Evaluating economies of scope and potential merger: an alternative approach
Bibliographic record
Abstract
Abstract In data envelopment analysis literature, the estimation of economies of scope involves comparing two frontiers: one for diversified firms producing two outputs together (the diversified frontier) and the other involving additive firms (the additive frontier). A firm’s scope economies can be assessed by comparing the costs of its outputs against these two frontiers. If the cost for the additive frontier exceeds or falls short of that for the diversified frontier, one can determine the presence or absence of scope economies for the diversified firm. However, constructing the additive frontier requires the assumption that the cost of joint production by a diversified firm equals the cost of separate production by specialized firms. In the absence of such an additive cost structure in empirical studies, scope economies evaluation becomes problematic. To address this, we propose an alternative measurement scheme. Using the free disposability postulate of production theory, our scheme creates two sets of virtual specialized firms from the observed diversified firms, then updates them within their respective specialized firm sets. This approach enables an evaluation of a firm's scope economies by comparing the cost of separate production against updated specialized technologies with the joint production cost against diversified technology. Finally, the scheme also allows an examination of whether a merger between any two specialized firms would be profitable.
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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 | 0.016 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".