Constructing Density Forecasts from Quantile Regressions

被引:21
|
作者
Gaglianone, Wagner Piazza [1 ]
Lima, Luiz Renato [2 ,3 ]
机构
[1] Banco Cent Brasil, Res Dept, Rio De Janeiro, Brazil
[2] Univ Tennessee, Dept Econ, Knoxville, TN USA
[3] Univ Fed Paraiba, BR-58059900 Joao Pessoa, Paraiba, Brazil
关键词
C13; C14; C51; C53; density forecast; loss function; quantile regression; surveys; COMBINATION; PREDICTION; CURVES; MODELS; COST;
D O I
10.1111/j.1538-4616.2012.00545.x
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
The departure from the traditional concern with the central tendency is in line with the increasing recognition that an assessment of the degree of uncertainty surrounding a point forecast is indispensable (Clements 2004). We propose an econometric model to estimate the conditional density without relying on assumptions about the parametric form of the conditional distribution of the target variable. The methodology is applied to the U.S. unemployment rate and the survey of professional forecasts. Specification tests based on Koenker and Xiao (2002) and Gaglianone et al. (2011) indicate that our approach correctly approximates the true conditional density.
引用
收藏
页码:1589 / 1607
页数:19
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