National legislatures and corporate transparency
Bibliographic record
Abstract
Purpose – The purpose of this study is to posit and test whether the presence and structure of national legislatures can account for the varying degree of corporate transparency displayed by firms operating in emerging economies. Design/methodology/approach – We conducted tests using a sample of 226,088 firm-level observations spanning 81 countries over the period 1990–2014. Findings - Firms located in political regimes which lack national legislatures display a lower level of transparency than those in regimes with semi-competitive legislative elections, and these in turn display lower transparency than firms located in countries with competitive elections. Research implications – Although scholars have emphasized the importance of investigating how institutions impact corporate transparency, and the research opportunities associated with studying these dynamics in the context of emerging economies, we are unaware of any prior work that differentiates among the types of formal institutional structures found among authoritarian regimes. Given that around two-thirds of emerging economies are governed by an authoritarian regime, our study begins to address an important gap in the literature by showing how the make-up of national legislatures influences firm outcomes with respect to an arena that is fundamental to the functioning of a market economy – information disclosure. Originality/value - We introduce a novel measure of institutional variation – multi-party legislatures. For decades, theoretical work has focused on firm performance in the context of advanced economies. But because they are almost always democratic, there is no variation with regard to whether the legislature allows for multi-party representation. By allowing this institutional structure to vary, we extend the understanding of corporate transparency in nondemocracies, the most common form of government among emerging economies.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".