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S. Racine Jeffrey, Professor, Department of Economics | Professor, Graduate Program in Statistics, Department of Mathematics and Statistics | Senator William McMaster Chair in Econometrics | Fellow of Journal of Econometrics | Deputy Editor-in-Chief, Econometrics | Associate Editor, Econometric Reviews | Associate Editor, Journal of Econometric Methods

Jeffrey S. Racine

Professor, Department of Economics | Professor, Graduate Program in Statistics, Department of Mathematics and Statistics | Senator William McMaster Chair in Econometrics | Fellow of Journal of Econometrics | Deputy Editor-in-Chief, Econometrics | Associate Editor, Econometric Reviews | Associate Editor, Journal of Econometric Methods

Faculty
Department of Economics

Area(s) of Interest:

Biography

Jeffrey S. Racine (Ph.D. University of Western Ontario, 1989) is a Professor in the Department of Economics and a Professor in the Graduate Program in Statistics in the Department of Mathematics and Statistics at McMaster University. He occupies the Senator William McMaster Chair in Econometrics and is a Fellow of Journal of Econometrics. He has held previous appointments at Syracuse University, University of South Florida, University of California San Diego (two-year visiting appointment), and York University.

His research interests include nonparametric estimation and inference, cross-validatory model selection, frequentist model averaging, nonparametric instrumental methods, and entropy-based measures of dependence and their statistical underpinnings. He is also interested in parallel distributed computing paradigms and their application to computationally intensive nonparametric estimators.

He is currently serving as the Associate Editor for Econometric Reviews and the Journal of Econometric Methods and as the Deputy Editor-in-Chief for Econometrics.

He is the co-author of Nonparametric Econometrics: Theory and Practice (co-authored with Qi Li, published by Princeton University Press, 2007, 768 pages, with a Chinese translation published in 2015), the author of Nonparametric Econometrics: A Primer (published by Foundations and Trends in Econometrics, 2008 with a Russian translation published in the journal Quantile in 2008), has published extensively in his field and has co-authored the R packages np and crs that are available on the Comprehensive R Archive Network (CRAN).

Education

Ph.D. University of Western Ontario 1989

M.A. McMaster University 1985

B.A. McMaster University 1984 (Summa Cum Laude)

Research

Books

Li, Q. and J.S. Racine (2007), Nonparametric Econometrics: Theory and Practice, Princeton University Press, ISBN: 9780691121611, 768 Pages.

Chinese Translation:

Li, Q. and J.S. Racine, Nonparametric Econometrics: Theory and Practice, Translated by Ye Zhong, Wu Xianbgo et al., Peking University Press (2015), ISBN: 9787301249673.

Here is the table of contents (pdf), Chapter 1 (pdf), the Errata (pdf), the solution manual containing code and answers to odd numbered questions (pdf), and R code for answers to all applied questions (zip). A solution manual containing code and answers to all questions (odd and even) is available to instructors upon request. To receive a copy kindly email me your course syllabus along with your surface mailing address. A hard copy will then be sent via surface mail.

You can order the book directly from Princeton University Press (press.princeton.edu/titles/8355.html) or from your favourite online retailer.

Monographs

Racine, J.S. (2008), Nonparametric Econometrics: A Primer,  Foundations and Trends in Econometrics: Vol. 3: No 1, pp 1-88. http://dx.doi.org/10.1561/0800000009

Russian Translation:

An edited version of this monograph is reprinted in Russian and appears as Racine, J.S. (2008) "Nonparametric Econometrics: A Primer", Quantile, Number 4, pp 7-56.

Here is the R code to replicate examples in this primer (zip).

Edited Volumes

Oxford Handbook of Semiparametric and Nonparametric Econometric Methods, ISBN 978–0–19–985794–4, Edited By Jeffrey S. Racine, Liangjun Su, and Aman Ullah, Published: 2014.

Advances In Econometrics: Nonparametric Econometric Methods, Volume 25,  ISBN: 978-1-84950-623-6, Edited by: Qi Li, Jeffrey S. Racine, Published: 2009.

Gallery of Code and Applications for the np, npRmpi, and crs R Packages

The following link (link to gallery) will take you to a gallery where you can find some commented examples of working code for a range of estimators contained in the np, npRmpi, and crs packages outlined below. Feel free to email me with suggestions. I welcome code/examples that can be showcased and shared with other users, so please feel free to send me code that you would like to share and I will host it in the gallery along with your contact information.

The R np and npRmpi Packages

Consult the np FAQ (pdf) for responses to commonly asked questions and the user manual (pdf) for functions, descriptions, and examples. 

The R (www.r-project.org) np and npRmpi packages (current version 0.60-3) implement a variety of nonparametric and semiparametric kernel-based methods in R, an open source platform for statistical computing and graphics. Methods include kernel regression, kernel density estimation, kernel conditional density estimation, and a range of inferential procedures. See the links to the vignettes below for an overview of both packages (I would advise starting with the np vignette).

The np package is the standard package you would use under R, while the npRmpi package is a version that uses the message passing interface for parallel computing. The npRmpi package is designed for executing batch programs on compute clusters and multi-core computing environments to reduce the run time for computationally intensive jobs. See the example files in the demo directory of the npRmpi package for illustrative npRmpi code, and see the examples in the help files and the link for replicating examples for the primer above for code to generate a range of illustrative examples.

Here is a direct link to the np package on the Comprehensive R Archive Network (CRAN), a direct link to the npRmpi package on CRAN, a direct link to the CHANGELOG file on CRAN (documents differences between all versions), an npRmpi test file `test.R' (text), the npRmpi .Rprofile file (text), install instructions for npRmpi under Windows (text), and instructions for compiling the npRmpi binary from scratch under Windows (text), and instructions for compiling the npRmpi source from scratch for Mac OS X Mountain Lion (text). See the npRmpi github repository (link below) for a recent npRmpi MS Windows binary (available as a binary zip file from the github Downloads menu) and a recent npRmpi Mac OS X binary (available as a binary tgz file from the github Downloads menu).

See the October 2007 Rnews article (pdf) that describes the np package,  the np vignette (pdf) for an overview of the np package, the npRmpi vignette (pdf) for an overview of the installation and use of the npRmpi package, and the entropy-based inference vignette for an overview of computing entropy measures (pdf) (R code).

See also the review of the np package that appeared in 2008 in the Journal of Applied Econometrics (link to article in the Wiley Online Library) and the review of the npRmpi package that appeared in 2011 in the Journal of Applied Econometrics (link to article in the Wiley Online Library).

These packages are hosted on github (link)

NP Badge

The R crs Package

Consult the crs FAQ (pdf) for responses to commonly asked questions and the user manual (pdf) for functions, descriptions, and examples. 

The R (www.r-project.org) crs package (current version 0.15-26) implements multivariate regression splines (and quantile regression splines as of version 0.15-8) with both continuous and categorical predictors in R, an open source platform for statistical computing and graphics. See the links to the vignettes below for an overview of the package.

Here is a direct link to the crs package on the Comprehensive R Archive Network (CRAN), a direct link to the CHANGELOG file on CRAN (documents differences between all versions). 

See the R Journal article (pdf) that describes the crs package, the crs vignette (pdf) for an overview of the crs package and the spline primer vignette for an overview of regression splines (pdf).

This package is hosted on github (link).

CRS Badge

The R ma Package

Consult the user manual (pdf) for functions, descriptions, and examples, and the vignette (pdf) for an overview. 

The R (www.r-project.org) ma package (current version 1.0-8) implements model averaging using a variety of multivariate bases and averaging criteria.

This package is hosted on github (link).
 
The R hr Package
 
Consult the user manual (pdf) for functions, descriptions, and examples.

The R (www.r-project.org) ma package (current version 1.0-1) implements the Hansen-Racine bootstrap model average unit root test

This package is hosted on github (link).
 
Stata Implementations of Mixed Data Kernel Estimation (Racine & Li (2004) Journal of Econometrics, Li & Racine (2004) Statistica Sinica)
 
As of Stata Version 15, Stata users now have access to our mixed-datatype kernel regression methods. See http://www.stata.com/manuals/rnpregress.pdf for details. The Stata 15 function npregress is the counterpart to the function npreg in the R package np, albeit with different defaults and options. 
 
Recent Research Papers

Li, C., H. Li and J.S. Racine (forthcoming), “Cross-Validated Mixed Datatype Bandwidth Selection for Nonparametric Cumulative Distribution/Survivor Functions,” Econometric Reviews.

Centorrino, S. and J.S. Racine (forthcoming), “Semiparametric Varying Coefficient Models With Endogenous Covariates,” Annals of Economics and Statistics.

Beheshti, N. and J.S. Racine and E.S. Soofi (forthcoming), "Information Measures of Kernel Estimation," Econometric Reviews.

Kiefer, N.M. and J.S. Racine (2017), “The Smooth Colonel and the Reverend Find Common Ground,” Econometric Reviews, Volume 36, pages 241–256.

Koch, S.F. and J.S. Racine (2016), "Health Care Facility Choice and User Fee Abolition: Regression Discontinuity in a Multinomial Choice Setting," Journal of the Royal Statistical Society, Series A, Volume 179, 927–950.

Racine, J.S. (2016), "Local Polynomial Derivative Estimation: Analytic or Taylor?" Advances in Econometrics, Volume 36, 617-633.

Maasoumi, E. and J.S. Racine (2016), "A Solution to Aggregation and an Application to Multidimensional `Well-Being' Frontiers," Journal of Econometrics, Volume 191, 374-383.

Chakrabarty, M. and A. Majumder and J.S. Racine (2015), "Household Preference Distribution and Welfare Implication: An Application of Multivariate Distributional Statistics," Journal of Applied Statistics, Volume 42, Pages 2754-2768.

Ma, S. and J.S. Racine and L. Yang (2015), "Spline Regression in the Presence of Categorical Predictors," Journal of Applied Econometrics, Volume 30, 705-717. 

Hall, P. and J.S. Racine (2015), "Infinite-Order Cross-Validated Local Polynomial Regression," Journal of Econometrics, Volume 185, 510-525.

Racine, J.S. (2015), "Mixed Data Kernel Copulas," Empirical Economics, Volume 48, 37-59.

Gao, Q. and L. Liu and J.S. Racine (2015), "A Partially Linear Kernel Estimator for Categorical Data," Econometric Reviews, 34 (6-10), 958-977.

Racine, J.S. and C. Parmeter (2014), "Data-Driven Model Evaluation: A Test for Revealed Performance," in `Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics', Oxford University Press, (A. Ullah, J.S. Racine and L. Su Eds), 308-345.

Du, P. and C. Parmeter and J.S. Racine (2013), "Nonparametric Kernel Regression with Multiple Predictors and Multiple Shape Constraints," Statistica Sinica, Volume 23, 1343-1372.

Li, C. and J.S. Racine (2013), "A Smooth Nonparametric Conditional Density Test for Categorical Responses," Econometric Theory, Volume 29, 629-641.

Li, Q. and D. Ouyang and J.S. Racine (2013), "Categorical Semiparametric Varying-Coefficient Models," Journal of Applied Econometrics, Volume 28, 551-579.

Ma, S. and J.S. Racine (2013), "Additive Regression Splines with Irrelevant Categorical and Continuous Regressors," Statistica Sinica, Volume 23, 515-541.

Li, Q. and J. Lin and J.S. Racine (2013), "Optimal Bandwidth Selection for Nonparametric Conditional Distribution and Quantile Functions," Journal of Business and Economic Statistics, Volume 31, 57-65 (19 pages of supplementary material [proofs] available online at http://tandfonline.com/r/JBES).

Nie, Z. and J.S. Racine (2012), "The crs Package: Nonparametric Regression Splines for Continuous and Categorical Predictors," The R Journal, Volume 4, 48-56.

Parmeter, C. and J.S. Racine (2012), "Smooth Constrained Frontier Analysis," in `Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis: Essays in Honor of Halbert L. White, Jr.', Springer Verlag, (X. Chen and N.R. Swanson Eds), 463-488.

Racine, J.S. (2012), "RStudio: A Platform Independent IDE for R and Sweave," Journal of Applied Econometrics, Volume 27, 167-172.

Hansen, B. and J.S. Racine (2012), "Jackknife Model Averaging," Journal of Econometrics, Volume 167, 38-46.

Gyimah-Brempong, K. and J.S. Racine and A. Gyapong (2012), "Aid and Economic Growth: Sensitivity Analysis," Journal of International Development, Volume 24, 17-33. 

Working Papers, Citation Summary, and Miscellany

Working Papers and Articles (RePEc Author Service)

Citation Counts and Related Indices (Google Scholar Citations)

Top 25% Institutions and Economists in Canada (RePEc)

Top 10% Institutions and Economists in the Field of Econometrics (RePEc)

Top 1% Research Items by Number of Citations (RePEc)

Academic Software Rankings and Related Metrics (Depsy.org)

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