In this paper, we propose a state-varying endogenous regime switching model (the SERS model), which includes the endogenous regime switching model by Chang, Choi and Park (2017), the CCP model, as a special case. To estimate the unknown parameters involved in the SERS model, we propose a maximum...

Bandwidth plays an important role in determining the performance of local linear estimators. In this paper, we propose a Bayesian approach to bandwidth selection for local linear estimation of time-varying coefficient time series models, where the errors are assumed to follow the Gaussian kernel...

In this paper, we introduce a regime switching panel data model with interactive fixed effects. We propose a maximum likelihood estimation method and develop an expectation and conditional maximization algorithm to estimate the unknown parameters. Simulation results show that the algorithm works...