Bag leakage: The effect of disposable carryout bag regulations on unregulated bags

https://doi.org/10.1016/j.jeem.2019.01.001Get rights and content

Abstract

Leakage occurs when partial regulation of consumer products results in increased consumption of these products in unregulated domains. This article quantifies plastic leakage from the banning of plastic carryout bags. Using quasi-random policy variation in California, I find the elimination of 40 million pounds of plastic carryout bags is offset by a 12 million pound increase in trash bag purchases—with small, medium, and tall trash bag sales increasing by 120%, 64%, and 6%, respectively. The results further reveal 12–22% of plastic carryout bags were reused as trash bags pre-regulation and show bag bans shift consumers towards fewer but heavier bags. With a substantial proportion of carryout bags already reused in a way that avoided the manufacture and purchase of another plastic bag, policy evaluations that ignore leakage effects overstate the regulation's welfare gains.

Introduction

Governments often regulate or tax the consumption of products with negative externalities (e.g., alcohol, tobacco, sugar, and gasoline). However, policies are not always complete in their coverage, applying to only a subset of jurisdictions or products contributing negative externalities. Leakage occurs when partial regulation directly results in increased consumption of these products in unregulated parts of the economy (Fowlie, 2009). If unregulated consumption is easily substituted for regulated consumption, basing the success of a regulation solely on reduced consumption in the regulated market overstates the regulation's welfare gains.

In this article, I quantify leakage from the regulation of plastic in consumer goods. The United Nations Environmental Program estimates that 10 to 20 million tonnes of plastic enters the world's oceans each year, costing $13 billion in environmental damage to marine ecosystems, including losses incurred by fisheries and tourism (UNEP, 2014). With growing concern about the costs of plastic waste, governments are turning to economic incentives and command-and-control regulations to curb the use of consumer plastics. An increasingly popular environmental policy has been the regulation of disposable carryout bags (DCB).1 Approximately 242 local governments in the U.S. adopted DCB policies between 2007 and 2016, across 20 states and the District of Columbia.2 Most DCB policies in the U.S. prohibit retail food stores from providing customers with thin plastic carryout bags at checkout and require stores to charge a minimum fee for paper and other reusable carryout bags. However, all remaining types of disposable bags are left unregulated (e.g., trash bags and waste bin liners). Given DCBs can be reused as trash bags before they are disposed,3 this article asks the empirical question: Do bans on plastic carryout bags cause consumers to increase their purchases of unregulated plastic trash bags?

The answer to this question is not only relevant for quantifying leakage; it also provides a key variable for evaluating the environmental effectiveness of DCB policies. Life-cycle assessments (LCAs)—studies that estimate a product's cradle-to-grave environmental impact—are used, and often required, by governments around the world in designing environmental legislation (Ehrenfeld, 1997; Rebitzer et al., 2004).4 LCAs of plastic, paper, and reusable carryout bags have been shown to be sensitive to assumptions made about the weight and number of trash bags displaced by the secondary use of plastic carryout bag, with the reuse of plastic carryout bags as bin liners substantially improving their environmental performance (Mattila et al., 2011). According to a UK Environmental Agency (2011) study, a shopper needs to reuse a cotton carryout bag 131 times to have the same global warming potential (measured in kilograms of CO2 equivalent) as plastic carryout bags with zero reuse, while that same cotton bag needs to be reused 327 times if all plastic carryout bags are reused as bin liners. Thus, a contribution of this paper is to provide an estimate for the reuse of plastic carryout bags that policymakers can use as a benchmark for calculating and interpreting LCA results.

Determining the causal relationship between regulations and leakage is challenging because one must construct a credible counterfactual for consumption in the absence of the regulation, both for regulated and unregulated goods. To understand the causal effect of DCB policies on regulated and unregulated bag consumption, I take advantage of quasi-random variation in local government DCB policy adoption in California—where 139 policies were implemented over nine years. Having more than one policy change over time allows me to separate the causal effect of the policies from other time-varying factors. The second challenge I address is that of limited data. I bring together two data sources: (i) weekly retail scanner data with store-level price and quantity information on trash bag sales, and (ii) observational transaction-level data collected in-store for the number and types of carryout bags used at checkout. Leakage, in this case, is quantified by comparing changes in trash bag sales (from the scanner data) to changes in carryout bag use (from the observational data). While data on trash bags sales are readily available to researchers in retail scanner datasets, such as the one used in this paper, transaction-level data on carryout bag use (for both bags obtained in the store and those brought from outside) are more challenging to obtain, due to their manual, time-consuming nature to collect.5 Thus, another contribution of this paper is the combination of scanner and observational data, which does not rely on consumers self-reporting their bag use.6

Using quasi-random variation in policy adoption and bag use data over time, I employ an event study design to quantify the effect of DCB policies on the use of plastic, paper, reusable carryout bags, as well as the sale of four types of trash bags. The results show that a 40 million pound reduction of plastic per year from the elimination of plastic carryout bags is offset by an additional 12 million pounds of plastic from increased purchases of trash bags. In particular, sales of small, medium, and tall trash bags increase by 120%, 64%, and 6%, respectively. This means that 28.5 percent of the plastic reduction from DCB policies is lost due to consumption shifting towards unregulated trash bags. The results also provide a lower bound for the reuse of plastic carryout bags, with 12–22% of plastic carryout bags reused as trash bags pre-regulation. In other words, a substantial proportion of carryout bags were already reused in a way that avoided the manufacture and purchase of another plastic bag.

These results provide an estimate of the share of consumers already behaving in a manner that reduces waste and carbon emissions. This is akin to the economic debate over how many recipients of environmental subsidies are “non-additional”—i.e., getting paid to do what they would have done anyway (Joskow and Marron, 1992; Chandra et al., 2010; Gallagher and Muehlegger, 2011; Boomhower and Davis, 2014; Ito, 2015).7 For instance, Boomhower and Davis (2014) find that half of all study participants that received an energy-efficiency subsidy would have replaced their appliances with no subsidy. The concern is that a subsidy will not be cost-effective if a large enough fraction of consumers is non-additional. In the case of DCB policies, instead of rewarding too many consumers for the green behavior they would have done anyway, DCB policies restrict the choice set of green behaviors available, preventing green behaviors that would have been done anyway. Therefore, this paper empirically addresses the critical question of “subtractionality”—i.e., how many consumers would have reused their plastic carryout bags as trash bags, had they not been banned. Moreover, this paper examines who are the subtractional customers. Supplemental heterogeneity analyses reveal that plastic bag reuse is correlated with having a pet or a baby (i.e., having dependents whose waste must be collected and disposed of), spending less per item (i.e., bargain shopping), purchasing more items per trip, and having a college degree.

This article also extends the literature on pollution leakage and spillover effects. While numerous studies analyze leakage related to regulating production-driven externalities (such as greenhouse gas emissions),8 the empirical literature examining leakage from regulating consumption-driven externalities is limited. Adda and Cornaglia (2010) analyze the effect of smoking bans in public places on exposure to second-hand smoke. The authors find that bans displace smokers to private places where they contaminate non-smokers, especially young children. Davis (2008) studies a policy in Mexico City where drivers are prohibited from using their vehicles one weekday per week on the basis of the last digit of their vehicle's license plate. The author finds no change in air quality due to the policy; instead, drivers circumvent the restriction by increasing the total number of vehicles in circulation. Similar to these studies, I find that DCB policies are circumvented by consumers substituting towards unregulated plastic bags.

Finally, this paper contributes to the literature by examining the persistent effects of behavioral interventions. Do interventions set a new behavioral status quo (or default) which lasts indefinitely, or do behaviors drift as people re-optimize? Cronqvist et al. (2018) argue that this question has not received enough attention, and as it is inevitably an empirical question, we should expect variability across contexts. Cronqvist et al. (2018) find that the effects of defaults in pension plan selection are remarkably persistent, lasting nearly two decades. Allcott and Rogers (2014) study the short-run and long-run effects of monthly social comparison reports on energy use and find the average treatment effect increases at a declining rate over the first four reports and then persists for the remainder of the reports. Conversely, Jacobsen (2011) found that the release of Al Gore's documentary An Inconvenient Truth led to a temporary increase in household purchases of voluntary carbon offsets—the effect only lasting a couple of months. Similar to these studies, this paper is able to analyze the persistent effects of DCB regulations on bag use. The results reveal that increased sales of trash bags persist at least four years after policy implementation (the entire length of the post-policy sample period).

Policy-induced changes in plastic bag use have implications for greenhouse gas emissions, marine debris, and landfilling. I conclude this article by discussing the benefits of reduced litter and marine debris from thin plastic carryout bags, the costs of greater emissions from the production of thicker bags, and the costs of thicker bags taking up more space in landfills. If carbon footprint was the only metric of environmental success, the results in this paper suggest DCB policies are having an adverse effect. However, if the unmeasured benefits with respect to marine debris, toxicity, and wildlife are great enough, they could outweigh the greenhouse gas costs. While the upstream relationship between plastic production and carbon footprint is well understood, the downstream relationship between plastic litter and marine ecosystems is less established, making it challenging to evaluate the environmental success of DCB policies. However, it is clear that ignoring leakage overstates the regulation's welfare gains.

The remainder of the article is organized as follows. Section 2 describes the policy implementation variation and catalogs the data. Section 3 presents the event study empirical design. Section 4 reports the event study results, as well as robustness checks. Section 5 quantifies the leakage effect and discusses the environmental implications of changes in the composition of plastic bags, with respect to carbon footprint, landfilling, and marine pollution. Section 6 presents heterogeneity analyses, introducing supplemental data at the customer-level. Section 7 concludes with policy implications and future research.

Section snippets

Adoption of disposable carryout bag regulations

With variation in policy adoption across time and space, California provides an exceptional quasi-experiment for analyzing the effects of DCB policies. From 2007 through 2015, 139 Californian cities and counties implemented DCB policies, affecting over one third of California's population.9 This local legislative momentum continued and culminated with the

Scanner data event studies

I estimate the causal effect of DCB policies on bag purchases using an event study design. I aggregate the raw retail scanner data to the store-by-month-by-product-group level and employ the following event study regression model:YsjmB=l=1212βlDl,jm+θsj+δm+εsjmwhere YsjmB is the outcome variable for store s in jurisdiction j and month-of-sample m with respect to bag product group B, θsj is a vector of store fixed effects, and δm is a vector of month-of-sample fixed effects. Dl,jm is a dummy

Scanner data results

The figures in this section present the results from the estimation of event study Equation (1), where the βˆl point estimates and 95% confidence intervals are displayed graphically.15 Unless specified otherwise, I cluster the standard errors two ways—by jurisdiction (19) and by month-of-sample (84)—to allow for spatial and temporal correlation in the data.16

Quantifying leakage

The previous section revealed that banning plastic carryout bags led to increased purchases of plastic garbage bags—with small, medium, and tall trash bag sales increasing by 120%, 64%, and 6% respectively. In this section, I calculate the leakage rate by comparing the estimated increase in pounds of plastic trash bags to the estimated decrease in pounds of plastic carryout bags. This is a key contribution of the paper. To calculate the rate of leakage, it is not enough to show substitution

Heterogeneity analysis

Who are the subtractional customers—i.e., the customers that would have reused their plastic grocery bags as trash bags had they not been banned? To understand who is responding to DCB policies by purchasing trash bags, I estimate the difference-in-difference version of equation (1) interacted with several subgroups.32

Conclusion

This article is the first to evaluate how regulating the use of plastic carryout bags affects the sale of unregulated disposable bags. Using quasi-random variation of local government policy adoption in California in an event study design, I find that the banning of plastic carryout bags leads to significant increases in the sale of trash bags, and in particular small and medium trash bags. When converted into pounds of plastic, 28.5% of the plastic reduction from DCB policies is lost due to

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    I dedicate this paper to Peter Berck, for his enduring advice and mentorship, on this paper and in life. I thank Kendon Bell, Lee Clemon, Meredith Fowlie, Joshua Graff Zivin, Hilary Hoynes, Andrea La Nauze, Leslie Martin, Louis Preonas, Andrew Stevens, and Sofia Berto Villas-Boas for helpful discussions and suggestions. I also thank Kate Adolph, Katherine Cai, Samantha Derrick, Tess Dunlap, Valentina Fung, Claire Kelly, Ben Miroglio, Nikhil Rao, Lucas Segil, Corinna Su, Edwin Tanudjaja, and Sarah Zou for their superb research assistance. This project would not be possible without the institutional and technical support of the retailers that provided data and access to their stores. This paper reflects the author's own analyses and calculations based on data from individual retailers and data from The Nielsen Company (US), LLC and marketing databases provided by the Kilts Center for Marketing Data at the University of Chicago Booth School of Business, Copyright © 2018 The Nielsen Company (US), LLC, all rights reserved. The conclusions drawn from the Nielsen data are those of the researchers and do not reflect the views of Nielsen. Nielsen is not responsible for, had no role in, and was not involved in analyzing and preparing the results reported herein. I declare that I have no relevant or material financial interests that relate to the research described in this paper.

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