Bayesian and other likelihood-based methods require specification of a statistical model may not be fully satisfactory for inference on quantities, such as quantiles, that are naturally defined parameters. In this paper, we construct direct model-free Gibbs posterior distribution multivariate quantiles. Being means inferences drawn from the subject to misspecification bias, being no priors or m...

Abstract The standard method of creating post-strata is to define the boundaries strata on basis population characteristics auxiliary variables. Estimation treats as for stratified-sample estimation. Samples often contain empty requiring adjustment estimation procedure. To avoid post-strata, we propose using sample distribution function an variable post-strata. We show that large-sample efficie...

This paper focuses on the role of absorptive capacity in determining whether or not domestic firms benefit from productivity spillovers from FDI using establishment level data for the UK. We allow for different effects of FDI on establishments located at different quantiles of the productivity distribution by using conditional quantile regression. Overall, while there is some heterogeneity in r...

A framework is introduced allowing to apply nonparametric quantile regression to Value at Risk (VaR) prediction at any probability level of interest. A monotonized double kernel local linear estimator is used to estimate moderate (1%) conditional quantiles of index return distributions. For extreme (0.1%) quantiles, nonparametric quantile regression is combined with extreme value theory. The ab...

c. Determine the quantiles (Q) associated to the following series of cumulated relative frequencies: 1x10, 1x10, 1x10, 1x10, 1x10, 0.25, 0.5, 0.75, 0.99, 0.999, 0.9999, 0.99999, 0.999999). To this aim we used the program Matlab v.7.10 (Mathworks, USA). Although “relative frequencies” and “probabilities” are different mathematical entities (i.e., probabilities are the asymptotic limit of the rel...

Multivariate quantiles have been defined by a number of researchers and can be estimated by different methods. However, little work can be found in the literature about Bayesian estimation of joint quantiles of multivariate random variables. In this paper we present a multivariate quantile function model and propose a Bayesian method to estimate the model parameters. The methodology developed h...

The EKC literature has ignored the importance of natural resources on environmental degradation. Thus, this paper aims to investigate impact renewable energy consumption and abundance CO2 emissions for a panel 82 countries by using quantile regressions. Empirical results show that reduces its effect increases in higher quantiles. carbon resource is negative at lower quantiles but positive mediu...