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In addition to reporting fitted cumulative distribution function and associated 95% CIs, we reported certain quantiles and means.
It is thus expected that companies with less extreme (moderate) earnings will have accruals with higher quality; that is, it is expected that quantiles 10, 20, and 90 will have higher standard deviations of residuals than quantiles 30 through 80.
The low flow quantiles of regional frequency distribution (growth curves) were estimated for different return periods and accuracy of these estimates were assessed under Relative Root Mean Square Error (RRMSE), Absolute Bias (AB), Relative Absolute Bias (RAB) together with Lower Error Bound (LEB) and Upper Error Bounds (UEB).
Particularly if a declining trend on the returns to schooling is found in the upper quantiles but not in the lower quantiles, a reduction of inequality between the top and lower quantiles is predicted.
The main contribution of this paper is in risk estimation of the JSE all share index above high quantiles.
In order to investigate the influencing factors of cotton trading price on different quantiles, the quantile regression model is established as follows:
Taking into account that a QR model proposes different regression lines for the different quantiles of the earnings distribution, the contribution of the socioeconomics characteristics on different levels of earnings can be compared.
We begin with Banker's SDEA model and estimate numerous quantiles.
The goal of this technique is to quantify the associations between exposure and specific quantiles of the outcome distribution, thereby allowing one to identify whether specific individuals with certain outcome levels are more affected by exposure.
Realizing the shortcomings of the Oaxaca-Blinder decomposition method when the gap varies across the wage distribution, Kandil (2009) followed the Machado and Mata (2005) methodology to measure the wage gap at different quantiles of the wage distribution.
Their topics include univariate extreme value mixture modeling, the threshold modeling of non-stationary extremes, max-autoagressive and moving maxima models for extremes, Bayesian inference for extreme value modeling, estimating extreme conditional quantiles, an overview of nonparametric tests of extreme-value dependence and of some related statistical procedures, and the analysis of bivariate survival data based on copulas with log-generalized extreme value marginals.
But their focus is on the mutual spillover effects among the three indexes and asymmetric dependence in different range of returns (low, medium, and high quantiles, and positive versus negative returns).