Jeffrey Racine
Jeffrey S. Racine is a Professor of Economics, Professor in the Graduate Program in Statistics, and the holds the Senator William McMaster Chair in Econometrics at McMaster University, Canada. He received his PhD degree in economics from the University of Western Ontario in 1989. His research interests include nonparametric estimation and inference, cross-validatory model selection, nonparametric instrumental methods, and entropy-based measures of dependence and their statistical underpinnings. He has contributed three packages to the R community that implement a range of estimators he has developed (np, npRmpi, crs). He is currently an Associate Editor for Econometric Reviews, the Journal of Econometric Methods, and is editing a volume of the Oxford Handbook of Economics and Statistics.
Racine, J. S. & Van Keilegom, I. (2020). A Smooth Nonparametric, Multivariate, Mixed-Data Location-Scale Test. Journal of Business and Economic Statistics, 38(4), 784-795. https://doi.org/10.1080/07350015.2019.1574227
Racine, J. S. (2019). An Introduction to the Advanced Theory and Practice of Nonparametric Econometrics: A Replicable Approach Using R. Cambridge University Press. https://doi.org/10.1017/9781108649841
Racine, J. S. (2019). Energy, economics, replication & reproduction. Energy Economics, 82, 264-275. https://doi.org/10.1016/j.eneco.2017.06.027
Beheshti, N., Racine, J. S. & Soofi, E. S. (2019). Information measures of kernel estimation. Econometric Reviews, 38(1), 47-68. https://doi.org/10.1080/07474938.2016.1222236
Parmeter, C. F. & Racine, J. S. (2019). Nonparametric Estimation and Inference for Panel Data Models. In Panel Data Econometrics: Theory (pp. 97-129). Elsevier. https://doi.org/10.1016/B978-0-12-814367-4.00004-6
Ma , S., Ullah, A. & Racine, J. S. (2019). Nonparametric Estimation of Marginal Effects in Regression-Spline Random Effects Models. University of California at Riverside, Department of Economics. https://economics.ucr.edu/repec/ucr/wpaper/201920.pdf
Racine, J. S. (2019). Reproducible Econometrics Using R. Oxford University Press.
Li, C., Li, Q., Racine, J. S. & Zhang, D. (2018). Optimal model averaging of varying coefficient models. Statistica Sinica, 28(4), 2795-2809. https://doi.org/10.5705/ss.202017.0034
Li, C., Li, H. & Racine, J. S. (2017). Cross-validated mixed-datatype bandwidth selection for nonparametric cumulative distribution/survivor functions. Econometric Reviews, 36(6-9), 970-987. https://doi.org/10.1080/07474938.2017.1307900
Centorrino, S. & Racine, J. S. (2017). Semiparametric Varying Coefficient Models With Endogenous Covariates. Annals of Economics and Statistics, (128), 261-295. https://doi.org/10.15609/annaeconstat2009.128.0261
Kiefer, N. M. & Racine, J. S. (2017). The smooth colonel and the reverend find common ground. Econometric Reviews, 36(1-3), 241-256. https://doi.org/10.1080/07474938.2015.1114304
Maasoumi, E. & Racine, J. S. (2016). A solution to aggregation and an application to multidimensional 'well-being' frontiers. Journal of Econometrics, 191(2), 374–383. https://doi.org/10.1016/j.jeconom.2015.12.008
Koch, S. F. & Racine, J. S. (2016). Healthcare facility choice and user fee abolition: regression discontinuity in a multinomial choice setting. Journal of the Royal Statistical Society, Series A (Statistics in Society), 179(4), 927-950. https://doi.org/10.1111/rssa.12161
Racine, J. S. (2016). Local Polynomial Derivative Estimation: Analytic or Taylor? In G. González-Rivera, R. C. Hill & T-H. Lee (Eds.), Essays in Honor of Aman Ullah (pp. 617 - 633). Emerald Group Publishing. Advances in Econometrics Vol. 36 https://doi.org/10.1108/S0731-905320160000036027
Racine, J. S., Chakrabarty, M. & Majumder, A. (2015). Household budget-share distributions and welfare implications: an application of multivariate distributional statistics. Journal of Applied Statistics, 42(12), 2754-2768. https://doi.org/10.1080/02664763.2015.1049132
Racine, J. S. (2015). Mixed data kernel copulas. Empirical Economics, 48(1), 37–59. https://doi.org/10.1007/s00181-015-0913-3
Racine, J. S., Gao, Q. & Liu, L. (2014). A Partially Linear Kernel Estimator for Categorical Data. Econometric Reviews, 34(6-10), 959-978. https://doi.org/10.1080/07474938.2014.956613
Gyimah-Brempong, K. & Racine, J. S. (2014). Aid and Economic Growth: A Robust Approach. Journal of African Development, 16(1), 1-35. http://www.jadafea.com/vol16-1/
Cong, L. & Racine, J. S. (2013). A smooth nonparametric conditional density test for categorical responses. Econometric Theory, 29(3), 629-641. https://doi.org/10.1017/S0266466612000382
Ma, S. & Racine, J. S. (2013). Additive regression splines with irrelevant categorical and continuous regressors. Statistica Sinica, 23(2), 515-541. https://doi.org/10.5705/ss.2011.096
Li, Q., Ouyang, D. & Racine, J. S. (2013). Categorical semiparametric varying-coefficient models. Journal of Applied Econometrics, 28(4), 551-579. https://doi.org/10.1002/jae.1261
Du, P., Parmeter, C. F. & Racine, J. S. (2013). Nonparametric kernel regression with multiple predictors and multiple shape constraints. Statistica Sinica, 23(3), 1347-1371. https://doi.org/10.5705/ss.2012.024
Li, Q., Lin, J. & Racine, J. S. (2013). Optimal bandwidth selection for nonparametric conditional distribution and quantile functions. Journal of Business and Economic Statistics, 31(1), 57-65. https://doi.org/10.1080/07350015.2012.738955
Li, Q. & Racine, J. S. (2007). Nonparametric Econometrics: Theory and Practice. Princeton University Press.
