the researcher to control for unobservable individual heterogeneity. The linear fixed effects model is the most commonly used method in empirical work to control for unobservable heterogeneity. Chapter 1 reviews the special features of the linear fixed effects model in detail, giving special attention to the definition of fixed effects and correlated random effects. It discusses the issues that arise when we move from a linear model to fully nonseparable models and reviews the two strands of the literature that are relevant for this dissertation: (1) the literature on nonlinear parametric panel data models with fixed effects, (2) the literature on nonparametric identification in nonseparable panel data models. Chapter 2 falls under the parametric nonlinear panel data models with fixed effects. Nonlinear panel data models with fixed effects are an important example in econometrics where the incidental parameter problem arises and the maximum likelihood estimator (MLE) is asymptotically biased. Bias correction of the MLE achieves consistency without increasing the asymptotic variance. Chapter 2 proposes a shrinkage estimator that combines that is shown to lead to a higher-order mean-square error improvement over the analytical bias-corrected estimator. Chapter 3 falls under the literature on nonparametric identification in nonseparable panel data models. Starting from a general DGP that exhibits nonseparability of the structural function, arbitrary individual and time heterogeneity, I give a necessary and sufficient condition for the point-identification of the APE for a subpopulation. This condition is then used to characterize the trade-off between assumptions on unobservable heterogeneity and the structural function that achieve identification. The identifying assumptions here have clear testable implications on the distribution of observables. I hence propose bootstrap-adjusted Kolmogorv-Smirnov and Cramer-von-Mises statistics to test these implications. Chapter 4 is an empirical paper that studies the issue of manipulation of air pollution data by Chinese cities. It applies tests similar in spirit to the tests proposed in Chapter 3 to test the presence of manipulation.
Book Synopsis Identification and Estimation of Nonparametric Panel Data Regressions with Measurement Error by : Daniel Wilhelm
Download or read book Identification and Estimation of Nonparametric Panel Data Regressions with Measurement Error written by Daniel Wilhelm and published by . This book was released on 2015 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper provides a constructive argument for identification of nonparametric panel data models with measurement error in a continuous explanatory variable. The approach point identifies all structural elements of the model using only observations of the outcome and the mismeasured explanatory variable; no further external variables such as instruments are required. In the case of two time periods, restricting either the structural or the measurement error to be independent over time allows past explanatory variables or outcomes to serve as instruments. Time periods have to be linked through serial dependence in the latent explanatory variable, but the transition process is left nonparametric. The paper discusses the general identification result in the context of a nonlinear panel data regression model with additively separable fixed effects. It provides a nonparametric plug-in estimator, derives its uniform rate of convergence, and presents simulation evidence for good performance in finite samples.
Book Synopsis Essays on Nonlinear Panel Models with Unobserved Heterogeneity by : Robert Martin
Download or read book Essays on Nonlinear Panel Models with Unobserved Heterogeneity written by Robert Martin and published by . This book was released on 2017 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Panel Data Econometrics with R by : Yves Croissant
Download or read book Panel Data Econometrics with R written by Yves Croissant and published by John Wiley & Sons. This book was released on 2018-08-10 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and applications as well as more advanced topics and recent developments in this field including error component models, spatial panels and dynamic models. They have developed the software programming in R and host replicable material on the book’s accompanying website.
Book Synopsis The Behavior of the Fixed Effects Estimator in Nonlinear Models by : William H. Greene
Download or read book The Behavior of the Fixed Effects Estimator in Nonlinear Models written by William H. Greene and published by . This book was released on 2008 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: The nonlinear fixed effects models in econometrics has often been avoided for two reasons one practical, one methodological. The practical obstacle relates to the difficulty of estimating nonlinear models with possibly thousands of coefficients. In fact, in a large number of models of interest to practitioners, estimation of the fixed effects model is feasible even in panels with very large numbers of groups. The more difficult, methodological question centers on the incidental parameters problem that raises questions about the statistical properties of the estimator. There is very little empirical evidence on the behavior of the fixed effects estimator. In this note, we use Monte Carlo methods to examine the small sample bias in the binary probit and logit models, the ordered probit model, the tobit model, the Poisson regression model for count data and the exponential regression model for a nonnegative random variable. We find three results of note: A widely accepted result that suggests that the probit estimator is actually relatively well behaved appears to be incorrect. Perhaps to some surprise, the tobit model, unlike the others, appears largely to be unaffected by the incidental parameters problem, save for a surprising result related to the disturbance variance estimator. Third, as apparently unexamined previously, the estimated asymptotic estimators for fixed effects estimators appear uniformly to be downward biased.
Book Synopsis Longitudinal and Panel Data by : Edward W. Frees
Download or read book Longitudinal and Panel Data written by Edward W. Frees and published by Cambridge University Press. This book was released on 2004-08-16 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to foundations and applications for quantitatively oriented graduate social-science students and individual researchers.
Book Synopsis Three Essays on Panel Data Models with Interactive and Unobserved Effects by : Nicholas Lynn Brown
Download or read book Three Essays on Panel Data Models with Interactive and Unobserved Effects written by Nicholas Lynn Brown and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Large-dimensional Panel Data Econometrics: Testing, Estimation And Structural Changes by : Feng Qu
Download or read book Large-dimensional Panel Data Econometrics: Testing, Estimation And Structural Changes written by Feng Qu and published by World Scientific. This book was released on 2020-08-24 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to fill the gap between panel data econometrics textbooks, and the latest development on 'big data', especially large-dimensional panel data econometrics. It introduces important research questions in large panels, including testing for cross-sectional dependence, estimation of factor-augmented panel data models, structural breaks in panels and group patterns in panels. To tackle these high dimensional issues, some techniques used in Machine Learning approaches are also illustrated. Moreover, the Monte Carlo experiments, and empirical examples are also utilised to show how to implement these new inference methods. Large-Dimensional Panel Data Econometrics: Testing, Estimation and Structural Changes also introduces new research questions and results in recent literature in this field.
Book Synopsis Generalized Linear Models and Extensions, Second Edition by : James W. Hardin
Download or read book Generalized Linear Models and Extensions, Second Edition written by James W. Hardin and published by Stata Press. This book was released on 2007 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deftly balancing theory and application, this book stands out in its coverage of the derivation of the GLM families and their foremost links. This edition has new sections on discrete response models, including zero-truncated, zero-inflated, censored, and hurdle count models, as well as heterogeneous negative binomial, and more.
Book Synopsis Nonlinear Factor Models for Network and Panel Data by : Mingli Chen
Download or read book Nonlinear Factor Models for Network and Panel Data written by Mingli Chen and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Factor structures or interactive effects are convenient devices to incorporate latent variables in panel data models. We consider fixed effect estimation of nonlinear panel single-index models with factor structures in the unobservables, which include logit, probit, ordered probit and Poisson specifications. We establish that fixed effect estimators of model parameters and average partial effects have normal distributions when the two dimensions of the panel grow large, but might suffer from incidental parameter bias. We show how models with factor structures can also be applied to capture important features of network data such as reciprocity, degree heterogeneity, homophily in latent variables and clustering. We illustrate this applicability with an empirical example to the estimation of a gravity equation of international trade between countries using a Poisson model with multiple factors.
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 Estimation of Structural Parameters and Marginal Effects in Binary Choice Panel Data Models with Fixed Effects by : Iván Fernández-Val
Download or read book Estimation of Structural Parameters and Marginal Effects in Binary Choice Panel Data Models with Fixed Effects written by Iván Fernández-Val and published by . This book was released on 2005 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fixed effects estimators of nonlinear panel models can be severely biased due to the incidental parameters problem. In this paper I find that the most important component of this incidental parameters bias for probit fixed effects estimators of index coefficients is proportional to the true value of these coefficients, using a large-T expansion of the bias. This result allows me to derive a lower bound for this bias, and to show that fixed effects estimates of ratios of coefficients and average marginal effects have zero bias in the absence of heterogeneity and have negligible bias relative to their true values for a wide variety of distributions of regressors and individual effects. Numerical examples suggest that this small bias property also holds for logit and linear probability models, and for exogenous variables in dynamic binary choice models. An empirical analysis of female labor force participation using data from the PSID shows that whereas the significant biases in fixed effects estimates of index coefficients do not contaminate the estimates of marginal effects in static models, estimates of both index coefficients and marginal effects can be severely biased in dynamic models. Improved bias corrected estimators for index coefficients and marginal effects are also proposed for both static and dynamic models.
Author :Stephen W. Raudenbush Publisher :Scientific Software International ISBN 13 :9780894980541 Total Pages :324 pages Book Rating :4.9/5 (85 download)
Download or read book HLM 6 written by Stephen W. Raudenbush and published by Scientific Software International. This book was released on 2004 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimation of Nonlinear Panel Models with Multiple Unobserved Effects by :
Download or read book Estimation of Nonlinear Panel Models with Multiple Unobserved Effects written by and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonlinear Panel Data Models with High-Dimensional Fixed Effects by : Amrei Stammann
Download or read book Nonlinear Panel Data Models with High-Dimensional Fixed Effects written by Amrei Stammann and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :John M. Abowd Publisher :Université de Montréal, Centre de recherche et développement en économique ISBN 13 : Total Pages :94 pages Book Rating :4.:/5 (318 download)
Book Synopsis High Wage Workers and High Wage Firms by : John M. Abowd
Download or read book High Wage Workers and High Wage Firms written by John M. Abowd and published by Université de Montréal, Centre de recherche et développement en économique. This book was released on 1994 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: We study a longitudinal sample of over one million French workers and over 500,000 employing firms. Real total annual compensation per worker is decomposed into components related to observable characteristics, worker heterogeneity, firm heterogeneity and residual variation. Except for the residual, all components may be correlated in an arbitrary fashion. At the level of the individual, we find that person-effects, especially those not related to observables like education, are the most important source of wage variation in France. Firm-effects, while important, are not as important as person-effects. At the level of firms, we find that enterprises that hire high-wage workers are more productive but not more profitable. They are also more capital and high-skilled employee intensive. Enterprises that pay higher wages, controlling for person-effects, are more productive and more profitable. They are also more capital intensive but are not more high-skilled labor intensive. We also find that person-effects explain 92% of inter-industry wage differentials.
