Intellectual Property Rights, Investment Climate and FDI in Developing Countries
Bibliographic record
Abstract
What is the impact of intellectual property rights (IPR) protection on foreign direct investment (FDI)? Has the coming into effect of the Agreement on Trade Related Aspects of Intellectual Property Rights (TRIPS) had any impact on FDI inflows in developing countries? This paper answers these questions by the use of panel data for a cross – section of 75 developing countries over a period of 19 years (1985 – 2003). The results of the study indicate that: 1) strengthening IPR has a positive effect on FDI; 2) the impact of patent protection on FDI after the TRIPS agreement is far and above that of the pre – TRIPS era; 3) the degree of openness, growth rate of the economy and investment are also key determinants of FDI. The findings of the study suggest that strengthening IPR is only one component of the many factors needed to maximize the potential of developing countries to attract FDI.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".