Empirical likelihood inference for threshold autoregressive conditional heteroscedasticity model

Abstract This paper considers the parameter estimation problem of a first-order threshold autoregressive conditional heteroscedasticity model by using empirical likelihood method. We obtain ratio statistic based on estimating equation least squares and construct confidence region for parameters. Simulation studies indicate that method outperforms normal approximation-based in terms coverage probability.