Search Results - subject:"estimation error"

Generalized (Cross) Spectral Tests for Optimal Forecasts and Conditional Predictive Ability Under Generalized Loss Functions

Lee, Tae-Hwy; Hong, Yongmiao - Econometric Society - 2004

Under the squared error loss, the optimal forecast is the conditional mean, and the one-step forecast error is a martingale difference (MD). The one-step forecast error forms the conditional moment condition obtained from the loss derivative with respect to the forecast. Similarly, under a...

Persistent link: https://www.econbiz.de/10005329017

Some Recent Developments in Predictive Accuracy Testing With Nested Models and (Generic) Nonlinear Alternatives

Corradi, Valentina; Swanson, Norman - Department of Economics, Rutgers University-New Brunswick - 2003

We provide analytical formulae for the asymptotic bias (ABIAS) and mean squared error (AMSE) of the IV estimator, and obtain approximations thereof based on an asymptotic scheme which essentially requires the expectation of the first stage F-statistic to converge to a finite (possibly small)...

Persistent link: https://www.econbiz.de/10005750228

Bootstrap Specification Tests for Diffusion Processes

Corradi, Valentina; Swanson, Norman R. - Department of Economics, Rutgers University-New Brunswick - 2003

that reflect data dependence and parameter estimation error (PEE). In order to obtain asymptotically valid critical values …

Persistent link: https://www.econbiz.de/10005839064

Bootstrap Conditional Distribution Tests In the Presence of Dynamic Misspecification

Corradi, Valentina; Swanson, Norman R. - Department of Economics, Rutgers University-New Brunswick - 2003

distribution tests when there is dynamic misspecification and parameter estimation error. Our approach di®ers from the literature … misspecification and parameter estimation error. In order to provide valid asymptotic critical values we suggest an extention of the … empirical process version of the block bootstrap to the case of non vanishing parameter estimation error. The findings from …

Persistent link: https://www.econbiz.de/10005839091

The Accuracy and the Computational Complexity of a Multivariate Binned Kernel Density Estimator

Holmström, Lasse - In: Journal of Multivariate Analysis 72 (2000) 2, pp. 264-309

The computational cost of multivariate kernel density estimation can be reduced by prebinning the data. The data are discretized to a grid and a weighted kernel estimator is computed. We report results on the accuracy of such a binned kernel estimator and discuss the computational complexity of...

Persistent link: https://www.econbiz.de/10005221482