propose a model-based bias-corrected estimation approach. Our simulation results indicate that bias strongly relates to the … substantial differences in measured tail-thickness due to small sample bias. As a consequence, high quantile estimation may lead …

samples than the confidence regions that can be constructed from the smoothed bootstrap method recently suggested by Horowitz …

urban economics. Using bootstrap inference and the J-test, the paper shows that while NEG theory is supported by the data …

we show that the bootstrap is able to capture the negative bias and the skewness of the test statistic. It yields better … fixed link functions. In this paper we consider a bootstrap specification test that detects nonparametric deviations of the … link function. The bootstrap is used with the aim to find a more accurate distribution under the null than the normal …

LM sup-statistic and characterize the asymptotic p-value by Hansen's (1996) bootstrap method. In our simulations, we … randomly select all STAR parameters in order not to bias experimental results based on the use of "safe", "interior" parameter …

emerging markets. The statistical significance of these results were checked by a bootstrap procedure. The results imply that …

cointegration model is estimated. The TC model not only explains the downward bias of the coefficient estimates, but also the sample …

, the root mean square error, bias and finally directional accuracy. The forecasts are even compared to naive random walk … by the naive random walk model. Tests of bias indicate that the Swedish forecasters underestimate GDP-growth and …, root mean square error, directional accuracy, bias, revisions, final respective preliminary outcomes, Theil index, naïve …