Causal Relationship among Education Expenditure, Health Expenditure and GDP: A Case Study for Bangladesh
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
This paper investigated the causal relationship among health expenditure, education expenditure and GDP for Bangladesh. First we present the extension form of the augmented Solow Growth model by including education expenditure and health expenditure as education and health capital. In our empirical study we used time series data for the period 1990 to 2009. From the ECM methodology we found that an including of health and education expenditure as an investment in health and education capital improve the significance of the coefficient of human and physical capital in the growth model for Bangladesh. Secondly, we find out the causal relationship among these variables by Var Granger Causality test. From the empirical study we found the existence of bidirectional causality from education expenditure to GDP and also from education expenditure to health expenditure and only unidirectional causality is obtained from health expenditure to GDP. This paper will provide a significant policy guideline to the policy maker.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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