No CrossRef data available.
Article contents
THE ET INTERVIEW: PROFESSOR JOEL L. HOROWITZ
Published online by Cambridge University Press: 13 February 2025
Abstract
An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.

- Type
- ET INTERVIEW
- Information
- Copyright
- © The Author(s), 2025. Published by Cambridge University Press
References
REFERENCES
Blundell, R., & Horowitz, J. L. (2007). A nonparametric test for exogeneity.
Review of Economic Studies
, 74, 1035–1058.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, 29–51.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, 291–304.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, 877–899.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, S1–S18.CrossRefGoogle Scholar
Bugni, F. A., & Horowitz, J. L. (2021). Permutation tests for equality of distributions of functional data.
Journal of Applied Econometrics
, 36, 861–877.CrossRefGoogle Scholar
Forsythe, R., Horowitz, J. L., Savin, N. E., & Sefton, M. (1994). Fairness in simple bargaining experiments.
Games and Economic Behavior
, 6, 347–369.CrossRefGoogle Scholar
Freyberger, J., & Horowitz, J. L. (2015). Identification and shape restrictions in nonparametric instrumental variables estimation.
Journal of Econometrics
, 189, 41–53.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, 23–40.CrossRefGoogle Scholar
Hall, P., & Horowitz, J. L. (1990). Bandwidth selection in semiparametric estimation of censored linear regression models.
Econometric Theory
, 6, 123–150.CrossRefGoogle Scholar
Hall, P., & Horowitz, J. L. (1996). Bootstrap critical values for tests based on generalized-method-of-moments estimators.
Econometrica
, 64, 891–916.CrossRefGoogle Scholar
Hall, P., & Horowitz, J. L. (2005). Nonparametric methods for inference in the presence of instrumental variables.
Annals of Statistics
, 33, 2904–2929.CrossRefGoogle Scholar
Hall, P., & Horowitz, J. L. (2007). Methodology and convergence rates for functional linear regression.
Annals of Statistics
, 35, 70–91.CrossRefGoogle Scholar
Hall, P., & Horowitz, J. L. (2013). A simple bootstrap method for constructing confidence bands for functions.
Annals of Statistics
, 41, 1892–1914.CrossRefGoogle Scholar
Hall, P., Horowitz, J. L., & Jing, B.-Y. (1995). On blocking rules for the bootstrap with dependent data.
Biometrika
, 82, 561–574.CrossRefGoogle Scholar
Härdle, W., & Horowitz, J. L. (1994). Testing a parametric model against a semiparametric alternative.
Econometric Theory
, 10, 821–848.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, 1632–1640.Google Scholar
Härdle, W., Horowitz, J. L., & Kreiss, J.-P. (2003). Bootstrap methods for time series.
International Statistical Review
, 71, 435–459.CrossRefGoogle Scholar
Horowitz, J. L. (1992). A smoothed maximum score estimator for the binary response model.
Econometrica
, 60, 505–531.CrossRefGoogle Scholar
Horowitz, J. L. (1996). Semiparametric estimation of a regression model with an unknown transformation of the dependent variable.
Econometrica
, 64, 103–137.CrossRefGoogle Scholar
Horowitz, J. L. (1998b). Bootstrap methods for median regression models.
Econometrica
, 66, 1327–1351.CrossRefGoogle Scholar
Horowitz, J. L. (1999). Semiparametric estimation of a proportional hazard model with unobserved heterogeneity.
Econometrica
, 67, 1001–1028.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. 3159–3228). Elsevier.Google Scholar
Horowitz, J. L. (2002). Bootstrap critical values for tests based on the smoothed maximum score estimator.
Journal of Econometrics
, 111, 141–167.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, 193–204.CrossRefGoogle Scholar
Horowitz, J. L., & Huang, J. (2013). Penalized estimation of high-dimensional models under a generalized sparsity condition.
Statistica Sinica
, 23, 725–748.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, 2609–2632.Google Scholar
Horowitz, J. L., & Mammen, E. (2004). Nonparametric estimation of an additive model with a link function.
Annals of Statistics
, 32, 2412–2443.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, 2589–2619.CrossRefGoogle Scholar
Horowitz, J. L., & Mammen, E. (2011). Oracle-efficient nonparametric estimation of an additive model with an unknown link function.
Econometric Theory
, 27, 582–608.CrossRefGoogle Scholar
Horowitz, J. L., Mammen, E., & Klemelä, J. (2006). Optimal estimation in additive regression models.
Bernoulli
, 12, 271–298.CrossRefGoogle Scholar
Horowitz, J. L., & Manski, C. F. (1995). Identification and robustness with contaminated and corrupted data.
Econometrica
, 63, 281–302.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, 1057–1082.CrossRefGoogle Scholar
Horowitz, J. L., & Neumann, G. R. (1987). Semiparametric estimation of employment duration models.
Econometric Reviews
, 6, 5–40.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, 234–240.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, 599–631.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, 822–835.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, 587–613.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), 1–75.Google Scholar