Inefficiency and inequity of the law review submission system

Where a legal scholar works shapes publication outcomes nearly as much as what they write. Law reviews, the primary publication market for legal scholarship in the United States, are run by student editors who face thousands of submissions for a handful of slots and rely heavily on institutional prestige as a proxy for article quality. We build a calibrated agent-based simulation of this market and benchmark it against deferred acceptance, a centralized matching algorithm used in markets like medical residencies. The simulation predicts severe misallocation: more than 60% of top-tier placements differ from what centralized signal-based matching would produce, and the rank correlation between article quality and journal prestige is 0.45 versus 0.79 under centralized matching. Which system produces better placements overall depends on how many authors are competing for how many slots. As competition intensifies, the current system's disadvantage grows, with the model predicting up to 13.4% loss in match quality. Partial reforms like extending deadlines have negligible effects; in the simulation, the primary source of inefficiency is the decentralized structure of the market itself. The simulation also reveals that credential dependence produces inequity that persists even among articles of comparable quality: authors from prestigious institutions receive markedly better placements regardless of the matching mechanism. Centralized matching fixes the sorting problem but not this equity problem, because prestige bias is embedded in editorial signals and would require changes to how articles are evaluated, not just how they are assigned.