The productivity effect of public R&D in the Netherlands
Bibliographic record
Abstract
Using a vector-error-correction model (VECM) with endogenous stocks for total factor productivity (TFP), domestic and foreign public and private Research and Development (R&D) as well as the GDP from which current resources are taken, we find that for the Netherlands for the period 1968-2014, extra investment in public R&D has a clear positive effect on total factor productivity growth. Taking into account the costs of these extra investments, we find that the rate of return to such a policy is positive and generally high. Including private R&D in the policy from the beginning is better than increasing public R&D alone and private R&D only following. Transitory and permanent shocks to only domestic public R&D in 1971 show positive effects on private domestic and foreign private and public R&D, total factor productivity and GDP. Under a permanent shock to the growth rate of domestic public R&D by 0.005 (an additional half percentage point on the baseline growth rate), TFP is 27.5% higher than baseline after 70 years, and the GDP is 61% higher because a higher TFP also attracts international capital one-to-one with GDP. Foreign private R&D reacts much more positively then foreign public R&D. Private R&D capital increases by up to 5.5% compared to baseline and returns to baseline in the long run. The internal rate of return is 131 percent obtained already in 1988. If domestic and foreign public R&D are increased by the same permanent shock of 0.005, there are positive effects for thirty five years in domestic private R&D but permanently so for all other variables; TFP would have been higher by 0.56% and GDP by 9.4%, much less than under the first strategy without the symmetric and simultaneous foreign policy. The rate of return is 4-6 percent for horizons 2014, 2024, and 2040 because of higher gains in later periods. If domestic and foreign public and private R&D growth get a shock of 0.0025 (each an additional quarter of a percent on baseline) TFP increases by 13 percent until 2040, GDP by 28 percent and the internal rate of return is 77%.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".