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) data. They have only seven observations available to estimate of the bias of technical progress in United States … manufacturing in the nineteenth century. They are able to offer estimates of the bias only by assuming that production technology is …
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Bias correction can often improve the finite sample performance of estimators. We show that the choice of bias … estimate of the bias is asymptotically linear. It is also shown that bootstrap, jackknife, and analytical bias estimates are … estimators the straightforward bootstrap bias correction gives the same higher-order variance as more complicated analytical or …
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a k-step parametric bootstrap bias corrected estimator. We prove that our estimator is asymptotically normal and is … centered at the true parameter if T grows faster than ∛n. In addition to bias correction, we construct a confidence interval …’s is smaller than those of the alternatives. We also propose bias correction for average marginal effects …
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Many financial decisions such as portfolio allocation, risk management, option pricing and hedge strategies are based on the forecast of the conditional variances, covariances and correlations of financial returns. Although the decisions are based on forecasts covariance matrix little is known...
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We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight...
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