Research Areas
My research program is organized into two streams that address core questions in public and nonprofit management and finance.
Guided by my commitment to advancing research that makes strong scholarly contributions while delivering value to the public, my work examines: (1) how managerial decisions and administrative structures influence the fiscal outcomes and service-delivery capacity of local governments, and (2) how institutional and fiscal constraints shape managerial behavior in nonprofit organizations.
Across both streams, my work seeks to refine financial and organizational decision-making practices that promote fiscal sustainability and resilient governance in local governments and nonprofits.
Selected Peer-reviewed Journal Publications
Hong, Minji & Benedict Jimenez. (2024).
Strategy Formulation Process and Interorganizational Collaboration.
Public Performance & Management Review
Jimenez, Benedict, Laiyang Ke, & Minji Hong. (2024).
Mayoral partisanship and municipal fiscal health.
Public Choice
Ke, Laiyang, Eunjoo Kwon, Minji Hong, & Benedict Jimenez (2025)
Assessing the Implementation of ARPA Coronavirus State and Local Fiscal Recovery Funds: The View from City Officials.
Publius: The Journal of Federalism
Selected Works-in-Progress
Hong, Minji (2025). Funding the Mission by Funding the Back Office: Evidence from the Paycheck Protection Program
[Won the 2025 ARNOVA Best Conference Paper Award and Emerging Scholars Program. Complete draft available upon request]
Award Citation: This paper was chosen for the ARNOVA Best Conference Paper Award because it exemplifies both theoretical innovation and methodological excellence. It tackles an important and underexplored issue regarding how unrestricted or overhead funding can lead to positive spillover effects on mission-related activities. The author(s) ground their analysis in conditional grant theory and use the Paycheck Protection Program (PPP) as a natural experiment to assess whether funding allocated specifically for administrative costs, such as payroll, can indirectly enhance an organization’s mission delivery. Their findings challenge the "overhead myth" by providing strong empirical evidence that supporting operational functions can improve nonprofit performance. What further sets this paper apart is its use of advanced causal inference methods, including doubly robust difference-in-differences and synthetic control techniques. These sophisticated approaches are rarely applied in nonprofit research and significantly strengthen the credibility of the results. Overall, the paper was selected for its clear contribution to advancing both the theory and practice of nonprofit management, offering timely insights backed by rigorous analysis.
Hong, Minji. Tying Their Own Hands: The Effectiveness and Unintended Consequences of Self-Imposed Debt Limits
[Won the 2025 National Tax Association Fiscal Sustainability Fellowship. Complete draft available upon request]
Using a NSF-funded large-scale survey data from 3,000 municipal governments across the U.S., I investigate whether internal constraints effectively curb municipal debt, testing predictions from new institutionalism and from strategic financial management literature. The findings reveal that self-imposed debt limits show no significant association with debt outcomes; in fact, ordinance-based limits show a positive association with debt level.
Hong, Minji. How Do Nonprofits Use Flexible Funding? Evidence from Unrestricted Grants
[Complete draft available upon request]
This paper examines how nonprofit organizations exercise discretion through unrestricted grants. Using system Generalized Method of Moments estimation on a panel of arts and culture nonprofits from 2009 to 2023, the essay tests competing predictions from stewardship theory and principal-agent theory. Unrestricted grants are found to be positively associated with administrative compensation, concentrated in compensation of existing personnel, rather than with increases in program spending, organizational capacity, workforce, or program reach.