Relating Product Prices to Long‐Run Marginal Cost: Evidence from Solar Photovoltaic Modules
Bibliographic record
Abstract
Abstract A basic tenet of microeconomics is that for a competitive industry in equilibrium the market price of a product will be equal to its marginal cost. This paper develops a model framework and a corresponding empirical inference procedure for estimating long‐run marginal cost in industries where production costs decline over time. In the context of the solar photovoltaic (PV) module industry, we rely primarily on firm‐level financial accounting data to estimate the long‐run marginal cost of PV modules for the years 2008–2013. During those years, the industry experienced both unprecedented price declines and significant expansions of manufacturing capacity. We compare the trajectory of average sales prices with the estimated long‐run marginal costs in order to quantify the extent to which actual price declines were attributable to reductions in production costs. The trajectory of estimated product costs is then extrapolated to forecast an equilibrium trend line for future PV module prices.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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".