Research on the Dual Effects of Corporate Physical and Transition Climate Risks on Total Factor Productivity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study empirically investigates the impacts of corporate climate risk, physical climate risk, and transition climate risk on firms’ total factor productivity (TFP), along with their underlying mechanisms, by employing a panel multidimensional fixed-effects model. The sample comprises Chinese listed companies spanning the period from 2007 to 2022. The findings reveal a significant positive effect of corporate climate risk and transition climate risk on corporate TFP, whereas physical climate risk exerts a substantial negative impact. Specifically, corporate climate risk and transition climate risk enhance TFP by elevating green technological innovation levels. Conversely, physical climate risk amplifies financing constraints, thereby diminishing TFP. Notably, these effects are accentuated in firms with higher return on assets, superior internal control quality, and greater institutional investor ownership, particularly among heavily polluting enterprises. Furthermore, while the positive effects of corporate climate risk and transition climate risk on TFP persist with a four-year lag, the negative impact of physical climate risk on TFP diminishes and becomes statistically insignificant over the same period.
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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 | 0.000 | 0.000 |
| 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 it