Now showing items 1-10 of 155
Smoothing quantile regressions
We propose to smooth the entire objective function rather than only the check function in a linear quantile regression context. We derive a uniform Bahadur-Kiefer representation for the resulting convolution-type kernel ...
EXPLORING THE URBAN-RURAL LABOR INCOME GAP IN URUGUAY: A QUANTILE REGRESSION DECOMPOSITION
(ILADES - Universidad Alberto Hurtado., 2010)
Mean and quantile regression Oaxaca-Blinder decompositions with an application to caste discrimination
This paper extends the Oaxaca-Blinder decomposition method to the quantile regression random-coefficients framework. Mean-based decompositions are obtained as the integration of the quantile regression decomposition process. ...
Testing linearity against threshold effects: uniform inference in quantile regression
(Springer Heidelberg, 2014-04)
This paper develops a uniform test of linearity against threshold effects in the quantile regression framework. The test is based on the supremum of the Wald process over the space of quantile and threshold parameters. We ...
Quantile effects of prenatal care utilization on birth weight in Argentina
(John Wiley & Sons Ltd, 2009-11)
The effects of prenatal care utilization on birth weight (BW) may vary by unobserved fetal health endowments. This heterogeneity will be masked by estimating the effects at BW mean but can be evaluated by estimating the ...
Evaluating Value-at-Risk models via Quantile regressions
(Fundação Getulio Vargas. Escola de Pós-graduação em Economia, 2008-09-04)
This paper is concerned with evaluating value at risk estimates. It is well known that using only binary variables to do this sacrifices too much information. However, most of the specification tests (also called backtests) ...
Reduced form vector directional quantiles
(Elsevier Inc, 2017-06)
In this paper, we develop a reduced form multivariate quantile model, using a directional quantile framework. The proposed model is the solution to a collection of directional quantile models for a fixed orthonormal basis, ...
Quantile Regression In Linear Mixed Models: A Stochastic Approximation Em Approach
(Int Press Boston, IncSomerville, 2017)
Comparing value-at-risk methodologies
(Sociedade Brasileira de Econometria, 2007-05-01)
In this paper, we compare four diﬀerent Value-at-Risk (V aR) methodologies through Monte Carlo experiments. Our results indicate that the method based on quantile regression with ARCH eﬀect dominates other methods that ...