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Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries

PROBLEM: Do conservative econometric models that comply with the Golden Rule of Forecasting provide more accurate forecasts? METHODS: To test the effects of forecast accuracy, we applied three evidence-based guidelines to 19 published regression models used for forecasting 154 elections in Australia...

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Detalles Bibliográficos
Autores principales: Graefe, Andreas, Green, Kesten C., Armstrong, J. Scott
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328130/
https://www.ncbi.nlm.nih.gov/pubmed/30629630
http://dx.doi.org/10.1371/journal.pone.0209850
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author Graefe, Andreas
Green, Kesten C.
Armstrong, J. Scott
author_facet Graefe, Andreas
Green, Kesten C.
Armstrong, J. Scott
author_sort Graefe, Andreas
collection PubMed
description PROBLEM: Do conservative econometric models that comply with the Golden Rule of Forecasting provide more accurate forecasts? METHODS: To test the effects of forecast accuracy, we applied three evidence-based guidelines to 19 published regression models used for forecasting 154 elections in Australia, Canada, Italy, Japan, Netherlands, Portugal, Spain, Turkey, U.K., and the U.S. The guidelines direct forecasters using causal models to be conservative to account for uncertainty by (I) modifying effect estimates to reflect uncertainty either by damping coefficients towards no effect or equalizing coefficients, (II) combining forecasts from diverse models, and (III) incorporating more knowledge by including more variables with known important effects. FINDINGS: Modifying the econometric models to make them more conservative reduced forecast errors compared to forecasts from the original models: (I) Damping coefficients by 10% reduced error by 2% on average, although further damping generally harmed accuracy; modifying coefficients by equalizing coefficients consistently reduced errors with average error reductions between 2% and 8% depending on the level of equalizing. Averaging the original regression model forecast with an equal-weights model forecast reduced error by 7%. (II) Combining forecasts from two Australian models and from eight U.S. models reduced error by 14% and 36%, respectively. (III) Using more knowledge by including all six unique variables from the Australian models and all 24 unique variables from the U.S. models in equal-weight “knowledge models” reduced error by 10% and 43%, respectively. ORIGINALITY: This paper provides the first test of applying guidelines for conservative forecasting to established election forecasting models. USEFULNESS: Election forecasters can substantially improve the accuracy of forecasts from econometric models by following simple guidelines for conservative forecasting. Decision-makers can make better decisions when they are provided with models that are more realistic and forecasts that are more accurate.
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spelling pubmed-63281302019-02-01 Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries Graefe, Andreas Green, Kesten C. Armstrong, J. Scott PLoS One Research Article PROBLEM: Do conservative econometric models that comply with the Golden Rule of Forecasting provide more accurate forecasts? METHODS: To test the effects of forecast accuracy, we applied three evidence-based guidelines to 19 published regression models used for forecasting 154 elections in Australia, Canada, Italy, Japan, Netherlands, Portugal, Spain, Turkey, U.K., and the U.S. The guidelines direct forecasters using causal models to be conservative to account for uncertainty by (I) modifying effect estimates to reflect uncertainty either by damping coefficients towards no effect or equalizing coefficients, (II) combining forecasts from diverse models, and (III) incorporating more knowledge by including more variables with known important effects. FINDINGS: Modifying the econometric models to make them more conservative reduced forecast errors compared to forecasts from the original models: (I) Damping coefficients by 10% reduced error by 2% on average, although further damping generally harmed accuracy; modifying coefficients by equalizing coefficients consistently reduced errors with average error reductions between 2% and 8% depending on the level of equalizing. Averaging the original regression model forecast with an equal-weights model forecast reduced error by 7%. (II) Combining forecasts from two Australian models and from eight U.S. models reduced error by 14% and 36%, respectively. (III) Using more knowledge by including all six unique variables from the Australian models and all 24 unique variables from the U.S. models in equal-weight “knowledge models” reduced error by 10% and 43%, respectively. ORIGINALITY: This paper provides the first test of applying guidelines for conservative forecasting to established election forecasting models. USEFULNESS: Election forecasters can substantially improve the accuracy of forecasts from econometric models by following simple guidelines for conservative forecasting. Decision-makers can make better decisions when they are provided with models that are more realistic and forecasts that are more accurate. Public Library of Science 2019-01-10 /pmc/articles/PMC6328130/ /pubmed/30629630 http://dx.doi.org/10.1371/journal.pone.0209850 Text en © 2019 Graefe et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Graefe, Andreas
Green, Kesten C.
Armstrong, J. Scott
Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries
title Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries
title_full Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries
title_fullStr Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries
title_full_unstemmed Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries
title_short Accuracy gains from conservative forecasting: Tests using variations of 19 econometric models to predict 154 elections in 10 countries
title_sort accuracy gains from conservative forecasting: tests using variations of 19 econometric models to predict 154 elections in 10 countries
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328130/
https://www.ncbi.nlm.nih.gov/pubmed/30629630
http://dx.doi.org/10.1371/journal.pone.0209850
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