Nonparametric Time Varying Coefficient Panel Data Models With Fixed Effects

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Nonparametric Time-varying Coefficient Panel Data Models with Fixed Effects

Author : Degui Li
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (752 download)

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Book Synopsis Nonparametric Time-varying Coefficient Panel Data Models with Fixed Effects by : Degui Li

Download or read book Nonparametric Time-varying Coefficient Panel Data Models with Fixed Effects written by Degui Li and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is concerned with developing a nonparametric time varying coefficient model with fixed effects to characterize nonstationarity and trending phenomenon in nonlinear panel data analysis. We develop two methods to estimate the trend function and the coefficient function without taking the first difference to eliminate the fixed effects. The first one eliminates the fixed effects by taking cross{sectional averages, and then uses a nonparametric local linear approach to estimate the trend function and the coefficient function. The asymptotic theory for this approach reveals that although the estimates of both the trend function and the coefficient function are consistent, the estimate of the coefficient function has a rate of convergence of (Th) that is slower than that of the trend function, which has a rate of (NTh). To estimate the coefficient function more efficiently, we propose a pooled local linear dummy variable approach. This is motivated by a least squares dummy variable method proposed in parametric panel data analysis. This method removes the fixed effects by deducting a smoothed version of cross{time average from each individual. It estimates the trend function and the coeficient function with a rate of convergence of (NTh). The asymptotic distributions of both of the estimates are established when T tends to infinity and N is fixed or both T and N tend to infinity. Simulation results are provided to illustrate the finite sample behavior of the proposed estimation methods.

Panel Data Econometrics

Author : Mike Tsionas
Publisher : Academic Press
ISBN 13 : 0128144319
Total Pages : 432 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Panel Data Econometrics by : Mike Tsionas

Download or read book Panel Data Econometrics written by Mike Tsionas and published by Academic Press. This book was released on 2019-06-19 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Panel Data Econometrics: Theory introduces econometric modelling. Written by experts from diverse disciplines, the volume uses longitudinal datasets to illuminate applications for a variety of fields, such as banking, financial markets, tourism and transportation, auctions, and experimental economics. Contributors emphasize techniques and applications, and they accompany their explanations with case studies, empirical exercises and supplementary code in R. They also address panel data analysis in the context of productivity and efficiency analysis, where some of the most interesting applications and advancements have recently been made. Provides a vast array of empirical applications useful to practitioners from different application environments Accompanied by extensive case studies and empirical exercises Includes empirical chapters accompanied by supplementary code in R, helping researchers replicate findings Represents an accessible resource for diverse industries, including health, transportation, tourism, economic growth, and banking, where researchers are not always econometrics experts

Nonlinear Time Series

Author : Jianqing Fan
Publisher : Springer Science & Business Media
ISBN 13 : 0387693955
Total Pages : 565 pages
Book Rating : 4.3/5 (876 download)

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Book Synopsis Nonlinear Time Series by : Jianqing Fan

Download or read book Nonlinear Time Series written by Jianqing Fan and published by Springer Science & Business Media. This book was released on 2008-09-11 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.

Panel Data Econometrics with R

Author : Yves Croissant
Publisher : John Wiley & Sons
ISBN 13 : 1118949188
Total Pages : 328 pages
Book Rating : 4.1/5 (189 download)

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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.

Intermediate Statistics and Econometrics

Author : Dale J. Poirier
Publisher : MIT Press
ISBN 13 : 9780262161497
Total Pages : 744 pages
Book Rating : 4.1/5 (614 download)

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Book Synopsis Intermediate Statistics and Econometrics by : Dale J. Poirier

Download or read book Intermediate Statistics and Econometrics written by Dale J. Poirier and published by MIT Press. This book was released on 1995 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: The standard introductory texts to mathematical statistics leave the Bayesian approach to be taught later in advanced topics courses-giving students the impression that Bayesian statistics provide but a few techniques appropriate in only special circumstances. Nothing could be further from the truth, argues Dale Poirier, who has developed a course for teaching comparatively both the classical and the Bayesian approaches to econometrics. Poirier's text provides a thoroughly modern, self-contained, comprehensive, and accessible treatment of the probability and statistical foundations of econometrics with special emphasis on the linear regression model. Written primarily for advanced undergraduate and graduate students who are pursuing research careers in economics, Intermediate Statistics and Econometrics offers a broad perspective, bringing together a great deal of diverse material. Its comparative approach, emphasis on regression and prediction, and numerous exercises and references provide a solid foundation for subsequent courses in econometrics and will prove a valuable resource to many nonspecialists who want to update their quantitative skills. The introduction closes with an example of a real-world data set-the Challengerspace shuttle disaster-that motivates much of the text's theoretical discussion. The ten chapters that follow cover basic concepts, special distributions, distributions of functions of random variables, sampling theory, estimation, hypothesis testing, prediction, and the linear regression model. Appendixes contain a review of matrix algebra, computation, and statistical tables.

The Oxford Handbook of Panel Data

Author : Badi Hani Baltagi
Publisher :
ISBN 13 : 0199940045
Total Pages : 705 pages
Book Rating : 4.1/5 (999 download)

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Book Synopsis The Oxford Handbook of Panel Data by : Badi Hani Baltagi

Download or read book The Oxford Handbook of Panel Data written by Badi Hani Baltagi and published by . This book was released on 2015 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Oxford Handbook of Panel Data examines new developments in the theory and applications of panel data. It includes basic topics like non-stationary panels, co-integration in panels, multifactor panel models, panel unit roots, measurement error in panels, incidental parameters and dynamic panels, spatial panels, nonparametric panel data, random coefficients, treatment effects, sample selection, count panel data, limited dependent variable panel models, unbalanced panel models with interactive effects and influential observations in panel data. Contributors to the Handbook explore applications of panel data to a wide range of topics in economics, including health, labor, marketing, trade, productivity, and macro applications in panels. This Handbook is an informative and comprehensive guide for both those who are relatively new to the field and for those wishing to extend their knowledge to the frontier. It is a trusted and definitive source on panel data, having been edited by Professor Badi Baltagi-widely recognized as one of the foremost econometricians in the area of panel data econometrics. Professor Baltagi has successfully recruited an all-star cast of experts for each of the well-chosen topics in the Handbook.

Nonlinear Time Series

Author : Jiti Gao
Publisher : CRC Press
ISBN 13 : 1420011219
Total Pages : 249 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Nonlinear Time Series by : Jiti Gao

Download or read book Nonlinear Time Series written by Jiti Gao and published by CRC Press. This book was released on 2007-03-22 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve dimensionality reduction problems arising from using fully

Identification and Estimation of a Nonparametric Time-varying Panel Data Model with Completely Missing Regressors in Some Periods

Author : Jiangang Zeng
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)

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Book Synopsis Identification and Estimation of a Nonparametric Time-varying Panel Data Model with Completely Missing Regressors in Some Periods by : Jiangang Zeng

Download or read book Identification and Estimation of a Nonparametric Time-varying Panel Data Model with Completely Missing Regressors in Some Periods written by Jiangang Zeng and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: I consider a nonparametric time-varying panel data model with the primary interest regressor completely missing in some periods. Under standard assumptions in panel data and nonparametric model literature, I provide constructive identification results for all the unknown functions and the distributions of the completely missing regressors. In particular, I show one period completely observed data is enough to identify the random effects model, while two periods completely observed data are needed for the fixed effects model. Following the identification, I develop nonparametric estimators and derive their convergence rates. Simulation exercises indicate that the estimators perform well in finite samples.

Nonparametric Econometric Methods

Author : Qi Li
Publisher : Emerald Group Publishing
ISBN 13 : 1849506248
Total Pages : 570 pages
Book Rating : 4.8/5 (495 download)

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Book Synopsis Nonparametric Econometric Methods by : Qi Li

Download or read book Nonparametric Econometric Methods written by Qi Li and published by Emerald Group Publishing. This book was released on 2009-12-04 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains a selection of papers presented initially at the 7th Annual Advances in Econometrics Conference held on the LSU campus in Baton Rouge, Louisiana during November 14-16, 2008. This work is suitable for those who wish to familiarize themselves with nonparametric methodology.

Semiparametric Varying-coefficient Mixed Effects Modeling Approaches to Longitudinal Data

Author :
Publisher :
ISBN 13 :
Total Pages : 126 pages
Book Rating : 4.:/5 (974 download)

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Book Synopsis Semiparametric Varying-coefficient Mixed Effects Modeling Approaches to Longitudinal Data by :

Download or read book Semiparametric Varying-coefficient Mixed Effects Modeling Approaches to Longitudinal Data written by and published by . This book was released on 2015 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Longitudinal (panel) studies focus on the models and data that arise from repeated measurements taken from a group of subjects. In this dissertation, we consider mixed effects modeling approaches with nonparametric estimation methods to model the dynamics in the longitudinal data, and explore the study in three focused research topics. Firstly, motivated by establishing a reliable quantitative investigation of the inequalities in developing countries, we use China’s health care expenditure data as an example, and adapt a semi-parametric varying-coefficients spatial panel data model. A profile likelihood based estimation procedure with a fully iterated two-step local estimation method is proposed to estimate the varying coefficients, spatial specific effects, and spatial autoregressive parameter. Simulation studies are conducted to examine the performance of the proposed estimators. The simulation results indicate our methods work very well. Comparison of the estimated coefficients indicates that the semi-parametric spatial varying coefficient panel data model surpasses the parametric one, confirming that the estimated coefficients are time-varying and can better describe the impact of those important factors. We secondly investigate human immunodeficiency virus (HIV) dynamic modeling. HIV dynamic models have been introduced to characterize short-term acquired immune deficiency syndrome (AIDS) treatment. However, in long-term HIV dynamics, viral load will typically increase over the treatment period due to the development of drug resistance. Time-varying drug resistance can be incorporated into the ordinary differential equations (ODEs) model, but often has no close form solution. In clinical practice, only viral load and CD4+ T-cell counts can be censored with measurement errors due to technical constraints. In this study, we consider a mixed-effects nonlinear parametric model describing short-term longitudinal AIDS treatment, along with a set of mixed-effects ODE models fitting long-term longitudinal AIDS clinical trial data. We propose a multi-stage estimation procedure to estimate the mean constant dynamic parameters and time-varying curve functions, and also quantify individual heterogeneity among subjects. Bootstrap confidence intervals for the constant dynamic parameters are calculated to evaluate the estimation procedure. The finite sample properties of the proposed estimator are studied via simulations and the methodology is also applied to a longitudinal AIDS clinical data set. The results suggest that the proposed estimation procedure is effective and appropriate to estimate both individual constant dynamic parameters and time-varying curve functions in long-term HIV dynamic models. Finally, we propose three deterministic linear dynamic models in general forms describing longitudinal dynamic systems, which are designed to be applicable across multiple disciplines. The proposed models are characterized by a set of ODEs in which all state variables in the system are used to interpret each of their derivatives. In this study, we consider multi-stage smoothing-based and mixed effects modeling approaches to estimate both unknown functional varying coefficients and constant parameters. Further, we develop a cross validation based method to identify the parametric and nonparametric components in the proposed models, and show two computational algorithms for illustrations. A simulation study of the FitzHugh-Nagumo system, a biophysical two dimension model of neuronal spike generation, is conducted. The results indicate the importance of data quality for achieving reliable estimates of dynamic parameters. Nonetheless, good estimates can still be obtained from large noise data given a large number of time points with sufficient subjects.

Nonparametric Econometrics

Author : Qi Li
Publisher : Princeton University Press
ISBN 13 : 1400841062
Total Pages : 769 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Nonparametric Econometrics by : Qi Li

Download or read book Nonparametric Econometrics written by Qi Li and published by Princeton University Press. This book was released on 2011-10-09 with total page 769 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, up-to-date textbook on nonparametric methods for students and researchers Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers. Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data—nominal and ordinal—in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory. This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types—continuous, nominal, and ordinal—within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables. Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.

Large-dimensional Panel Data Econometrics: Testing, Estimation And Structural Changes

Author : Feng Qu
Publisher : World Scientific
ISBN 13 : 9811220794
Total Pages : 167 pages
Book Rating : 4.8/5 (112 download)

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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.

Mixed Effects Models for Complex Data

Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

Handbook of Data Analysis

Author : Melissa A Hardy
Publisher : SAGE
ISBN 13 : 1446203441
Total Pages : 729 pages
Book Rating : 4.4/5 (462 download)

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Book Synopsis Handbook of Data Analysis by : Melissa A Hardy

Download or read book Handbook of Data Analysis written by Melissa A Hardy and published by SAGE. This book was released on 2009-06-17 with total page 729 pages. Available in PDF, EPUB and Kindle. Book excerpt: ′This book provides an excellent reference guide to basic theoretical arguments, practical quantitative techniques and the methodologies that the majority of social science researchers are likely to require for postgraduate study and beyond′ - Environment and Planning ′The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher′ - Clive Seale, Brunel University ′With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. ′ - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa ′This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments′ - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. The book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters. A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.

Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences

Author : Stephanie T. Lanza
Publisher : Springer Nature
ISBN 13 : 3030709442
Total Pages : 150 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences by : Stephanie T. Lanza

Download or read book Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences written by Stephanie T. Lanza and published by Springer Nature. This book was released on 2021-05-06 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first to introduce applied behavioral, social, and health sciences researchers to a new analytic method, the time-varying effect model (TVEM). It details how TVEM may be used to advance research on developmental and dynamic processes by examining how associations between variables change across time. The book describes how TVEM is a direct and intuitive extension of standard linear regression; whereas standard linear regression coefficients are static estimates that do not change with time, TVEM coefficients are allowed to change as continuous functions of real time, including developmental age, historical time, time of day, days since an event, and so forth. The book introduces readers to new research questions that can be addressed by applying TVEM in their research. Readers gain the practical skills necessary for specifying a wide variety of time-varying effect models, including those with continuous, binary, and count outcomes. The book presents technical details of TVEM estimation and three novel empirical studies focused on developmental questions using TVEM to estimate age-varying effects, historical shifts in behavior and attitudes, and real-time changes across days relative to an event. The volume provides a walkthrough of the process for conducting each of these studies, presenting decisions that were made, and offering sufficient detail so that readers may embark on similar studies in their own research. The book concludes with comments about additional uses of TVEM in applied research as well as software considerations and future directions. Throughout the book, proper interpretation of the output provided by TVEM is emphasized. Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences is an essential resource for researchers, clinicians/practitioners as well as graduate students in developmental psychology, public health, statistics and methodology for the social, behavioral, developmental, and public health sciences.

Statistical Analysis of Panel Count Data

Author : Jianguo Sun
Publisher : Springer Science & Business Media
ISBN 13 : 1461487153
Total Pages : 283 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Statistical Analysis of Panel Count Data by : Jianguo Sun

Download or read book Statistical Analysis of Panel Count Data written by Jianguo Sun and published by Springer Science & Business Media. This book was released on 2013-10-09 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Panel count data occur in studies that concern recurrent events, or event history studies, when study subjects are observed only at discrete time points. By recurrent events, we mean the event that can occur or happen multiple times or repeatedly. Examples of recurrent events include disease infections, hospitalizations in medical studies, warranty claims of automobiles or system break-downs in reliability studies. In fact, many other fields yield event history data too such as demographic studies, economic studies and social sciences. For the cases where the study subjects are observed continuously, the resulting data are usually referred to as recurrent event data. This book collects and unifies statistical models and methods that have been developed for analyzing panel count data. It provides the first comprehensive coverage of the topic. The main focus is on methodology, but for the benefit of the reader, the applications of the methods to real data are also discussed along with numerical calculations. There exists a great deal of literature on the analysis of recurrent event data. This book fills the void in the literature on the analysis of panel count data. This book provides an up-to-date reference for scientists who are conducting research on the analysis of panel count data. It will also be instructional for those who need to analyze panel count data to answer substantive research questions. In addition, it can be used as a text for a graduate course in statistics or biostatistics that assumes a basic knowledge of probability and statistics.

Advances in Spatial Econometrics

Author : Luc Anselin
Publisher : Springer Science & Business Media
ISBN 13 : 3662056178
Total Pages : 516 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Advances in Spatial Econometrics by : Luc Anselin

Download or read book Advances in Spatial Econometrics written by Luc Anselin and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: World-renowned experts in spatial statistics and spatial econometrics present the latest advances in specification and estimation of spatial econometric models. This includes information on the development of tools and software, and various applications. The text introduces new tests and estimators for spatial regression models, including discrete choice and simultaneous equation models. The performance of techniques is demonstrated through simulation results and a wide array of applications related to economic growth, international trade, knowledge externalities, population-employment dynamics, urban crime, land use, and environmental issues. An exciting new text for academics with a theoretical interest in spatial statistics and econometrics, and for practitioners looking for modern and up-to-date techniques.