Essays on model selection - Guo, Y (2021)
This dissertation has two goals. Firstly, we consider the problem of model selection for nonlinear time series models and study an auxiliary-regression-based test for serial correlation. Under the assumption of martingale difference errors, rejection of the test would imply model misspecification in the adopted functional form or insufficient dynamic specification. The proposed test allows for the presence of stationary and/or non-stationary variables, and the test statistic follows a standard chi-square distribution asymptotically. Monte Carlo simulations show that the proposed test has good finite sample properties.