Income and Democracy: A Smooth Varying Coefficient Redux
Bibliographic record
Abstract
Summary Acemoglu et al. ( American Economic Review 2008; 98 : 808–842) find no effect of income on democracy when controlling for fixed effects in a dynamic panel model. Work by Moral‐Benito and Bartolucci ( Economics Letters 2012; 117 : 844–847) and Cervellati et al. ( American Economic Review 2014; 104 : 707–719) suggests that the original model might have been misspecified and proposes alternative specifications instead. We formally test these parametric specifications by implementing Lee's ( Journal of Econometrics 2014; 178 : 146–166) dynamic panel test of linear parametric specifications against a general class of nonlinear alternatives robustly and reject all these specifications. However, using a more flexible model proposed by Cai and Li ( Econometric Theory 2008; 24 : 1321–1342) we find that the relationship between income and democracy appears to be mediated by education, but results are not statistically significant. Copyright © 2016 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".