Empirical likelihood inference for semi-parametric varying-coefficient partially linear EV models

In this paper, we apply empirical likelihood method to study the semi-parametric varying-coefficient partially linear errors-in-variables models. Empirical log-likelihood ratio statistic for the unknown parameter beta, which is of primary interest, is suggested. We show that the proposed statistic is asymptotically standard chi-square distribution under some suitable conditions, and hence it can be used to construct the confidence region for the parameter beta. Some simulations indicate that, in terms of coverage probabilities and average lengths of the confidence intervals, the proposed method performs better than the least-squares method. We also give the maximum empirical likelihood estimator (MELE) for the unknown parameter beta, and prove the MELE is asymptotically normal under some suitable conditions.