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Constructing Density Forecasts from Quantile Regressions

Wagner Gaglianone () and Luiz Lima ()

Journal of Money, Credit and Banking, 2012, vol. 44, issue 8, 1589-1607

Abstract: 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.

Date: 2012
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https://doi.org/10.1111/j.1538-4616.2012.00545.x

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Journal of Money, Credit and Banking is currently edited by Robert deYoung, Paul Evans, Pok-Sang Lam and Kenneth D. West

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