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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3PP5P5S
Repositorysid.inpe.br/mtc-m21b/2017/10.05.15.31
Last Update2017:10.05.15.32.51 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m21b/2017/10.05.15.31.08
Metadata Last Update2021:07.28.21.54.24 (UTC) administrator
DOI10.1371/journal.pone.0184353
ISSN1932-6203
Labelself-archiving-INPE-MCTIC-GOV-BR
Citation KeySilvaPutSilCarFra:2017:FiFoAc
TitleFinancial forecasts accuracy in Brazil's social security system
Year2017
MonthAug.
Access Date2024, July 27
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size4826 KiB
2. Context
Author1 Silva, Carlos Patrick Alves da Silva
2 Puty, Claudio Alberto Castelo Branco
3 Silva, Marcelino Silva da
4 Carvalho, Solon Venâncio de
5 Francês, Carlos Renato Lisboa
Resume Identifier1
2
3
4 8JMKD3MGP5W/3C9JJ99
Group1
2
3
4 LABAC-COCTE-INPE-MCTIC-GOV-BR
Affiliation1 Universidade Federal do Pará (UFPA)
2 Universidade Federal do Pará (UFPA)
3 Universidade Federal do Pará (UFPA)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 Universidade Federal do Pará (UFPA)
Author e-Mail Address1 patrickalves@ufpa.br
2
3
4 solon.carvalho@inpe.br
JournalPLoS One
Volume12
Number8
Pagese0184353
Secondary MarkA1_ZOOTECNIA_/_RECURSOS_PESQUEIROS A1_SAÚDE_COLETIVA A1_QUÍMICA A1_ODONTOLOGIA A1_NUTRIÇÃO A1_MEDICINA_VETERINÁRIA A1_MEDICINA_III A1_MEDICINA_II A1_MEDICINA_I A1_INTERDISCIPLINAR A1_GEOGRAFIA A1_GEOCIÊNCIAS A1_FARMÁCIA A1_ENGENHARIAS_III A1_ENGENHARIAS_I A1_ENFERMAGEM A1_EDUCAÇÃO_FÍSICA A1_CIÊNCIAS_AMBIENTAIS A1_CIÊNCIAS_AGRÁRIAS_I A1_CIÊNCIA_DE_ALIMENTOS A1_CIÊNCIA_DA_COMPUTAÇÃO A1_BIOTECNOLOGIA A1_BIODIVERSIDADE A1_ADMINISTRAÇÃO,_CIÊNCIAS_CONTÁBEIS_E_TURISMO A2_PSICOLOGIA A2_PLANEJAMENTO_URBANO_E_REGIONAL_/_DEMOGRAFIA A2_MATERIAIS A2_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA A2_ENGENHARIAS_IV A2_ECONOMIA A2_CIÊNCIAS_BIOLÓGICAS_III A2_CIÊNCIAS_BIOLÓGICAS_II A2_CIÊNCIAS_BIOLÓGICAS_I A2_ASTRONOMIA_/_FÍSICA B1_EDUCAÇÃO B3_SERVIÇO_SOCIAL B3_LETRAS_/_LINGUÍSTICA B3_CIÊNCIAS_SOCIAIS_APLICADAS_I B3_ANTROPOLOGIA_/_ARQUEOLOGIA C_ENGENHARIAS_II
History (UTC)2017-10-05 15:31:08 :: simone -> administrator ::
2017-10-05 15:31:41 :: administrator -> simone :: 2017
2017-10-05 15:32:51 :: simone -> administrator :: 2017
2021-07-28 21:54:24 :: administrator -> simone :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
AbstractLong-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.
AreaCOMP
Arrangementurlib.net > DIDSA > Financial forecasts accuracy...
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agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGP3W34P/3PP5P5S
zipped data URLhttp://urlib.net/zip/8JMKD3MGP3W34P/3PP5P5S
Languageen
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Archiving Policyallowpublisher allowfinaldraft
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ESGTTP
Citing Item Listsid.inpe.br/bibdigital/2013/09.22.23.14 3
sid.inpe.br/mtc-m21/2012/07.13.15.00.34 3
DisseminationWEBSCI; PORTALCAPES; MGA; SCOPUS.
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
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