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Financial forecasts accuracy in Brazil’s social security system

Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government’s proposed pension reform that p...

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Detalles Bibliográficos
Autores principales: da Silva, Carlos Patrick Alves, Puty, Claudio Alberto Castelo Branco, da Silva, Marcelino Silva, de Carvalho, Solon Venâncio, Francês, Carlos Renato Lisboa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5578642/
https://www.ncbi.nlm.nih.gov/pubmed/28859172
http://dx.doi.org/10.1371/journal.pone.0184353
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author da Silva, Carlos Patrick Alves
Puty, Claudio Alberto Castelo Branco
da Silva, Marcelino Silva
de Carvalho, Solon Venâncio
Francês, Carlos Renato Lisboa
author_facet da Silva, Carlos Patrick Alves
Puty, Claudio Alberto Castelo Branco
da Silva, Marcelino Silva
de Carvalho, Solon Venâncio
Francês, Carlos Renato Lisboa
author_sort da Silva, Carlos Patrick Alves
collection PubMed
description Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government’s proposed pension reform that plans to radically change the Brazilian Constitution insofar as Social Security is concerned. However, the reliability of official results is uncertain since no systematic evaluation of these forecasts has ever been published by the Brazilian government or anyone else. This paper aims to present a study of the accuracy and methodology of the instruments used by the Brazilian government to carry out long-term actuarial forecasts. We base our research on an empirical and probabilistic analysis of the official models. Our empirical analysis shows that the long-term Social Security forecasts are systematically biased in the short term and have significant errors that render them meaningless in the long run. Moreover, the low level of transparency in the methods impaired the replication of results published by the Brazilian Government and the use of outdated data compromises forecast results. In the theoretical analysis, based on a mathematical modeling approach, we discuss the complexity and limitations of the macroeconomic forecast through the computation of confidence intervals. We demonstrate the problems related to error measurement inherent to any forecasting process. We then extend this exercise to the computation of confidence intervals for Social Security forecasts. This mathematical exercise raises questions about the degree of reliability of the Social Security forecasts.
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spelling pubmed-55786422017-09-15 Financial forecasts accuracy in Brazil’s social security system da Silva, Carlos Patrick Alves Puty, Claudio Alberto Castelo Branco da Silva, Marcelino Silva de Carvalho, Solon Venâncio Francês, Carlos Renato Lisboa PLoS One Research Article Long-term social security statistical forecasts produced and disseminated by the Brazilian government aim to provide accurate results that would serve as background information for optimal policy decisions. These forecasts are being used as support for the government’s proposed pension reform that plans to radically change the Brazilian Constitution insofar as Social Security is concerned. However, the reliability of official results is uncertain since no systematic evaluation of these forecasts has ever been published by the Brazilian government or anyone else. This paper aims to present a study of the accuracy and methodology of the instruments used by the Brazilian government to carry out long-term actuarial forecasts. We base our research on an empirical and probabilistic analysis of the official models. Our empirical analysis shows that the long-term Social Security forecasts are systematically biased in the short term and have significant errors that render them meaningless in the long run. Moreover, the low level of transparency in the methods impaired the replication of results published by the Brazilian Government and the use of outdated data compromises forecast results. In the theoretical analysis, based on a mathematical modeling approach, we discuss the complexity and limitations of the macroeconomic forecast through the computation of confidence intervals. We demonstrate the problems related to error measurement inherent to any forecasting process. We then extend this exercise to the computation of confidence intervals for Social Security forecasts. This mathematical exercise raises questions about the degree of reliability of the Social Security forecasts. Public Library of Science 2017-08-31 /pmc/articles/PMC5578642/ /pubmed/28859172 http://dx.doi.org/10.1371/journal.pone.0184353 Text en © 2017 Silva 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
da Silva, Carlos Patrick Alves
Puty, Claudio Alberto Castelo Branco
da Silva, Marcelino Silva
de Carvalho, Solon Venâncio
Francês, Carlos Renato Lisboa
Financial forecasts accuracy in Brazil’s social security system
title Financial forecasts accuracy in Brazil’s social security system
title_full Financial forecasts accuracy in Brazil’s social security system
title_fullStr Financial forecasts accuracy in Brazil’s social security system
title_full_unstemmed Financial forecasts accuracy in Brazil’s social security system
title_short Financial forecasts accuracy in Brazil’s social security system
title_sort financial forecasts accuracy in brazil’s social security system
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5578642/
https://www.ncbi.nlm.nih.gov/pubmed/28859172
http://dx.doi.org/10.1371/journal.pone.0184353
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