Assessing Productivity Channels of Human Capital in the Southern African Development Community: New Insights from Women’s Empowerment
Bibliographic record
Abstract
There is massive and growing volume of literature on human capital and productivity. However, there is little emphasis on the growth channels of human capital, particularly on women’s empowerment, despite its theoretical underpinning and relevance in the Southern African Development Community (SADC). Understanding the effective channels of human capital is essential for policymakers in promoting sustainable growth and improved welfare. Given this, the study examines the effect of women’s empowerment through the ‘factor accumulation channel’ and the ‘productivity channel’ on SADC using cross-sectionally augmented autoregressive distributed lag (CS-ARDL) and the Dumitrescu–Hurlin non-causality test. Evidence from short- and long-run effects using the CS-ARDL shows that the factor accumulation and productivity channels of women’s empowerment have not benefited productivity growth in the SADC, although causality flows from the human capital indicators to productivity growth. The vital way for policy to boost productivity in SADC is to improve investment in female education and ensure that human capital is appropriately distributed and matches the economy’s dynamic demands. Based on the findings, the study suggests developing a framework to ascertain from time to time the marginal benefits of investment in female education compared to the marginal costs, both at the levels of the factor accumulation channel and the productivity channel in SADC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 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".