Coase and Transaction Costs Reconsidered: The Case of the English Lighthouse System
Bibliographic record
Abstract
What is Coase’s understanding of transaction costs in economic theory and history? Our argument in this paper is twofold, one theoretical and the other empirical. First, Coase regarded positive transaction costs as the beginning, not the end, of any analysis of market processes. From a Coasean perspective, positive transaction costs represent a profit opportunity for entrepreneurs to erode such transaction costs, namely by creating gains from trade through institutional innovation. We demonstrate the practical relevance of entrepreneurship for reducing transaction costs by revisiting the case of the lightship at the Nore, an entrepreneurial venture which had arisen to erode the transaction costs associated with regulation by Trinity House, the main lighthouse authority of England and Wales. By intervening into the entrepreneurial market process, Trinity House would pave the way for the nationalization of the entire English and Welsh lighthouse system. By connecting our theoretical contribution with an empirical application, we wish to illustrate that Coase’s theoretical understanding of transaction costs is inherently linked to an empirical analysis of market processes.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".