@Article{SilvaPutSilCarFra:2017:FiFoAc,
author = "Silva, Carlos Patrick Alves da Silva and Puty, Claudio Alberto
Castelo Branco and Silva, Marcelino Silva da and Carvalho, Solon
Ven{\^a}ncio de and Franc{\^e}s, Carlos Renato Lisboa",
affiliation = "{Universidade Federal do Par{\'a} (UFPA)} and {Universidade
Federal do Par{\'a} (UFPA)} and {Universidade Federal do
Par{\'a} (UFPA)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Universidade Federal do Par{\'a} (UFPA)}",
title = "Financial forecasts accuracy in Brazil's social security system",
journal = "PLoS One",
year = "2017",
volume = "12",
number = "8",
pages = "e0184353",
month = "Aug.",
abstract = "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and the use of outdated data compromises forecast results.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.",
doi = "10.1371/journal.pone.0184353",
url = "http://dx.doi.org/10.1371/journal.pone.0184353",
issn = "1932-6203",
label = "self-archiving-INPE-MCTIC-GOV-BR",
language = "en",
urlaccessdate = "27 abr. 2024"
}