R&D Investment, Skill-Based Wage Gap, and Firm Innovation Performance: Evidence from Chinese Listed Companies
Bibliographic record
Abstract
Against China’s innovation-driven strategy, this study explores the impact of R&D investment on firm innovation performance and the mediating role of the wage gap between high- and low-skilled labor (HLWG) using data from Chinese A-share non-financial listed firms spanning 2010–2022. Employing static panel regression, Bootstrap test, and instrumental variables (R&D investment deduction, college enrollment expansion), the study finds three key results. First, R&D investment positively affects both firm innovation performance and HLWG. Second, HLWG exerts a positive impact on firm innovation performance. Third, HLWG plays a partial mediating role in the relationship between R&D investment and firm innovation performance. Robustness tests and instrumental variable regression confirm the stability of these conclusions. This finding enriches the theoretical understanding of the R&D-innovation transmission mechanism, offers insights into enterprises to coordinate R&D investment and wage structure optimization, and provides policy references for refining innovation incentives and labor market policies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".