Herding in Quality Assessment: An Application to Organ Transplantation

Stephanie de Mel (), Kaivan Munshi (), Soenje Reiche and Hamid Sabourian
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Stephanie de Mel: Institute for Fiscal Studies
Kaivan Munshi: Institute for Fiscal Studies and University of Cambridge
Soenje Reiche: Institute for Fiscal Studies
Hamid Sabourian: Institute for Fiscal Studies

No W20/22, IFS Working Papers from Institute for Fiscal Studies

Abstract: There are many economic environments in which an object is offered sequentially to prospective buyers. It is often observed that once the object for sale is turned down by one or more agents, those that follow do the same. One explanation that has been proposed for this phenomenon, which goes back to Banerjee (1992) and Bikhchandani (1992) is that agents making choices further down the line rationally ignore their own assessment of the object's quality and herd behind their predecessors. We develop novel tests to detect information-based herding, based on heterogeneity in agent ability, together with a methodology to quantify its welfare consequences, that are applied to organ transplantation in the U.K. We find that herding is common and is an important contributor to the high rate at which organs are rejected by transplant centers (and subsequently discarded). However, herding does not raise discard rates much above the level that would be obtained if private assessments were made publicly available. Instead, the (limited) information contained in predecessors' decisions substantially reduces the acceptance of bad organs. This is because in our application (i) high ability centers are often willing to deviate from the herd and follow their own positive signals, and (ii) sequences are exogenously terminated relatively quickly.

Date: 2020-07-09
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