Nonparametric Econometrics

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Nonparametric Econometrics

Author : Qi Li,Jeffrey Scott Racine
Publisher : Princeton University Press
Page : 768 pages
File Size : 44,8 Mb
Release : 2023-07-18
Category : Business & Economics
ISBN : 9780691248080

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Nonparametric Econometrics by Qi Li,Jeffrey Scott Racine Pdf

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.

Nonparametric Econometrics

Author : Adrian Pagan,Aman Ullah
Publisher : Cambridge University Press
Page : 446 pages
File Size : 50,9 Mb
Release : 1999-06-28
Category : Business & Economics
ISBN : 9780521355643

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Nonparametric Econometrics by Adrian Pagan,Aman Ullah Pdf

Covering the vast literature on the nonparametric and semiparametric statistics and econometrics that has evolved over the last five decades, this book will be useful for first year graduate courses in econometrics.

Applied Nonparametric Econometrics

Author : Daniel J. Henderson,Christopher F. Parmeter
Publisher : Cambridge University Press
Page : 381 pages
File Size : 42,5 Mb
Release : 2015-01-19
Category : Business & Economics
ISBN : 9781107010253

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Applied Nonparametric Econometrics by Daniel J. Henderson,Christopher F. Parmeter Pdf

The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignores the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls.

Nonparametric Econometrics

Author : Jeffrey Scott Racine
Publisher : Now Publishers Inc
Page : 103 pages
File Size : 50,9 Mb
Release : 2008
Category : Econometrics
ISBN : 9781601981103

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Nonparametric Econometrics by Jeffrey Scott Racine Pdf

Nonparametric Econometrics is a primer for those who wish to familiarize themselves with nonparametric econometrics. While the underlying theory for many of these methods can be daunting for practitioners, this monograph presents a range of nonparametric methods that can be deployed in a fairly straightforward manner. Nonparametric methods are statistical techniques that do not require a researcher to specify functional forms for objects being estimated. The methods surveyed are known as kernel methods, which are becoming increasingly popular for applied data analysis. The appeal of nonparametric methods stems from the fact that they relax the parametric assumptions imposed on the data generating process and let the data determine an appropriate model. Nonparametric Econometrics focuses on a set of touchstone topics while making liberal use of examples for illustrative purposes. The author provides settings in which the user may wish to model a dataset comprised of continuous, discrete, or categorical data (nominal or ordinal), or any combination thereof. Recent developments are considered, including some where the variables involved may in fact be irrelevant, which alters the behavior of the estimators and optimal bandwidths in a manner that deviates substantially from conventional approaches.

The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

Author : Jeffrey Racine,Liangjun Su,Aman Ullah
Publisher : Oxford University Press
Page : 562 pages
File Size : 49,6 Mb
Release : 2014-04
Category : Business & Economics
ISBN : 9780199857944

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The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics by Jeffrey Racine,Liangjun Su,Aman Ullah Pdf

This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures.

An Introduction to the Advanced Theory of Nonparametric Econometrics

Author : Jeffrey S. Racine
Publisher : Cambridge University Press
Page : 435 pages
File Size : 54,9 Mb
Release : 2019-06-27
Category : Business & Economics
ISBN : 9781108483407

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An Introduction to the Advanced Theory of Nonparametric Econometrics by Jeffrey S. Racine Pdf

Provides theory, open source R implementations, and the latest tools for reproducible nonparametric econometric research.

Semiparametric and Nonparametric Econometrics

Author : Aman Ullah
Publisher : Springer Science & Business Media
Page : 180 pages
File Size : 52,7 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9783642518485

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Semiparametric and Nonparametric Econometrics by Aman Ullah Pdf

Over the last three decades much research in empirical and theoretical economics has been carried on under various assumptions. For example a parametric functional form of the regression model, the heteroskedasticity, and the autocorrelation is always as sumed, usually linear. Also, the errors are assumed to follow certain parametric distri butions, often normal. A disadvantage of parametric econometrics based on these assumptions is that it may not be robust to the slight data inconsistency with the particular parametric specification. Indeed any misspecification in the functional form may lead to erroneous conclusions. In view of these problems, recently there has been significant interest in 'the semiparametric/nonparametric approaches to econometrics. The semiparametric approach considers econometric models where one component has a parametric and the other, which is unknown, a nonparametric specification (Manski 1984 and Horowitz and Neumann 1987, among others). The purely non parametric approach, on the other hand, does not specify any component of the model a priori. The main ingredient of this approach is the data based estimation of the unknown joint density due to Rosenblatt (1956). Since then, especially in the last decade, a vast amount of literature has appeared on nonparametric estimation in statistics journals. However, this literature is mostly highly technical and this may partly be the reason why very little is known about it in econometrics, although see Bierens (1987) and Ullah (1988).

Semiparametric and Nonparametric Econometrics

Author : Aman Ullah
Publisher : Physica
Page : 0 pages
File Size : 46,6 Mb
Release : 2012-05-26
Category : Business & Economics
ISBN : 3642518508

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Semiparametric and Nonparametric Econometrics by Aman Ullah Pdf

Over the last three decades much research in empirical and theoretical economics has been carried on under various assumptions. For example a parametric functional form of the regression model, the heteroskedasticity, and the autocorrelation is always as sumed, usually linear. Also, the errors are assumed to follow certain parametric distri butions, often normal. A disadvantage of parametric econometrics based on these assumptions is that it may not be robust to the slight data inconsistency with the particular parametric specification. Indeed any misspecification in the functional form may lead to erroneous conclusions. In view of these problems, recently there has been significant interest in 'the semiparametric/nonparametric approaches to econometrics. The semiparametric approach considers econometric models where one component has a parametric and the other, which is unknown, a nonparametric specification (Manski 1984 and Horowitz and Neumann 1987, among others). The purely non parametric approach, on the other hand, does not specify any component of the model a priori. The main ingredient of this approach is the data based estimation of the unknown joint density due to Rosenblatt (1956). Since then, especially in the last decade, a vast amount of literature has appeared on nonparametric estimation in statistics journals. However, this literature is mostly highly technical and this may partly be the reason why very little is known about it in econometrics, although see Bierens (1987) and Ullah (1988).

Semiparametric and Nonparametric Methods in Econometrics

Author : Joel L. Horowitz
Publisher : Springer
Page : 276 pages
File Size : 40,5 Mb
Release : 2009-08-07
Category : Business & Economics
ISBN : 0387928693

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Semiparametric and Nonparametric Methods in Econometrics by Joel L. Horowitz Pdf

Standard methods for estimating empirical models in economics and many other fields rely on strong assumptions about functional forms and the distributions of unobserved random variables. Often, it is assumed that functions of interest are linear or that unobserved random variables are normally distributed. Such assumptions simplify estimation and statistical inference but are rarely justified by economic theory or other a priori considerations. Inference based on convenient but incorrect assumptions about functional forms and distributions can be highly misleading. Nonparametric and semiparametric statistical methods provide a way to reduce the strength of the assumptions required for estimation and inference, thereby reducing the opportunities for obtaining misleading results. These methods are applicable to a wide variety of estimation problems in empirical economics and other fields, and they are being used in applied research with increasing frequency. The literature on nonparametric and semiparametric estimation is large and highly technical. This book presents the main ideas underlying a variety of nonparametric and semiparametric methods. It is accessible to graduate students and applied researchers who are familiar with econometric and statistical theory at the level taught in graduate-level courses in leading universities. The book emphasizes ideas instead of technical details and provides as intuitive an exposition as possible. Empirical examples illustrate the methods that are presented. This book updates and greatly expands the author’s previous book on semiparametric methods in econometrics. Nearly half of the material is new.

Non-Parametric Econometrics

Author : Ibrahim Ahamada,Emmanuel Flachaire
Publisher : OUP Oxford
Page : 176 pages
File Size : 41,7 Mb
Release : 2010-12-23
Category : Business & Economics
ISBN : 9780199578009

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Non-Parametric Econometrics by Ibrahim Ahamada,Emmanuel Flachaire Pdf

This book allows those with a basic knowledge of econometrics to learn the main nonparametric and semiparametric techniques used in econometric modelling, and how to apply them correctly. It looks at kernel density estimation, kernel regression, splines, wavelets, and mixture models, and provides useful empirical examples throughout. Using empirical application, several economic topics are addressed, including income distribution, wage equation, economic convergence, the Phillipscurve, interest rate dynamics, returns volatility, and housing prices. A helpful appendix also explains how to implement the methods using R.This useful book will appeal to practitioners and researchers who need an accessible introduction to nonparametric and semiparametric econometrics. The practical approach provides an overview of the main techniques without including too much focus on mathematical formulas. It also serves as an accompanying textbook for a basic course, typically at undergraduate or graduate level.

Nonparametric Econometric Methods and Application

Author : Thanasis Stengos
Publisher : MDPI
Page : 224 pages
File Size : 42,5 Mb
Release : 2019-05-20
Category : Business & Economics
ISBN : 9783038979647

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Nonparametric Econometric Methods and Application by Thanasis Stengos Pdf

The present Special Issue collects a number of new contributions both at the theoretical level and in terms of applications in the areas of nonparametric and semiparametric econometric methods. In particular, this collection of papers that cover areas such as developments in local smoothing techniques, splines, series estimators, and wavelets will add to the existing rich literature on these subjects and enhance our ability to use data to test economic hypotheses in a variety of fields, such as financial economics, microeconomics, macroeconomics, labor economics, and economic growth, to name a few.

Nonparametric Econometric Methods

Author : Qi Li,Jeffrey Scott Racine
Publisher : Emerald Group Publishing
Page : 570 pages
File Size : 55,9 Mb
Release : 2009-12-04
Category : Business & Economics
ISBN : 9781849506236

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Nonparametric Econometric Methods by Qi Li,Jeffrey Scott Racine Pdf

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.

Nonparametric and Semiparametric Methods in Econometrics and Statistics

Author : William A. Barnett,James Powell,George E. Tauchen
Publisher : Cambridge University Press
Page : 512 pages
File Size : 50,7 Mb
Release : 1991-06-28
Category : Business & Economics
ISBN : 0521424313

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Nonparametric and Semiparametric Methods in Econometrics and Statistics by William A. Barnett,James Powell,George E. Tauchen Pdf

Papers from a 1988 symposium on the estimation and testing of models that impose relatively weak restrictions on the stochastic behaviour of data.

Nonparametric Econometric Methods

Author : Qi Li,Jeffrey Scott Racine
Publisher : Emerald Group Publishing
Page : 570 pages
File Size : 55,9 Mb
Release : 2009-12-04
Category : Business & Economics
ISBN : 9781849506236

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Nonparametric Econometric Methods by Qi Li,Jeffrey Scott Racine Pdf

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.

Introduction to Nonparametric Estimation

Author : Alexandre B. Tsybakov
Publisher : Springer Science & Business Media
Page : 222 pages
File Size : 51,7 Mb
Release : 2008-10-22
Category : Mathematics
ISBN : 9780387790527

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Introduction to Nonparametric Estimation by Alexandre B. Tsybakov Pdf

Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.