Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy / Edward L. Glaeser, Andrew Hillis, Scott Duke Kominers, Michael Luca.

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Glaeser, Edward L

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Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w22124.Publication details: Cambridge, Mass. National Bureau of Economic Research 2016.Description: 1 online resource: illustrations (black and white)Subject(s):

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Abstract: 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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Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber w22124 (Browse shelf(Opens below))	Not For Loan

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March 2016.

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.