Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy †

By Edward L. Glaeser, Andrew N. Hillis, Scott Duke Kominers, Michael Luca. 2016

97 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research, Safety Research

Citations in the corpus

• The State of Applied Econometrics - Causality and Policy Evaluation (2016, neutral): “They perform well in prediction contests; for example, in a recent economics paper (Glaeser et al. [2016]) on crowd-sourcing predictive algorithms for city governments through contests, the winning algorithm was a random forest.”
• How Valuable Is FinTech Innovation? (2019, unknown): “Other work studies the application of machine-learning methods to economics (e.g., Kleinberg et al. 2015; Glaeser et al. 2016; Naik, Raskar, and Hidalgo 2016; Athey and Wager 2018; Athey, Tibshirani, and Wager 2018).”