Pass‐Through and the Prediction of Merger Price Effects |
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| Authors: | Nathan H Miller Marc Remer Conor Ryan Gloria Sheu |
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| Institution: | 1. Georgetown University, McDonough School of Business, Washington, D.C., U.S.A.;2. Department of Economics, Swarthmore College, Swarthmore, Pennsylvania, U.S.A.;3. Department of Economics, University of Minnesota, Minneapolis, Minnesota, U.S.A.;4. Department of Justice, Antitrust Division, Washington, D.C., U.S.A. |
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| Abstract: | 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 2013 ]. 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. |
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