The Impact of the Nonprofit Sector on Employment and Unemployment in Developed Economies: Dynamic Panel Data Analysis
Bibliographic record
Abstract
In the last quarter of the last century, the reshaping of the state apparatus under the domination of liberal economics and globalization led to a rapid and radical transformation of the nonprofit sector. With growing incomes, expenditures, staff and volunteers, these organizations have become major economic actors in many countries today. Indeed, economic research and technical reports on the sector have started to attract attention in the last few decades. When we look at these studies, we can say that the sector has a very active presence in labor markets, especially in developed countries. However, these studies do not econometrically evaluate the direction and extent to which the sector actually affects employment in countries. Therefore, the subject of this study was to investigate the data set of the 16 developed countries for the period of 2008 to 2018 using the least squares dummy variable corrected estimator. It was observed that there is a positive relationship between the employment rate and the gross value added of nonprofit organizations, and there is no statistically significant relationship between the employment rate and the world giving index. In addition, a negative relationship was found between the unemployment rate and the gross value added of nonprofit organizations and the world giving index.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 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".