Investments, Economic Growth and Employment: VAR Method for Romania
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
Abstract Economic growth can be seen as an effect of both fiscal policies and different legislative norms applied at national and macroeconomic level. Investments are a determining factor in the evolution of socio-economic life, influencing also the employment rate. This paper aims to identify the influence of investments on economic growth and employment using the vector autoregressive model (VAR). Based on the quarterly data from Romania, between the first quarter of 2000 and the second quarter of 2018, the Granger causality test and the impulse - response function was applied to identify the effect of the investments on the sustainable development of the Romanian economy. The results revealed that investments in Romania influence the economic growth and, implicitly, the employment. In terms of impulse – response function, a negative relationship between investment and employment was identified, which may be due to the fact that the need for human resources is no longer a priority in some sectors of activity due to technology.
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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) | 0.001 | 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