Imperfect Competition and Rents in Labor and Product Markets: The Case of the Construction Industry
Bibliographic record
Abstract
Existing work on imperfect competition typically focuses on either the labor market or the product market in isolation.In contrast, we analyze imperfect competition in both markets jointly, showing theoretically and empirically that focusing on one market in isolation may result in a limited or misleading picture of the degree and impacts of market power.Our empirical setting is the US construction industry.We develop, identify and estimate a model where construction firms imperfectly compete with one another for workers in the labor market and for projects in both the private market and the government market, where government projects are procured through auctions.Our analyses combine the universe of business and worker tax records with newly collected records from government procurement auctions.We use the estimated model to quantify the markdown of wages and the markup of prices, to show that the impacts of an increase in market power in one market are attenuated by the existence of market power in the other market, and to quantify the rents, rent-sharing, and incidence of procurements in the US construction industry.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".