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A study of the impact of data sharing on article citations using journal policies as a natural experiment

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  • Garret Christensen
  • Allan Dafoe
  • Edward Miguel
  • Don A Moore
  • Andrew K Rose

Abstract

This study estimates the effect of data sharing on the citations of academic articles, using journal policies as a natural experiment. We begin by examining 17 high-impact journals that have adopted the requirement that data from published articles be publicly posted. We match these 17 journals to 13 journals without policy changes and find that empirical articles published just before their change in editorial policy have citation rates with no statistically significant difference from those published shortly after the shift. We then ask whether this null result stems from poor compliance with data sharing policies, and use the data sharing policy changes as instrumental variables to examine more closely two leading journals in economics and political science with relatively strong enforcement of new data policies. We find that articles that make their data available receive 97 additional citations (estimate standard error of 34). We conclude that: a) authors who share data may be rewarded eventually with additional scholarly citations, and b) data-posting policies alone do not increase the impact of articles published in a journal unless those policies are enforced.

Suggested Citation

  • Garret Christensen & Allan Dafoe & Edward Miguel & Don A Moore & Andrew K Rose, 2019. "A study of the impact of data sharing on article citations using journal policies as a natural experiment," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-13, December.
    • Handle: RePEc:plo:pone00:0225883
    DOI: 10.1371/journal.pone.0225883
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    References listed on IDEAS

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    1. Garret Christensen & Edward Miguel, 2018. "Transparency, Reproducibility, and the Credibility of Economics Research," Journal of Economic Literature, American Economic Association, vol. 56(3), pages 920-980, September.
    2. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    3. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    4. Heather A Piwowar & Roger S Day & Douglas B Fridsma, 2007. "Sharing Detailed Research Data Is Associated with Increased Citation Rate," PLOS ONE, Public Library of Science, vol. 2(3), pages 1-5, March.
    5. Daron Acemoglu & Simon Johnson & James A. Robinson, 2001. "The Colonial Origins of Comparative Development: An Empirical Investigation," American Economic Review, American Economic Association, vol. 91(5), pages 1369-1401, December.
    6. Sebastian Galiani & Ramiro H. Gálvez, 2017. "The Life Cycle of Scholarly Articles across Fields of Research," NBER Working Papers 23447, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Brodeur, Abel & Cook, Nikolai M. & Hartley, Jonathan S. & Heyes, Anthony, 2022. "Do Pre-Registration and Pre-analysis Plans Reduce p-Hacking and Publication Bias?," GLO Discussion Paper Series 1147, Global Labor Organization (GLO).
    2. Joel Ferguson & Rebecca Littman & Garret Christensen & Elizabeth Levy Paluck & Nicholas Swanson & Zenan Wang & Edward Miguel & David Birke & John-Henry Pezzuto, 2023. "Survey of open science practices and attitudes in the social sciences," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Abel Brodeur & Nikolai Cook & Carina Neisser, 2024. "p-Hacking, Data type and Data-Sharing Policy," The Economic Journal, Royal Economic Society, vol. 134(659), pages 985-1018.
    4. Troy J. Bouffard & Ekaterina Uryupova & Klaus Dodds & Vladimir E. Romanovsky & Alec P. Bennett & Dmitry Streletskiy, 2021. "Scientific Cooperation: Supporting Circumpolar Permafrost Monitoring and Data Sharing," Land, MDPI, vol. 10(6), pages 1-17, June.
    5. Edward Miguel, 2021. "Evidence on Research Transparency in Economics," Journal of Economic Perspectives, American Economic Association, vol. 35(3), pages 193-214, Summer.
    6. Brian Jackson, 2021. "Open Data Policies among Library and Information Science Journals," Publications, MDPI, vol. 9(2), pages 1-12, June.
    7. Aguinis, Herman & Banks, George C. & Rogelberg, Steven G. & Cascio, Wayne F., 2020. "Actionable recommendations for narrowing the science-practice gap in open science," Organizational Behavior and Human Decision Processes, Elsevier, vol. 158(C), pages 27-35.
    8. Qianjin Zong & Zhihong Huang & Jiaru Huang, 2023. "Do open science badges work? Estimating the effects of open science badges on an article’s social media attention and research impacts," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3627-3648, June.
    9. Barbara McGillivray & Paola Marongiu & Nilo Pedrazzini & Marton Ribary & Mandy Wigdorowitz & Eleonora Zordan, 2022. "Deep Impact: A Study on the Impact of Data Papers and Datasets in the Humanities and Social Sciences," Publications, MDPI, vol. 10(4), pages 1-40, October.
    10. Abel Brodeur & Nikolai M. Cook & Jonathan S. Hartley & Anthony Heyes, 2024. "Do Preregistration and Preanalysis Plans Reduce p-Hacking and Publication Bias? Evidence from 15,992 Test Statistics and Suggestions for Improvement," Journal of Political Economy Microeconomics, University of Chicago Press, vol. 2(3), pages 527-561.
    11. Liwei Zhang & Liang Ma, 2021. "Does open data boost journal impact: evidence from Chinese economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3393-3419, April.

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