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
相关论文
共 50 条
  • [1] Constructing density forecasts from quantile regressions: Multimodality in macrofinancial dynamics
    Mitchell, James
    Poon, Aubrey
    Zhu, Dan
    JOURNAL OF APPLIED ECONOMETRICS, 2024, 39 (05) : 790 - 812
  • [2] Quantile Aggregation of Density Forecasts
    Busetti, Fabio
    OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 2017, 79 (04) : 495 - 512
  • [3] Combining Value-at-Risk forecasts using penalized quantile regressions
    Bayer, Sebastian
    ECONOMETRICS AND STATISTICS, 2018, 8 : 56 - 77
  • [4] CONSTRUCTING OPTIMAL DENSITY FORECASTS FROM POINT FORECAST COMBINATIONS
    Gaglianone, Wagner Piazza
    Lima, Luiz Renato
    JOURNAL OF APPLIED ECONOMETRICS, 2014, 29 (05) : 736 - 757
  • [5] Mixtures of quantile regressions
    Wu, Qiang
    Yao, Weixin
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2016, 93 : 162 - 176
  • [6] Unconditional Quantile Regressions
    Firpo, Sergio
    Fortin, Nicole M.
    Lemieux, Thomas
    ECONOMETRICA, 2009, 77 (03) : 953 - 973
  • [7] Smoothing Quantile Regressions
    Fernandes, Marcelo
    Guerre, Emmanuel
    Horta, Eduardo
    JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 2021, 39 (01) : 338 - 357
  • [8] Stock returns and inflation: Evidence from quantile regressions
    Alagidede, Paul
    Panagiotidis, Theodore
    ECONOMICS LETTERS, 2012, 117 (01) : 283 - 286
  • [9] Load probability density forecasting by transforming and combining quantile forecasts
    Zhang, Shu
    Wang, Yi
    Zhang, Yutian
    Wang, Dan
    Zhang, Ning
    APPLIED ENERGY, 2020, 277 (277)
  • [10] Inference in predictive quantile regressions
    Maynard, Alex
    Shimotsu, Katsumi
    Kuriyama, Nina
    JOURNAL OF ECONOMETRICS, 2024, 245 (1-2)