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A. Sorokin, D. Forsyth (2008)
Utility data annotation with Amazon Mechanical Turk2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
L. Einav, Theresa Kuchler, Jonathan Levin, Neel Sundaresan (2015)
Assessing Sale Strategies in Online Markets Using Matched ListingsAmerican Economic Journal: Microeconomics, 7
Winter Mason, D. Watts (2009)
Financial incentives and the "performance of crowds"
Panagiotis Ipeirotis (2010)
Analyzing the Amazon Mechanical Turk marketplaceXRDS: Crossroads, The ACM Magazine for Students, 17
(2015)
WWW '15 International World Wide Web Conferences Steering Committee Republic and Canton of Geneva
D. Difallah, Michele Catasta, Gianluca Demartini, P. Cudré-Mauroux (2014)
Scaling-Up the Crowd: Micro-Task Pricing Schemes for Worker Retention and Latency ImprovementProceedings of the AAAI Conference on Human Computation and Crowdsourcing
Ming Yin, Siddharth Suri, Mary Gray (2018)
Running Out of Time: The Impact and Value of Flexibility in On-Demand CrowdworkProceedings of the 2018 CHI Conference on Human Factors in Computing Systems
Jacob Abernethy, Yiling Chen, Chien-Ju Ho, Bo Waggoner (2015)
Low-Cost Learning via Active Data ProcurementProceedings of the Sixteenth ACM Conference on Economics and Computation
L. Irani, M. Silberman (2013)
Turkopticon: interrupting worker invisibility in amazon mechanical turkProceedings of the SIGCHI Conference on Human Factors in Computing Systems
Aaron Smith (2016)
Gig Work, Online Selling and Home Sharing
Alan Benson, Aaron Sojourner, Akhmed Umyarov (2017)
The Value of Employer Reputation in the Absence of Contract Enforcement: A Randomized ExperimentOrganizations & Markets: Formal & Informal Structures eJournal
Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Vaughan (2015)
Incentivizing high quality crowdwork
Eric Huang, Haoqi Zhang, D. Parkes, Krzysztof Gajos, Yiling Chen (2010)
Toward automatic task design: a progress report
(2003)
)) on all descriptions. LDA requires the choice of a parameter K which determines how many topics the algorithm should try to discover: we estimate models with K ∈ {5
Anirban Dasgupta, Arpita Ghosh (2013)
Crowdsourced judgement elicitation with endogenous proficiencyProceedings of the 22nd international conference on World Wide Web
M. Fosgerau, E. Melo, A. Palma, M. Shum (2017)
DISCRETE CHOICE AND RATIONAL INATTENTION: A GENERAL EQUIVALENCE RESULTInternational Economic Review, 61
M. Marge, S. Banerjee, Alexander Rudnicky (2010)
Using the Amazon Mechanical Turk for transcription of spoken language2010 IEEE International Conference on Acoustics, Speech and Signal Processing
José Azar, I. Marinescu, Marshall Steinbaum (2017)
Labor Market ConcentrationThe Journal of Human Resources, 57
D. Chandler, J. Horton (2011)
Labor Allocation in Paid Crowdsourcing: Experimental Evidence on Positioning, Nudges and Prices
M. Goldfield (2004)
Monopsony in Motion - Imperfect Competition in Labor Markets.Journal of Economics, 82
Mary Gray, Siddharth Suri, Syed Ali, Deepti Kulkarni (2016)
The Crowd is a Collaborative NetworkProceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing
(2011)
Amazon’s Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data?,
Goran Radanovic, B. Faltings (2016)
Learning to Scale Payments in Crowdsourcing with PropeRBoost
Michael Rabadi (2015)
Kernel Methods for Machine Learning
(2020)
Monopsony in Online Labor Markets: Dataset.
(2017)
Noncompetes in the US labor force,
(2018)
Appendix A Monopsony on Mechanical Turk We assume a large number L of employers, denoted as i, who initially post Ni jobs, each worth pi only if completed before time Ti
(2015)
Computer-Supported Cooperative Work & Social Computing, 134–47
D. Lindley (1997)
The choice of sample size, 46
Lawrence Katz, A. Krueger (2016)
The Rise and Nature of Alternative Work Arrangements in the United States, 1995–2015ILR Review, 72
U. Gadiraju, Ricardo Kawase, S. Dietze (2014)
A taxonomy of microtasks on the webProceedings of the 25th ACM conference on Hypertext and social media
Winter Mason, Siddharth Suri (2010)
Conducting behavioral research on Amazon’s Mechanical TurkBehavior Research Methods, 44
P. Dörrenberg, D. Duncan, Max Loeffler (2016)
Asymmetric Labor-Supply Responses to Wage-Rate Changes: Evidence from a Field ExperimentRandomized Social Experiments eJournal
Jeffrey Heer, M. Bostock (2010)
Crowdsourcing graphical perception: using mechanical turk to assess visualization designProceedings of the SIGCHI Conference on Human Factors in Computing Systems
D. Staiger, J. Spetz, C. Phibbs (1999)
Is There Monopsony in the Labor Market? Evidence from a Natural ExperimentJournal of Labor Economics, 28
David Card, A. Cardoso, Joerg Heining, Patrick Kline (2016)
Firms and Labor Market Inequality: Evidence and Some TheoryJournal of Labor Economics, 36
P. Robinson (1988)
ROOT-N-CONSISTENT SEMIPARAMETRIC REGRESSIONEconometrica, 56
Arindrajit Dubé, A. Manning, S. Naidu (2018)
Monopsony and Employer Mis-Optimization Explain Why Wages Bunch at Round NumbersNBER Working Paper Series
Áron, Anier (2017)
Should We Treat Data as Labor? Moving Beyond “Free”
(2008)
No HIT groups posted sequentially (not randomized
Matthew Crump, John McDonnell, T. Gureckis (2013)
Evaluating Amazon's Mechanical Turk as a Tool for Experimental Behavioral ResearchPLoS ONE, 8
X. Gabaix, David Laibson, Deyuan Li, Hongyi Li, S. Resnick, C. Vries (2016)
The impact of competition on prices with numerous firmsJ. Econ. Theory, 165
Chris Callison-Burch (2014)
Crowd-Workers: Aggregating Information Across Turkers to Help Them Find Higher Paying WorkProceedings of the AAAI Conference on Human Computation and Crowdsourcing
J. Manyika, Susan Lund, Kelsey Robinson, J. Valentino, R. Dobbs (2015)
A labor market that works: connecting talent with opportunity in the digital age
S. Naidu, E. Posner, E. Weyl (2018)
Antitrust Remedies for Labor Market PowerMicroeconomics: Production
D. Blei, A. Ng, Michael Jordan (2009)
Latent Dirichlet Allocation
A. Krueger, O. Ashenfelter (2018)
Theory and Evidence on Employer Collusion in the Franchise SectorThe Journal of Human Resources, 57
Quoc Le, Tomas Mikolov (2014)
Distributed Representations of Sentences and Documents
Gary Hsieh, Rafal Kocielnik (2016)
You Get Who You Pay for: The Impact of Incentives on Participation BiasProceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing
L. Breiman (2001)
Random ForestsMachine Learning, 45
Matthew Honnibal, Mark Johnson (2015)
An Improved Non-monotonic Transition System for Dependency Parsing
Jakob Rogstadius, V. Kostakos, A. Kittur, Boris Smus, Jim Laredo, M. Vukovic (2011)
An Assessment of Intrinsic and Extrinsic Motivation on Task Performance in Crowdsourcing MarketsProceedings of the International AAAI Conference on Web and Social Media
Jia Deng, Wei Dong, R. Socher, Li-Jia Li, K. Li, Li Fei-Fei (2009)
ImageNet: A large-scale hierarchical image database2009 IEEE Conference on Computer Vision and Pattern Recognition
We run Doc2Vec model Le and Mikolov (2014) on all titles, descriptions, and keywords in the data, producing a 50-dimensional semantic information vector for each
Adam Berinsky, G. Huber, Gabriel Lenz (2012)
Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical TurkPolitical Analysis, 20
J. Horton, Lydia Chilton (2010)
The labor economics of paid crowdsourcingLabor: Human Capital eJournal
Ming Yin, Mary Gray, Siddharth Suri, Jennifer Vaughan (2016)
The Communication Network Within the CrowdProceedings of the 25th International Conference on World Wide Web
Efraim Benmelech, Nittai Bergman, Hyunseob Kim (2018)
Strong Employers and Weak EmployeesThe Journal of Human Resources, 57
J. Horton, David Rand, R. Zeckhauser (2010)
The online laboratory: conducting experiments in a real labor marketExperimental Economics, 14
P. Kuhn (2004)
Is monopsony the right way to model labor markets? a review of Alan Manning's monopsony in motionInternational Journal of the Economics of Business, 11
Sara Kingsley, Mary Gray, Siddharth Suri (2015)
Accounting for Market Frictions and Power Asymmetries in Online Labor MarketsPolicy & Internet, 7
(2017)
Monopsony, Misoptimization, and Round Number Bunching in the Wage Distribution
V. Chernozhukov, D. Chetverikov, Mert Demirer, E. Duflo, Christian Hansen, Whitney Newey, J. Robins (2017)
Double/Debiased Machine Learning for Treatment and Structural ParametersEconometrics: Econometric & Statistical Methods - Special Topics eJournal
AbstractDespite the seemingly low switching and search costs of on-demand labor markets like Amazon Mechanical Turk, we find substantial monopsony power, as measured by the elasticity of labor supply facing the requester (employer). We isolate plausibly exogenous variation in rewards using a double machine learning estimator applied to a large dataset of scraped MTurk tasks. We also reanalyze data from five MTurk experiments that randomized payments to obtain corresponding experimental estimates. Both approaches yield uniformly low labor supply elasticities, around 0.1, with little heterogeneity. Our results suggest monopsony might also be present even in putatively “thick” labor markets. (JEL C44, J22, J23, J42)
American Economic Review: Insights – American Economic Association
Published: Mar 1, 2020
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