Pass-Through and the Prediction of Merger Price Effects

Nathan H. Miller, Marc Remer, Conor Ryan, Gloria Sheu

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


We use Monte Carlo experiments to study how pass-through can improve merger price predictions, focusing on the first order approximation (FOA) proposed in Jaffe and Weyl []. FOA addresses the functional form misspecification that can exist in standard merger simulations. We find that the predictions of FOA are tightly distributed around the true price effects if pass-through is precise, but that measurement error in pass-through diminishes accuracy. As a comparison to FOA, we also study a methodology that uses pass-through to select among functional forms for use in simulation. This alternative also increases accuracy relative to standard merger simulation and proves more robust to measurement error.

Original languageEnglish (US)
Pages (from-to)683-709
Number of pages27
JournalJournal of Industrial Economics
Issue number4
StatePublished - Dec 1 2016

All Science Journal Classification (ASJC) codes

  • Accounting
  • General Business, Management and Accounting
  • Economics and Econometrics


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