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Author: M. Hashem Pesaran
Publisher: Oxford University Press, USA
ISBN: 0198759983
Category : Business & Economics
Languages : en
Pages : 1095
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Book Description
The book describes and illustrates many advances that have taken place in a number of areas in theoretical and applied econometrics over the past four decades.
Author: M. Hashem Pesaran
Publisher: Oxford University Press, USA
ISBN: 0198759983
Category : Business & Economics
Languages : en
Pages : 1095
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Book Description
The book describes and illustrates many advances that have taken place in a number of areas in theoretical and applied econometrics over the past four decades.
Author: Manuel Arellano
Publisher: OUP Oxford
ISBN: 0191529672
Category : Business & Economics
Languages : en
Pages : 244
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Book Description
This book, by one of the world's leading experts on dynamic panel data, presents a modern review of some of the main topics in panel data econometrics. The author concentrates on linear models, and emphasizes the roles of heterogeneity and dynamics in panel data modelling. The book combines methods and applications, so will appeal to both the academic and practitioner markets. The book is divided in four parts. Part I concerns static models, and deals with the problem of unobserved heterogeneity and how the availability of panel data helps to solve it, error component models, and error in variables in panel data. Part II looks at time series models with error components. Its chapters deal with the problem of distinguishing between unobserved heterogeneity and individual dynamics in short panels, modelling strategies of time effects, moving average models, inference from covariance structures, the specification and estimation of autoregressive models with heterogeneous intercepts, and the impact of assumptions about initial conditions and heteroskedacity on estimation. Part III examines dynamics and predeterminedness. Its two chapters consider alternative approaches to estimation from small and large T perspectives, looking at models with both strictly exogenous and lagged dependent variables allowing for autocorrelation of unknown form, models in which the errors are mean independent of current and lagged values of certain conditioning variables but not with their future values. Together Parts II and III provide a synthesis, and unified perspective, of a vast literature that has had a significant impact on recent econometric practice. Part IV reviews the main results in the theory of generalized method of moments estimation and optimal instrumental variables.
Author: Panchanan Das
Publisher: Springer Nature
ISBN: 9813290196
Category : Business & Economics
Languages : en
Pages : 574
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Book Description
This book introduces econometric analysis of cross section, time series and panel data with the application of statistical software. It serves as a basic text for those who wish to learn and apply econometric analysis in empirical research. The level of presentation is as simple as possible to make it useful for undergraduates as well as graduate students. It contains several examples with real data and Stata programmes and interpretation of the results. While discussing the statistical tools needed to understand empirical economic research, the book attempts to provide a balance between theory and applied research. Various concepts and techniques of econometric analysis are supported by carefully developed examples with the use of statistical software package, Stata 15.1, and assumes that the reader is somewhat familiar with the Strata software. The topics covered in this book are divided into four parts. Part I discusses introductory econometric methods for data analysis that economists and other social scientists use to estimate the economic and social relationships, and to test hypotheses about them, using real-world data. There are five chapters in this part covering the data management issues, details of linear regression models, the related problems due to violation of the classical assumptions. Part II discusses some advanced topics used frequently in empirical research with cross section data. In its three chapters, this part includes some specific problems of regression analysis. Part III deals with time series econometric analysis. It covers intensively both the univariate and multivariate time series econometric models and their applications with software programming in six chapters. Part IV takes care of panel data analysis in four chapters. Different aspects of fixed effects and random effects are discussed here. Panel data analysis has been extended by taking dynamic panel data models which are most suitable for macroeconomic research. The book is invaluable for students and researchers of social sciences, business, management, operations research, engineering, and applied mathematics.
Author: Mike Tsionas
Publisher: Academic Press
ISBN: 0128144319
Category : Business & Economics
Languages : en
Pages : 434
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Book Description
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
Author: Yves Croissant
Publisher: John Wiley & Sons
ISBN: 1118949188
Category : Mathematics
Languages : en
Pages : 435
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Book Description
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.
Author: Donggyu Sul
Publisher: Routledge
ISBN: 0429752989
Category : Business & Economics
Languages : en
Pages : 165
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Book Description
In the last 20 years, econometric theory on panel data has developed rapidly, particularly for analyzing common behaviors among individuals over time. Meanwhile, the statistical methods employed by applied researchers have not kept up-to-date. This book attempts to fill in this gap by teaching researchers how to use the latest panel estimation methods correctly. Almost all applied economics articles use panel data or panel regressions. However, many empirical results from typical panel data analyses are not correctly executed. This book aims to help applied researchers to run panel regressions correctly and avoid common mistakes. The book explains how to model cross-sectional dependence, how to estimate a few key common variables, and how to identify them. It also provides guidance on how to separate out the long-run relationship and common dynamic and idiosyncratic dynamic relationships from a set of panel data. Aimed at applied researchers who want to learn about panel data econometrics by running statistical software, this book provides clear guidance and is supported by a full range of online teaching and learning materials. It includes practice sections on MATLAB, STATA, and GAUSS throughout, along with short and simple econometric theories on basic panel regressions for those who are unfamiliar with econometric theory on traditional panel regressions.
Author: Feng Qu
Publisher: World Scientific
ISBN: 9811220794
Category : Business & Economics
Languages : en
Pages : 167
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Book Description
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.
Author: Gebhard Kirchgässner
Publisher: Springer Science & Business Media
ISBN: 9783540687351
Category : Business & Economics
Languages : en
Pages : 288
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Book Description
This book presents modern developments in time series econometrics that are applied to macroeconomic and financial time series. It contains the most important approaches to analyze time series which may be stationary or nonstationary.
Author: Erik Biørn
Publisher: Oxford University Press
ISBN: 0198753446
Category : Business & Economics
Languages : en
Pages : 417
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Book Description
Panel data is a data type increasingly used in research in economics, social sciences, and medicine. Its primary characteristic is that the data variation goes jointly over space (across individuals, firms, countries, etc.) and time (over years, months, etc.). Panel data allow examination of problems that cannot be handled by cross-section data or time-series data. Panel data analysis is a core field in modern econometrics and multivariate statistics, and studies based on such data occupy a growing part of the field in many other disciplines. The book is intended as a text for master and advanced undergraduate courses. It may also be useful for PhD-students writing theses in empirical and applied economics and readers conducting empirical work on their own. The book attempts to take the reader gradually from simple models and methods in scalar (simple vector) notation to more complex models in matrix notation. A distinctive feature is that more attention is given to unbalanced panel data, the measurement error problem, random coefficient approaches, the interface between panel data and aggregation, and the interface between unbalanced panels and truncated and censored data sets. The 12 chapters are intended to be largely self-contained, although there is also natural progression. Most of the chapters contain commented examples based on genuine data, mainly taken from panel data applications to economics. Although the book, inter alia, through its use of examples, is aimed primarily at students of economics and econometrics, it may also be useful for readers in social sciences, psychology, and medicine, provided they have a sufficient background in statistics, notably basic regression analysis and elementary linear algebra.
Author: John D. Levendis
Publisher: Springer
ISBN: 3319982826
Category : Business & Economics
Languages : en
Pages : 418
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Book Description
In this book, the author rejects the theorem-proof approach as much as possible, and emphasize the practical application of econometrics. They show with examples how to calculate and interpret the numerical results. This book begins with students estimating simple univariate models, in a step by step fashion, using the popular Stata software system. Students then test for stationarity, while replicating the actual results from hugely influential papers such as those by Granger and Newbold, and Nelson and Plosser. Readers will learn about structural breaks by replicating papers by Perron, and Zivot and Andrews. They then turn to models of conditional volatility, replicating papers by Bollerslev. Finally, students estimate multi-equation models such as vector autoregressions and vector error-correction mechanisms, replicating the results in influential papers by Sims and Granger. The book contains many worked-out examples, and many data-driven exercises. While intended primarily for graduate students and advanced undergraduates, practitioners will also find the book useful.
