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Record W4323565637 · doi:10.3390/jrfm16030178

When Institutional Plates Collide: The Dynamic Impact of Informal Institutions on Capital Market Development

2023· article· en· W4323565637 on OpenAlexvenueno aff
Robert Lindorfer, Anne d’Arcy, Igor Filatotchev

Bibliographic record

VenueJournal of risk and financial management · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsSocial capitalInstitutional theoryLegitimacyContext (archaeology)NewspaperProxy (statistics)Capital marketBusinessEconomicsPublic economicsPolitical scienceSociologyFinanceSocial science

Abstract

fetched live from OpenAlex

We provide an institutional theory perspective to examine societal legitimacy in the context of capital market development. While prior research has focused on the importance of formal institutions, firms are embedded within broader socio-economic structures associated with informal institutions. Using content analysis and a unique dataset of 3244 newspaper articles between 2004 and 2013, we develop a dynamic measure capturing the public perception of capital markets as a proxy of informal institutions. We run a Prais–Winsten regression with panel-corrected standard errors to explore the dynamic relationship between public perception of capital markets and equity market size in Austria and Poland. We further theoretically and empirically explore how formal and informal institutions mutually reinforce each other in the context of capital market development. Our results suggest that informal institutions matter differently in developed and emerging economies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.003
Scholarly communication0.0060.006
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.220
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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