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Impression management, government agencies' regulation and analyst forecasts: empirical evidence from an emerging market

2026-01-02Artigo científico Acesso restrito
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datacite.subject.sdg16:Paz, Justiça e Instituições Eficazes
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
dc.contributor.authorCastro, Lívia Arruda
dc.contributor.authorPonte, Vera
dc.contributor.authorViana Junior, Dante Baiardo C.
dc.date.accessioned2026-03-03T14:34:26Z
dc.date.available2026-03-03T14:34:26Z
dc.date.issued2026-01-02
dc.description.abstractPurpose- This study aims to investigate the relationship between government agencies' regulation and analyst forecasts in an emerging market and whether this relationship is mediated by impression management in earnings press releases.Design/methodology/approachThe sample consists of 1,816 quarterly observations of Brazilian listed firms from 2003 to 2021, based on data from Thomson Reuters (R). The impression management of the sample firms is obtained by analyzing their earnings releases using the Watson Natural Language Understanding (NLU) platform developed by IBM (R). We employ a manual firm-level classification procedure to detect regulated and non-regulated firms by government agencies.FindingsBased on structural equation modeling, the findings suggest that firms regulated by government agencies present, on average, lower levels of impression management in earnings press releases. Additionally, we find that the level of firms' impression management, in turn, is negatively related to analyst forecast errors. These empirical results indicate that impression management in earnings press releases is a crucial mediating channel between government agencies' regulation and analyst forecast errors. Moreover, we find that government agencies' regulation has a positive and direct effect on analyst forecast errors, possibly due to its impact on other firm-level incentives and market dynamics, which may be positively or negatively associated with analyst forecasts.Originality/valueThis study contributes to the previous literature on the relationship between government agencies' regulation and analyst forecasts by theoretically discussing and empirically analyzing the mediating role of impression management as an important factor in this relationship, exploring the various facets through which state regulation ends up changing the structure of the informational environment in which companies are located. An important debate for the emerging markets literature is also provided, and policy discussions are featured.eng
dc.description.sponsorshipUID/06522/2025, 404658/2023-7
dc.identifier.doi10.1108/ara-03-2025-0083
dc.identifier.eissn1758-8863
dc.identifier.issn1321-7348
dc.identifier.urihttp://hdl.handle.net/10400.1/28316
dc.language.isoeng
dc.peerreviewedyes
dc.publisherEmerald
dc.relationCSG - Research in Social Sciences and Management
dc.relationCenter for Advanced Studies in Management and Economics
dc.relation.ispartofAsian Review of Accounting
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAnalyst forecasts
dc.subjectImpression management
dc.subjectEconomic regulation
dc.titleImpression management, government agencies' regulation and analyst forecasts: empirical evidence from an emerging marketeng
dc.typejournal article
dspace.entity.typePublication
oaire.awardNumberUIDB/04521/2020
oaire.awardNumberUIDB/04007/2020
oaire.awardTitleCSG - Research in Social Sciences and Management
oaire.awardTitleCenter for Advanced Studies in Management and Economics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04521%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04007%2F2020/PT
oaire.citation.titleAsian Review of Accounting
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameViana Junior
person.givenNameDante Baiardo C.
person.identifier.orcid0000-0001-6902-3057
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublication79a3455a-71af-4594-a8de-a0cf0f01f420
relation.isAuthorOfPublication.latestForDiscovery79a3455a-71af-4594-a8de-a0cf0f01f420
relation.isProjectOfPublication6224ba96-466e-41c1-83e6-3cf57ce9c4fa
relation.isProjectOfPublication2fa5dcac-9207-4f5b-b4be-54fcf7dcdd7d
relation.isProjectOfPublication.latestForDiscovery6224ba96-466e-41c1-83e6-3cf57ce9c4fa

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