Current Projects

There is a resounding call from academics and practitioners to transition critical infrastructure systems, such as drinking water, storm water, transportation, and electricity, to both mitigate negative human influence on the environment and ensure that such critical systems can maintain their desired performance in unprecedented environmental changes (a.k.a., resilience). Moreover, the opportunity for transition coincides with increasing recognition of the need to fairly distribute the benefits and costs of infrastructure systems given their fundamental public value.

However, given profound uncertainty pertaining to environmental and sociopolitical futures that our infrastructure systems are embedded within, it is imperative that our focus in deriving solutions extends beyond discrete investment or policy recommendations and examines the technical, institutional, and human determinants of information processing capacity that govern public infrastructure at multiple jurisdictional levels. One-shot policies can get our systems closer to a desired state, but neglecting the processes responsible for enacting and implementing the policy avoids the reality that there will always be a future problem.

Thus, the central motivation behind this project, which serves as the core of my postdoctoral work at Princeton and the Levin Lab, is understanding (i) the technical, institutional, and human constraints on information processing within policy and administrative systems governing public infrastructure and (ii) the implications of these constraints for the resilience and fairness of our critical infrastructure systems.

The project consists of two parallel lines of scholarly investigation: one empirical and one theoretical. The empirical work centers around a survey of local infrastructure providers in the US, specializing in flooding and EV charging infrastructure, regarding their investment priorities, strategies, and collaborative behavior with regional organizations and peer providers. The planned survey is a follow-up to a 2022 survey conducted by Indiana University (website) as an assessment of Biden era infrastructure legislation implementation. Given repeals of federal funding in 2025, this next survey will also serve to assess the effect major investment repeals on local infrastructure planning and perception of policy uncertainty.

On the theory side, I am developing an agent-based model (ABM) of collective information processing in a regional coupled infrastructure system that extends prior work I have done on information processing in infrastructure providers (see below) to a network of multiple coordinating providers in a common biophysical and sociopolitical environment. The ABM will allow for simulation of the effect alternative regional cooordination schemes, investment priorities, and planning protocols will have on the robustness of infrastructure systems.

Across the US, there is a resounding call to transition critical public infrastructure systems to facilitate broader sustainability goals, including climate adaptation, clean energy, water quality, affordability, and fair economic access. Yet, such transitions must grapple with the complex politics of infrastructure investment. In the US and abroad, there has been, a well-documented gap in investment in infrastructure directly attributable to political context and contingencies. In the US, local governments face a significant portion of the responsibility for such investment. Overall, a major reason for investment hesitancy is resistance to raising service fees and taxes (or “rates”) necessary to fund investments. Many infrastructure projects are not only capital intensive, but also have long lead times (design, construction, etc.), where costs to taxpayers accumulate before uncertain public benefits are realized, especially considering short-term electoral timescales.

This project is a large-scale narrative analysis of local news media pertaining to proposed rate increases to fund drinking water infrastructure investments across U.S. cities. The analysis will be used to identify common topics and possible successful narrative elements in generating political support. We theoretically situate this work within the Narrative Policy Framework in policy process research and seek to identify narrative attributes, through computational text analysis, that both descriptively characterize local policy narratives in the U.S. and relate the attributes to indicators of salience and political support.

Within this project, I advance theoretical understanding of shared infrastructure political economies via computational modeling. Despite the tendency of most infrastructure systems work to silo specialities in a particular type (e.g., electricity or public transit), there are common patterns in the political economy (political and economic forces, here, cannot be separated!) of infrastructure investment that deserve higher level study. Public infrastructures are capital-intensive, high-inertia (difficult to alter), necessary for multiple types of economic activity, and responsible for universal public values that often take on the level of *rights* (e.g., one's right to drinking water). Because of this, investment decisions are incredibley complex, subjected to multiple environmental, rule-based, financial, and electoral constraints, but there are similar objectives pertaining to desired levels of fairness, reliability, and quality within uncertain biophysical and sociopolitical contexts.

The central product within this project is a political economic model of shared infrastructure systems (see figure), involving an abstract infrastructure, a resource that requires infrastructure to use, users with varying capacities, and a public infrastructure provider (PIP) responsible for raising revenue (taxes) and investing in infrastructure.

My first manuscript with the model (under review) considers three key factors in public infrastructure systems: (i) the possibility for users to invest in private infrastructure instead of public or shared infrastructure, (ii) the possibility for the PIP to raise taxes only through use of the shared system (e.g., user fees) or to also tax private infrastructure use, and (iii) electoral competition for selecting PIPs. Adding these considerations to an abstract shared infrastructure system, I derive five propositions to ground the political economy of shared infrastructure and orient future empirical studies:

1. Inequality, among users, in the ability to invest in private infrastructure decreases shared infrastructure robustness when there is a user fee revenue system.
2. Taxing private infrastructure use can increase shared infrastructure robustness if the PIP is insulated from elite capture .
3. The effect of equal political representation on shared infrastructure robustness depends on the biases and learning process of voters towards tax policy.
4. The length of electoral cycles has a parabolic relationship with shared infrastructure robustness. Increasing electoral cycle length increases robustness up to a point where further increasing the cycle length decreases robustness.
5. Increasing the ideological sensitivity of candidates decreases shared infrastructure robustness.

My doctoral research was motivated by a key gap in how urban water systems are modeled. Despite wide recognition that governance processes affect system response to change, they are rarely included in dynamic models, which can generate misleading findings about resilience. Thus, I developed a dynamical systems model, informed by workshops with Phoenix managers, that uses robust control algorithms to direct investment and ratemaking in urban water systems. I investigated the way institutions can increase costs to act (e.g., veto points) and affect the response of three Phoenix area cities to disruptions in Colorado River supply (Wiechman et al., 2024, Water Resources Research). I found that institutional costs can substantially decrease supply resilience but can benefit user rate burden. I am now leading a public administration paper (under review) to relate the institutional details governing ratemaking to the model’s institutional parameters.

While I developed the model with the Urban Water Transitions Team, I also worked with a team led by Aaron Deslatte to trace the effect of institutional designs on decision making and response to environmental changes in Phoenix and Indianapolis, IN (see Public Administration, 2025 and International Review of Public Policy, 2023). This established the empirical basis for the modeling work that I am leading in the public administration paper noted above.

Infrastructure providers, whether they are cities are regional entities, do not make decisions within their own system silo. There is always collaboration occuring between peers or across jurisdictional levels. While I was in Arizona, I saught to understand the collaborative governance processes at play in drinking water, primarily within the municipal space.

The work consisted of two parts. First, I conducted interviews with managers in the Phoenix Metro Area. I found that forums focusing on a subset of similar actors can create tight coordination and pooling of resources that spills over to other benefits (e.g., lobbying), but may negatively impact actors not included (Wiechman et al., 2023, Journal of Public Administration Research). The second part consisted of a survey to compare multiple forums in Arizona, each with differing levels of inclusion in their membership rules (e.g., one required only public municipal providers with certain water rights while anothing allowed any user that used a certain amount of water). Thus, the central question in the survey work pertained to the trade-off between inclusion and consensus in forum design. I found that members in less inclusive forums benefit from capacities that require tight coordination (e.g., lobbying) while those in more inclusive forums are more likely to perceive their region as cooperative (under review). As environmental issues continue to cross jurisdictions, this work informs the design of needed collaborative forums.