WEBVTT 1 00:00:02.800 --> 00:00:13.489 Parisa Moghaddam: Welcome to the Tobacco Online Policy Seminar, TOPS. Thank you for joining us today. I'm Parisa Moghaddam, a PhD student in health economics at The Ohio State University. 2 00:00:14.070 --> 00:00:26.690 Parisa Moghaddam: TOPS is organized by Mike Pesko at University of Missouri, Seisheng at Ohio State University, Michael Darden at Johns Hopkins University, Jamie Hartmann-Boyce at the University of Los Angeles at Ahmad, and Justin White at Boston University. 3 00:00:26.690 --> 00:00:38.469 Parisa Moghaddam: The seminar will be one hour, with questions from the moderator and discussant. The audience may post questions and comments in the Q&A panel, and the moderator will draw from these questions and comments in conversation with the presenter. 4 00:00:39.100 --> 00:00:47.790 Parisa Moghaddam: Please review the guidelines on TobaccoPolicy.org for acceptable questions. Please keep the questions professional and related to the research being discussed. 5 00:00:47.810 --> 00:01:03.480 Parisa Moghaddam: Questions that meet the Seminar series guidelines will be shared with the presenter afterwards, even if they are not read aloud. Your questions are very much appreciated. This presentation is being video recorded and will be made available along with the presentation slides on the TOPS website, TobaccoPolicy.org. 6 00:01:03.520 --> 00:01:10.779 Parisa Moghaddam: I will turn the presentation over to today's moderator, Jamie Hartmann-Boyce from the University of Massachusetts at Amres, to introduce our speaker. 7 00:01:11.090 --> 00:01:29.399 Jamie Hartmann-Boyce: Hello, everyone! Today, we continue our Summer 2026 season with a single paper presentation by Julia He, entitled, Standardizing Excise Taxes and Estimating Tax Pass-Through Rate for Oral Nicotine Pouches in the U.S. Market. This presentation was selected by a competitive review process by submission through the TOPS website. 8 00:01:29.880 --> 00:01:47.230 Jamie Hartmann-Boyce: Dr. He is a health economist and senior research scientist at the Center for Tobacco Research in the Ohio State University Comprehensive Cancer Center. Her research uses economic analysis and policy evaluation to examine tobacco use in the U.S. and internationally, generating evidence to inform tobacco regulation. 9 00:01:47.320 --> 00:02:03.109 Jamie Hartmann-Boyce: Her recent work focuses on oral nicotine pouches, an emerging class of nicotine products. Dr. C. Sheng, an associate professor at The Ohio State University, is a co-author of the study and will answer select questions in the Q&A. Dr. He, thank you so much for presenting for us today. 10 00:02:05.000 --> 00:02:06.929 Julia He: Hi, everyone, 11 00:02:07.110 --> 00:02:18.810 Julia He: It's my pleasure to be here today. Thank you for the introduction, and thank you for joining my presentation today. Today, let me share my screen first. 12 00:02:19.360 --> 00:02:23.360 Julia He: Yeah. 13 00:02:23.410 --> 00:02:42.400 Julia He: Today, I will be presenting my study titled, Standardizing Access Taxes and Estimating the Tax Pass-Through Rates for Oral Nicotine Pouches in the U.S. Market. So, oral nicotine pouches are becoming increasingly popular product in the U.S. in recent years. 14 00:02:42.400 --> 00:02:50.879 Julia He: However, states use various methods to tax these products, making it difficult to compare tax levels across states. 15 00:02:51.320 --> 00:03:04.119 Julia He: In this study, I will introduce a method to the, to standardize OMP access taxes so that all taxes can be compared at this, across states. 16 00:03:10.190 --> 00:03:22.369 Julia He: Okay, so this is my founding statement. This study was supported by the OSU T-Course project. I was also supported by the OSU T-Course pilot project. 17 00:03:22.560 --> 00:03:29.560 Julia He: I declare that I have never received funding from tobacco, vaping, and pharmaceutical industries. 18 00:03:30.150 --> 00:03:46.720 Julia He: This study uses the NielsenIQ retail scanner data. As always, the conclusions drawn from the data are those of the authors and do not represent the views of the NewsIQ, and I have no other conflict of interest to declare. 19 00:03:48.020 --> 00:03:57.410 Julia He: So, what are oral nicotine pouches, or OMPs? OMPs are small pouches that contain nicotine, but do not contain tobacco leaf. 20 00:03:57.660 --> 00:04:03.680 Julia He: They are placed between the gum and upper lip, allowing nicotine to be absorbed. 21 00:04:03.680 --> 00:04:22.250 Julia He: through oral mucosa. Some of the OMTs contain tobacco-derived nicotines, whereas other… others contain non-tobacco nicotine, also called synthetic nicotine. Some of the well-known brands include Zin, Ong, ROG, and Velo. 22 00:04:22.260 --> 00:04:24.640 Julia He: OMPs are available, you know. 23 00:04:24.670 --> 00:04:38.009 Julia He: range of nicotine concentration, ranging from 1.5mg to 8 mg per pouch. Some of the OMPs contain up to nearly 50 milligram nicotine per pouch. 24 00:04:38.060 --> 00:04:44.740 Julia He: OMGs are also available in a wide variety of flavors. 25 00:04:45.350 --> 00:04:55.860 Julia He: You can name it, many, many flavors. And, such as mint, Mansaw, wintergreen, spearmint, fruit, to Tobacco, coffee, etc. 26 00:04:56.140 --> 00:05:06.740 Julia He: So, usually, you know, generally speaking, OMPs are considered lower-risk nicotine products. However, they still contain nicotine. 27 00:05:07.050 --> 00:05:12.509 Julia He: And they have the potential to lead to nicotine addiction. 28 00:05:14.430 --> 00:05:17.540 Julia He: So why is it important to study 29 00:05:17.590 --> 00:05:34.579 Julia He: OMPs. The primary reason is that the OMP market has grown rapidly in recent years. Since early sales data show that the OMP sales increased from just 163,000 30 00:05:35.000 --> 00:05:50.950 Julia He: units in 2016 to 46 million units in 2020. Our more recent work found that the OMP sales has continued to accelerate since 2021, with monthly OMP sales 31 00:05:50.950 --> 00:06:03.669 Julia He: Rising from 327 million units in July 2021 to over 1 billion units by May 2024, and similar trends has also been observed globally. 32 00:06:04.000 --> 00:06:09.849 Julia He: At the same time, the awareness and OMP use prevalence has also increased. 33 00:06:10.120 --> 00:06:22.429 Julia He: National survey data showed that 3% of U.S. adults reported ever use of OMPs in 2021, and nearly 30% of adults who smoked 34 00:06:22.440 --> 00:06:39.530 Julia He: had ever seen or heard of OMPs, and 5.6% had ever tried OMPs, and nearly 17% reported interest in using OMPs in the next 6 months. Use use has also increased. 35 00:06:39.850 --> 00:06:50.790 Julia He: The past 30-day use among high school students increased from 1.1% in 2021 all the way to 2.4% in 2024. 36 00:06:51.450 --> 00:06:57.299 Julia He: These trends highlight the growing public health importance of OMPs. 37 00:06:59.220 --> 00:07:08.580 Julia He: So, one of the key questions surrounding OMPs is whether they contribute to harm reduction. 38 00:07:09.310 --> 00:07:14.140 Julia He: This discussion is similar to the debate around e-cigarettes. 39 00:07:14.300 --> 00:07:33.970 Julia He: So the overall public health impact depends on who use them and how they are used. On one hand, harm may reduce if adults use OMPs to quit smoking, or if individuals who would otherwise initiate cigarette smoking use OMPs instead. 40 00:07:34.710 --> 00:07:36.719 Julia He: However, on the other hand. 41 00:07:36.910 --> 00:07:47.420 Julia He: harm may increase if people who… if smokers do use OMP, cigarettes and OMPs, rather than quit smoking altogether. 42 00:07:47.640 --> 00:08:02.400 Julia He: In addition, if people who never used nicotine, especially adolescents, begin using OMPs and become addicted, the net public health impact could be negative. These competing possibilities 43 00:08:02.480 --> 00:08:11.909 Julia He: Highlight the importance for the evidence-based… how evidence-based policies, such as taxisations, 44 00:08:12.590 --> 00:08:21.700 Julia He: can, maximize the potential, benefits of OMPs while minimizing the unintended consequences. 45 00:08:23.520 --> 00:08:35.619 Julia He: So this figure illustrates the OMP tax landscape in the United States. As of December 2025, no federal tax has been imposed 46 00:08:35.750 --> 00:08:37.200 Julia He: on OMPs. 47 00:08:37.990 --> 00:08:41.749 Julia He: Taxation was determined at the state level. 48 00:08:41.919 --> 00:08:45.430 Julia He: among 50 states and Washington, D.C. 49 00:08:45.770 --> 00:08:57.410 Julia He: 30… 29 states and DC do not impose any taxes on OMPs. Among the 20… 21 states. 50 00:08:57.780 --> 00:09:00.100 Julia He: that have OMP taxes. 51 00:09:00.460 --> 00:09:13.349 Julia He: 3 applied weight-based specific taxes measured at dollar per ounce, and 4 applied uni-based specific taxes measured at 52 00:09:13.550 --> 00:09:15.180 Julia He: At dollar per can. 53 00:09:15.470 --> 00:09:27.050 Julia He: And 11 applied at volume taxes based on wholesale prices. 3 applied at volume taxes based on manufacturer prices. 54 00:09:28.320 --> 00:09:30.330 Julia He: Regarding the product type. 55 00:09:30.560 --> 00:09:35.960 Julia He: 15 states tax OMPs containing both TDN and NTN. 56 00:09:36.080 --> 00:09:38.990 Julia He: And there is 5 states. 57 00:09:39.330 --> 00:09:48.459 Julia He: tax only OMPs with TDN. Nevada is the only state that tax only OMPs with NTN. 58 00:09:49.340 --> 00:09:56.240 Julia He: the number of states that imposed excess taxes on OMPs increased from 59 00:09:56.520 --> 00:10:03.330 Julia He: 12 in 2017 to 21 in 2025. 60 00:10:04.730 --> 00:10:20.720 Julia He: So, regarding the tax pass-through rates, previous literature found that cigarette taxes were fully passed or overshifted to prices, with higher tax pass-through rates observed for higher-priced cigarettes. 61 00:10:21.050 --> 00:10:27.289 Julia He: Research on moist enough shows similar pattern. My previous study found that 62 00:10:27.530 --> 00:10:35.150 Julia He: Mohamed Nav taxes were fully passed through to prices at the 25th and 50th percentile 63 00:10:35.370 --> 00:10:45.780 Julia He: percentiles, and over-shifted at the 75th percentile. However, to date, no evidence exists on OMP, 64 00:10:45.940 --> 00:10:49.539 Julia He: on the… on the tax pass-through rates for OMTs. 65 00:10:50.070 --> 00:10:59.959 Julia He: So this… based on the… these, research gaps, this study has two main objectives. First, we sought to… 66 00:11:00.160 --> 00:11:09.889 Julia He: develop a method to standardize OMP tax… OMP access taxes. Second, we will use the… 67 00:11:10.490 --> 00:11:17.139 Julia He: A standardized text measure to assess the tax pass-through rates for OMPs. 68 00:11:17.920 --> 00:11:23.729 Julia He: Then I will move to the first objective, standardizing OMP access taxes. 69 00:11:24.720 --> 00:11:26.450 Julia He: So, the method… 70 00:11:26.690 --> 00:11:40.609 Julia He: So the key idea is to select a single tax base as a common anchor, and convert all other text bases into this shared metric, so that all taxes can be compared. 71 00:11:41.880 --> 00:11:57.969 Julia He: So we developed two, standardized tax measures. First, we construct, we convert ad valorem taxes and unit-based, specific taxes to weight-based, taxes. 72 00:11:58.070 --> 00:12:11.750 Julia He: We construct both time-invariant and time-varying measures. Time-invariant measures involve using a fixed benchmark price, whereas time-varying measures involve 73 00:12:11.900 --> 00:12:15.230 Julia He: Using a, varying prices. 74 00:12:16.080 --> 00:12:24.170 Julia He: And then the… And second, we convert all the specific taxes to adolarum taxes. 75 00:12:24.590 --> 00:12:27.719 Julia He: So, these standardized tax measures. 76 00:12:27.910 --> 00:12:39.059 Julia He: will, support future studies by enabling robust statistical analysis and comparisons of OMP tax levels across states. 77 00:12:39.650 --> 00:12:50.479 Julia He: So, the OMP tax data was hand-select, collected through direct communication with each state's tax agencies. 78 00:12:51.240 --> 00:12:59.490 Julia He: For those states that did not respond to our email inquiries, we submit a FOIA request. 79 00:13:00.090 --> 00:13:16.500 Julia He: And then the… we also used the Nielsen IQ retail scanner data to extract OMP prices and sales. The CPI data was used to calculate the, inflation-adjusted OMP prices. 80 00:13:18.000 --> 00:13:25.850 Julia He: So, first, I will discuss the method for converting all other tax bases to weight-based taxes. 81 00:13:26.070 --> 00:13:43.190 Julia He: Since, the can weight, vary across brands. For example, a thin can with 0.21 ounces. However, the Ong can with, 0… 82 00:13:43.310 --> 00:13:56.760 Julia He: 0.19 ounces. So we, we first, we, calculate the market share weighted average can weight. We call the standard… a standard can weed. 83 00:13:57.320 --> 00:14:00.130 Julia He: Based on our previous research. 84 00:14:00.260 --> 00:14:07.860 Julia He: The four brands seen on ROG and Velo, accounted for 99% of market share. 85 00:14:07.990 --> 00:14:10.539 Julia He: So, we use these four brands. 86 00:14:10.820 --> 00:14:18.530 Julia He: And each market share, and then calculate the, standard count weight, which is 0.23. 87 00:14:19.090 --> 00:14:31.570 Julia He: Then we use this standard kind weight to convert the unit-based taxes to weight-based taxes. For example, Texas imposed $1.46 88 00:14:31.790 --> 00:14:43.710 Julia He: Taxes, or can, which translates to the weight-based taxes is… $6.26… cents per ounce. 89 00:14:44.470 --> 00:14:46.119 Julia He: When we, 90 00:14:47.080 --> 00:15:01.889 Julia He: convert ad valorem taxes to weight-based taxes. For the time invariant measure, we use the following, formula. So the benchmark price, how we, determine the benchmark price. 91 00:15:02.070 --> 00:15:15.010 Julia He: Since 2017, it's the first year that the OMP sales data, sales record is available in the NRSD. Only in three, non-tax states. 92 00:15:15.050 --> 00:15:17.010 Julia He: Health sales record. 93 00:15:17.040 --> 00:15:19.300 Julia He: And, 3 of the… 94 00:15:19.300 --> 00:15:43.050 Julia He: of them had fewer than 3-month sales record. So we consider that it's not, representative of the national data, national price. Therefore, we, extend the year to 2018. So we used the average sales weighted retail prices from 2017 to 2018 across 11 non- 95 00:15:43.050 --> 00:15:43.870 Julia He: state. 96 00:15:44.000 --> 00:15:48.510 Julia He: non-tax states. Then we calculate the benchmark price. 97 00:15:48.800 --> 00:15:59.829 Julia He: Then we use two assumptions for the markup rate. One is 35 markup rate, and the other one is 20% markup rate. 98 00:16:00.100 --> 00:16:10.629 Julia He: Then I will give you two examples. The first example, Minnesota imposes taxes at the 95% of wholesale prices. 99 00:16:10.630 --> 00:16:20.790 Julia He: So first, we calculate the fixed benchmark price. According to our data, the benchmark price is $4.39 per cap. 100 00:16:21.700 --> 00:16:26.609 Julia He: Then translate… we translate this price to… into, weight-based. 101 00:16:26.770 --> 00:16:32.340 Julia He: So that corresponds to $18.83 per ounce. 102 00:16:32.590 --> 00:16:45.580 Julia He: Then we calculate the benchmark wholesale price according to the markup… the markup rate, 35 markup rate. That is $13.95 per ounce. 103 00:16:45.810 --> 00:17:01.599 Julia He: Then we use the formula. We divide this benchmark wholesale price by 1 plus tax rate, and then multiply by tax rate. That is $6.79 per ounce. 104 00:17:02.180 --> 00:17:15.209 Julia He: And then the second example is Colorado. Colorado imposed a tax at a 56% of the manufacturer list price. The only difference is… 105 00:17:15.270 --> 00:17:25.679 Julia He: We, you know, when we… we need to calculate the benchmark manufacturer price, so we divide the… the… the benchmark retail price 106 00:17:25.750 --> 00:17:33.169 Julia He: By 1.35 square. So that's the only difference. 107 00:17:34.240 --> 00:17:43.129 Julia He: And then we use the same formula to calculate the standardized way-based taxes, that is $3.71. 108 00:17:45.970 --> 00:17:51.830 Julia He: So the methods, to convert to weight-based taxes, 109 00:17:51.890 --> 00:18:06.300 Julia He: using, time-varying measures. So, the time invariant measure captures only policy-driven changes. However, it doesn't reflect the actual… actual levels of ad valorem taxes. 110 00:18:06.420 --> 00:18:12.040 Julia He: So we, we calculate the, time-varying, weight-based taxes. 111 00:18:12.280 --> 00:18:19.659 Julia He: So we replaced the nominator, you know, the benchmark price with the varying price levels. 112 00:18:20.110 --> 00:18:26.030 Julia He: So, that… the prevailing, prices. So, it's worth noting that in case 113 00:18:26.200 --> 00:18:37.700 Julia He: This measure, you know, if the price data is missing for a given state-month combination, the corresponding standardized specific tax values will be missing. 114 00:18:39.100 --> 00:18:46.859 Julia He: And then the, next, we will introduce the… how we convert to add volume taxes. 115 00:18:47.240 --> 00:18:48.350 Julia He: So… 116 00:18:48.530 --> 00:18:59.979 Julia He: So, there are two, type of specific taxes. One is weight-based taxes, and the other one is unit-based taxes. So, in this case, we first convert 117 00:19:00.010 --> 00:19:14.289 Julia He: the wheat-based taxes into unit-based taxes using the standard con wheat, and then we convert the unit-based taxes to add volum taxes at the wholesale level using this formula. 118 00:19:14.540 --> 00:19:27.949 Julia He: Basically, the denominator is the unit-based specific taxes, and then the denominator is the benchmark prices exclusive of specific taxes. 119 00:19:28.560 --> 00:19:39.669 Julia He: And then for states that impose, ad valorem taxes at the manufacturer level, we just divide this tax rate by 1 plus, 120 00:19:39.880 --> 00:19:41.969 Julia He: 1 plus markup rate. 121 00:19:42.770 --> 00:19:48.719 Julia He: So I will pause here, and then see if, discussant has any questions. 122 00:19:49.260 --> 00:19:52.509 Julia He: And also the audience, if it has any questions. 123 00:19:52.780 --> 00:20:09.859 Jamie Hartmann-Boyce: Thank you so much. So yes, audience, please do submit questions through the Q&A, but first, I'm very happy to introduce today's moderator. I mean, today's discussant, sorry. Our discussant is Dr. Lauren Czaplicki, an associate scientist from Johns Hopkins Bloomberg School of Public Health. 124 00:20:09.940 --> 00:20:19.649 Jamie Hartmann-Boyce: Lauren studies the content and influence of tobacco marketing, particularly nicotine pouch marketing, in the U.S. Over to you, Lauren, for any initial thoughts or questions. 125 00:20:19.650 --> 00:20:29.380 Lauren Czaplicki: Thank you, and thank you so much, Julia, for the amazing, introduction to this topic and setting the stage for how important understanding this is. 126 00:20:29.380 --> 00:20:54.309 Lauren Czaplicki: And I think at this point, I just wanted to take a little bit of a bigger picture lens and try to understand, when thinking about tax policy, if you could talk a little bit about how tax policy in the U.S. works, or other international contexts, if that seems relevant. So are there any federally mandated taxes on to Tobacco products currently? I know you said that there's no federal 127 00:20:54.310 --> 00:21:18.560 Lauren Czaplicki: excise tax on OMPs, but anything that's relevant for us to know about how other tobacco products are taxed, and also how states or other localities might have authority to, to, have their own, measures, and whether any of that might be preempted by federal law. So, just kind of a broader overview of how taxes as a policy mechanism works. 128 00:21:19.140 --> 00:21:38.710 Julia He: Okay, okay, good. That's a great question. So, tobacco taxes actually are very different. For combustible cigarettes, in the U.S, we use a unified tax measure. You know, all taxes are levied on, when, 129 00:21:39.090 --> 00:21:51.199 Julia He: one package of 20 cigarettes, right? That's a unified taxes. We don't need to standardize, yeah. And then… but for other to Tobacco and nicotine product. 130 00:21:51.240 --> 00:21:56.450 Julia He: Packs are becoming, like, excess taxes are becoming complicated. 131 00:21:56.490 --> 00:22:15.859 Julia He: For example, e-cigarettes, you know, because there are many types of e-cigarettes, including open, open cigarettes, and closed system, open system cigarettes, and closed system cigarettes. And then some states tax, you know, on the… 132 00:22:15.910 --> 00:22:26.289 Julia He: you know, as we can see, you know, for the OMPs, you know, some states, you know, they just use various methods to tax e-cigarettes. 133 00:22:26.350 --> 00:22:39.470 Julia He: And for… for smoke-based Tobacco, you know, it's similar to OMPs, because as I, conducted, you know, the email inquiries to… directly to the, you know. 134 00:22:39.540 --> 00:22:55.220 Julia He: each state's, tax agencies, and many states told me that, you know, in their states, OMP taxes are… OMPs are taxed at the, you know, similarly to, moist enough. 135 00:22:55.220 --> 00:23:06.690 Julia He: So, you know, for… for moist enough, because, for smoothies to Tobacco, there are many, there are several types of smoothies to Tobacco. For example, they, they have, they include moist enough. 136 00:23:06.690 --> 00:23:25.300 Julia He: dry snuff, snooze, right? And, what, what's, what's the other one? Snooze, and also, oh, sorry, yeah, there's four types, yeah, four types. I did a paper on this, on this one. So, so you, yeah, the, 137 00:23:25.560 --> 00:23:40.609 Julia He: So the taxes, excess taxes on smallest tobacco need also to be standardized in order, you know, they can be used to examine, okay, what is the tax… tax effects on use behaviors, right, on sales? 138 00:23:40.610 --> 00:23:45.900 Julia He: So, without these unified measures, we cannot do the statistical analysis. 139 00:23:45.900 --> 00:24:00.099 Julia He: And for OMPs, you know, it's, it's, it is very similar, you know, to, smokeless tobacco. So, in the beginning, you know, many states, they tax OMPs just like, smoke, moist enough. 140 00:24:00.300 --> 00:24:16.600 Julia He: But for other states, you know, like, they adopt adolarium taxes, which is the percent of the prices. They can use the manufacturer price as the base price, or the wholesale price as the base price. 141 00:24:16.600 --> 00:24:25.750 Julia He: So, yeah, so this variety, you know, they create such a heterogeneity in the PEX methods. So, which… 142 00:24:26.120 --> 00:24:36.790 Julia He: you know, make it… makes it very difficult to compare tax levels across states. So that provides the motivation for this, present study. 143 00:24:37.150 --> 00:24:41.070 Lauren Czaplicki: Yeah, that's so helpful to kind of have that broader picture of how 144 00:24:41.420 --> 00:24:59.110 Lauren Czaplicki: this all works, especially as we're thinking about price as a policy lever, you know, wanting to have a price that's accessible to adults who might want to use this product. If they already are using tobacco, might want to use this product to help quit, versus, you know, maybe making it 145 00:24:59.110 --> 00:25:10.059 Lauren Czaplicki: cost enough to deter young people who have less, you know, money to spend on these products. So, really interested to dig into your results and see what you have to say. Yeah. 146 00:25:10.060 --> 00:25:18.340 Julia He: Okay, okay, good, good. I will go ahead to present the results. Okay. Let me share my screen first. 147 00:25:20.040 --> 00:25:21.480 Julia He: Okay, good. 148 00:25:22.540 --> 00:25:24.739 Julia He: I will pre… sorry. 149 00:25:26.230 --> 00:25:41.280 Julia He: I will proceed to the… to the results. So this figure shows the, descriptive, results from the, you know, the… our, standardized weight-based taxes. So the first two bars. 150 00:25:41.500 --> 00:25:53.180 Julia He: presents the average tax rate, for the… using the time invariant price, which is the benchmark price. And the last two bars presents the results 151 00:25:53.360 --> 00:25:57.249 Julia He: The average tax, using the variant price. 152 00:25:57.350 --> 00:26:16.080 Julia He: And then we can see that the, Tam invariant, average, whey-based tax is, $4.2 per ounce, ranging from $4.2 per ounce to, $4.6 per ounce. 153 00:26:16.080 --> 00:26:21.910 Julia He: Depending on different, you know, markup rate assumption. And then the, average. 154 00:26:22.880 --> 00:26:31.010 Julia He: When we use the variant price, price level, the, the average 155 00:26:31.530 --> 00:26:40.090 Julia He: Weight-based tax range from 4.7 ounces to 5.1 ounces. 156 00:26:40.280 --> 00:26:42.019 Julia He: $1 per ounce. 157 00:26:42.470 --> 00:26:58.830 Julia He: And then this figure shows the corresponding, the standardized unit-based taxes. So, roughly speaking, so the time invariant average standardized taxes is about $1 per can, per standard can. 158 00:27:00.070 --> 00:27:03.169 Julia He: And then the right figure shows the… 159 00:27:03.330 --> 00:27:10.219 Julia He: the standardized OMG taxes from 2017 to 2025. 160 00:27:10.300 --> 00:27:24.990 Julia He: So, for… in nominal terms, we can see that the OMG taxes exhibit… exhibit an upward trend. However, in real terms, OMG taxes remain relatively stable. 161 00:27:25.170 --> 00:27:43.000 Julia He: Figure in the… on the left shows the… oh, the figure on the right shows the national average time invariant specific taxes. Figure on the left shows the average time invariant standardized specific taxes. 162 00:27:43.060 --> 00:27:50.319 Julia He: Which, you know, we restrict sample to only states that, have OMP taxes. 163 00:27:50.570 --> 00:28:03.460 Julia He: And then figure on the left shows that, you know, the, the average, when we restrict sample to, those states have… that have OMT taxes, the average 164 00:28:03.820 --> 00:28:08.000 Julia He: Standardized OMP taxes exhibit a downward trend. 165 00:28:09.080 --> 00:28:21.410 Julia He: And then, these figures shows the standardized ad valorem taxes. So, right figure shows the national average ad valorem taxes. So, the 166 00:28:21.410 --> 00:28:41.290 Julia He: assuming a 35% markup rate, the average at Bolarium taxes range from 45% in 2017 to 53% in 2025. However, when we restrict sample to those states that have OMP taxes. 167 00:28:41.400 --> 00:28:52.969 Julia He: the average The average, Adler taxes, exhibit a downward trend, you know, declining from. 168 00:28:52.970 --> 00:29:04.330 Julia He: 194% in 2017 to 135% in 2025, assuming a 35% markup rate. 169 00:29:05.080 --> 00:29:12.110 Julia He: And then this table illustrates the comparison of tax levels between different products. 170 00:29:12.400 --> 00:29:21.100 Julia He: the middle… the estimates in the middle three, columns are sourced from Coti's paper, and then the… 171 00:29:21.340 --> 00:29:30.849 Julia He: Estimates for the moist NAF, is sourced from, my previous paper published in 2024. 172 00:29:31.290 --> 00:29:44.679 Julia He: So, in this paper, assuming a 35% markup rate, OMPs, the standardized OMP, taxes is about, 92 cents. 173 00:29:45.120 --> 00:29:50.270 Julia He: 92 cents per can in the fourth quarter of 2023. 174 00:29:51.760 --> 00:29:57.530 Julia He: That corresponds to a $3.95 per ounce. 175 00:29:57.940 --> 00:30:06.030 Julia He: When expressed as a percentage of the cigarette tax… percentage of cigarette tax rates based on ounces. 176 00:30:06.600 --> 00:30:13.290 Julia He: OMPs are taxed at a 86% of cigarette taxes. 177 00:30:14.560 --> 00:30:20.389 Julia He: That is substantially higher, substantially higher than e-cigarettes and moist enough. 178 00:30:20.780 --> 00:30:22.330 Julia He: Well expressed. 179 00:30:22.560 --> 00:30:28.709 Julia He: As a percentage of cigarette tax rates based on equivalent units. 180 00:30:28.870 --> 00:30:30.589 Julia He: OMPs are text. 181 00:30:30.820 --> 00:30:36.680 Julia He: As a… at a nearly 29% of cigarette tax rates. 182 00:30:36.790 --> 00:30:42.089 Julia He: Which is also substantially higher than e-cigarettes and moist enough. 183 00:30:43.460 --> 00:30:50.689 Julia He: Then I will, proceed to talk about the OMP tax pass-through rates to prices. 184 00:30:51.390 --> 00:30:53.169 Julia He: The method. 185 00:30:53.460 --> 00:31:06.940 Julia He: that I use is I conducted 3 separate OIS models. The outcome variables are OMT prices at the 25th, 50th, and 75th percentile. 186 00:31:07.510 --> 00:31:23.539 Julia He: percentiles, and then that enables me to examine how the tax rates will vary across products with different price levels. And then the X, the independent variable is the standardized OMP tax measures. 187 00:31:24.540 --> 00:31:30.050 Julia He: The… in the primary analysis, I employed a two-way fixed effect. 188 00:31:30.350 --> 00:31:34.540 Julia He: And to test the robustness of my findings. 189 00:31:34.670 --> 00:31:43.309 Julia He: And we conducted two sensitivity analyses. First, we restrict sample to those states with specific taxes. 190 00:31:43.810 --> 00:31:51.869 Julia He: Second… we conducted a DCDH event study with continuous treatment. 191 00:31:52.350 --> 00:32:00.309 Julia He: And then these results… This table shows the estimates from the primary analysis. 192 00:32:00.450 --> 00:32:03.649 Julia He: So one can see that OMPs are… 193 00:32:04.350 --> 00:32:14.009 Julia He: For OMPs priced at the 25th percentile, the taxes were undershifted to prices. 194 00:32:14.120 --> 00:32:26.240 Julia He: However, for ONPs priced at 50th percentile, or… and… and 75th percentile, taxes are over-shifted to prices. 195 00:32:27.840 --> 00:32:33.280 Julia He: This… Table shows the results from the restricted sample analysis. 196 00:32:33.500 --> 00:32:44.960 Julia He: we can see a similar pattern, to, you know, the primary analysis. So, for lower-priced OMPs, taxes are undershifted. 197 00:32:44.960 --> 00:32:56.110 Julia He: for higher-priced OMPs, taxes are overshifted, or exactly shifted, even though, you know, these estimates are not statistically significant. 198 00:32:56.190 --> 00:33:04.529 Julia He: These results should be viewed with caution, because they are the small, number of observations. 199 00:33:05.760 --> 00:33:21.350 Julia He: And then, next, I will show the results from the DCDH approach. So, this graph shows the, we did not observe any significant tax pass-through, to prices, tax effects. 200 00:33:21.610 --> 00:33:26.430 Julia He: You know, for OMPs priced at the 25th percentile. 201 00:33:26.690 --> 00:33:38.829 Julia He: And then, next one, for the OMPs priced at the 50th percentile, we observed that the, the significant tax effects starting 202 00:33:39.580 --> 00:33:45.610 Julia He: Starting with the… the second, post, treatment period. 203 00:33:45.990 --> 00:33:59.369 Julia He: And the average cumulative, treatment effect is 0.8. That indicates that the… we observed… that indicates that the taxi effects are significant. 204 00:33:59.470 --> 00:34:07.610 Julia He: And then the, taxes are significant… can significantly increase, OMP prices. 205 00:34:07.760 --> 00:34:17.359 Julia He: We also observed that the principal tests show no significant pre-treatment effect. That provides the, 206 00:34:18.050 --> 00:34:34.380 Julia He: The, the assurance that, you know, the no, par… The assurance for the parallel time trend, parallel trends assumption, and that also strengthens the, validity of our causal estimates. 207 00:34:34.679 --> 00:34:44.299 Julia He: And then the next one shows the results for the… for OMPs priced at 75th percentile. And, similar to the… 208 00:34:44.310 --> 00:35:02.090 Julia He: the last figure, you know, taxes were exactly shifted, to, retail prices at the 75th percentile, level. And then the cumulative, effect is 0.95. 209 00:35:03.390 --> 00:35:10.409 Julia He: And then to conclude, you know, this, I will highlight the two main findings. First. 210 00:35:10.510 --> 00:35:20.789 Julia He: Our standardized tax measure showed that OMPs are priced at $4.30 per ounce. 211 00:35:20.790 --> 00:35:35.840 Julia He: or about $1 per standard can. This place OMPs, you know, the tax levels of OMPs comparable to cigarettes, and substantially higher than e-cigarettes and smoothies tobacco. 212 00:35:36.030 --> 00:35:40.809 Julia He: The… we also observed that the tax pass-through rates 213 00:35:41.030 --> 00:35:49.819 Julia He: for OMPs, you know, for lower-priced OMPs, taxes are either not or undershifted to prices. 214 00:35:50.140 --> 00:36:07.349 Julia He: depending on the modeling choices. For, middle, you know, for the medium, the, the OMPs at the medium level are, or, 75th, percentile prices, taxes may be under exactly, or over-shifted to prices. 215 00:36:07.460 --> 00:36:24.830 Julia He: And these findings are consistent with existing literature, you know, we observed in cigarettes and smokeless tobacco, which, you know, like, generally find that cigarettes are fully or over-shifted to prices, and higher 216 00:36:25.410 --> 00:36:31.500 Julia He: Tax pass-through rates are observed for higher-priced, tobacco products. 217 00:36:32.360 --> 00:36:46.120 Julia He: And then I would also, you know, discuss the potential, the explain… the explanations of the, the tax pass-through rate that we observed in this study, you know. 218 00:36:46.210 --> 00:37:02.949 Julia He: OMP market is highly concentrated, as OMPs are dominated by several large tobacco companies. In such markets, you know, companies may use a similar strategy in their response to 219 00:37:02.950 --> 00:37:08.889 Julia He: Cigarette taxes by over-shifting taxes to prices for profit. 220 00:37:09.230 --> 00:37:17.110 Julia He: However, you know, OMPs represents a relatively new and rapidly growing market. 221 00:37:17.540 --> 00:37:22.389 Julia He: Companies may also have the incentive to undershift taxes. 222 00:37:22.520 --> 00:37:27.389 Julia He: So that, you know, they can maintain, pricing, competitiveness. 223 00:37:28.130 --> 00:37:34.530 Julia He: and then to, and then to encourage people to use, OMPs. 224 00:37:34.850 --> 00:37:41.450 Julia He: And then we, this, this study also, you know, either, highlights the, 225 00:37:41.510 --> 00:37:54.379 Julia He: the… the need for future, for future research. You know, the, in the future research, we can examine how the OMP taxes can influence prices. 226 00:37:54.380 --> 00:38:04.179 Julia He: how OMP taxis can influence consumer responses, can influence, consume, the use behaviors or product switching behaviors. 227 00:38:05.330 --> 00:38:11.419 Julia He: Okay, that's pretty much, all that, all that I have. Thank you so much. 228 00:38:12.370 --> 00:38:21.340 Jamie Hartmann-Boyce: Thank you so much! So, I would like to, again, turn over to our discussant, and for people listening, please do put chat questions in the Q&A. 229 00:38:21.870 --> 00:38:31.230 Lauren Czaplicki: Great. So thank you so much again, Julia, for preparing, such an engaging kind of conversation and talk on this topic. 230 00:38:31.230 --> 00:38:52.119 Lauren Czaplicki: And I think that, what you're saying about the tax rates being, similar to cigarettes is really… is very interesting, both in kind of the… the standardized level and in what maybe we're seeing with over-shifting or undershifting costs to consumers. And I was wondering if you could… 231 00:38:53.300 --> 00:39:18.119 Lauren Czaplicki: I take the point that O&Ps are trying to break through, in the marketplace, and so maybe that's why there's some under-shifting. But could you say a little bit more about maybe the brands that we're seeing in the 25, 25th percentile? Are they, like, sort of the market leaders, or are they more, the brands that maybe have less of a market growth? 232 00:39:18.400 --> 00:39:42.420 Lauren Czaplicki: Like, kind of… if you're able to parse through, like, why that undershifting might be happening in terms of, trying to, in terms of the brand kind of composition, if that's available in the data that you looked at, as well as kind of what that might be saying about potentially, like, how these products could reach youth or other consumers, with kind of undershifting the cost. 233 00:39:43.330 --> 00:40:01.219 Julia He: Yeah, yeah, that's a good question. So, actually, you know, in the, because we extract the OMP prices from the news and retail scanner data, and then when we look at the, the detailed, you know, the each sales record, you know, when we 234 00:40:01.430 --> 00:40:13.560 Julia He: actually, you know, we… we aggregate the NRSD, you know, the sales data to state and month level. So, but before the aggregation, I… 235 00:40:13.960 --> 00:40:20.360 Julia He: Look at… look at some, you know, sales record, especially for those You know, like, 236 00:40:20.710 --> 00:40:36.340 Julia He: The price for each, those sales records that, you know, you can see the price are extremely low. You know, some of the sales records, they even indicate, like, less than $1. 237 00:40:36.490 --> 00:40:45.269 Julia He: So that may indicate, you know, in some period, you know, some retailers may have, like, a price promotion. 238 00:40:45.300 --> 00:40:56.709 Julia He: So, yeah, some promotions were going on, so that, you know, greatly decreased the, the, the, the price of OMPs. 239 00:40:57.710 --> 00:41:14.920 Lauren Czaplicki: Okay, that was another question that I had, was sort of how does the discounting and the promotions get accounted for, in the standardization process? And so, so you can see it in the data, but, so how, like. 240 00:41:14.920 --> 00:41:25.889 Lauren Czaplicki: Could you maybe walk us through how… how those… those maybe seasonal, ticks, like, are accounted for, and the process that you use to standardize the… the tax rate? 241 00:41:31.680 --> 00:41:36.540 Julia He: When I standardized the OMP taxes, 242 00:41:36.920 --> 00:41:40.940 Julia He: Actually, I used the, for the… 243 00:41:41.130 --> 00:41:48.730 Julia He: time invariant measure, I… I construct a benchmark price, which is a fixed price level. 244 00:41:48.980 --> 00:41:55.510 Julia He: So that benchmark price applies to all states, all time periods. 245 00:41:55.510 --> 00:41:56.290 Lauren Czaplicki: Okay. 246 00:41:56.290 --> 00:42:05.389 Julia He: Yeah, so that will give us a tax measure that is free of market change, free of tax pass-through change. 247 00:42:06.580 --> 00:42:10.260 Julia He: That only reflect the change in tax rates. 248 00:42:11.370 --> 00:42:20.730 Julia He: So that, you know, that will not, you know, the, so the product, promotion will not affect the benchmark price. 249 00:42:21.010 --> 00:42:21.660 Lauren Czaplicki: Okay. 250 00:42:21.660 --> 00:42:22.270 Julia He: Yeah. 251 00:42:22.920 --> 00:42:34.739 Julia He: And then… but for the time-varying measures, the price levels, because we use the varying price, right? The prevailing price for each state. 252 00:42:34.970 --> 00:42:35.330 Lauren Czaplicki: each month. 253 00:42:35.330 --> 00:42:49.720 Julia He: Yeah. And then that, you know, if, the product, there is a product promotion going on, that will greatly affect the, the time-varying measures of, yeah, OMPs. 254 00:42:50.010 --> 00:42:50.790 Julia He: Paxis. 255 00:42:50.790 --> 00:42:52.670 Lauren Czaplicki: It's a complex marketplace. 256 00:42:52.670 --> 00:42:53.020 Julia He: Yes. 257 00:42:53.360 --> 00:43:02.549 Julia He: Well, yeah, that's why we observe a great, a greater, you know, variation in the, time-varying measures. 258 00:43:02.820 --> 00:43:03.600 Julia He: Yeah. 259 00:43:04.480 --> 00:43:11.959 Lauren Czaplicki: Do you, so with Nielsen data, could you talk a little bit about, maybe this, the… 260 00:43:12.000 --> 00:43:36.950 Lauren Czaplicki: there are a lot of strengths to it, but maybe some of the limitations, and to the best of my understanding, online sales aren't always accounted for. So do you have any thoughts on how online sales might be the same or different than what we're seeing in the brick-and-mortar retail environment? And any thoughts on how you might want to go about understanding that in your own, like, future research as well? 261 00:43:37.390 --> 00:43:45.360 Julia He: Okay, good, good, good question. Yeah, so we use the news IQ Retail Scanner data, that's a, 262 00:43:45.410 --> 00:43:50.520 Julia He: rig on the mortar data, right? Because, but, you know, the, 263 00:43:50.520 --> 00:44:09.789 Julia He: The, according to a previous literature, I think, a laborer published a paper, you know, talking about the, how representativeness of the, the NRSD data. So, actually, you know, according to what they found on, 264 00:44:09.790 --> 00:44:18.770 Julia He: So the NRSD represents, you know, 80… I think it's 84% of total to Tobacco sales in the United States. 265 00:44:19.290 --> 00:44:25.199 Julia He: Based on the, you know, because OMPs are dominated by large tobacco companies. 266 00:44:25.390 --> 00:44:38.460 Julia He: So we expect that the OMPs have a similar, you know, retail channel than, you know, traditional cigarettes. So that's why we expect, you know, the OMP sales is, 267 00:44:38.460 --> 00:44:56.380 Julia He: is well represented in this data set. However, you know, online sales, you know, besides the brick and mortar sales, you know, online sales, you know, we know there are a great portion of OMPs, you know, occurred, you know, online. 268 00:44:56.380 --> 00:45:07.239 Julia He: But we do not have the data for online sales… well, for online sales, so we… we are unable to expect… to estimate how large is the online sales. 269 00:45:09.020 --> 00:45:12.119 Lauren Czaplicki: Okay, yeah, and any, like… 270 00:45:12.480 --> 00:45:25.370 Lauren Czaplicki: Any… any thoughts or any resources you can share on, like, how… how we might even go about understanding the online sales environment? Like, is… 271 00:45:25.810 --> 00:45:45.060 Lauren Czaplicki: Yeah, I guess everything is proprietary, I suppose, in terms of that data getting shared, but it seems like such a gap in kind of our understanding, and so, yeah, I don't know if there's anyone… any conversations in your field about, like, how to better characterize the online sales market. 272 00:45:47.340 --> 00:46:04.780 Julia He: Actually, I… I'm sorry that I do not have estimates, you know, because the online sales data is not available, so we… we do not have estimates of, you know, how much is the online… how large is the online sales, you know. 273 00:46:04.990 --> 00:46:11.170 Julia He: But we do have the, you know, the news and retails, the, you know, the news and sales data. 274 00:46:11.170 --> 00:46:11.850 Lauren Czaplicki: Yeah. 275 00:46:11.850 --> 00:46:23.079 Julia He: Using this data, we can analyze, you know, how OMP sales has increased, and how this market, you know, we can analyze how much… how many brands in this data. 276 00:46:23.080 --> 00:46:34.060 Julia He: And how are the sales volume of each brand, and how this, you know, this market evolves. That's what we can do. But for online sales, you know. 277 00:46:34.060 --> 00:46:37.150 Julia He: Just, you know, the inability of the data, you know? 278 00:46:38.360 --> 00:46:52.710 Lauren Czaplicki: Yeah. Yeah. I think, like, those, I can pause here if there are any, Q&A questions, I think, Jamie, if you wanted to share. I know maybe some of them have been answered, but we can also have an online discussion. 279 00:46:52.710 --> 00:46:58.439 Jamie Hartmann-Boyce: Sure, that sounds great. Thank you both so much for the really interesting discussion. It's such a complex and… 280 00:46:58.580 --> 00:47:03.790 Jamie Hartmann-Boyce: highly Highly complex market, so… 281 00:47:04.210 --> 00:47:20.290 Jamie Hartmann-Boyce: C has answered a lot of these questions, but I do have a new one that's just come in from Erika Mansur, who's asked, did your data set reveal whether states with more comprehensive nicotine regulation beyond taxation experience different pricing or sales trends than states relying primarily on excise taxes? 282 00:47:20.290 --> 00:47:25.909 Jamie Hartmann-Boyce: And as new nicotine analogs and products enter the market, do you believe existing tax structures are flexible enough 283 00:47:25.910 --> 00:47:31.869 Jamie Hartmann-Boyce: To capture those products, or will legislatures need to revisit their tax statutes? 284 00:47:33.510 --> 00:47:34.030 Jamie Hartmann-Boyce: Okay. 285 00:47:34.030 --> 00:47:36.799 Julia He: Oh, it's a long question. It's a long question. 286 00:47:36.800 --> 00:47:37.350 Jamie Hartmann-Boyce: You can break it down. 287 00:47:37.350 --> 00:47:41.339 Julia He: A lot! Yeah, yeah, yeah. Yeah. Yeah, can you break it down? 288 00:47:41.340 --> 00:47:42.020 Jamie Hartmann-Boyce: Yeah, arsen 289 00:47:42.630 --> 00:48:02.630 Jamie Hartmann-Boyce: So the first part of that question is whether your dataset reveals if states with more comprehensive nicotine regulations, so not just taxes, but, you know, whatever other regulations might be in place, experience different pricing or sales trends than states that relied primarily on excise taxes as a way to regulate these products. 290 00:48:03.000 --> 00:48:06.580 Julia He: Okay, yeah, so, good question. So, 291 00:48:06.900 --> 00:48:19.960 Julia He: about the regulation, as far as I know, you know, some states, for example, California, and some, you know, localities, you know, they, imposed the flavor restrictions. 292 00:48:19.960 --> 00:48:28.679 Julia He: And that flavor restrictions also includes OMPs. Well, some states, they do have flavor restrictions on other tobacco products. 293 00:48:28.720 --> 00:48:36.139 Julia He: However, that flavor restrictions do not apply to OMPs. So that's a big… 294 00:48:36.250 --> 00:48:45.009 Julia He: You know, heterogeneity in how those flavor restrictions are applied, what products are, you know. 295 00:48:45.500 --> 00:48:51.610 Julia He: do they apply to? So that's, yeah, I think that's, 296 00:48:51.790 --> 00:49:05.719 Julia He: And also, you know, in recent years, more researchers, they, they also bring up a question on the, the pack size, how the pack size will influence the OMP sales. 297 00:49:05.900 --> 00:49:12.460 Julia He: So… so as far as I know, you know, I… 298 00:49:12.730 --> 00:49:16.029 Julia He: I do not know whether FDA has 299 00:49:16.430 --> 00:49:28.960 Julia He: ever, you know, like, issued, regulation on park, pack size, that's… I actually… I… I don't know, I don't know, so, yeah, so, 300 00:49:29.120 --> 00:49:39.000 Julia He: And then… For the comprehensiveness, of the other… other regulations that's, 301 00:49:39.690 --> 00:49:44.979 Julia He: Yeah, so for… yeah, flavor restrictions is a big one, so… 302 00:49:45.390 --> 00:49:51.160 Julia He: Yeah, and, many… several states has already have that regulation. 303 00:49:51.340 --> 00:49:52.100 Julia He: Yeah. 304 00:49:52.830 --> 00:50:06.430 Jamie Hartmann-Boyce: And is that something that we could… that you have, or theoretically could look at in your data set, right? Whether the… that comprehensive nicotine regulation, as opposed to relying primarily on taxes, is impacting pricing or sales of pouches? 305 00:50:09.270 --> 00:50:25.120 Julia He: taxes do have an effect on the pricing of OMPs. That's what I did in the… in these present studies, and we observed significant tax effects, right? And for, you know, from the event study. 306 00:50:25.560 --> 00:50:27.950 Julia He: But… if other… 307 00:50:28.500 --> 00:50:40.720 Julia He: factors also influence the pricing of ONPs. You know, I did another study, you know, which I presented in the Tobacco regulatory science meeting. 308 00:50:40.720 --> 00:50:41.270 Jamie Hartmann-Boyce: study. 309 00:50:41.460 --> 00:50:46.950 Julia He: Yes, that one, you know, you know, I, I found that the, 310 00:50:47.140 --> 00:50:50.010 Julia He: OMPs are, you know, the, 311 00:50:50.260 --> 00:50:54.940 Julia He: OMP sales are higher for those flavored products. 312 00:50:55.260 --> 00:50:58.540 Julia He: Okay. So, yeah. And also, you know… 313 00:50:58.870 --> 00:51:06.800 Julia He: you know, OMP sales are higher, you know, OMP sales per capita are higher in rural areas than in urban areas. 314 00:51:06.980 --> 00:51:14.829 Julia He: But… and also, you know, I found that OMPs are priced lower in rural areas than in urban areas. 315 00:51:14.940 --> 00:51:29.130 Julia He: So this, but why did, tobacco industry price OMP differently in urban and rural areas? That is a question that we need to examine, right? 316 00:51:29.380 --> 00:51:31.409 Julia He: That's a question, yeah. 317 00:51:31.410 --> 00:51:35.360 Jamie Hartmann-Boyce: Yeah, really interesting. You've got a busy couple of days presenting today. 318 00:51:35.360 --> 00:51:36.260 Julia He: I love it. 319 00:51:36.260 --> 00:51:36.850 Jamie Hartmann-Boyce: Yeah. 320 00:51:37.320 --> 00:51:41.630 Jamie Hartmann-Boyce: There's another question within this question, so… 321 00:51:42.190 --> 00:51:59.740 Jamie Hartmann-Boyce: As new nicotine analogs, or new other variations on products, new products enter the market, do you think that existing tax structures are flexible enough to capture those products, right? To, for example, apply to nicotine analogs, or do you think legislatures might need to revisit their tax statutes? 322 00:52:01.250 --> 00:52:03.860 Julia He: You know, as… 323 00:52:03.980 --> 00:52:10.480 Julia He: It's unlike cannabis, you know, some of the states tax cannabis based on their potency level. 324 00:52:10.690 --> 00:52:16.540 Julia He: However, I… OMPs are not taxed based on the nicotine concentration. 325 00:52:16.940 --> 00:52:24.250 Julia He: Right So that's, that's something, you know. 326 00:52:25.080 --> 00:52:28.019 Julia He: State legislators may consider, you know. 327 00:52:28.020 --> 00:52:28.450 Jamie Hartmann-Boyce: in, you know. 328 00:52:28.450 --> 00:52:39.950 Julia He: in the future, you know, whether tobacco products, especially like e-cigarettes, you know, these e-cigarettes also vary by nicotine concentration, right? 329 00:52:40.290 --> 00:52:46.610 Julia He: coaching strengths. So… Yeah, that's, and also we need signs from, 330 00:52:47.050 --> 00:53:03.669 Julia He: from, biostatistics and, from randomized control trials, you know, whether, you know, how those, nicotine strengths will influence, health outcomes. So we also need data from that part. 331 00:53:04.110 --> 00:53:04.900 Julia He: Yeah. 332 00:53:05.250 --> 00:53:10.300 Jamie Hartmann-Boyce: Yeah, absolutely, and then you've got nicotine analogs, which might be an even, 333 00:53:10.530 --> 00:53:13.220 Jamie Hartmann-Boyce: Different but related part of that picture. 334 00:53:13.950 --> 00:53:27.229 Jamie Hartmann-Boyce: Particularly when thinking about nicotine strength. All right, well, thank you so much. I don't think we have any other questions open in the Q&A. Lauren, was there anything else you wanted to add before we close out? 335 00:53:27.440 --> 00:53:46.179 Lauren Czaplicki: I did, on the point of standardization, I do think it's interesting to look at other countries. So recently, Bangladesh actually, passed a law to standardize the size and the shape of their smokeless tobacco products. 336 00:53:46.180 --> 00:54:11.150 Lauren Czaplicki: They had a wide variety. I think with these nicotine pouches, at least, we're seeing kind of a standard shape and quantity, but other things like gums and lozages, those are, you know, come in variable sizes, and so I think this is a case where looking to, like, what other countries are doing and complementary policies is really interesting, because I can only imagine that standardizing a shape and size of something would harm 337 00:54:11.150 --> 00:54:29.750 Lauren Czaplicki: some of the tax structure around how things are implemented, and make it a lot easier, at least, to administer a tax-related system. So that's just a little bit of context from an international perspective as well. So, yeah. 338 00:54:31.100 --> 00:54:44.739 Jamie Hartmann-Boyce: Thank you so much for sharing that. Well, I think that closes us out, then. Thank you all so much. Thank you for the wonderful presentation and wonderful discussion and great questions, and I will hand over to our MC. 339 00:54:46.150 --> 00:54:55.919 Parisa Moghaddam: We are out of time. Thank you to our presenter, moderator, and discussant. Finally, thank you to the audience of nearly 110 people for your participation. Have a Top Snatch weekend!