Sustainable economic growth in the European Union: The role of<scp>ICT</scp>, venture capital, and innovation
Bibliographic record
Abstract
Abstract Over the past 30 years, the economies in Europe have undergone major transformations that have been powered by diffusion of information and communication technology ( ICT ), intensification of innovation, and reforms in the financial sector to support innovative endeavors. The primary objective of this study was to examine the causal relationships among ICT diffusion, innovation diffusion, venture capital investment, and economic growth for 25 countries in Europe for the period from 1989 to 2016. Using a vector error‐correction model, the study examines the underlying short‐run and long‐run relationships for the above variables. The empirical analysis shows that in the long run, venture capital investment, ICT diffusion, and innovation diffusion have significant impacts on economic growth in Europe. However, in the short run, the direction of the causality varies depending on the specific measures of ICT diffusion and innovation diffusion that are utilized. Results from this study provide valuable insights into the types of policies that will contribute to sustainable economic growth in Europe.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".