Social Environment Determinants of Life Expectancy in Developing Countries: A Panel Data Analysis
Bibliographic record
Abstract
<p>Despite remarkable improvements in health over the past 50 years, there still remain a great number of health challenges around the world. This study examined the relationship between life expectancy rate (as a proxy for health status) with health expenditure, gross domestic product, education index, improved water coverage, and improved sanitation facilities in 108 selected developing countries using annual panel data within the period of 2006–2010. The empirical results from using the panel data approach showed a positive relationship between life expectancy rate and all of those explanatory variables. The relationship between life expectancy with education index and gross domestic product were significant at 1% and 5% significance levels, respectively. Furthermore, the causality finding showed that there is no short-run causality between life expectancy and its determinants. There is a unidirectional causality running from the independent variables of health expenditure, education index, improved water, and improved sanitation to life expectancy at birth. On the other hand, bidirectional causality exists between life expectancy and income in the long-run by employing VECM test. These independent variables can be considered as important determinants for investment in health status in the long-run. This study could be used as a guideline and may be significant for future researchers and policy makers who aim to improve the life expectancy in developing countries.</p>
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".