1. Interpret the Alternative Specific Constants (ASCs) in Table 3. Also, interpret the ASC interaction terms.
2. How are the willingness-to-pay estimates calculated in Table 4? Interpret these estimates.
3. Explain the difference between the three latent classes estimated in Table 7 with respect to the estimated parameters.
4. Describe the simulation results I and J presented in Table 8 and in Figure 1.
To ‘vape’ or smoke? Experimental evidence on adult smokers: To ‘vape’ or smoke? TO “VAPE” OR SMOKE? EXPERIMENTAL EVIDENCE ON ADULT SMOKERS JOACHIM MARTI, JOHN BUCKELL, JOHANNA CATHERINE MACLEAN and JODY SINDELAR∗ A growing share of the U.S. population uses e-cigarettes but the optimal regulation of these controversial products remains an open question. We conduct a discrete choice experiment to investigate how adult tobacco cigarette smokers’ demand for e-cigarettes and tobacco cigarettes varies by four attributes: (1) whether e-cigarettes are considered healthier than tobacco cigarettes, (2) the effectiveness of e-cigarettes as a cessation device, (3) bans on use in public places, and (4) price. We find that adult smokers’ demand for e-cigarettes is motivated more by health concerns than by the desire to avoid smoking bans or higher prices. (JEL C35, I12, I18) I. INTRODUCTION E-cigarettes are relatively new products in U.S. tobacco markets; they were developed in China in 2003 and entered the United States in 2007 (Riker et al. 2012). Since that time, e-cigarette use has proliferated among Ameri- cans. Currently 5.5% of adults (Kasza et al. 2017) and 16% of high school students (Singh 2016) use these products. E-cigarettes are battery-operated devices containing a liquid which typically con- tains nicotine along with other components such as propylene glycol, glycerin, and flavors. A heat- ing element vaporizes the liquid and the resulting vapor is inhaled by the user (“vaping”). Unlike other nicotine delivery systems (e.g., nicotine ∗Research reported in this publication was supported by grant number P50DA036151 from the National Institute on Drug Abuse (NIDA) and FDA Center for Tobacco Products (CTP). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Food and Drug Administration. Marti: Associate Professor, Institute of Social and Preven- tive Medicine (IUMSP), Centre Hospitalier Universitaire Vaudois, Université de Lausanne, Lausanne, 1010, Switzerland. Phone +41 (0)21 314 02 63, E-mail
[email protected] Buckell: Post-doctoral Associate, School of Public Health, Yale University, New Haven, CT 06511. Phone 203-785- 6921, E-mail
[email protected] Maclean: Associate Professor, Department of Economics, Temple University, Philadelphia, PA 19122; NBER, New York, NY 10016; IZA, 53113 Bonn, Germany. Phone 215-204-0560, E-mail
[email protected] Sindelar: Professor, School of Public Health, Yale University, New Haven, CT 06511; NBER, New York, NY 10016; IZA, 53113 Bonn, Germany. Phone 203-785-5287, Fax 203-785-6287, E-mail
[email protected] gum, nicotine patches), e-cigarettes are specif- ically designed to simulate the experience of tobacco cigarette smoking. Because tobacco is not burned, far fewer toxins are produced (Sha- hab et al. 2017), e-cigarettes are often considered a healthier alternative to tobacco cigarettes. How- ever, there is controversy over whether e-cigarette use improves or harms public health (Kenkel 2016; NHS Health Scotland 2017; Ribisl, Seiden- berg, and Orlan 2016; Riker et al. 2012; Royal College of Physicians 2016). Evidence of the effect of e-cigarette regula- tions on e-cigarette use is critical to informing government decision-making, yet is generally unavailable due to the current lack of revealed preference data on e-cigarette use and quasi- experimental variation in e-cigarette attributes. Initial e-cigarette regulations in the United States were implemented beginning in 2010 (Lempert, Grana, and Glantz 2016). Most early regulations target youth (e.g., minimum legal purchase ages) and data necessary to study a broader set of regulations that plausibly affect a larger ABBREVIATIONS AIC: Akaike Information Criterion CTP: Center for Tobacco Products DCE: Discrete Choice Experiment DD: Differences-in-Differences FDA: Food and Drug Administration GMXL: Generalized Mixed Logit IIA: Independence of Irrelevant Alternatives MMNL: Mixed Multinomial Logit TUS: Tobacco Use Supplement WTP: Willingness to Pay 705 Economic Inquiry (ISSN 0095-2583) Vol. 57, No. 1, January 2019, 705–725 doi:10.1111/ecin.12693 Online Early publication July 18, 2018 © 2018 Western Economic Association International 706 ECONOMIC INQUIRY share of the population (e.g., taxes), including adults, is particularly limited. Thus, standard regulation evaluation methods (e.g., differences- in-differences [DD] models) are not feasible.1 We conduct a discrete choice experiment (DCE) in a sample of adult tobacco cigarette smokers to help address these information gaps. DCE, a stated preference technique, is increasingly employed by economists to study tobacco-related products (Buckell, Marti, and Sindelar 2018; Czoli et al. 2016a; Ida and Goto 2016; Kenkel et al. 2017; Marti 2012a, 2012b; Pesko et al. 2016b; Regmi et al. 2017; Shang et al. 2017). These methods are grounded in consumer choice theory established by Lancaster (1966). DCEs are based on the premise that a good or service can be described as a set of attributes and consumers value goods and ser- vices as a sum of their attributes and underlying product preferences. In addition, DCEs allow estimation of causal effects of attributes on product choice using experimental variation, and can allow testing of attributes not observed in real-world markets. DCEs are especially attrac- tive, as is the case for e-cigarettes, when suitable revealed preference data are not available. Choice data from the DCE are used to examine how adult smokers choose between e-cigarettes and tobacco cigarettes, and also how they respond to changes in product attributes and their levels. We focus on three cigarette types: nonrefillable, disposable e-cigarettes; refillable, rechargeable e-cigarettes; and tobacco cigarettes. We include four policy-relevant attributes: whether e-cigarettes are healthier than tobacco cigarettes; the effectiveness of e-cigarettes as a cessation device; bans on use in public places 1. Major U.S. health surveys commonly leveraged by economists to study regulation effects have only recently added e-cigarette questions. For example, the National Health Interview Survey added e-cigarette questions in 2014 and the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance Survey added e-cigarette questions in 2016. There is often at least a 1-year delay from survey data collection to survey data release. Thus, these datasets will not offer researchers the opportunity to study the early effects of state regulations through standard regulation evaluation meth- ods for several years. DD regression models used to evaluate regulations are identified off regulation changes and therefore several years of data and regulation changes are required for identification of treatment effects. While findings from future studies employing these data and methods will be important and offer critical insight on how best to regulate e-cigarettes based on historical regulation changes, our argument is that currently, as policymakers are developing new regulations and fine-tuning existing regulations, there is little rigorous anal- ysis using standard data and methods. Thus, it seems pru- dent to consider alternative methods to elicit this necessary information. such as bars and restaurants; and price. We also estimate willingness to pay (WTP) for nonprice cigarette attributes. Importantly, we estimate heterogeneity in preferences across different groups of smokers by using latent class logit models. In turn, we use the estimated heterogeneity in smoker choice overall and across types of smokers to identify different responses. We use our estimates to sim- ulate changes in market shares. We first simulate a base case scenario that reflects the state of the world and then we sequentially change the regulation variables and simulate hypothetical market shares overall, and for each of the smoker types we identify. To the best of our knowledge, only a few extant studies use DCEs in the context of e-cigarettes (Buckell, Marti, and Sindelar 2018; Czoli et al. 2016a; Kenkel et al. 2017; Pesko et al. 2016b; Shang et al. 2017). These studies examine the effects of flavors, warning labels, price, and nico- tine content on e-cigarette choice. Overall, these studies suggest that higher prices, reduced flavor availability, and health warnings deter e-cigarette choice while the effect of nicotine is mixed. We add to this small literature in several impor- tant ways: (1) We consider tobacco cigarettes alongside both disposable and rechargeable e-cigarettes, which allows us to better charac- terize the tobacco product market and allows us to explore differences in pricing schemes across the two e-cigarette types. (2) We examine the importance of relative health harms between e-cigarettes and tobacco cigarettes, e-cigarette effectiveness as a cessation aid, and the ability to use e-cigarettes to evade tobacco cigarette public use bans. (3) We use a large, nationally representative sample. (4) We estimate WTP for nonprice attributes. (5) We explore group-wise preference heterogeneity which we argue is essential for development of effective regulation given the vastly different reasons for e-cigarette use. (6) We provide policy-relevant simulations of the effect of alternative regulations. II. REGULATORY ISSUES, CONTROVERSY SURROUNDING E-CIGARETTES, AND CONSUMER KNOWLEDGE AND PERCEPTIONS OF E-CIGARETTES A. Regulatory Issues Related to DCE Product Attributes We examine four attributes in our DCE: rel- ative health; effectiveness as a cessation device; bans on use in public places; and price. We select MARTI ET AL.: VAPE 707 these attributes as they are amenable to policy changes by the U.S. Food and Drug Administra- tion (FDA) and other regulators (e.g., state and local governments). While the relevance of price and public use bans for regulation is obvious and there are numerous historical examples of the application of these regulations in the United States, that is, governments increase price through taxation and prohibit product use in a wide range of public places (Centers for Disease Control and Prevention 2016), the relevance for regulation purposes of our remaining product attributes is perhaps less obvious. We discuss the ability of regulators to influence these attributes, and hence, the credibility of including these attributes in our DCE. At the federal level, the Center for Tobacco Products (CTP) at the FDA has broad authority over the manufacturing, distribution, and market- ing of tobacco products, including e-cigarettes as of 2016, through the Family Smoking Act (2009). Thus, the FDA can both directly and indirectly regulate the healthiness of e-cigarettes and the effectiveness of e-cigarettes as a cessation device. Regulation can affect actual product features and consumers’ perceptions of these features, both of which are important for consumer choice over e-cigarettes and tobacco cigarettes (Czoli et al. 2016a; Kenkel et al. 2017; Maclean, Webber, and Marti 2014; Viscusi 2016). In terms of directly affecting e-cigarette healthiness and effectiveness as a cessation device, the CTP can determine the healthiness of e-cigarettes through regulation of allowable ingredients in these products (e.g., ban harm- ful toxins such as diacetyl, a butter flavoring used in e-cigarettes which causes lung dam- age [Barrington-Trimis, Samet, and McConnell 2014], and nicotine which can harm health [Benowitz 1997]) and device features such as limiting the voltage permitted in e-cigarettes to prevent explosions (Kosmider et al. 2014). Relatedly, the FDA, through the Center for Drug Evaluation and Research, has the authority to regulate e-cigarettes that are sold for cessation or therapeutic purposes. This agency can therefore control which e-cigarettes are sold as cessation devices. The FDA can place high standards