Free Plastic Bags Are Back—What Happens When Green Policies Get Repealed?

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A recent Journal of Marketing Research article sheds light on how consumers respond to green policy repeals. The researchers examined plastic bag bans and fees in Austin and Dallas, Texas. These policies aimed to reduce single-use plastic bag consumption at checkout. As reported in previous studies, the authors expected that when consumers like Maria could no longer reuse grocery bags as trash can liners, trash bag sales would surge—a negative spillover. In Austin and Dallas, the negative spillovers were 68% and 71%, respectively—a significant increase over baseline.

But could these spillover behaviors persist as “carryovers” even after the policy disappears? The study provides the first systematic analysis of post-repeal carryover effects and develops a break-even framework to assess whether a repealed policy leaves us worse off than if the policy had never been implemented. The authors find that after the repeal, Austin’s trash bag sales stayed elevated—a persistent carryover effect—while Dallas reverted to baseline more rapidly, though still over the course of 13 months.

Strikingly, behavioral stickiness appears to depend on policy duration: Austin’s five-year ban may have created much stronger habits than Dallas’s five-month fee. A break-even analysis shows that consumers need to save only one plastic bag every five trips in Austin, or every seven trips in Dallas, to offset the trash bag spillover. These are remarkably modest thresholds, suggesting that even with negative spillovers and carryovers, the policies probably deliver net environmental benefits, with repeals leaving plastic use no worse than before the policy was implemented.

How to Evaluate the Net Effects of a Policy

A key challenge in evaluating the net effect of a policy—whether during implementation, when spillovers emerge, or after repeal, when those spillovers may persist as carryovers—is that policymakers often cannot observe all relevant behaviors. In this study, the authors observe changes in trash bag purchases but have no data on grocery bag usage at checkout. To address this limitation, the authors introduce a break-even evaluation tool that translates incremental trash bag use induced by the policy and its persistence after repeal into intuitive behavioral thresholds for assessing net effects. The approach, illustrated below, helps analyze if a policy delivers net benefits even with imperfect implementation or eventual repeal.

To understand how to apply these insights in practice, we spoke with three of the article’s authors: Dinesh Puranam, Sungjin Kim, and Jihoon Hong. They shared insights into what inspired their research, practical guidance for policymakers, and how their framework can be adapted to different policy contexts.

Inspiration: What inspired you to study policy repeals rather than just policy implementation? Was there any observation that made you realize carryover effects were an important gap in the literature?

A: While we all shared a common interest in understanding how green policies affect consumer and firm behaviors, several interesting aspects motivated us to study repeals. In previous work on soda tax policy implementation and repeal, Dr. Kim found that retailers passed through more than the full tax amount to consumers. More interestingly, even after the tax was repealed, those higher prices lingered, and retailers didn’t immediately adjust. This price stickiness made us realize that repeal of policies is not simply the reverse of implementation—it can create lingering effects of its own. So we naturally wondered, if a repeal results in retailer inertia, could consumers also exhibit similar behaviors?

In reviewing plastic policies across the US, we discovered almost 100 green policies were repealed between 2016 and 2020. It turns out, repeals are very common. Every administration, across federal, state, and local jurisdiction levels, terminates or redirects resources away from some policies. Yet the literature has focused heavily on policy implementations, and it was theoretically unclear whether carryovers would manifest after repeal, and if they did, could we be worse off than before the policy was implemented? This question has profound implications. Physicians follow the principle “do no harm”—we wondered whether policy cycles could inadvertently violate a similar principle for policymakers.

The marketing discipline is especially well equipped to address this type of empirical question, as it can draw on rich consumer theories, state-of-the-art methods, and rich transaction data. We also realized that while there are many papers on health and financial behavior, there aren’t many on pro-environmental behavior empirically. Plastic bag regulation offered an ideal context because it relates to daily shopping behavior. These aspects persuaded us that there was an opportunity to make a meaningful contribution.

Policy Design Advice: When policymakers design a policy targeting one behavior, how should they think about potential spillovers? Is there a step-by-step process, like first identifying substitute products, then considering consumer motivations, then looking at timing? What’s your recommended framework for anticipating non-targeted behaviors?

A: We would hesitate to call it a formal framework. Every policy is different, and individual implementations vary considerably in scope (regional, local, state, or federal) and stickiness.

However, there are several key considerations. First, map substitutes and secondary users/uses. It’s crucial to understand how the product targeted by the policy is actually used in daily life, which reveals what consumers will turn to when it’s restricted. For example, if you ban flavored milk in schools, kids may switch to other sugar-sweetened beverages. Our analysis across different trash bag sizes confirmed this principle: small bags (4 gallons) showed significant spillover effects as close substitutes, medium bags showed weaker patterns, while tall and large bags showed no effects at all. This understanding can come from industry surveys, not just academic research. Second, consider that behavioral inertia matters for repeals. Once consumers adopt new behaviors in response to a policy, those habits can persist even after the policy is repealed. Critically, how long the policy is in place may determine how sticky these habits become. Third, explicitly consider the possibility of repeal. This paper’s main contribution is highlighting the need to account for potential repeals. Develop break-even analysis and scenario analysis to understand boundary conditions, following the “do no harm” principle. The break-even approach translates abstract policy goals into concrete metrics: “one bag every five trips” is something consumers, retailers, and monitors can actually observe and track. Fourth, consider pilots and complementary strategies. Where possible, we advocate for small-scale randomized trials in several cities before wider adoption, allowing observation of actual substitution patterns and behavioral responses. This can also help inform decisions about policy type (fee versus ban).  Overall, it’s about being more thorough about considering the possibility of repeal, which hasn’t been on the radar for most policy discussions.

Positive vs. Negative Spillover Drivers: As you mentioned, non-targeted behavior can be either positive or negative. What would be the potential drivers for each separately? And what would be the implications for policymakers based on those potential drivers?

A: It is difficult to identify a single mechanism that governs all types of positive and negative spillovers. We are still discovering where spillovers emerge and what mechanisms underlie them. Prior research identifies several drivers that can produce either positive or negative spillovers depending on context. These are active areas of research. Within specific domains, certain patterns have emerged. Certain policies tap into aspects of human psychology, resulting in particular behaviors or economic criteria that may be more salient. However, there is considerable heterogeneity. Take Karmarkar and Bollinger’s (2015) work as an example. They find that promoting “bring your own bag” policies led to two different outcomes: increased purchases of both organic foods and indulgent foods due to licensing effects. This illustrates how a single green behavior can generate both positive and negative spillovers simultaneously. It’s not only customer heterogeneity that matters, but even the same customer can exhibit different behaviors simultaneously. This is a different kind of problem. We are not simply saying that we have two different segments of customers and, if we know enough about them, we can treat them differently. Consequently, identifying underlying mechanisms is challenging.

Because of this heterogeneity, we are not ready to conduct a systematic study or meta-analysis yet. What is more critical at this point is establishing that spillovers exist, demonstrating that they can carry over after a repeal, and seeking measurements that will help understand what could be driving those behaviors. Is it product substitution as we examine here? Are these licensing effects? Or is there some sort of behavioral momentum and inertia at play? This is an exciting and growing space that deserves more research.

Break-Even Framework: Can you walk us through how your break-even framework could apply to a different policy? For example, how would this work for something like a soda tax, where there might be positive spillovers (healthier eating) or negative ones (substitution to other sugary products)?

A: Let’s use the soda tax as an example. The direct intended effect is straightforward: people buy and consume less soda, which is great from a public health perspective. But there’s a potential negative spillover—customers might substitute soda with other sugary drinks like juice, sports drinks, or untaxed snacks.

This is where the break-even approach comes in. The key question becomes: how much must total sugar consumption fall for the policy to be considered successful, even after accounting for increased sugar consumption from substitute products? The break-even point is where health benefits from reduced soda consumption exactly offset health costs from increased consumption of alternatives. What makes this framework useful is that we can translate this threshold into concrete, observable behavior. Instead of abstract numbers, we can ask, “How many fewer sodas must a person drink per week to make up for one extra candy bar?” This makes the analysis much more understandable and intuitive.

We used this exact framework in our plastic bag study, calculating that, for the policy to be environmentally beneficial, a household only needed to save one plastic bag for every five shopping trips, a modest and realistic behavior change. This translation to specific behaviors serves two purposes: it allows researchers to reality-check their assumptions, and it provides actionable metrics for monitoring policies during implementation. The soda tax example is more complex, but the core logic remains the same. It’s about bringing rigor and transparency to policy evaluation, especially when policies might be reversed.

Store-Level Programs vs Policy Mandates: In your paper, you mention store-level recycling programs as an alternative. Could you elaborate on what you mean by that and how store-level voluntary programs might create different behavioral dynamics compared to city-wide bans or fees?

A: We gave a couple of examples in the paper, such as the partnership between TerraCycle and Kroger, where retail stores have recycling programs, bottle deposits, or collection points for plastic bags and other recyclables. These are voluntary, retailer-driven initiatives that aim to reduce plastic waste through consumer participation rather than regulatory enforcement. The insight is that there is a range of policy tools. Consider fees, bans, and voluntary actions from the perspective of consumers, retailers, and channel partners. Multiple actors can play a role in implementation.

There are different strategies for achieving a policy objective, and there is value in being open-minded about all of them. Each has strengths and weaknesses. A fee or ban is a mandated requirement. It imposes limitations on consumer freedom and costs on retailers and other participants throughout the channel. Those costs can be high. A voluntary action relieves that pressure because it allows self-selection. For policymakers, promoting store-led programs alongside formal regulations can create a layered strategy: mandates deliver immediate reductions, while voluntary programs reinforce sustainable practices and help offset residual plastic use. This combination can strengthen both short-term impact and long-term cultural adoption of waste-reduction norms. It still improves outcomes by co-opting the retailer and turning participation into a branding opportunity, as the TerraCycle-Kroger partnership illustrates. This creates benefits that retailers value and can communicate to shareholders, stakeholders, and the community. Such innovative approaches can be very effective.

Migration Between Policy Environments: What do you think happens when someone moves from Austin (where they’ve developed the trash bag buying habit during the ban) to a city that never had a plastic bag policy? Do these habits travel with people, and what does that mean for the overall environmental impact?

A: This is an interesting question that depends heavily on context.  First, note that people may even travel to avoid the effects of a ban. Folks on the borders of Austin or Dallas could buy groceries from neighboring cities, thus avoiding the policy altogether—a challenge we carefully address in the paper.

Coming back to your question about migration: The evidence from our analysis suggests that carryovers do dissipate in the absence of policy. When someone moves from Austin to a city without a ban, they are no longer subject to the policy, so we could expect some carryover with a possible decay over time. However, community norms also matter. Moving to a city without a policy may lead to quick adjustment if people can easily use free grocery bags as trash liners. But shopping at places like Whole Foods or Trader Joe’s, where sustainability norms tend to be more visible, can reinforce sustainable habits. As White, Habib, and Hardisty (2019) note in their review of sustainable consumer behavior, social influence and habit formation are key psychological factors that can either reinforce or undermine individual habits depending on context.

Our research shows that carryover effects can arise after a repeal. Although people want to maintain environmentally friendly behavior, our data shows that convenience can win over time when the convenient choice is given. The persistence depends on how deeply the policy connects with people. If someone is told that a children’s snack has high lead content, they will never go back to that brand. But with plastic bag policies, once the requirement is removed, there’s a slow decline in the behavior. This variation depends on what caused the spillover in the first place. It is also worth noting that consumers sometimes avoid policies—those at city borders might shop in neighboring untaxed regions, creating a different challenge for policy effectiveness. The net effect of these multitude of behavioral factors presents an interesting research question.

Source: Dinesh Puranam, Sungjin Kim, Jihoon Hong, and Hai Che (2025), “Are We Worse Off After Policy Repeals? Evidence from Two Green Policies,” Journal of Marketing Research, 62 (2), 189–206.

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