Variance and Skewness in Density Predictions : A World GDP Growth Forecast Assessment

Variance and Skewness in Density Predictions : A World GDP Growth Forecast Assessment

The paper introduces a Bayesian cross-entropy forecast (BCEF) procedure to assess the variance and skewness in density forecasting. The methodology decomposes the variance and skewness of the predictive distribution accounting for the shares of selected risk factors. The method assigns probabil...

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Main Author: Mendez-Ramos, Fabian
Format: Working Paper
Published: World Bank, Washington, DC 2020
Subjects:
NON-SYMMETRIC DENSITY FORECAST
FORECAST UNCERTAINTY
FORECASTS
BAYESIAN CROSS-ENTROPY
ECONOMIC GROWTH
IMPLIED VOLATILITY
VARIANCE DECOMPOSITION
SCORING RULES
SKEWNESS
Online Access:http://documents.worldbank.org/curated/en/802551502718519493/Variance-and-Skewness-in-Density-Predictions-A-World-GDP-Growth-Forecast-Assessment
http://hdl.handle.net/10986/33116
id okr-10986-33116
recordtype oai_dc
spelling okr-10986-331162021-05-25T10:54:39Z Variance and Skewness in Density Predictions : A World GDP Growth Forecast Assessment Mendez-Ramos, Fabian NON-SYMMETRIC DENSITY FORECAST FORECAST UNCERTAINTY FORECASTS BAYESIAN CROSS-ENTROPY ECONOMIC GROWTH IMPLIED VOLATILITY VARIANCE DECOMPOSITION SCORING RULES SKEWNESS The paper introduces a Bayesian cross-entropy forecast (BCEF) procedure to assess the variance and skewness in density forecasting. The methodology decomposes the variance and skewness of the predictive distribution accounting for the shares of selected risk factors. The method assigns probability distributions to baseline-projections of an economic or social random variable—for example, gross domestic product growth, inflation, population growth, poverty headcount, among others—combining ex-post and ex-ante market information. The generated asymmetric density forecasts use information derived from surveys on expectations and implied statistics of predictive models. The BCEF procedure is applied to produce world GDP growth forecasts for three-year horizons using information spanning the period of October 2005–August 2015. The scores indicate that the BCEF density forecasts are more accurate and reliable than some naïve—symmetric and normal distributed confidence interval—predictions, illustrating the value-added of the introduced methodology. 2020-01-01T00:00:14Z 2020-01-01T00:00:14Z 2017-08 Working Paper http://documents.worldbank.org/curated/en/802551502718519493/Variance-and-Skewness-in-Density-Predictions-A-World-GDP-Growth-Forecast-Assessment http://hdl.handle.net/10986/33116 Policy Research Working Paper;No. 8165 Revised CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Publications & Research :: Policy Research Working Paper Publications & Research
repository_type Digital Repository
institution_category Foreign Institution
institution Digital Repositories
building World Bank Open Knowledge Repository
collection World Bank
topic NON-SYMMETRIC DENSITY FORECAST
FORECAST UNCERTAINTY
FORECASTS
BAYESIAN CROSS-ENTROPY
ECONOMIC GROWTH
IMPLIED VOLATILITY
VARIANCE DECOMPOSITION
SCORING RULES
SKEWNESS
spellingShingle NON-SYMMETRIC DENSITY FORECAST
FORECAST UNCERTAINTY
FORECASTS
BAYESIAN CROSS-ENTROPY
ECONOMIC GROWTH
IMPLIED VOLATILITY
VARIANCE DECOMPOSITION
SCORING RULES
SKEWNESS
Mendez-Ramos, Fabian
Variance and Skewness in Density Predictions : A World GDP Growth Forecast Assessment
relation Policy Research Working Paper;No. 8165 Revised
description The paper introduces a Bayesian cross-entropy forecast (BCEF) procedure to assess the variance and skewness in density forecasting. The methodology decomposes the variance and skewness of the predictive distribution accounting for the shares of selected risk factors. The method assigns probability distributions to baseline-projections of an economic or social random variable—for example, gross domestic product growth, inflation, population growth, poverty headcount, among others—combining ex-post and ex-ante market information. The generated asymmetric density forecasts use information derived from surveys on expectations and implied statistics of predictive models. The BCEF procedure is applied to produce world GDP growth forecasts for three-year horizons using information spanning the period of October 2005–August 2015. The scores indicate that the BCEF density forecasts are more accurate and reliable than some naïve—symmetric and normal distributed confidence interval—predictions, illustrating the value-added of the introduced methodology.
format Working Paper
author Mendez-Ramos, Fabian
author_facet Mendez-Ramos, Fabian
author_sort Mendez-Ramos, Fabian
title Variance and Skewness in Density Predictions : A World GDP Growth Forecast Assessment
title_short Variance and Skewness in Density Predictions : A World GDP Growth Forecast Assessment
title_full Variance and Skewness in Density Predictions : A World GDP Growth Forecast Assessment
title_fullStr Variance and Skewness in Density Predictions : A World GDP Growth Forecast Assessment
title_full_unstemmed Variance and Skewness in Density Predictions : A World GDP Growth Forecast Assessment
title_sort variance and skewness in density predictions : a world gdp growth forecast assessment
publisher World Bank, Washington, DC
publishDate 2020
url http://documents.worldbank.org/curated/en/802551502718519493/Variance-and-Skewness-in-Density-Predictions-A-World-GDP-Growth-Forecast-Assessment
http://hdl.handle.net/10986/33116
_version_ 1764478034374557696

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