A0439
Title: Estimation of nonstationary nonparametric regression model with multiplicative structure
Authors: Ekaterina Smetanina - University of Chicago (United States) [presenting]
Abstract: A multiplicative nonstationary nonparametric regression model is presented, which allows for a broad class of nonstationary processes. We propose a three-step estimation procedure to uncover the conditional mean function and establish uniform convergence rates and asymptotic normality of our estimators. The new model can also be seen as a dimension reduction technique for a general two-dimensional time-varying nonparametric regression model, which is especially useful in small samples and for estimating explicitly multiplicative structural models. We consider two applications: estimating a pricing equation for the US aggregate economy to model consumption growth, and estimating the shape of the monthly risk premium for S\&P 500 Index data.