• DOI:10.1080/15309576.2019.1657915
• Corpus ID: 203468837

Common Source Bias, Key Informants, and Survey-Administrative Linked Data for Nonprofit Management Research

@article{Kim2020CommonSB,
  title={Common Source Bias, Key Informants, and Survey-Administrative Linked Data for Nonprofit Management Research},
  author={Mirae Kim and Jamie Levine Daniel},
  journal={Public Performance \& Management Review},
  year={2020},
  volume={43},
  pages={232 - 256}
}

• Mirae Kim, J. L. Daniel
• Published 2 January 2020
• Economics
• Public Performance & Management Review

Abstract In this study, we examine the increasingly popular strategy of supplementing survey data with administrative/archival data as a strategy to overcome common source bias. As the strategy does not present a cure-all solution, we argue it is a questionable recommendation and provide advice on how to approach this issue with due consideration. Focusing on the nonprofit sector, we compare the data drawn from a survey of financial estimates completed by nonprofit leaders and the IRS 990 forms-based financial data of corresponding nonprofit organizations. After presenting the evidence of some differences between the two data sources, we identify a set of key informant characteristics that are correlated with the level of differences. We echo George and Pandey (2018)’s claim that the criticisms toward common source bias have been somewhat exaggerated and urge public and nonprofit management researchers to be aware of other pitfalls they might face when trying to address common source bias.