Constructing Density Forecasts from Quantile Regressions
提出一种无需假设目标变量条件分布参数形式的计量模型来估计条件密度，并应用于美国失业率与专业预测者调查数据，检验表明该方法能正确逼近真实条件密度。
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.