Showing 1 - 10 of 2,245
We present a robust Generalized Empirical Likelihood estimator and confidence region for the parameters of an autoregression that may have a heavy tailed error, and the error may be conditionally heteroscedastic of unknown form. The estimator exploits two transformations for heavy tail...
Persistent link: https://www.econbiz.de/10013035987
This paper considers estimation of moving average (MA) models with non-Gaussian errors. Information in higher-order cumulants allows identification of the parameters without imposing invertibility. By allowing for an unbounded parameter space, the generalized method of moments estimator of the...
Persistent link: https://www.econbiz.de/10010201380
We propose non-nested hypotheses tests for conditional moment restriction models based on the method of generalized empirical likelihood (GEL). By utilizing the implied GEL probabilities from a sequence of unconditional moment restrictions that contains equivalent information of the conditional...
Persistent link: https://www.econbiz.de/10012771848
In this paper we examine the finite sample bias of sample skewness estimator for financial returns. We show that the … bias of conventional sample skewness comes from two sources: the covariance between past return and future volatility … volatility feedback effect. We derive explicit expressions for this bias and propose a nearly unbiased skewness estimator under …
Persistent link: https://www.econbiz.de/10012836109
In this paper, we study the finite sample accuracy of confidence intervals for index functional built via parametric bootstrap, in the case of inequality indices. To estimate the parameters of the assumed parametric data generating distribution, we propose a Generalized Method of Moment...
Persistent link: https://www.econbiz.de/10011823357
We develop theory of a novel fast bootstrap for dependent data. Our scheme deploys i.i.d. resampling of smoothed moment indicators. We characterize the class of parametric and semiparametric estimation problems for which the method is valid. We show the asymptotic re refinements of the new...
Persistent link: https://www.econbiz.de/10012179669
We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non …-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact … identical. Next, based on a detailed simulation study, we show that when the model is stationary this simple bias formula …
Persistent link: https://www.econbiz.de/10010336196
investigate multiplicative and additive bias correction methods within our framework. The multiplicative bias correction method …
Persistent link: https://www.econbiz.de/10013323654
This paper studies the asymptotic normality for the kernel deconvolution estimator when the noise distribution is logarithmic chi-square; both identical and independently distributed observations and strong mixing observations are considered. The dependent case of the result is applied to obtain...
Persistent link: https://www.econbiz.de/10011297541
, however, causes bias in small samples and possibly asymptotically when the variance is infinite, so we exploit a rarely used …
Persistent link: https://www.econbiz.de/10013090751