De internationale verspreiding van de Efficient Market Hypothesis en de rol van insitutionele context
Bibliographic record
Abstract
First coined by Nobel prize winning financial economist Eugene Fama in 1965, the EMH remains a fundamental theory in financial economics. This study researches the international dissemination of the Efficient Market Hypothesis (EMH) using a combination of exploratory and explanatory methods. A temporal and geographical analysis of citations in academic publications of the seminal articles (1965; 1970; 1991) regarding the EMH, following Wojcik, Kreston and McGill (2013), reveals that there is widespread internationalization, but this only took off after the year 2000. It is found that the United States still appears to be a dominant force in the field. Furthermore, supporting the propositions of Fourcade (2009) and institutional theory, institutional context seems to be a structuring factor for economists. Using panel GLS regression analysis, it is found that the institutional context of a country, characterized by the Liberal Market Economy (LME) – Coordinated Market Economy (LME) distinction of Hall and Gingerich (2009) is a significant factor in the international diffusion of the EMH. The EMH, interwoven with the Chicago School’s laissez-faire principles, is more likely to spread to countries characterized by an institutional context that resembles a LME. A convincing longitudinal effect of changes in institutional context on the citation pattern is not found. Further research should evaluate whether this relationship is structurally altered since the development of the internet as the exploratory results seem to suggest.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".