This monograph contains solutions to the exercises appearing in Li and Racine ( ). Solutions to the empirical exercises are provided in the. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types–continuous, nominal, and ordinal–within one coherent. Nonparametric Econometrics: Theory and Practice. Qi Li and Jeffrey Scott Racine . Article in Journal of the American Statistical Association (June)
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Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in econometrjcs 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 economtrics 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 nonparametrric data–nominal and ordinal–in applied settings.
The conventional nonparametric approach to dealing with nonparameric 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. The Best Books of Check out the top books of the year on our page Best Books of Product details Format Hardback pages Dimensions x x Looking for beautiful books?
Visit our Beautiful Books page and find lovely books for kids, photography lovers and more. Back cover copy “Nonparametric Econometrics by Li and Racine is a must for any serious econometrician or statistician who is working on cutting-edge problems. The theoretical treatment of nonparametric methods is remarkably complete in its coverage of mainstream and relatively arcane topics.
I particularly like Li and Racine’s general treatment of continuous and discrete regressors and of specification testing, topics that I have not seen handled in such a comprehensive fashion.
I will certainly use this in my graduate econometrics courses and in conducting my own research. The lack of applications of those techniques is perhaps attributable to the lack of a good textbook that explains intuitively how and why those techniques work.
This book by Li and Racine serves both applied researchers onnparametric graduate students. It is written in plain language so that it can be understood by anyone with nonparamehric econometrics but zero knowledge of nonparametric methods. And it contains enough specifics that clearly spell out steps to implement those methods.
It provides an extremely thorough coverage of our knowledge in the area of nonparametric and semiparametric methods as they apply to economic models and economic data.
And it makes accessible, for the first time, a body of relatively new material relating to discrete and ‘mixed’ data. There is a good balance of theoretical material and applications. Giles, University of Victoria show more. Nonparametric Kernel Methods 1 Chapter 1: Density Estimation 3 1. Rule-of-Thumb and Plug-In Methods 14 1.
Nonparametric Econometrics: Theory and Practice
Cross-Validation ZMethods 15 1. Cross- Validation Methods 23 1. Rule-of-Thumb and Plug-In Methods 26 1. Cross-Validation Methods 27 1. Least Squares Cross-Validation 83 2. Frequency Estimation with Mixed Data 3. Nnparametric Frequency Approach 3.
Kernel Estimation with Mixed Data 4. The Irrelevant Regressor Case 4.
Nonparametric Econometrics: Theory and Practice
Relevant Regressors 4. Irrelevant Regressors 4.
Conditional Density Estimation 5. Relevant Variables 5. Irrelevant Variables 5. Semiparametric Methods Chapter 7: Semiparametric Partially Linear Models 7. Semiparametric Single Index Models 8. Selectivity Models Censored Models Model Specification Tests Nonsmoothing Tests K-Nearest Neighbor Methods The Univariate Case Nonparametric Series Methods Endogeneity in Nonparametric Regression Models Weakly Dependent Data Panel Data Models Ignoring the Variance Structure Topics in Applied Nonparametric Estimation Assessing the Efficacy of Right Heart Catheterization Review quote “Overall, the text is a must for graduate students undertaking research in this area; the large number of exercises at the end of each chapter makes it very suitable for a graduate class on nonparametric and semiparametric techniques.
Nonparametric Econometrics : Theory and Practice
In addition, because the coverage of the book is very comprehensive and up-to-date, it constitutes an excellent reference for researchers applying these techniques. Therefore, it can satisfy the needs of both audiences with a solid background in theoretical econometrics and more applied audiences. Li and Racine have done a fantastic job of bringing together all the latest developments in non-parametric estimation and treating them in a unified, accessible way.
In particular, recent developments on using mixed continuous and discrete data, research to which Li and Raci have contributed immensely, are well covered. Book ratings by Goodreads. Goodreads is the world’s largest site for readers with over 50 million reviews.
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