Author: PSJ Editorial Team

When sunshine gets you down: The role of transparency on public sentiment toward the Amazon HQ2 competition

by Eric Stokan, Ian G. Anson, and Nathan M. Jensen

In 2017, Amazon launched a high-profile competition to choose a location for its second headquarters (HQ2). More than 230 U.S. cities submitted bids, many offering huge incentive packages to lure the tech giant. While researchers have long studied why governments offer these economic development deals to corporations, one question remains: Does making these bids public change how people feel about them? This study uses the Amazon HQ2 contest to explore how transparency and/or secrecy shapes public sentiment and political discourse. This case study applies the Political Market Framework (PMF) to better understand exchanges between policy demanders (e.g., Amazon) and policy suppliers (e.g., local governments).

Hypotheses

The authors test four hypotheses:

  1. Expressions of sentiment in locations with private or redacted bids, rather than public bids, will be more positive than those associated with public bids.
  2. Business stakeholders will express more positive sentiment and be less influenced by transparency.
  3. Government officials will express more positive sentiment and be less influenced by transparency.
  4. Public expressions of sentiment will be more positive when bids are private or redacted, relative to public bids.

Methodology

The authors analyzed nearly 40,000 tweets about HQ2 from 2017 to 2021, which were grouped by actor type (i.e., public, media, politicians, and pro-development stakeholders) and linked to bid transparency status (i.e., whether the local bid was public, redacted, or private). Using a RoBERTa model, the authors determined the positivity and negativity of each Tweet.  Additionally, they used multivariate regression modeling to determine whether the transparency of the bid and the type of Twitter user influenced the expression of sentiment in the Tweet.

Key Findings

Less Transparency, More Optimism

Table 1 shows that Tweets from locations with private or redacted bids were significantly more positive than those from places that published full details. When billion-dollar tax subsidies are hidden, the authors explain, people tend to underestimate the costs and view the bid more optimistically–a phenomenon known as “fiscal illusion.” This finding challenges the idea that transparency always builds trust. In this case, openness and honesty about the costs and benefits provided the sunshine to accurately evaluate the true cost of the bids which was met with public backlash, in support of their hypothesis 1.

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Table 1. Bid availability by sentiment.

Business Stays Positive, No Matter What

Figure 1 reveals that business stakeholders were consistently upbeat, regardless of bid transparency status. Unlike the general public, the authors point out, pro-development actors benefit directly from these types of incentive deals, so transparency does not dampen their enthusiasm. This finding highlights a key asymmetry: while public sentiment turns negative when costs are revealed, business voices remain supportive and influential. Hypothesis 2 is thus supported.

Image Description

Figure 1. Bid transparency by actor on sentiment.

Why It Matters

This study shows that transparency in economic development deals can have unintended consequences. Instead of building trust, the authors explain, revealing the full price tag of economic development bids often sparks criticism. This finding raises tough questions for policymakers considering how to balance openness with the risk of public backlash. They take care to note that this is not a reason policymakers should avoid providing transparency, but they should carefully consider the full costs of these deals before promoting them. The authors call on researchers to look at other high-profile incentive deals and explore how transparency interacts with partisan framing and media coverage.

Read the original article in Policy Studies Journal:

Stokan, Eric, Ian Anson and Nathan M. Jensen. 2025. “When Sunshine Gets You Down: The Role of Transparency on Public Sentiment Toward the Amazon HQ2 Competition.” Policy Studies Journal 53(2): 499–523. https://doi.org/10.1111/psj.70016.

About the Authors

Eric Stokan is an Associate Professor in the Department of Political Science and Affiliate Faculty in the School of Public Policy at the University of Maryland Baltimore County (UMBC). He is the Director of the Center for Social Science Scholarship at UMBC and Co-Director of the Metropolitan Governance and Management Transitions Lab (MGMT) at the Paul H. O’Neil School of Public and Environmental Affairs at Indiana University Bloomington and is faculty affiliate to the Center for Urban Studies at Wayne State University. He serves on the editorial boards for the Urban Affairs Review and State and Local Government Review. His research examines how local governments balance environmental sustainability, economic growth, and community development. He also evaluates the social equity implications of these decisions.

Ian G. Anson is an Associate Professor in the Department of Political Science at UMBC. Dr. Anson arrived at UMBC in 2015 after matriculating from Indiana University in Bloomington, Indiana. He holds a Ph.D. in political science and a M.S. in applied statistics. Dr. Anson’s primary scholarly interests lie at the intersection of the fields of public opinion, political communication, and political behavior. His work often focuses on partisan biases, motivated reasoning, and factual misperceptions in American public opinion. Dr. Anson also contributes to the scholarship of teaching and learning (SoTL). His recent book, entitled Following the Ticker: The Political Origins and Consequences of Americans’ Stock Market Perceptions (2023, SUNY Press), examines how public opinion and political behavior have been reshaped since the 1980s by media attention to the stock market.

Nathan M. Jensen (2002, Yale Ph.D.) is a Professor in the Department of Government at the University of Texas-Austin. He only speaks in the third person for the purposes of bios. He was previously an associate professor in the Department of International Business at George Washington University (2014–2016) and associate professor in the Political Science Department at Washington University in St. Louis (2002–2014).

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Climate policy support in the UK: An interaction of worldviews and policy types

by Christian Bretter & Felix Schulz

Public support is critical for reaching net-zero goals, yet most research treats climate policies as a single, homogenous category. This approach effectively overlooks how climate policies differ in how much they reflect people’s cultural values and sense of personal freedom. This article therefore asks: Does support for climate policies in the UK depend on the interaction between policy type and cultural worldview? The authors use a UK case study with a representative sample and actual policy proposals to examine how preferences vary by both worldview and the degree of freedom offered by different policy instruments.

Hypotheses

The authors test three sets of hypotheses:

  • Hypothesis 1: Support for different policy types varies across cultural worldview groups.
  • Hypothesis 2a: Communitarian-egalitarians prefer command-and-control policies most, followed by market-based, information-based, and voluntary policies.
  • Hypothesis 2b: Individualist-hierarchists prefer voluntary policies most, followed by information-based, market-based, and command-and-control policies.
  • Hypothesis 3a: Support for command-and-control and market-based policies is strongest among communitarian-egalitarians and weakest among individualist-hierarchists.
  • Hypothesis 3b: Support for information-based and voluntary policies is strongest among individualist-hierarchists and weakest among communitarian-egalitarians.
  • Hypothesis 3c & 3d: Differences between individualist-egalitarians and communitarian-hierarchists follow similar patterns.

Methodology

The authors surveyed 1,911 UK residents using a validated cultural cognition scale to measure worldviews and support for 16 real-world decarbonization proposals grouped into four policy types:

  1. Command-and-control (strict regulations)
  2. Market-based (taxes or incentives)
  3. Information-based (education and awareness)
  4. Voluntary (encouragement without mandates)

Through a two-step statistical analysis, the authors examined whether policy support relates to a policy type—cultural worldview interaction (step 1) and the likelihood of agreeing with a policy type depending on cultural worldview (step 2).

Key Findings

Egalitarians Prefer Information Over Regulation

Figure 1 shows how cultural worldviews interact with policy types. Surprisingly, egalitarian-commutarians, who often favor strong regulation, preferred information-based policies over command-and-control. They also showed high support for voluntary and market-based measures, which indicates a broader openness to diverse policy instruments. This finding challenges the assumption that collectivist groups always want heavy-handed regulation, therefore disproving hypothesis 2a.

Image Description

Figure 1. Decarbonization policy support by cultural worldviews and policy types. The numbers show the estimated marginal means. Standard errors are shown in parentheses. N = 1911.

Individualists Favor Freedom Over Regulation

On the other hand, Figure 1 also shows that individualist-hierarchists strongly favored voluntary policies and were least supportive of strict regulations. This pattern closely aligns with cultural cognition theory, which suggests that people who value hierarchy and personal autonomy prefer policies that minimize government coercion. The finding underscores the role of individual freedom as a key determinant of climate policy preferences, thereby supporting hypothesis 2b. It also highlights the significant challenges of implementing stringent decarbonization policies among groups that value autonomy and market-driven solutions.

Why It Matters

This case study reveals that climate policy support is not just about being “for” or “against” climate action; rather, it is about whether policies align with deeper values around freedom and authority. The authors build on cultural cognition theory scholarship by providing actionable guidance for policymakers: that one-size-fits-all policy strategies do not work. Voluntary and informational measures may resonate better with some groups, while others accept market-based tools. The authors call on scholars to test these patterns in other countries, explore how mixed-policy packages influence support, and examine the role of trust and political polarization over time.

Read the original article in Policy Studies Journal:

Bretter, Christian and Felix Schulz. 2025. “Climate Policy Support in the UK: An Interaction of Worldviews and Policy Types.” Policy Studies Journal 53(2): 388–413. https://doi.org/10.1111/psj.12570.

About the Authors

Christian Bretter is a research fellow in environmental psychology at the Net-Zero Observatory at the University of Queensland. By integrating psychology and environmental behavior research, he is interested in why and when individuals are behaving or thinking in environmentally (un)friendly ways and in designing and testing interventions that create positive behavior change.

Felix Schulz is an interdisciplinary researcher at Lund University Centre for Sustainability Studies. His research draws from labor economics, sociology of work and social psychology to understand individuals and institutions’ perceptions of climate change and just transition policies.

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So You Want to Publish in a Policy Journal? Here’s What To Expect

by Gwen Arnold, Senior Associate Editor

The peer review process can be confusing and intimidating, especially for researchers who are new to academia. This blog post provides an overview of the peer review process in theory and practice, specifically in reference to the Policy Studies Journal (PSJ). Our goal is to sketch a roadmap for emerging policy scholars interested in publishing their work in academic outlets. 

What is Peer Review, and Why Do We Do It? 

The peer review process allows the academic community to ensure their work is trustworthy, rigorous, and impactful to the field. It is a team effort, as scholars rely on one another to check the quality of their research before it is shared publicly. The ultimate goal is to make our research stronger, clearer, and more valuable to academic and non-academic audiences.

Here is an overview of how the peer review process works:

  1. When a researcher feels confident about their findings, they write a paper and submit it to an academic journal for feedback. Choosing the right journal, however, is a whole topic in itself!
  2. Upon submission, the journal secures 2-4 scholars with relevant expertise to evaluate the paper. In most cases, the author does not know the identities of their reviewers. PSJ practices double-blind review, where reviewers do not know the author’s identity either. On the other hand, single-blind review allows reviewers to know the author’s identity.
  3. The reviewers closely examine the paper’s methods, ideas, and overall quality. Then, they write up their feedback and share recommendations with the journal.
  4. Based on the reviewer reports, editors decide whether to reject the paper or ask the author to revise it. If revisions are requested, the author revises their paper according to reviewer (and maybe also editor) feedback—sometimes through several rounds.

Steps in the Peer Review Process 

Step 1: Submit and await desk-reject decision

Timeline: 1-3 weeks

After submitting a paper, editors conduct a quick initial review to determine whether it fits the journal’s scope and meets basic quality standards. If it does not, they may issue a “desk rejection,” meaning the paper is declined without being sent out for peer review. This decision is typically made within a few weeks. If the paper passes this initial screening, it moves on to the peer review stage, where editors invite external reviewers to evaluate it in depth.

Step 2: Journal editors identify reviewers

Timeline: 1-3 months

Once a paper passes the initial screening, editors begin looking for scholars with the relevant expertise to review it. The author may be able to suggest potential reviewers through the journal’s submission system; if not, they can include suggestions in the cover letter. While editors are not obligated to use the recommendations, they often find them helpful. This step typically takes about a month, though sometimes longer. Since academics receive many review requests, editors must identify reviewers who are both qualified and available.

Step 3: Reviewers prepare and submit their reports

Timeline: 1-3 months

Reviewers carefully read the paper and write a report summarizing their evaluation. Ideally, they assess the rigor of the methods, the paper’s contribution to existing scholarship, its originality, and how well it aligns with the journal’s scope and aims. This process typically takes a few months. Their reports include comments for the author and a recommendation to the editors—typically suggesting whether the paper should proceed to revision or be rejected.

Step 4: Editors make a decision

Timeline: Within weeks of receiving reviewer reports (varies by outlet and editorial team workload).

After reviewing the reviewer reports, editors weigh the feedback and issue a decision. The most common outcomes are either (1) a rejection or (2) a revise and resubmit (R&R), which invites the author to address the reviewers’ comments and submit a revised paper draft. A major R&R is more common in the early stages of review and involves addressing a broad range of critiques—some straightforward, others more complex or challenging. A minor R&R suggests that small, less substantive changes are needed before the paper is ready for publication. While no R&R guarantees acceptance, a minor R&R often indicates the paper is close to meeting the journal’s standards. A less common outcome is reject and resubmit, which indicates that the paper has significant issues but shows enough potential that the editor is open to considering a substantially revised version as a new submission. Uncommon at this stage, but still possible, is that the paper receives a decision of accept (as-is) or conditional accept (accept after a few non-substantive changes). 

Reviewers usually provide separate evaluations, but their recommendations often align. When they conflict, editors rely on their own expertise and understanding of the field to weigh the feedback and make a final decision.

Step 5: Author revise and resubmit the paper (if applicable)

Timeline: 3 months for PSJ; anywhere between 1-6 months for other journals; editors are typically receptive to justified requests for extension.

After receiving an R&R decision, the author reviews the comments from reviewers and decides whether to revise the paper. Since an R&R is generally a positive signal, most authors choose to make revisions. However, if the feedback suggests changes that are too difficult or would shift the paper in an undesired direction, the author may decide to withdraw the submission.

Even if a paper is rejected, it is often worthwhile to revise based on helpful reviewer comments. Many papers are not accepted by the first journal, and incorporating constructive feedback can strengthen the work for future submissions. Keep in mind that academic communities are small—reviewers from Journal A may also be asked to review the paper at Journal B, and they may respond negatively if they see an author ignoring their earlier suggestions.

Reviewer feedback varies: some comments will be insightful and actionable, others may be less useful or difficult to implement; occasionally, a comment may be unnecessarily harsh (though this is rare and discouraged). While authors are not obligated to follow every suggestion, they should thoughtfully address most of them—especially those that could influence the reviewers’ recommendation.

When revising, use Track Changes and submit both tracked and clean versions of the manuscript. The author will also prepare a response memo detailing how they addressed each comment (or explaining why they did not do so). Reviewers will see this memo when evaluating the revised paper, so be respectful, collegial, and transparent in the responses.

Step 6: Second-round review begins (if applicable)

Timeline: As long as it takes; each round of additional review takes roughly 3-8 months, depending on author, reviewer, and editor circumstances.

After revising the paper, the author resubmits it to the journal. Editors typically invite the original reviewers to assess the revised manuscript. However, some reviewers may be unavailable or decline to participate, in which case editors may recruit new reviewers. These replacements, unfamiliar with the first version, may raise new concerns, potentially extending the review process.

This back-and-forth between author and editors/reviewers continues until all or most of the reviewers independently recommend acceptance or rejection. Remember: being at the R&R stage is not a promise of publication. At any point in this process, the reviewers or editors may identify problems that result in a rejection. Two rounds of review are fairly common; however, sometimes there are fewer rounds and other times there are more.

Step 7: Publish the paper

Timeline: As long as it takes.

Once a paper is accepted, the journal advances it to publication. Celebrate the success!

Tips

  • Rejection is quite common, regardless of the peer review stage. Don’t be discouraged! A rejection is not always about the quality of the manuscript; rather, it might just not fit the journal’s larger scope and aims. Reviewers might misunderstand the paper or provide poor-quality reviews. On the other hand, there might be real, well-founded issues that lead to rejection. Rejection offers authors an essential opportunity to improve their research and scholarship. To quote Dr. Tyler Scott, “Friends don’t let friends publish bad papers.”
  • Sometimes, a quick desk rejection can be a good thing. Editors often redirect authors to a more suitable outlet for their paper, instead of wasting time on the peer review process.
  • Be the kind of reviewer you want to experience as an author; be the kind of author you want to experience as a reviewer. The most effective peer review process involves constructive dialogue between the author and reviewers, with both parties collaborating to advance the best possible research. The process becomes much less productive when an author treats feedback as a personal attack, and reviewers focus on criticism rather than offering suggestions for improvement.
  • It is important to approach the peer review process with kindness and fairness. Editors and reviewers are real people—often colleagues you have met or will meet in the world of academia. While reviewers strive to evaluate submissions objectively, unconscious bias can still play a role if they recognize your work or recall past interactions. Editors, who do know your identity, may also form impressions based on previous email exchanges, conference encounters, or your contributions as a former reviewer. By being respectful and acting with integrity, you increase the chances of receiving it in return.

About the Author

Gwen Arnold is a professor in the Department of Environmental Science and Policy at University of California, Davis, and an affiliated faculty member at the Vincent and Elinor Ostrom Workshop in Political Theory and Policy Analysis at Indiana University, Bloomington. She also serves as a Senior Associate Editor at the Policy Studies Journal. Her research interests include policy entrepreneurship, local government decision-making, and using science in policymaking. Non-research interests mainly concern swimming, biking, and dogs.

Public enterprise pricing as redistributive policy

by David Switzer & Manuel P. Teodoro

Democratic governments provide a range of goods and services as “public enterprises” that recover all or part of their costs through user charges. Unlike commercial firms, which set prices in a competitive market, public enterprise pricing is a matter of public policy. This article explores public enterprise pricing as a redistributive policy, with governments setting prices more or less progressively depending on income inequality and larger electoral considerations.

Drawing on Cukierman and Meltzer’s (1991) taxation model, the authors analyze water utility prices in the United States to advance the theory that public enterprise pricing reflects the politics of inequality. Cukierman and Meltzer’s model suggests that income taxes are more progressive where the gap between average and median income is larger because elections incentivize politicians to redistribute government costs away from the median voter and toward higher-income citizens.

This study adapts and applies the theory to water utility pricing in the United States, showing how the same logic of citizen electoral behavior determines public enterprise pricing. Noting that larger homes and residential lots consume more water for discretionary uses like lawn irrigation, Switzer & Teodoro link income inequality to the structure of residential service prices with two hypotheses:

  1. Water utilities that serve areas with higher income inequality have more progressive price structures.
  2. The relationship between income inequality and rate progressivity is stronger for government-owned utilities than for investor-owned utilities.

The authors use regression models to evaluate the relationship between income inequality (mean-to-median ratio) and water price progressivity across 1,183 water utilities. They measure water rate progressivity using the Unit Price Ratio (UPR), which compares the average price paid per unit of water by a high-volume user to that paid by a low-volume user. A UPR greater than 1.0 indicates a progressive rate structure where high-volume users pay a higher unit price, while a UPR less than 1.0 signifies a regressive structure where high-volume users pay less per unit. This ratio provides a simple, continuous measure to assess how utility pricing policies distribute costs across different levels of water consumption.

Figure 1 plots standardized coefficients from their model to visualize the relationship between income inequality and price progressivity. The results show that the mean-to-median income ratio correlates strongly and positively with water rate progressivity. This finding suggests that governments adopt more progressive water rate structures where income inequality is higher, consistent with the political logic of redistributive policy and thus supports hypothesis 1. 

Image Description

Figure 1. Standardized coefficients from model predicting water price progressivity. Thin bars represent 95% confidence intervals.

Comparative analysis of pricing for government vs. investor-owned utilities further illustrates the political logic at work. The Cukierman-Meltzer hypothesis applies to local government water utilities, where tariff schedules are set by local elected officials. Investor-owned utilities and the regulatory commissions that set their rates are not directly accountable to voters, and so the hypothesized relationship between income inequality and pricing should be stronger where governments run water utilities.

To test that conditional relationship, Figure 2 adds an interaction term to the statistical model.. Consistent with the political logic of rate design, the results show that local income inequality correlates positively with water utility price progressive for government utilities, but not for investor-owned utilities.

Image Description

Figure 2. Estimated unit price ratios (UPR) at 30,000 gallons over income inequality by utility ownership. Dashed lines represent 95% confidence intervals.

In analyzing water utility structures as a form of redistributive policy, this article demonstrates that public enterprise pricing is shaped by democratic institutions and thereby subject to the same electoral considerations as taxation. The authors call on scholars to apply political economy models to other public enterprises where governments charge fees for service, such as hospitals, universities, and transit. Theories of comparative political economy may prove useful in understanding the politics of public enterprise management, quality, and performance.

Read the original article in Policy Studies Journal:

Switzer, David and Manuel P. Teodoro 2025. “Public Enterprise Pricing As Redistributive Policy.” Policy Studies Journal 53(2): 365–387. https://doi.org/10.1111/psj.70017.

About the Authors

David Switzer is an Associate Professor at the University of Missouri’s Truman School of Government and Public Affairs. His work focuses on how political and administrative variables shape the implementation and development of environmental policy at the local level in the United States. He received his Ph.D. in Political Science from Texas A&M University.

Manuel P. Teodoro is Robert F. & Sylvia T. Wagner Professor at the La Follette School of Public Affairs, University of Wisconsin-Madison. He studies public management and environmental policy, with an emphasis on water in the United States. He received his Ph.D. in Political Science & Public Policy at the University of Michigan.

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The Power of Policy Narratives in Electoral Autocracies: Lessons from a Pension Movement

by Elifcan Celebi & Volkan Yilmaz

Social movements rely on narratives to frame their struggles and mobilise support. How they craft these narratives is especially intriguing in electoral autocracies, where political competition exists to a degree but democratic freedoms are curtailed. Our article (Celebi & Yilmaz, 2025) builds on the Narrative Policy Framework (NPF) by analyzing the policy process within an electoral autocratic context, specifically how the Turkish pension movement generated support through policy narratives on social media. 

The Turkish pension movement (“those stuck in the pension age barrier,” or emeklilikte yaşa takılanlar (EYT) in Turkish) emerged in the mid-2010s in response to a 1999 reform that reinstated a pension age requirement, prompting some citizens who began working before the change to campaign against the rule being retroactively applied to them. Despite initial government resistance, the campaign ultimately led to the requirement’s removal in 2023 for those who had their first jobs before the 1999 reform.

One of our hypotheses was that when the government resisted removing the pension age for this group, the movement would broaden its constituency through strategic narrative framing. Figure 1 below shows that the movement tended to use narrative strategies emphasizing diffused benefits and costs. By adopting this approach, the movement extended victimhood onto a wider constituency than it actually represents. We argue that this strategy served to not only broaden the movement’s base but also to expand the scope of the conflict itself. Furthermore, it reiterates the movement’s strategic engagement with electoral competition.

Image Description

Figure 1. Number of narrative strategies used involving specific characters.

Second, the temporal analysis of narrative strategy shown in Figure 2 below shows that the movement alternated between using concentrated costs and diffused benefits strategies. When the likelihood of a positive government response was low, the movement adopted a concentrated costs strategy directed at the government. Conversely, when a positive government response seemed more likely, the movement shifted to a diffused benefits strategy to advance its goals.

Image Description

Figure 2. Trends in narrative strategies.

Our article explores the ways in which non-government actors can create and leverage impactful policy narratives in electoral autocratic contexts. When narratives highlight injustice, resonate with shared values of the population at large, and leave room for political manoeuvre, they can reshape policy debates even in regimes where the odds are stacked against citizens and social movements.

This paper builds on earlier NPF research, which remains limited in contexts beyond liberal democracies; research on social movements within these contexts is even more scarce. However, alternative policy narratives still hold power in electoral autocracies. We maintain the importance of applying the NPF to electoral autocratic contexts, highlighting three new research areas: (1) testing similar narrative strategies in other electoral autocracies and policy domains, (2) examining narratives in closed autocracies without elections, and (3) comparing the narrative content and strategies of single-issue movements with multi-issue organizations.

Read the original article in Policy Studies Journal:

Celebi, Elifcan and Volkan Yilmaz. 2025. “Narrative Power in Electoral Autocracies: The Policy Narrative Behind the Success of a Pension Movement.” Policy Studies Journal 53(2): 328–348. https://doi.org/10.1111/psj.70014.

About the Authors

Elifcan Celebi is an Assistant Professor at University College Dublin’s School of Politics and International Relations. She holds a PhD degree in Political Science from the Max Planck Institute for the Study of Societies and the University of Cologne. Her research primarily focuses on comparative politics and public policy in electoral autocracies with a particular emphasis on care, labour and digitalisation.

Volkan Yilmaz is a Lecturer in Social Policy at Ulster University, Belfast, within the School of Applied Social and Policy Sciences. He holds a PhD in Politics from the University of Leeds. He is one of the Editors-in-Chief for the Journal of Social Policy. He serves as the Coordinator of the Sociology of Social Policy and Social Welfare Research Network (RN26) of the European Sociological Association. His areas of expertise include the politics of social policy and welfare and public policy analysis with a special emphasis on health and social protection.

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A postcode lottery in education? Explaining regional inequality in multilevel systems

by Johanna Schnabel

Existing research focuses predominantly on inequality among individuals. But inequality also has a territorial dimension. This article seeks to better understand the drivers of regional inequality in education, a key area in modern knowledge-based societies. The article specifically explores the conditions that shape regional differences in student enrolment and educational attainment across 14 OECD countries: Australia, Austria, Belgium, Canada, Denmark, France, Germany, Italy, Norway, Spain, Sweden, Switzerland, the United Kingdom, and the United States. It uses Qualitative Comparative Analysis (QCA) to identify necessary and sufficient conditions of regional inequality.

The article is guided by the strong assumption in the literature on federalism, decentralization, and multilevel governance that regional authority (or, decentralization) is a key driver of regional inequality. Considering that regional authority might not be a direct cause of regional inequality, the article also explores the impact of several other factors; government spending, population size, and socioeconomic status.

More specifically, it examines the following four hypotheses:

  1. Level of Regional Authority: A high level of regional authority over educational policy is a necessary condition for a high level of regional inequality in education.
  2. Expenditures: The combination of a high level of regional authority over education policy and strong regional differences in education spending is a sufficient condition for a high level of regional inequality in education.
  3. Regional Size: The combination of a high level of regional authority over education policy and strong regional differences in population size is a sufficient condition for regional inequality in education.
  4. Socioeconomic Status: Strong regional differences in socioeconomic status are a sufficient condition for a high level of regional inequality in education.

The analysis relies on the OECD Regional Statistics database, which contains internationally comparable regional data on student enrolment and educational attainment. To measure regional authority over education, the article uses the Regional Education Authority Index developed by Garritzmann et al. (2021).

This study offers insights into how educational outcomes, and in turn opportunity and quality of life, can vary greatly across regions in any given nation (see Figures 1 and 2).

Image Description

Figure 1. Regional differences in enrolment in upper secondary education; data: OECD Regional Statistics, Statistics Norway, Statistics Sweden, Swedish National Agency for Education, Federal Statistical Office (Switzerland).

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Figure 2. Regional differences in attainment of upper secondary education; data: OECD Regional Statistics, Statistics Norway, Statistics Sweden.

Regarding the drivers of these inequalities, the analyses in the article show that regional authority over education is not a necessary condition for high regional inequality, as enrolment rates vary across regions in Austria and educational attainment varies in France despite low regional authority over education in both countries. Regional authority is also not an individually sufficient condition. However, it seems to be an important factor, as it is part of all configurations associated with high levels of regional inequality in educational attainment and student enrolment:

  • Educational Attainment: (1) A high degree of regional authority over education and strong regional spending differences. (2) A high degree of regional authority over education and strong differences in regional population size.
  • Student Enrolment: (1) A high level of regional authority over education, strong regional spending differences, and strong regional differences in population size.

Because the inclusion of Belgium might undermine the robustness of these findings due to data issues and the low number of regions, analyses were also run without Belgium. These confirmed that regional authority over education is an important factor, in combination with others.

In conclusion, the article demonstrates that regional authority over education plays an essential role in shaping educational inequality–but is not the only factor.

Read the original article in Policy Studies Journal:

Schnabel, Johanna. 2025. “A Postcode Lottery in Education? Explaining Regional Inequality in Multilevel Systems.” Policy Studies Journal 53(2): 263–284. https://doi.org/10.1111/psj.12565.

About the Author

Johanna Schnabel is a Lecturer and Researcher at the Chair of German Politics, Otto Suhr Institute of Political Science, Freie Universität Berlin. Her research largely focuses on intergovernmental relations and public policy in federal and decentralized countries. She received her Ph.D. in Political Science at the Institute of Political Studies at the University of Lausanne, Switzerland.

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Policy design and policy feedback in welfare retrenchment: A survey experiment in China

by Alex Jingwei He, Ling Zhu, and Jiwei Qian

Beyond conveying information about policy instruments, established government programs shape beliefs and expectations about policy benefits and burdens, as well as how individuals will be affected by existing policies. Social groups can then react to the information embedded in the design of policies, which, in turn, may strengthen or weaken them. The case study reported in this article explores how policy designs condition citizens’ behavioral and attitudinal responses to welfare retrenchment reforms in China. This article expands on recent policy feedback and comparative public policy literature by exploring how various policy designs, combined with individual proximity to reform, produce mixed responses. The article is guided by three hypotheses:

  1. Policy design that preserves individuals’ material self-interest will reduce opposition to welfare retrenchment reform.
  2. Policy design that improves the well-being of all in society will reduce opposition to welfare retrenchment reform.
  3. Individuals proximate to welfare retrenchment reform will exhibit stronger opposition than those with less policy proximity.

In 2020, the Chinese government engaged in a public consultation program regarding a proposed reform of the social health insurance system, which sought to reduce resources in individuals’ medical savings accounts. The authors conducted a survey experiment to gauge citizens’ responses to the proposed reforms and their hypothetical behavioral responses should the reforms go into effect. The survey participants were working and retired adults with social health insurance coverage and permanent residential status in Guangdong Province. Respondents were identified through a mature pre-existing sample and contacted via an online survey. The experiment measured socioeconomic characteristics and opposition to the healthcare reform before and after randomly receiving one of two policy design scenarios:

  1. Treatment Group 1 – Benefit-All Design: Reform will increase benefit generosity for both outpatient and inpatient care for social health insurance enrollees.
  2. Treatment Group 2 – Benefit-Family Design: Reform will allow individuals to use medical savings accounts to cover the healthcare expenses of their immediate family members.

The authors used a 1-4 Likert scale to measure opposition to the retrenchment reform. They measured demographic characteristics using a set of ordinal variables. They developed logistic regression models comparing group means with their corresponding 95% confidence intervals.

Figure 1 compares the mean opposition scores between groups before and after receiving the treatment message. Before treatment, the baseline preferences of the two groups were statistically similar. While both treatment messages reduced opposition, Treatment Group 2 (Benefit-Family Design) became more supportive of the reform compared to Treatment Group 1 (Benefit-All Design). At the same time, participants with higher educational attainment, poor health status, and large families were statistically more inclined to oppose the reform across both groups. These findings suggest that citizens prioritized preserving their material self-interest over supporting societal well-being. The authors therefore argue that sharing information on how a policy design allocates or reallocates resources garners meaningful attitudinal shifts. Therefore, this analysis supports hypotheses 1 and 2.

Figure 1. Comparing mean opposition scores before and after treatment. Vertical bars in the figure are the 95% confidence intervals.

Figure 2 compared whether the reduction of opposition to the reform varied by individuals’ proximity, specifically the frequency of medical savings account utilization. Based on the results, participants in Treatment Group 2 (Benefit-Family Design) who used their accounts at least once in the last 12 months showed significantly higher support for the reform compared to those in Treatment Group 1 (Benefit-All Design). Furthermore, individuals in Treatment Group 2 (Benefit-Family Design) who used their accounts more frequently (8-10 times) reported significantly higher opposition. These findings suggest that opposition to the reform increases as the frequency of utilization increases, which supports hypothesis 3.

Figure 2. Comparing mean opposition scores before and after treatment. Vertical bars in the figure are the 95% confidence intervals.

This article explores the significance of bridging policy design and feedback theories to better understand public response to the allocation and redistribution of material resources. While existing literature focuses on mass public opinion and participation behavior after policy adoption, this case study challenges scholars to examine citizens’ prospective assessments before policy changes as well. The authors suggest that future research should assess short-term feedback effects and long-term changes in those initial responses throughout the policy process. Unlike previous research, the findings reveal different sources of heterogeneous feedback effects other than partisanship, which vary by specific policy designs and individual experiences.

Read the original article in Policy Studies Journal:

He, Alex Jingwei, Ling Zhu and Jiwei Qian. 2025. “Policy Design and Policy Feedback in Welfare Retrenchment: A Survey Experiment in China.” Policy Studies Journal 53(2): 307–327. https://doi.org/10.1111/psj.12569.

About the Authors

Alex Jingwei is Associate Professor in the Division of Public Policy at the Hong Kong University of Science and Technology and Acting Director of the Institute for Public Policy at The Hong Kong University of Science and Technology (HKUST), where he also serves as the Co-Director of the Master of Public Policy (MPP) Program. He specializes in policy process theories, health policy and governance, and social welfare reforms. He received his PhD degree in Public Policy from the Lee Kuan Yew School of Public Policy, National University of Singapore.

Ling Zhu is Professor of Political Science at the University of Houston. Her research interests include public management, health disparities, social equity in health care access, as well as the management of local health care networks. She received her Ph.D in Political Science at Texas A&M University and joined the faculty at University of Houston.

Jiwei Qian is Senior Research Fellow at the East Asian Institute, National University of Singapore. He currently serves as the secretary of the East Asian Social Policy Research Network (EASP). His research interests lie in health economics, political economy, and development economics. He obtained his B.Sc. in computer science from Fudan University, China and Ph.D. degree in Economics from the National University of Singapore.

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The Dark Side of Policy Learning: When Learning Leads to Value Destruction

by Bishoy L. Zaki

Understanding why policy actors do what they do and how their actions influence the public have always been fundamental questions in not only public policy but also public administration and governance scholarship. To address these questions, scholars rely on various approaches. Those approaches for example include viewing policymaking and governance to be outcomes of belief updates, power struggles, crisis induced shocks, political opportunity structures, and/or the rules and traditions by which public institutions operate, among others. These different approaches provide important insights into the world of policymaking and governance, albeit of course, within certain contexts and under particular conditions.

Among these different approaches, policy learning stands out as one of the most omnipresent and fundamental. Simply put, in this approach, we analyze, dissect, and even predict why policy actors do what they do by tracing how, when, and why they learn about policy and governance problems. The potency of the policy learning lens owes to several reasons, chief of which is that it allows us to peek into the kernel of policy actors’ behavior. This is rooted in the “Homo discentis” view of the individual, which sees people as “learning beings” who are constantly collecting information and knowledge within the context of rapidly changing environments. So, in a policy learning process, individual and collective policy actors pursue and process information and knowledge about emerging problems, in an attempt to develop understandings of potential viable solutions. This is while reconciling this information and knowledge with existing cognitive and institutional structures, and biases within various contexts. This renders policy learning – at heart – a problem solving activity. Hence,  the idea of learning is normatively appealing, where all policy actors like to proclaim that their decisions are based on learning the ‘right lessons.’

Accordingly, policy learning is often hailed as a tool for helping policymakers make better policy decisions, ultimately creating value for the general public. But is this always the case? For years, existing research has done an outstanding job using a policy learning lens to analyze why and how policies change or do not change, and how it contributes to improvements in policy making and governance. However, scholarship only occasionally alludes to the unintended negative consequences of learning gone wrong. I therefore ask, is the story of learning always one of success, improvement, and glory?

My recent article explores the often-overlooked dark side of policy learning, demonstrating how learning failures can systematically lead to value destruction rather than value creation. Despite its normative appeal and origins, this article highlights that learning is not inherently positive. In fact, when misdirected, learning can also contribute to the erosion democratic values, weaken trust in institutions, and distort policy outcomes. To illustrate this, I conceptualized two main categories of learning failures that contribute to value destruction:

  1. Misdirected Learning Design Failures (non-intentional and cybernetic): These occur when policymakers genuinely attempt to solve problems but make errors in designing and undertaking the learning process. This is often facilitated by factors such as ambiguity and uncertainty underlying policy problems, or the influence of crisis shocks. 
  2. Normative Failures (intentional and deontological): These happen when policymakers intentionally manipulate learning processes for political or self-serving goals, such as justifying unpopular policies, limiting public participation, or consolidating power.

In building a conceptual framework that links policy learning to value destruction, I demonstrate how these failures negatively impact both public values (i.e., norms and principles guiding policymaking and governance) (e.g., democratic participation, accountability, transparency) and public value (i.e., added value that citizens experience and receive through public products and services) (e.g., the effectiveness, and efficiency of public offerings).

Figure 1. From policy learning governance to value destruction.

First, let’s begin by looking at Misdirected Learning Design Failures. When policymakers must address complex and/or rapidly changing issues, they may rely on poorly designed learning processes–which could eventually cause the misidentification of solutions or the development of ineffective, or even harmful, policies. For example, during the COVID-19 pandemic, the constraints of uncertainty and urgency often caused governments to undertake non-optimal learning, for example by mis-defining the policy problem at hand, excluding key stakeholders to be involved in the learning process, or misidentifying the optimal experts to learn from. These poor learning choices ultimately contributed to the loss of lives and livelihoods around the world. 

Second, in Normative failures, we see for example when policy actors attempt to deliberately limit learning to a particular group of actors that are known to legitimize predetermined political agendas, or engage in political learning to sidestep democratic decision-making norms, or exclude certain demographics from government services. These failures tend to take place when malintended policy actors strategically leverage ambiguity, complexity, and urgency to steer learning towards self-serving outcomes. 

My article ultimately challenges the assumption that learning always leads to better policies. By exposing the risks of learning failures, and theorizing failure types, it highlights the potential pitfalls of learning within the policymaking process and calls for stronger safeguards to prevent them. This is rooted in the idea that policy learning itself is a deliberately designed and governed process, where policy actors engineer how learning occurs, thus influencing its outcomes.

This serves as a crucial reminder that learning is inherently positive, and that without careful deliberate design and accountability, policy learning can just as easily contribute to value destruction as it can to value creation. To build on these theoretical developments, future research is encouraged to explore how different forms of governance (e.g., democratic vs. authoritarian) shape policy learning failures. It can also consider the increasing role of polycentricity and decentralization, and how learning therein contributes to value destruction at the subnational, national, and transnational levels.

Read the original article in Policy Studies Journal:

Zaki, Bishoy L. 2024. “ Hello Darkness My Old Friend: How Policy Learning Can Contribute to Value Destruction.” Policy Studies Journal 52(4): 907–924. https://doi.org/10.1111/psj.12566.

About the Author

Bishoy Louis Zaki is a professor of public policy and Administration at the department of Public Governance and Management at Ghent University, Belgium. His research and teaching focus on policy process theory with a focus on policy learning, and public management. He has several publications in leading international public administration and public policy journals including Public Administration Review, Policy & Society, Public Policy and Administration, the Journal of European Public Policy, Policy & Politics, Policy Design and Practice among others. He is also an editor at International Review of Public Policy journal, and a co-chair of the permanent study group on policy design and evaluation at the European Group for Public Administration (EGPA). Bishoy has over 14 years of experience in consulting, strategy, and policy where he served in different roles with several governments and international organizations worldwide. As a practitioner, Bishoy has overseen the design, implementation, and monitoring of large-scale international strategic capacity development, planning, and knowledge transfer initiatives.

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How does a focusing event shape public opinion? Natural experimental evidence from the Orlando mass shooting

by Youlang Zhang & Xinsheng Liu

Scholars of the policy process posit that focusing events often shift public attention, policy preferences, and reshape the policy agenda. The scholarship, however, has failed to fully explain how focusing events influence public opinion. Our paper aims to remedy this by analyzing the impact of one of the deadliest mass shootings in U.S. history—the 2016 Orlando nightclub attack—on public attention and attitudes toward terrorism, national security, and specific policies.

Policy process theories often assume that “focusing events” (i.e., sudden, dramatic, widely publicized incidents) can jolt public attention and lead to changes in policy preferences. Yet, empirical studies have produced mixed results. We argue that the literature falls short for two major reasons: (1) prior research neglects to properly consider the different components of the public’s reaction to focusing events and uses inconsistent dependent variables; (2) the research often relies on data collected over time without carefully considering confounders.

Figure 1. An analytic framework for public responses to a focusing event.

To address this, we propose a new framework that aims to distinguish between changes in attention to the generic policy issue (e.g., terrorism broadly), attention to sub-issues (e.g., airplane safety), support for a general policy action (e.g., antiterrorism investment), and support for specific policy actions (e.g., gun control). Using this framework, we assert the following hypotheses:

  • H1: The Orlando mass shooting increases overall attention to the generic terrorism and security issue (i.e., “splash effect).
  • H2: The less relevant a specific terrorism issue is, the smaller the positive impact of the Orlando mass shooting on public attention to it (i.e., “limited ripple effect”).
  • H3: The less relevant a specific terrorism issue is, the smaller the positive impact of the Orlando mass shooting on public support for increased government investment in preventing terrorism decreases (i.e., “limited ripple effect”).
  • H4: The Orlando mass shooting has a negligible impact on public support for specific preventive government actions (e.g., gun control or immigration restrictions) (i.e., “deep water null effect”).

To test these predictions, we used a natural experimental design. A public opinion survey funded by Texas A&M University was fortuitously being conducted when the Orlando attack occurred on June 12, 2016. This allowed us to compare responses from 416 participants surveyed before the attack with 284 surveyed after. Our analysis provided support for all four of our hypotheses, providing empirical evidence of the “splash effect,” “limited ripple effect,” and “deep-water null effect.” Put plainly, this focusing event increased attention to the general issue of terrorism and heightened support for a general policy action (i.e., increased government counterterrorism spending), but it did not alter concerns for other terror-related acts that were less relevant to the Orlando shooting.

 Figure 2. The effect of the Orlando mass shooting on respondents’ concerns about specific terrorism issues.

Our study reveals that while focusing events can heighten public concern and support for broad policy responses, they rarely shift entrenched views on controversial solutions. This “deep water null effect” has major implications: even horrific events may not translate into support for specific reforms, especially in a polarized political climate.

Read the original article in Policy Studies Journal:

Zhang, Youlang and Xinsheng Liu. 2025. “ How Does a Focusing Event Shape Public Opinion? Natural Experimental Evidence From the Orlando Mass Shooting.” Policy Studies Journal 53(2): 463-479. https://doi.org/10.1111/psj.12543.

About the Authors

Youlang Zhang is a Professor in the School of Public Administration and Policy and a Research Scientist at the Capital Development and Governance Institute, Renmin University of China. He is also a Research Fellow with the Institute for Science, Technology and Public Policy, the Bush School of Government and Public Service, Texas A&M University. His research interests include policy process, citizen-state interaction, and government management. 

Xinsheng Liu is a Senior Research Scholar and Research Scientist of the Institute for Science, Technology and Public Policy, Bush School of Government and Public Service, Texas A&M University. His research interests include public policy process, policy agenda, public opinion and participation, and comparative public management and governance.

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The interactive effects of policies: Insights for policy feedback theory from a qualitative study on homelessness

by Anna Kopec

Existing policy feedback literature on participation examines how policy designs shape political behavior and argues that policies can encourage some people to participate whilst discouraging others. This prompts the inquiry: how do the effects of policy design characteristics interact? How might the positive effects of one element of a policy, for example, interact with the negative effects of another to influence participation of a marginalized group? How might multiple negative or positive effects influence participation? To explore these complex effects, this study compares how homelessness policies affect political engagement in Melbourne, Australia, and Toronto, Canada.

Drawing on 118 qualitative interviews with individuals experiencing homelessness, service providers, and policymakers, this comparative study explores how the effects of policy design characteristics (i.e., distribution of benefit, generosity, eligibility, visibility, delivery design, and integration) work together to either mobilize or discourage political engagement. Table 1 defines these terms below:

Table 1. Policy design characteristic operationalization.

Figure 1 demonstrates how the interaction of multiple policies, through their design characteristics, influences political participation. These effects are shaped by the resources allocated, the signals policies send about individuals’ roles in society, and their broader impact on institutional capacity to facilitate engagement.

Figure 1. Interactive effects of policy characteristics on participation.

The qualitative interview data reveals diverse service access among participants, highlighting key variations in characteristics, particularly visibility, delivery, and integration. Table 2 outlines the policy areas by city and sector, detailing policy characteristics and their effects on engagement as reported by participants. While both cities have many negative policy effects, Melbourne’s housing and health policies showed more positive impacts, particularly in integration, visibility, and delivery.

Table 2. Policy design characteristics of policies utilized by the sample of participants and effects on participation.

Notably, Table 3 illustrates that individuals experiencing homelessness actively engage in various efforts to drive change. While 56-64% of participants reported voting in their last federal election, over 90% engaged in actions such as peer work, providing organizational feedback, and joining advisory groups.

Table 3. Participation according to venues in Melbourne and Toronto.

The way in which different policy design characteristics interact can either amplify exclusion or help counteract it, depending on how services are structured and delivered. For example, integrated service delivery can moderate the negative effects of means-tested programs with strict eligibility rules. In Melbourne, social workers traveling to service centers helped reduce barriers related to eligibility and stigma. In contrast, Toronto’s lack of visibility and integration often left participants feeling isolated.

Policy feedback scholars must pay closer attention to the lived experiences of marginalized populations. These perspectives reveal how policy design and the interplay of its characteristics directly shape political participation. Without this understanding, we risk overlooking the conditions under which participation influences policy or the ways we might create spaces that meaningfully support civic engagement.

This research highlights how policies are structured and delivered, not just how their content affects democratic engagement. Integrated, visible services can empower marginalized individuals to engage politically, even amid social and economic instability.

For marginalized and targeted populations, policy design can dictate their civic participation and relationship with the state. Too often, policies reinforce exclusion, further distancing individuals from decisions that directly impact their lives. By examining where and how these populations participate, we gain critical insight into whether their voices are meaningfully reflected in future policymaking.

Read the original article in Policy Studies Journal:

Kopec, Anna. 2025. “The Interactive Effects of Policies: Insights For Policy Feedback Theory From a Qualitative Study on Homelessness.” Policy Studies Journal 53(2): 243–262. https://doi.org/10.1111/psj.12532.

About the Author

Anna Kopec is an Associate Professor at the School of Public Policy at Carleton University. Her research agenda examines the relationship between political participation and public policy among marginalized populations in Western welfare states. How do policy designs influence the political agency of vulnerable groups, and how in turn do such groups participate to bring about changes to the policies and systems they interact with? This comparative work focuses on populations experiencing homelessness. A secondary research agenda examines intersectionality and homelessness, with a consideration of how policies and services individuals access influence how certain communities participate.

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