The Relationship Between Human Capital and Financial Development: A Case Study of Turkey
Bibliographic record
Abstract
The current growth literature has focused on the contribution of the human and financial variables to growth. This has led to an insufficient and low number of studies investigating the relationship between the financial and human variables. However, in order to establish effective public policies, the correlation between these two variables must be well known. In line with this necessity, this study aimed to contribute the relevant literature by investigating the relations of the two variables in the case of Turkey. To do so, firstly, the human and financial development index for Turkey was established. Subsequently, the financial development indicator was measured through the M2/GDP ratio, and the human capital indicator was measured through the education and health expenditures/GDP ratio. Through the econometric analysis carried out using the data from the period of 1998-2016, the existence of causality and the direction of this causality between the financial development and human capital accumulation in Turkey were investigated. As a result, it was observed that in Turkey, while financial development causes the accumulation of human capital, there is no significant causality directed from human capital to financial development.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".