In the presence of a nuisance parameter, one widely shared approach to likelihood inference on a scalar parameter of interest is based on the profile likelihood and its various modifications. In this paper, we add a penalization to the modified profile likelihood, which is based on a suitable...

The performance of a kernel HAC estimator depends on the accuracy of the estimation of the normalized curvature, an unknown quantity in the optimal bandwidth represented as the spectral density and its derivative. This paper proposes to estimate it with a general class of kernels. The AMSE of...

Conventional wisdom usually suggests that agents should use all the data they have to make the best possible prediction. In this paper, it is shown that agents may make better predictions by discarding old data if their model is mis-specified. The applicability of the results to some economic...