Books and Monographs
Books
Advanced Nonparametric Econometrics
Racine, J.S. (2019a), An Introduction to the Advanced Theory and Practice of Nonparametric Econometrics: A Replicable Approach Using R, Cambridge University Press.
Reproducible Econometrics Using R
Racine, J.S. (2019b), Reproducible Econometrics Using R, Oxford University Press.
Nonparametric Econometrics
Li, Q. and J.S. Racine (2007), Nonparametric Econometrics: Theory and Practice, Princeton University Press.
Chinese Translation
Li, Q. and J.S. Racine, Nonparametric Econometrics: Theory and Practice, translated edition, Peking University Press, 2015.
ISBN: 9787301249673.
Instructor materials for adopted courses, including slides, assignments, exams, and solution manuals, are available upon request where noted by the publisher companion material.
Topic Guides
Cambridge: Advanced Nonparametric Econometrics
The Cambridge book is the most direct companion for modern np / npRmpi work. Its manuscript source covers:
- R, RStudio, TeX, Git, and reproducible book workflows;
- discrete probability, continuous density and distribution functions, and mixed-data density/distribution methods;
- conditional moment functions, conditional mean regression, conditional variance, conditional density and distribution functions;
- semiparametric conditional mean models and conditional mean models with endogenous predictors;
- computational considerations and practicum material.
Public-facing companion files are listed on Downloads and Teaching. Instructor-only teaching materials remain available by request.
Oxford: Reproducible Econometrics Using R
The Oxford book is the broad reproducible-computation companion. Its source structure covers:
- R, RStudio, TeX, and Git workflows;
- maximum likelihood estimation and inference;
- robust parametric estimation and robust inference, including bootstrap and jackknife material;
- model uncertainty and model averaging;
- linear time series methods, including ARIMA, random walks, unit roots, and spurious relationships;
- regression splines and quadratic programming.
This book is the natural bridge between econometric practice and the reproducible workflow conventions reflected in the package ecosystem.
Princeton: Nonparametric Econometrics
The Princeton book remains the theory-and-practice foundation for many estimators implemented in np and npRmpi. The local book corpus includes source and companion material for kernel density, conditional density, CDF/quantile material, censored models, endogenous dependent variables, panel material, mixed smoothing, testing, and applied examples.
Public companion files currently surfaced here include the table of contents, errata, Chapter 1, odd-question solutions, and applied-question code.
Monograph
Racine, J.S. (2008), Nonparametric Econometrics: A Primer, Foundations and Trends in Econometrics, 3(1), 1-88. DOI link.
The R code used to replicate examples in the primer is available as a zip archive.
An edited Russian translation appeared as Racine, J.S. (2008), “Nonparametric Econometrics: A Primer”, Quantile, Number 4, 7-56.
Edited Volumes
- Oxford Handbook of Semiparametric and Nonparametric Econometric Methods, edited by Jeffrey S. Racine, Liangjun Su, and Aman Ullah, Oxford University Press, 2014.
- Advances In Econometrics: Nonparametric Econometric Methods, Volume 25, edited by Qi Li and Jeffrey S. Racine, Emerald, 2009.
Princeton Companion Files
A solution manual containing code and answers to all questions is available to instructors upon request. Please email a course syllabus and surface mailing address.