Bibliographic record
Abstract
This Paper studies empirically the effects of and the interactions amongst economic and political liberalizations. Economic liberalizations are measured by a widely used indicator that captures the scope of the market in the economy, and in particular of policies towards freer international trade (cf. Sachs and Werner, 1995; Wacziarg and Welch, 2003). Political liberalizations correspond to the event of becoming a democracy. Using a difference-in-difference estimation, we ask what are the effects of liberalizations on economic performance, on macroeconomic policy and on structural policies. The main results concern the quantitative relevance of the feedback and interaction effects between the two kinds of reforms. First, we find positive feedback effects between economic and political reforms. The timing of events indicates that causality is more likely to run from political to economic liberalizations, rather than vice versa, but we cannot rule out feedback effects in both directions. Second, the sequence of reforms matters. Countries that first liberalize and then become democracies do much better than countries that pursue the opposite sequence, in almost all dimensions.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 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".