-based estimation procedures for the parametric and nonparametric components, and derive the asymptotic properties thereof. For the …

distribution theory needed to conduct inference, propose some model free upper bound critical values, and apply our methods to …

/bootstrap theory applies, but at the expense of throwing away data and perhaps losing efficiency. An alternative is to use some sort of … theory changes and how to modify the resampling algorithms to accommodate the problem of missing data. We also discuss …

We develop estimation methodology for an additive nonparametric panel model that is suitable for capturing the pricing … techniques: cross-sectional nonparametric methods and kernel estimation for time varying dynamics in the time series context. The …

paper discusses identification and consistent estimation of the unknown functions H, M, G and F, where r (x, z) = H [M (x, z …)] and M (x, z) = G(x) + F (z). An estimation algorithm is proposed for each of the model's unknown components when r (x, z …

run volatility function. Our estimation is based on a two-step LAD procedure. We establish the relevant asymptotic theory … robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility … propose different robust estimation methods for nonstationary and strictly stationary GARCH parameters with nonparametric long …

show from inefficient estimation methods or technical difficulties. Based on local linear kernel smoother, we propose an … estimation method to estimate the single-index model without under-smoothing. Under some conditions, our estimator of the single … estimator and use them to define an optimal bandwidth for the purposes of index estimation. As a result we obtain a practically …