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THE ET INTERVIEW: PROFESSOR JOEL L. HOROWITZ

Published online by Cambridge University Press:  13 February 2025

Sokbae Lee*
Affiliation:
Columbia University
*
Sokbae Lee: Department of Economics, Columbia University, New York, USA; email: [email protected]

Abstract

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Type
ET INTERVIEW
Copyright
© The Author(s), 2025. Published by Cambridge University Press

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References

REFERENCES

Blundell, R., & Horowitz, J. L. (2007). A nonparametric test for exogeneity. Review of Economic Studies , 74, 10351058.CrossRefGoogle Scholar
Blundell, R., Horowitz, J. L., & Parey, M. (2012). Measuring the price responsiveness of gasoline demand: Economic shape restrictions and nonparametric estimation. Quantitative Economics , 3, 2951.CrossRefGoogle Scholar
Blundell, R., Horowitz, J. L., & Parey, M. (2017). Nonparametric estimation of a nonseparable demand function under the Slutsky inequality restriction. Review of Economics and Statistics , 99, 291304.CrossRefGoogle Scholar
Blundell, R., Horowitz, J. L., & Parey, M. (2022). Estimation of a heterogeneous demand function with Berkson errors. Review of Economics and Statistics , 104, 877899.CrossRefGoogle Scholar
Bugni, F. A., Hall, P., Horowitz, J. L., & Neumann, G. R. (2009). Goodness-of-fit tests for functional data. The Econometrics Journal , 12, S1S18.CrossRefGoogle Scholar
Bugni, F. A., & Horowitz, J. L. (2021). Permutation tests for equality of distributions of functional data. Journal of Applied Econometrics , 36, 861877.CrossRefGoogle Scholar
Forsythe, R., Horowitz, J. L., Savin, N. E., & Sefton, M. (1994). Fairness in simple bargaining experiments. Games and Economic Behavior , 6, 347369.CrossRefGoogle Scholar
Freyberger, J., & Horowitz, J. L. (2015). Identification and shape restrictions in nonparametric instrumental variables estimation. Journal of Econometrics , 189, 4153.CrossRefGoogle Scholar
Fu, J.-Y. M., Horowitz, J. L., & Parey, M. (2021). Testing exogeneity in nonparametric instrumental variables models identified by conditional quantile restrictions. The Econometrics Journal , 24, 2340.CrossRefGoogle Scholar
Hall, P., & Horowitz, J. L. (1990). Bandwidth selection in semiparametric estimation of censored linear regression models. Econometric Theory , 6, 123150.CrossRefGoogle Scholar
Hall, P., & Horowitz, J. L. (1996). Bootstrap critical values for tests based on generalized-method-of-moments estimators. Econometrica , 64, 891916.CrossRefGoogle Scholar
Hall, P., & Horowitz, J. L. (2005). Nonparametric methods for inference in the presence of instrumental variables. Annals of Statistics , 33, 29042929.CrossRefGoogle Scholar
Hall, P., & Horowitz, J. L. (2007). Methodology and convergence rates for functional linear regression. Annals of Statistics , 35, 7091.CrossRefGoogle Scholar
Hall, P., & Horowitz, J. L. (2013). A simple bootstrap method for constructing confidence bands for functions. Annals of Statistics , 41, 18921914.CrossRefGoogle Scholar
Hall, P., Horowitz, J. L., & Jing, B.-Y. (1995). On blocking rules for the bootstrap with dependent data. Biometrika , 82, 561574.CrossRefGoogle Scholar
Härdle, W., & Horowitz, J. L. (1994). Testing a parametric model against a semiparametric alternative. Econometric Theory , 10, 821848.Google Scholar
Härdle, W., & Horowitz, J. L. (1996). Direct semiparametric estimation of a single-index model with discrete covariates. Journal of the American Statistical Association , 91, 16321640.Google Scholar
Härdle, W., Horowitz, J. L., & Kreiss, J.-P. (2003). Bootstrap methods for time series. International Statistical Review , 71, 435459.CrossRefGoogle Scholar
Horowitz, J. L. (1992). A smoothed maximum score estimator for the binary response model. Econometrica , 60, 505531.CrossRefGoogle Scholar
Horowitz, J. L. (1996). Semiparametric estimation of a regression model with an unknown transformation of the dependent variable. Econometrica , 64, 103137.CrossRefGoogle Scholar
Horowitz, J. L. (1998a). Semiparametric methods in econometrics . Springer.CrossRefGoogle Scholar
Horowitz, J. L. (1998b). Bootstrap methods for median regression models. Econometrica , 66, 13271351.CrossRefGoogle Scholar
Horowitz, J. L. (1999). Semiparametric estimation of a proportional hazard model with unobserved heterogeneity. Econometrica , 67, 10011028.CrossRefGoogle Scholar
Horowitz, J. L. (2001). The bootstrap in econometrics. In Heckman, J. J. & Leamer, E. E. (Eds.), Handbook of econometrics (Chapter 52, Vol. 5, pp. 31593228). Elsevier.Google Scholar
Horowitz, J. L. (2002). Bootstrap critical values for tests based on the smoothed maximum score estimator. Journal of Econometrics , 111, 141167.CrossRefGoogle Scholar
Horowitz, J. L. (2009). Semiparametric and nonparametric methods in econometrics . Springer.CrossRefGoogle Scholar
Horowitz, J. L. (2019). Bootstrap methods in econometrics. Annual Review of Economics , 11, 193204.CrossRefGoogle Scholar
Horowitz, J. L., & Huang, J. (2013). Penalized estimation of high-dimensional models under a generalized sparsity condition. Statistica Sinica , 23, 725748.Google Scholar
Horowitz, J. L., & Krishnamurthy, A. (2018). A bootstrap method for construction of pointwise and uniform confidence bands for conditional quantile functions. Statistica Sinica , 28, 26092632.Google Scholar
Horowitz, J. L., & Mammen, E. (2004). Nonparametric estimation of an additive model with a link function. Annals of Statistics , 32, 24122443.CrossRefGoogle Scholar
Horowitz, J. L., & Mammen, E. (2007). Rate-optimal estimation for a general class of nonparametric regression models with unknown link functions. Annals of Statistics , 35, 25892619.CrossRefGoogle Scholar
Horowitz, J. L., & Mammen, E. (2011). Oracle-efficient nonparametric estimation of an additive model with an unknown link function. Econometric Theory , 27, 582608.CrossRefGoogle Scholar
Horowitz, J. L., Mammen, E., & Klemelä, J. (2006). Optimal estimation in additive regression models. Bernoulli , 12, 271298.CrossRefGoogle Scholar
Horowitz, J. L., & Manski, C. F. (1995). Identification and robustness with contaminated and corrupted data. Econometrica , 63, 281302.CrossRefGoogle Scholar
Horowitz, J. L., & Nesheim, L. (2021). Using penalized likelihood to select parameters in a random coefficients multinomial logit model. Journal of Econometrics , 222, 10571082.CrossRefGoogle Scholar
Horowitz, J. L., & Neumann, G. R. (1987). Semiparametric estimation of employment duration models. Econometric Reviews , 6, 540.CrossRefGoogle Scholar
Horowitz, J. L., & Neumann, G. R. (1992). A generalized moments specification test of the proportional hazards model. Journal of the American Statistical Association , 87, 234240.CrossRefGoogle Scholar
Horowitz, J. L., & Spokoiny, V. (2001). An adaptive, rate-optimal test of a parametric mean-regression model against a nonparametric alternative. Econometrica , 69, 599631.CrossRefGoogle Scholar
Horowitz, J. L., & Spokoiny, V. (2002). An adaptive, rate-optimal test of linearity for median regression models. Journal of the American Statistical Association , 97, 822835.CrossRefGoogle Scholar
Huang, J., Horowitz, J. L., & Ma, S. (2008). Asymptotic properties of bridge estimators in sparse, high-dimensional regression models. Annals of Statistics , 36, 587613.CrossRefGoogle Scholar
Huang, J., Horowitz, J. L., & Wei, F. (2010). Variable selection in nonparametric additive models. Annals of Statistics , 38, 2282–2231.CrossRefGoogle ScholarPubMed
Shen, G., Jiao, Y., Lin, Y., Horowitz, J. L., & Huang, J. (2024). Nonparametric estimation of non-crossing quantile regression process with deep ReQU neural networks. Journal of Machine Learning Research , 25(88), 175.Google Scholar