I am currently a PhD candidate in political science at the University of Missouri. I study issues at the intersection of public administration and management, administrative politics, and public policy. Most of research focuses on the broader network of government oversight with a specific emphasis the relationship between executive branch agencies, Congress, and experts in improving accountability and performance. My work is forthcoming at Policy Studies Journal.
Officials at all levels of government rely on expert administrators and auditing organizations to provide performance information and identify problem areas in public agencies. Important work has considered how elected officials hold government agencies accountable, but scholars largely ignore oversight mechanisms within agencies that monitor the implementation and formation of public policies and communicate information to elected officials and agency leaders. My dissertation research explores the implications of government-wide oversight initiatives (e.g., Inspectors General and Government Accountability Office) in enhancing administrative accountability, effective oversight, and agency performance. Through three empirical chapters, I examine (1) oversight performed by civil servants; (2) monitoring of agency activities by Offices of the Inspector General; and (3) the influence of elected officials on non-partisan institutions tasked with overseeing government agencies. My dissertation demonstrates that even non-partisan, expert oversight is subject to political manipulation and has implications for our understanding of accountability, performance, and effective oversight.
A copy of my CV is available here.
PhD, Political Science, 2020
University of Missouri
BS, Political Science, 2015
Black Hills State University
Scholars have long been interested in how policies and ideas spread from one observation to another. Yet, the spatial and temporal dynamics of policy diffusion present unique challenges that empirical researchers often neglect. Scholars often use temporally-lagged spatial lags (TLSL)—such as the number (or percentage) of prior adopters in a neighborhood—to test various mechanisms of delayed policy diffusion but are largely unaware of two under-appreciated issues. First, the effects are not limited to one time period but persist over time by changing the future value of neighboring observations. Second, minor, yet common, choices in model specification—such as omitting spatially-correlated and/or autoregressive covariates—can increase the risk of falsely inferring that the outcome is a result of spatial diffusion. Indeed, we offer two applications where small changes to the model specification of an otherwise well-specified model result in drastically different inferences about policy diffusion. We argue that scholars should avoid haphazardly including TLSLs without considerable theoretical justification, and we conclude on an optimistic note by offering straightforward solutions and new software to address these issues.
“The Importance of Agency and Oversight Capacity in Enhancing Accountability in Policy Implementation” with Lael R. Keiser
“Delegated Oversight and the Politics of Problem Monitoring: The Case of Federal Inspectors General”
“Watchdogs or Partisan Pawns? Agenda Setting and GAO Oversight”
“Society of Deputies: The Negative Externalities of Coproduction” with Nicholas Brothers
“Politicization and Bureaucratic Resistance to External Oversight”