skip to content

Faculty of Economics

Journal Cover

Linton, O., Mammen, E., Nielsen, J. P. and Van Keilegom, I.

Nonparametric Regression with Filtered Data


Vol. 17 no. 1 pp. 60-87 (2011)

Abstract: We present a general principle for estimating a regression function nonparametrically, allowing for a wide variety of data filtering, for example, repeated left truncation and right censoring. Both the mean and the median regression cases are considered. The method works by first estimating the conditional hazard function or conditional survivor function and then integrating. We also investigate improved methods that take account of model structure such as independent errors and show that such methods can improve performance when the model structure is true. We establish the pointwise asymptotic normality of our estimators.

Author links: Oliver Linton  

Publisher's Link:

Papers and Publications

Recent Publications

Fruehwirth, J., Iyer, S. and Zhang, A. Religion and Depression in Adolescence Journal of Political Economy [2019]

Ambrus, A. and Elliott, M. Investments in Social Ties, Risk Sharing, and Inequality Review of Economic Studies [2020]

Cavalcanti, T. and Santos, M. (Mis)Allocation Effects of an Overpaid Public Sector Journal of the European Economic Association [2020]

Li, Z. M., Laeven, R. J. A. and Vellekoop, M. H. Dependent Microstructure Noise and Integrated Volatility: Estimation from High-Frequency Data Journal of Econometrics [2020]