Cross-Border Price Effects of Mergers and Acquisitions -- A Quantitative Framework for Competition Policy
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
Decisions of national competition authorities have important effects on other jurisdictions. We provide a framework to quantify the domestic and cross-border effects of mergers, and to draw conclusions for the coordination of national merger policies. We develop a two-country model with many sectors. In each sector, producers vary in terms of their marginal costs, and are engaged in Cournot competition. We allow for profitable mergers to take place subject to the non-violation of a given national competition policy. Because of trade costs and perceived differences in qualities between domestic and foreign products, mergers may have different consumer surplus effects in the home and the foreign country. We calibrate the model using data for the year 2002 for 167 manufacturing sectors in the U.S. and Canada. We choose parameters to match relevant moments in the data, including industry sales, concentration ratios and trade flows. We find that in the majority of industries a merger approval policy based on domestic consumer surplus is too restrictive from the viewpoint of the neighboring country. We also show that adopting a supra-national policy that approves a merger if and only if it increases the sum of consumer surplus in the two countries would lead to significant gains for U.S. consumers but hurt consumers in Canada. These results highlight the difficulties in coordinating national competition policies in a way acceptable to all participating countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.007 | 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 it