Event study + recipient–provider similarity
Event-study estimates. Productivity (Poisson) of data providers vs. matched comparison group, 5 years before to 4 years after data sharing. Pre-treatment trends are parallel; the post-treatment trajectory shows no significant divergence.
Why no penalty? Provider–recipient research pairs are less similar (lower ZSimilarity, fewer shared subject codes and journals) than provider–provider or recipient–recipient pairs. Data recipients pursue distant questions, so diversion dominates competition.
Competition or Diversion? Effect of Public Sharing of Data on Research Productivity of Data Provider
Scientists worry that publicly disclosing research data hurts their own publication opportunities — rivals can race ahead with the same data. But the empirical evidence has been scant. Does mandatory data sharing harm the original data creators' research productivity?
- Setting NIH mandate to share data via dbGaP archive
- Method Panel DID + synthetic control on data providers vs matched controls
- Finding No negative impact on data providers’ research productivity
- Why Data recipients pursue research questions distant from providers’ — diversion dominates competition
- Implication Sustainable data-sharing policies can be designed without penalizing original teams
