@article{coupet_broussard_2021, title={Do Donors Respond to Nonprofit Performance? Evidence from Housing}, volume={44}, ISSN={["1557-9271"]}, DOI={10.1080/15309576.2020.1812409}, abstractNote={Abstract Standard economic theories of nonprofits argue that donors largely cannot observe nonprofit performance. Using market data from the US nonprofit housing sector, federal financial data, and rare internal production reports, this study examines the effects of nonprofit performance on donations with a dynamic panel model. Donors in our sample are only weakly sensitive to indicators of nonprofit productivity. Our results imply that nonprofit performance theory might be distinct from other sectors in that nonprofits cannot expect increased performance to be meaningfully rewarded with funding.}, number={1}, journal={PUBLIC PERFORMANCE & MANAGEMENT REVIEW}, author={Coupet, Jason and Broussard, Paul}, year={2021}, month={Jan}, pages={108–135} }
 @article{coupet_berrett_broussard_johnson_2021, title={Nonprofit Benchmarking With Data Envelopment Analysis}, volume={50}, ISSN={["1552-7395"]}, url={https://doi.org/10.1177/0899764020977670}, DOI={10.1177/0899764020977670}, abstractNote={ Benchmarking nonprofit performance can be challenging, constraining the ways nonprofits can use operational data to learn from each other and highlight organizational progress. Valid output or outcome data are scarce, and there is much to learn about measuring performance even when these data are available. Data envelopment analysis (DEA) is a mathematical linear programming technique that can be used to measure performance in a way that not only produces valid efficiency scores but also allows for benchmarking nonprofits with similar service missions. Using financial and production data from the nonprofit transportation sector, we walk through an example to explore DEA as a tool to measure and benchmark nonprofits. We conclude with suggestions for practice, emphasizing that DEA is useful for stakeholders looking to benchmark nonprofits by underscoring production and performance. }, number={3}, journal={NONPROFIT AND VOLUNTARY SECTOR QUARTERLY}, author={Coupet, Jason and Berrett, Jessica and Broussard, Paul and Johnson, Bradley}, year={2021}, month={Jun}, pages={647–661} }