Estimation of nonstationary nonparametric regression model with multiplicative structure
提出一种乘法非平稳非参数回归模型及三步估计法，能有效估计条件均值函数并实现降维，适用于小样本和显式乘法结构模型，并用美国消费增长和S&P 500月度风险溢价两个应用验证。
Summary This paper presents a multiplicative nonstationary nonparametric regression model 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.