Public investment and economic growth in the European Union member states
Bibliographic record
Abstract
The issue of public investments became a very challenging subject for public decision makers since it incorporates the question of state performance, the quality of public finance and their effects on growth.The quality of public finance (QPF) is a multidimensional concept. It may be regarded as representing all the arrangements and operations regarding the financial politics that sustain the macroeconomic objectives, particularly the long-term economic growth. Financial policies at European level highlight the fact that a concentration of the public expenses in areas that stimulate the economic growth and a more efficient use of the public resources are key methods for sustaining the economic growth. The empirical proofs seem to support the assumption according to which certain types of public expenses can supply incentives and other can negatively influence the economic growth. The paper tries to reveal the effects of capital spending on economic growth (GDP per capita) for the European Union member states. The gross domestic product per capita and the capital expenses (functional classification of public expenses - “COFOG”) have been obtained by considering the Eurostat statistics, the measurement unit for the dependent variable and for the independent one is the EURO, while the period of analyze is of 7 years ( 2000-2006)
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 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".