1 Department of Economics and John F. Kennedy School of Government, Harvard University, Littauer Center, 1805 Cambridge Street, Cambridge, MA 02138, and NBER (e-mail: ) · 2 Department of Economics, Harvard University, and Harvard Business School, Baker Library, Soldiers Field, Boston, MA 02163 (e-mail: ) · 3 Society of Fellows, Department of Economics, Center of Mathematical Sciences and Applications, Center for Research on Computation and Society, and Program for Evolutionary Dynamics, Harvard University, and Harvard Business School, Arthur Rock Center for Entrepreneurship, Soldiers Field, Boston, MA · 4 Harvard Business School, Baker Library, Soldiers Field, Boston, MA 02163 (e-mail: )
Abstract
The proliferation of big data makes it possible to better target city 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. A simple model suggests that open tournaments dominate consulting contracts when cities can tolerate risk and when there is enough labor with low opportunity costs. We also report on an inexpensive Boston-based restaurant tournament, which yielded algorithms that proved reasonably accurate when tested “out-of-sample” on hygiene inspections.