include profile likelihood, kernel smoothers, as well as series and sieve estimators. The practical application of …

using classic kernel smoothing methods to estimate the coefficient functions. Extending earlier work on nonstationary kernel … of stochastic and deterministic trends, complications which result in asymptotic degeneracy of the kernel-weighted signal … results that differ substantially from existing kernel regression asymptotics, leading to new limit theory under multiple …

relationships between nonstationary variables. In particular, we analyze nonparametric kernel regressions in which a potential …

Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric … models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we found the …