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Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy

Edward L. Glaeser, Andrew Hillis, Scott Duke Kominers, Michael Luca

NBER Working Paper No. 22124
Issued in March 2016
NBER Program(s):Public Economics, Productivity, Innovation, and Entrepreneurship

Can open tournaments improve the quality of city services? The proliferation of big data makes it possible to use predictive analytics to better target services like hygiene inspections, but city governments rarely have the in-house talent needed for developing prediction algorithms. Cities could hire consultants, but a cheaper alternative is to crowdsource competence by making data public and offering a reward for the best algorithm. This paper provides a simple model suggesting that open tournaments dominate consulting contracts when cities have a reasonable tolerance for risk and when there is enough labor with low opportunity costs of time. We also illustrate how tournaments can be successful, by reporting on a Boston-based restaurant hygiene prediction tournament that we helped coordinate. The Boston tournament yielded algorithms—at low cost—that proved reasonably accurate when tested “out-of-sample” on hygiene inspections occurring after the algorithms were submitted. We draw upon our experience in working with Boston to provide practical suggestions for governments and other organizations seeking to run prediction tournaments in the future.

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Document Object Identifier (DOI): 10.3386/w22124

Published: Edward L. Glaeser & Andrew Hillis & Scott Duke Kominers & Michael Luca, 2016. "Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy," American Economic Review, vol 106(5), pages 114-118. citation courtesy of

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