NONPARAMETRIC ADDITIVE MODELS FOR PANELS OF TIME SERIES
系统研究了时间序列面板数据的非参数可加模型，提出基于回拟合方法的估计方法，填补了高维面板数据非参数建模的理论空白。
This paper discusses nonparametric models for panels of time series. There is already a substantial literature on nonlinear models and nonparametric methods in a regression and time series setting. But almost without exception these developments have been limited to univariate and multivariate models of moderate dimensions. Very little has been done for panels, where the dimension, often corresponding to a number of individuals, typically is very large but where the number of observations for each individual may be small or moderate. It is the aim of this paper to start a systematic theoretical treatment of nonparametric models for panels of time series, in particular on additive models. Extending existing methodology to the panel situation is by no means trivial because already for the parametric case many problems are unsolved. Our estimation approach is based on backfitting methods.