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Title: Functional coefficient time series models with trending regressors Authors:  Tingting Cheng - Nankai University (China) [presenting]
Abstract: A functional coefficient time series model with trending regressors is studied, where the coefficients are unknown functions of time and random variables. We propose a local linear estimation method to estimate the unknown coefficient functions. An asymptotic distribution of the proposed local linear estimator is established under mild conditions. For practical use, we further propose a Bayesian approach to select bandwidths involved in this local linear estimator. Several numerical examples are provided to examine the finite sample performance of the proposed local linear estimator. The results show that the local linear estimator works well and the Bayesian bandwidth selection method is better than cross-validation method. Furthermore, we employ the functional coefficient model to study the relationship between consumption per capita and income per capita in U.S. and the results show that functional coefficient model with our proposed local linear estimator and Bayesian bandwidth selection method performs best in both in sample fitting and out of sample forecasting.