Research Implications of Electronic Filing of Nonprofit Information: Lessons from the United States’ Internal Revenue Service Form 990 Series
Autor: | Todd L. Ely, Thad D. Calabrese, Jihye Jung |
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Rok vydání: | 2021 |
Předmět: |
Public Administration
Sociology and Political Science Strategy and Management media_common.quotation_subject Open data Internal revenue Data quality Service (economics) Generalizability theory Business Business and International Management Marketing Electronic filing Social policy media_common Panel data |
Zdroj: | VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations. 34:20-28 |
ISSN: | 1573-7888 0957-8765 |
DOI: | 10.1007/s11266-021-00398-8 |
Popis: | Increased electronic filing, or e-filing, of nonprofit data in the United States and abroad quickens public availability, eliminates dependence on third-party proprietary datasets, and broadens access to information offering insight into previously neglected topics. On the other hand, increasingly open data require researchers to independently ensure data quality, understand limitations, and consider how data availability shapes research questions. As electronic filing becomes mandatory in the United States and more widespread elsewhere, this research considers how expanded e-filer data impact nonprofit research approaches and opportunities while assessing the generalizability and limits of existing e-filed data in the United States. While the data suggest increasing compliance with e-filing, analyses show that older nonprofits with greater capacity and sophisticated financial characteristics are historically more likely to e-file. Further, particular subsectors are more likely to e-file than others. Therefore, using existing e-filed IRS Form 990s for panel data analysis presents some generalizability concerns, although this will improve over time. Moving forward, e-filing and machine-readable access requirements bode well for both quantitative and qualitative nonprofit research, while the United States’ experience provides helpful lessons for other research settings. |
Databáze: | OpenAIRE |
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