Health and wealth: Short panel Granger causality tests for developing countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The world has experienced impressive improvements in wealth and health, with, for instance, the world's real GDP per capita having increased by 180% from 1970 to 2007 accompanied by a 50% decline in infant mortality rate. Healthier and wealthier. Pl Are health gains arising from wealth growth? Or, has a healthier population enabled substantial growth in wealth? We contribute to understanding the dynamic links between wealth and health by examining for causal, rather than associative, links between health (as measured by infant mortality rate) and wealth (as measured by GDP per capita) for a panel of 58 developing countries using quinquennial data covering the period 1960–2005. Estimating as a panel allows us to account for unobserved heterogeneity, as well as permitting heterogeneous causal effects. We test for panel and country-specific noncausality, and we explore robustness of outcomes to level of economic development (as measured by national income), whether we account for bias in least squares estimators, and to our heterogeneity assumption on the causal coefficients. Overall, our panel tests detect bidirectional links between wealth and health, compatible with other research. However, our country-specific work suggests that the panel results arise from the dominance of a few countries, as there is evidence of noncausality between health and wealth for a majority of countries. These findings contrast with earlier research, and likely arise from different metrics being used to measure the health of a nation. Our work highlights the usefulness of panel causality tests accompanied by unit specific analysis and the importance of examining different metrics for health.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it