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Data and Code for: Cite Unseen (Cites to Academic Articles Across the Quality Spectrum)

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ICPSR2021-01-01 更新2026-04-16 收录
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https://www.openicpsr.org/openicpsr/project/137041/version/V1/view
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资源简介:
This archive Stata data and code that the authors used to produce the tables and figures in the paper, <b>Cite Unseen: Theory and Evidence on the Effect of Open Access on Cites to Academic Articles Across the Quality Spectrum</b>, published in Managerial and Decision Economics. As described in the README file, we provide a separate program for each table and figure. Code and data are provided for the empirical regressions, and code is also provided for Monte Carlo simulations.<br><br><b>Paper abstract: </b>We model open access as facilitating full-text acquisition, which, while often increasing cites, can reduce cites from readers who refrain from citing superficially after realizing the article is not worth citing. We test the theory with data on over 200,000 science articles binned by cites in the pre-study period. Consistent with theory, we find that opening access to an article on the journal’s website has a “Matthew effect” on citations: negative for the least-cited articles, positive for the most cited, and monotonic for quality levels in between. Estimates for broader open-access platforms and for cites coming from insiders versus outsiders also follow patterns consistent with theory.<br><br><br><br>
提供机构:
Questrom School of Business, Boston University; Dartmouth College
创建时间:
2021-01-01
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