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Externalities in knowledge production: evidence from a randomized field experiment

Hinnosaar, Marit; Hinnosaar, Toomas; Kummer, Michael E.; Slivko, Olga

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Authors

Michael E. Kummer

Olga Slivko



Abstract

Are there positive or negative externalities in knowledge production? We analyze whether current contributions to knowledge production increase or decrease the future growth of knowledge. To assess this, we use a randomized field experiment that added content to some pages in Wikipedia while leaving similar pages unchanged. We compare subsequent content growth over the next four years between the treatment and control groups. Our estimates allow us to rule out effects on four-year growth of content length larger than twelve percent. We can also rule out effects on four-year growth of content quality larger than four points, which is less than one-fifth of the size of the treatment itself. The treatment increased editing activity in the first two years, but most of these edits only modified the text added by the treatment. Our results have implications for information seeding and incentivizing contributions. They imply that additional content may inspire future contributions in the short-and medium-term but do not generate large externalities in the long term. JEL: L17, L86, C93

Citation

Hinnosaar, M., Hinnosaar, T., Kummer, M. E., & Slivko, O. (2022). Externalities in knowledge production: evidence from a randomized field experiment. Experimental Economics, 25(2), 706-733. https://doi.org/10.1007/s10683-021-09730-x

Journal Article Type Article
Acceptance Date Aug 23, 2021
Online Publication Date Sep 1, 2021
Publication Date 2022-04
Deposit Date Aug 25, 2021
Publicly Available Date Sep 2, 2022
Journal Experimental Economics
Print ISSN 1386-4157
Electronic ISSN 1573-6938
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 25
Issue 2
Pages 706-733
DOI https://doi.org/10.1007/s10683-021-09730-x
Keywords knowledge accumulation; user-generated content; Wikipedia; public goods provision; field experiment
Public URL https://nottingham-repository.worktribe.com/output/6091385
Publisher URL https://link.springer.com/article/10.1007%2Fs10683-021-09730-x
Additional Information Data and code for this article are available in Hinnosaar et al. (2021a), Harvard Dataverse, doi: 10.7910/DVN/T4VFCX

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