Category: Research Resources

Balancing the Scales: Evaluating North Carolina’s Local Sales Tax Redistribution Policy Questions for Practitioners

By Jackson Dille and Whitney Afonso

Questions for Practitioners

  • How is the shift towards sales taxes affecting fiscal equity across North Carolina counties?
  • How has North Carolina’s local sales tax redistribution policy impacted the difference in per capita sales tax dollars between urban and rural counties?
  • What lessons does North Carolina’s experience offer for designing equitable fiscal policies in regions with stark urban-rural divides?

Introduction

Local sales taxes (LSTs) have become an increasingly important revenue source for local governments, growing from 7% of total local tax revenues in 1977 to 13% by 2020, with collections surpassing $100 billion. Their popularity stems from their flexibility, political palatability, and ability to diversify revenue streams while offering property tax relief and shifting the tax burden to non-residents. However, the benefits are unevenly distributed, as some jurisdictions experience tax “exportation”—benefiting from non-resident spending—while others suffer from “tax leakage” when residents shop elsewhere. These dynamics have led to significant disparities in sales tax revenues between retail-rich and retail-poor communities.

To address these inequities, North Carolina implemented a redistribution policy in 2017 that pooled a portion of local sales tax revenue at the state level and redistributed it based on a formula designed to reflect both place of sale and population. Then-Senate Majority Leader Harry Brown described the initiative as a way to ensure “all North Carolina counties benefit from tax dollars their own citizens pay.” While the motivation behind the policy is clear, its real-world impact had not been evaluated until recently. The study reviewed here is the first to assess whether this kind of policy meaningfully reduces fiscal inequities tied to sales tax revenue and whether it is well-designed to adapt over time.

Background of LST in North Carolina

In North Carolina, LSTs represent the second-largest source of revenue for counties, trailing only property taxes. However, not all counties have equal ability to generate this revenue. Tax leakage—when residents shop in neighboring counties, particularly from rural to urban areas—creates fiscal challenges for rural communities lacking commercial infrastructure. Urban counties, with more retail activity and larger visitor flows, benefit disproportionately. As a result, rural counties often face lower per capita LST collections and greater challenges funding essential services like education and public safety.

To correct this imbalance, the General Assembly enacted a reform in FY2017 that aimed to redistribute part of the LST revenue more equitably. Under this system, each county contributes a share of its LST collections into a state-managed pool. Revenues from Articles 39, 40, and 42 are included, and then redistributed to counties based on fixed allocation percentages derived from a projected 50–50 split between point-of-sale and per capita distributions. This policy sought to strengthen counties with weaker sales tax bases—typically rural areas—by supplementing their revenue and mitigating the impact of tax leakage. While well-intentioned, the fixed nature of these allocation percentages and their lack of alignment with actual county contributions have introduced challenges in implementation.

Impact of the Revenue Sharing Pool

To evaluate the policy’s effectiveness, researchers used financial data from the North Carolina Department of Revenue and categorized counties as urban or rural. In theory, rural counties with smaller LST bases would benefit the most, while urban counties with larger bases would contribute more than they receive. However, the actual outcomes proved more complex. In FY2017, approximately 75% of rural counties and 50% of urban counties were net beneficiaries. Some rural counties were net contributors, while some urban counties gained more than they paid in. This divergence is partially due to the imperfect alignment between rural/urban designations and actual tax base size. Some rural counties, despite their classification, had relatively strong retail sectors, and some urban counties had weaker ones.

A central issue is that the policy’s allocation formula does not factor in each county’s contribution to the pool. Instead, it relies on fixed distribution percentages based on projections from 2015. As a result, counties with higher contributions may not see proportional returns, and recipient counties may receive less than their level of need or contribution would suggest. In fact, 12 of the 33 counties with net negative revenues in FY2017 received less revenue than they contributed even though they were intended to be net recipients..

Still, the policy’s redistributive effect remains evident, especially when measured relative to per capita LST revenue. Urban counties with high sales tax capacity per capita experienced modest losses—median losses around 2.9%—while rural counties with low capacity gained significantly, with some seeing increases as high as 58%. Comparing actual revenue to a hypothetical 50–50 target also revealed that, post-policy, the gap between actual and intended revenue narrowed, particularly among rural counties. Over time, however, these gains have started to erode. As certain counties continue to grow economically, disparities in per capita LST revenue have begun to widen again, reflecting the policy’s limited adaptability. Figure 1 shows difference in LST dollars per capita across urban and rural counties over time.

Figure 1: Per Capita Dollar Difference Between Urban and Rural Counties

Source: Afonso et al. 2024

Conclusion

North Carolina’s LST redistribution policy represents a thoughtful effort to reduce fiscal disparities and address the challenge of tax leakage between counties. Many rural jurisdictions have meaningfully benefited, and the policy has helped align actual revenues more closely with a population-adjusted benchmark. At the same time, certain design features may limit the policy’s long-term effectiveness. Notably, the use of fixed allocation percentages—based on projections made in 2015—does not reflect counties’ actual contributions to the revenue pool or shifts in local economic conditions over time.

While the policy successfully narrowed revenue disparities in its early years, its static structure may benefit from future refinements to sustain that progress. Updating allocation percentages periodically, incorporating contributions into the formula, or adopting a broader definition of fiscal capacity (including other local revenue sources like property taxes or fees) could enhance both equity and responsiveness. North Carolina’s experience offers important insights for other states pursuing similar reforms: effective revenue-sharing policies can provide meaningful support to communities with lower fiscal capacity, but they are most impactful when designed to evolve alongside changing economic and demographic landscapes.

Finally, it is also critical to consider the cost to the counties that are the beneficiaries of tax leakage (those that import tax dollars) from those non-resident visitors.  Those who commute, travel, and shop in other jurisdictions also consume services and benefit from those public dollars.  As the state (and others) continue to consider what is fair, perhaps measuring the difference between the cost incurred by the counties that import sales tax dollars and the amount that they receive in surplus dollars is a worthwhile exercise.  Ultimately, careful consideration of policy goals and their impacts is warranted.  In the case of GS 105-524, the state set out to correct for tax leakage and they were largely successful in achieving that goal.

Full article: Afonso, Whitney, Alex Combs, and Christian Buerger. “Plugging the Tax Leak: An Analysis of North Carolina’s Local Sales Tax Redistribution Policy.” State and Local Government Review 56.1 (2024): 76-90.

 

Designing Public Budgeting Simulations: Leveraging Behavioral Insights to Enhance Engagement and Decision-Making

By Jackson Dille

Questions for Practitioners

  • How does the starting point of a budget simulation shape how participants engage with the budget making process?
  • What role can simple design elements—such as prompts, visual indicators, or default values—play in encouraging more realistic or legally compliant budget outcomes?
  • Is the purpose of your public engagement tool to collect preferences or actively educate participants about legal and fiscal constraints?

Introduction

Public budgeting might not seem like the most obvious place for behavioral economics, but it turns out to be a fertile ground for testing how people make decisions. As more governments turn to online budget simulations to engage residents, researchers are uncovering just how much small design choices—like where a budget starts or what kind of feedback users receive—can shape the public’s fiscal preferences. Despite increasing interest in choice architecture and nudging across the public sector, the literature on behavioral budgeting still lags behind practice. Recent work by Afonso and Mohr seeks to close that gap by exploring how to improve simulation outcomes without taking away users’ autonomy. The research builds on the NUDGES framework by Thaler and Sunstein, which identifies six key elements of effective choice design, from incentives to default settings to error expectations.

Research Design

To test how budget simulation design influences user behavior, researchers conducted an experiment using the Balancing Act budget tool. Participants interacted with a simulation modeled on a real municipal budget. They were randomly assigned to one of four conditions: beginning with a budget surplus or deficit, and either receiving or not receiving an informational prompt before submission.

In each scenario, participants had to adjust spending or revenue levels to balance the city’s budget, which was either pre-loaded with a $72.8 million surplus or deficit, indicated by a green or red “balance bar.” In surplus conditions, no action was required to complete the simulation—highlighting the potential power of defaults. However, for those in the ending surplus treatment group, a prompt reminded participants that North Carolina law requires a balanced budget, encouraging them to revise large surpluses. Participants could still submit unbalanced budgets, preserving autonomy. Despite the younger, more female, and more diverse demographic of the sample compared to the general population, there were no significant differences across treatment groups, allowing researchers to credibly test the influence of the experimental conditions using OLS regression.

Findings

The study revealed several actionable insights for local governments designing or deploying budget simulations:

  • Defaults drive decisions: Participants who started the simulation with a surplus tended to keep it, often ending with unrealistic surplus levels. This behavior likely stemmed from status quo bias or a perception that no changes were necessary. In contrast, starting with a deficit prompted more active engagement and larger budget adjustments.
  • Nudges increase engagement: The ending surplus prompt led to significantly more changes, especially to revenue categories, and helped reduce extreme surpluses. Participants did not alter spending categories as much—suggesting a stronger preference to maintain existing service levels. For practitioners, this highlights the power of targeted feedback to align participant behavior with legal or fiscal expectations without restricting choice.
  • Design for participation, not just compliance: Participants in surplus conditions made fewer and smaller changes overall. This suggests that simulations starting “in balance” may appear complete or safe, discouraging deeper participation. To encourage meaningful input, starting with a modest deficit may better prompt users to consider trade-offs—particularly when paired with a legally grounded prompt at the end.
  • Balance autonomy with guidance: While nudges can steer behavior, overly strong interventions may feel like instructions rather than choices, potentially undermining the quality of feedback. Practitioners must strike the right tone—providing enough context and encouragement to support better decisions without dictating outcomes.

Overall, these findings offer concrete strategies for enhancing the quality of engagement in public budget simulations. Whether the goal is education, consultation, or co-creation, governments can design more effective tools by leveraging behavioral insights and carefully structuring participant experiences.

Conclusion

Choice architecture is more than just simplifying heuristics or offering incentives—it’s a strategic framework for guiding behavior in complex decision environments like public budgeting. The NUDGES framework encourages practitioners to anticipate errors, design smart defaults, and offer meaningful feedback to support thoughtful, welfare-enhancing choices.

Crucially, public budgeting operates within regulatory and legal boundaries, meaning nudges alone may not always suffice. In such cases, “budges”—behaviorally informed interventions with more directive power—may be appropriate to ensure compliance while still capturing authentic public input. This study illustrates how simulations can honor both behavioral realism and institutional constraints.

For public administrators, this means designing tools that do more than just collect preferences—they should promote engagement, reduce error, and deliver legally viable and practically useful insights. The goal is to use digital simulations not just as feedback mechanisms, but as bridges between citizen preferences and responsible public finance.

 

Full article: Afonso, Whitney, and Zachary Mohr. “More than a wink and a nudge: examining the choice architecture of online government budget simulations.” Behavioural Public Policy (2024): 1-17.

Citizen Engagement Tools: Online Budget Simulations

Blog post by Whitney Afonso, Zach Mohr, and Scott Powell

Questions for Practitioners:

  • When (as in time of year) should you engage citizens in budget simulations?
  • Can I expect trust in our government to increase if we engage citizens in budget simulations?
  • How do starting budget conditions affect revenue and expenditure preferences, and what role do deficits, surpluses, and balanced conditions play in shaping these preferences?
  • In what ways can local government practitioners enhance the design of budget simulations based on the findings, and what considerations should they take into account when implementing such simulations to engage citizens in the budget process?

 

Introduction

In the rapidly evolving landscape of budget engagement, online budget simulations have gained prominence. This blog addresses the increasing use of these simulations, particularly in local governments, and emphasizes the need for a thoughtful evaluation of design choices. While previous studies focused on federal budgets, this blog delves into municipal budget simulations, posing the question: does beginning the simulation in balance, deficit, or surplus affect respondents’ engagement and budget preferences?

The blog post summarizes an article published in the journal Public Budgeting & Finance.  We also discuss findings that were not presented in the article that suggests that starting the simulations in deficit really does not affect trust. The blog is useful to anyone that is looking to think more deeply about how to set up an online budget simulation.  They may also be useful to those that want to do experiments in budget and finance settings, which have some important practical challenges.

The findings from the research are highly relevant to local government budget practitioners who wish to engage citizen to participate in the budget process. As budgeting preferences are shown to be a function of design, budgeteers should think critically about the design of their simulations.  Specifically, we think that starting from a small budget deficit position, such as the level of inflation, may be the best way to practically get more engagement with the budget simulation, but this may influence the budget outcomes from the simulation.  At any rate, a choice on how to start the simulation must be made.

Summary of the Article

While traditional in-person engagement has been the norm, the shift to online methods, accelerated by the COVID-19 pandemic, brings benefits such as broad accessibility to the simulation and speed to complete them (although this may also be a bit of a problem).  The article first traces the evolution of online budget simulations from national to local levels, emphasizing their growth in popularity and recognition as a best practice in public engagement, with examples of awards received by local governments. The newer “dynamic” simulations, allowing simultaneous adjustments to revenue and expenditures, are highlighted for their widespread adoption and relevance for both local governments and scholars interested in testing budget engagement theories.

Behavioral Model and Hypotheses

In the article, we discuss the impact of information presentation in budget simulations on participant engagement and budgetary preferences. Referring to previous studies, we establish that the way information is presented, especially concerning cost and performance, influences budget preferences. The model proposed suggests that starting a simulation with different budgetary conditions affects participant engagement and preferences. Unlike prior assumptions of intrinsic motivation, this research explores how the simulation structure influences engagement levels, potentially influencing other perceptions like trust in the government, which we discuss more below.

Research Design and Analysis

Participants engaged in the simulation as part of an online survey experiment. The study aimed to understand how starting conditions (balanced, a 5% deficit, or a 5% surplus) influenced participant engagement, preferences, and perceptions.

Due to local leaders’ concerns about public perception, the simulation had to be conducted in a controlled lab environment rather than in the field. This field-in-lab experiment involved randomly assigning participants to different budgetary conditions, mirroring those of a nearby local government. The participants were younger and more diverse than the general population, being students from the university, thus the specific policy preferences indicated in the simulation are not generalizable to the population.

The analysis focused on three main aspects: level of engagement, budgetary preferences, and final budgetary balance. Contrary to expectations, the time spent on the simulation did not significantly differ between deficit, surplus, and balanced conditions. However, the deficit treatment significantly reduced the number of participants completing the simulation, indicating potential difficulties. The deficit treatment increased the number of changes made to both expenditures and revenues, while the surplus treatment primarily influenced changes in revenues.

Starting conditions significantly affected both revenues and expenditures. Participants tended to maintain taxes when starting in balance, reduce them in surplus, and either maintain or increase them in deficit. Expenditure changes were idiosyncratic, with deficits leading to more significant cuts.

The results partially supported hypotheses related to the size of changes and the final budgetary balance. Participants starting in deficit made larger changes to expenditures, but the final balance was only significantly influenced by the surplus condition, aligning with anchoring and status quo bias. The study sheds light on how starting conditions in budget simulations impact participant behavior, providing valuable insights for both academic research and practical applications in local government budget engagement.

Discussion

The experiment demonstrates that different starting conditions significantly impact engagement and budgetary preferences. Two out of three engagement outcomes were influenced by starting conditions, indicating their substantial role in shaping participant behavior. The deficit condition particularly amplified cuts to services like the police, suggesting that unpopular services might be more vulnerable during financial downturns. Despite the expected increase in time spent on the simulation due to varied starting conditions, time was not significantly affected, potentially influenced by the participants’ choice to avoid difficult tasks.

The deficit condition reduced the likelihood of participants completing the simulation, highlighting cognitive limitations and avoidance of challenging situations. This finding has practical implications for practitioners, emphasizing the trade-off between obtaining more information through deficit starting conditions and the decrease in completions. Future research could explore predictors of completion, such as math literacy, to enhance engagement. Additionally, practitioners may need to consider when to run simulations, as participants’ responses could vary depending on the budget preparation cycle.

Observations of “chunking” behavior in deficit conditions, where participants made larger changes, suggest a dynamic relationship between engagement and budgetary preferences. The study encourages further behavioral theory development in the context of budget simulations.

The research contributes to understanding individual psychological processes like anchoring, loss aversion, and decisional inertia in budget engagement, offering insights for practitioners on designing effective simulations. Practical implications include adjusting starting conditions based on desired outcomes and considering the impact of performance information on budget engagement. The study advocates for more field experiments and “field-in-lab” experiments to refine the choice architecture of politically sensitive topics like budget simulations, enhancing the usability and effectiveness of engagement efforts. Overall, the findings underscore the importance of behaviorally informed changes in shaping public engagement and preferences in budget-related decision-making.

The Simulation’s Effect on Trust

One of the things that was particularly important to our local government partner that we were helping to test the effect of starting position was to make sure that this did not have an effect on citizen’s trust.  The city had carefully maintained its well earned reputation for being a good steward of taxpayers money and it did not want to see that reputation tarnished because citizens’ were asked to do a budget simulation that started in deficit.  This was a major reason that we ran the simulation on students where we could properly debrief them that the scenario was not real and we took out all mentions to this specific city in the simulation.

We also saw that it was an opportunity to test the effect of the simulation and the simulation starting position on the outcome of trust in local government.  So, we actually designed an experiment within the experiment that would look at the effect of seeing no simulation relative to seeing a simulation.  We also are able to see if the effect of the treatment of balance, deficit, and surplus had an effect on trust.  So, the experiment participants were first given a series of demographic questions and a question about trust in different levels in government, they were then randomly assigned into one of the four treatments shown in figure 1 and were asked to complete the simulation, and then the participants were asked about their level of trust in government again.  So, this can be treated as either a between subject or pre-post design.

Figure 1: The four treatment conditions

 

It really doesn’t matter, though, how we analyze the data because there was no statistically significant effect of the simulation on trust.  There was likewise no effect between the different starting treatments on the levels of trust between the treatments or the change in the trust.  Put simply, starting a budget in deficit is not going to influence the level of trust – at least as we measured it.  One of the things that we are doing with future surveys is looking at whether the simulations had effects on other perceptions about the government.

Conclusion

The results of the published study and the results that we are presenting here suggest that there are only minimal negative effects of starting a budget in deficit.  Most importantly it may modestly reduce the number of completions.  However, starting the budget simulation in a small deficit – such as the current rate of inflation – may lead the respondents that complete the budget to adjust more types of revenue and expenditure and provide budgeteers with more realistic information about how citizens would balance the budget.  Starting the budget simulation in deficit is also found not to reduce trust.  Future research is ongoing about the responses to different levels of deficit (2.5%, 5%, 7.5% or 10%) and effects on other perceptual outcomes.  We would invite the budget community to propose other types of experiments that they would like to see researchers address and the research community should continue to work with local governments to test their most promising behavioral changes to these simulations.

 

Citation to journal article:

Mohr, Zach, and Whitney Afonso. “Budget starting position matters: A “field‐in‐lab” experiment testing simulation engagement and budgetary preferences.” Public Budgeting & Finance (2023).

One Working Capital Management Strategic Tool: Interfund Transfers

By Michelle Lofton and Mikhail Ivonchyk

Working capital management is a managerial strategy that monitors and uses current assets (e.g., cash, accounts receivable, and inventory) and current liabilities (e.g., accounts payable and notes payable) to ensure smooth operations. The purpose is to maintain cash flows for liquidity to meet short-term operating expenses and obligations. This integral part of sound financial management uses a variety of strategic tools to manage cash flows. These can include the use of unrestricted cash, savings, interfund borrowing, interfund transfers, delaying payments, receivables, a line of credit, direct lending arraignments, and short-term debt. Yet, little academic research on governments has evaluated the process for selecting different tools, the policies governments have in place to implement them, and the consequences of using one tool over another.

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Social Impact Bonds: A Magic Tool for Financing Innovation?

Have you heard about social impact bonds (SIBs) yet?  If not there are a lot of resources and discussion out there regarding this magical fix of financial woes of government.  While many have viewed these as too good of an opportunity to pass up (for example, see here and here), others have been slightly more skeptical.

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A New Collection Available from an Old Resource

In this post, I wanted to share that the School of Government’s Knapp Library has a new collection for North Carolina’s assessment community. This is a short post because I anticipate most of the reading will occur as you explore the links in this post. In January, IAAO announced the availability of their new collection of informational books on assessment, Apendium.

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Do cities and counties circumvent state policy? One potential mechanism.

Cities and counties are constructs of their respective states. Counties are almost always created by state constitutional decree. Cities are municipal corporations created by state legislative action. Regardless of the method of creation, states exercise significant control over what cities and counties can and cannot do. From the taxes levied to debt issuances to services that can or cannot be provided, the state determines the role of local governments within its borders. States have been pre-empting local policies at an increasing rate. The National League of Cities has documented a number of these actions. Popular targets are restrictions locally imposed minimum wages (24 states), paid leave (18 states), and public provision of broadband internet (17 states). Of these three, North Carolina is included in all. There are many other areas where states have been pre-empting local actions. This top-down view suggests that local governments have little ability to chart their own course. However, this isn’t quite right. There are many ways that cities and counties push back against state policy. In the news now, Sanctuary Cities in Texas are pushing back against new laws restricting their actions. This is a highly visible example; however, cities and counties often have other options that are less visible.

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North Carolina’s County and Municipal Fiscal Analysis Tool: Research Review

Have you ever used the County and Municipal Fiscal Analysis tool that is housed on Treasurer’s website?  It allows municipalities and counties in the state to see how they are doing with regard to financial condition and compare their performance to peers.  It has recently become the focus of new research coming from colleagues at the University of South Dakota and Indiana University.  Ed Gerrish and Luke Spreen presented their research on our benchmarking tool earlier this month at the Public Management Research Conference and it is forthcoming at the Journal of Public Administration Research and Theory.  In this Research Review I am going to discuss their research and pull a few findings that are especially notable for those of you that work in budgeting and finance.

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Crowdsourcing for Local Governments: Research Review

Research Review is a place for me to bring you academic research that I think might be of interest or relevant to you all.  It is not necessarily the Cliff notes of the paper, but it will present some key findings or insights from the paper.

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Welcome!

Benjamin Frankin, (1706-1790) , North American printer, publisher, writer, scientist, inventor and statesman. Source: Wkipedia

Our new Constitution is now established, and has an appearance that promises permanency; but in this world nothing can be said to be certain, except death and taxes.

Benjamin Franklin, in a letter to Jean-Baptiste Leroy, 1789

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