Economic and econometric methods to measure the illicit tobacco trade: A scoping review

TL;DR

This review explores economic and econometric methods used to measure the illicit tobacco trade and highlights the need for better health equity focus in future research.

Contribution

The paper provides a comprehensive overview of methods for measuring illicit tobacco trade and emphasizes the importance of health equity in method selection.

Findings

39 studies were reviewed, with 16 using consumption gap analysis and 23 using other econometric models.

Consumption gap analysis is effective for market trends but limited in subpopulation and policy impact analysis.

Only six studies addressed health equity, indicating a need for more equity-focused research.

Abstract

This scoping review aimed to identify suitable economic and econometric methods for measuring the illicit tobacco trade. We searched six key databases for public health and economics papers (PubMed, CINAHL, EMBASE, EconLit, ABI/Inform, and Medline), two economic working paper platforms (SSRN and IDEAS), and grey literature via Google and expert-identified articles. Initial screening was undertaken by all authors, with at least three authors conducting a second screening and final paper selection. We included English-language papers (published from 2010 to July 2023) that applied economic or econometric models to illicit tobacco or related topics. We examined the methods, assessing their strengths and limitations from a health equity perspective, and evaluated their applicability to priority populations (rather than assessing the quality of individual models). The review included 39 studies: 16 applied consumption gap analysis (CGA), and 23 used other economic or econometric models (i.e., Exponentiated, Discrete Choice, Extended Cost–Benefit Analysis and A Static Partial Equilibrium, Consumption, Risk Prediction, A Forward-looking Behavioural, Integrated Micro-Macro Demand, Endogenous Switching Regression, Multiple and Non-Linear Regression, Dynamic Projection, Demand-driven Analytical, Econometric Regressions and Modelling and Two-way Fixed Effects models). CGA was primarily used to estimate the size and trends of the illicit tobacco market, whereas other models assessed and quantified past, existing, or potential behaviours related to engagement with tobacco and other products, including illicit tobacco. Only six of the 39 studies addressed health equity. Measuring the illicit tobacco trade is challenging due to its covert nature, methodological limitations, and scarce high-quality data. Method selection depends on the research objective: CGA is suitable for assessing national market trends but is limited in evaluating subpopulations or future policy impacts. Other non-CGA-based economic and econometric models are better for analysing or predicting user behaviour, including from a health equity perspective. Implications for public health: Measuring the illicit tobacco trade is challenging. This review identified a wide variety of economic or econometric methods on this topic and highlighted the need for a greater equity focus when applying these methods. Triangulating findings across the various methods is important moving forward.

Figures

Flow chart for the study selection using the PRISMA flow diagram.

Full text

Introduction

The World Health Organization (WHO) defines illicit tobacco trade as “any practice or conduct prohibited by law that relates to the production, shipment, receipt, possession, distribution, sale, or purchase of tobacco, including any practice or act intended to facilitate such activity.” [1]. The WHO had estimated that about 10% of all tobacco products consumed globally are illicit [2].

The tobacco industry often highlights the potential for an increase in illicit tobacco as a strategy to delay or reverse the implementation of tobacco control policies, while at the same time engaging in the illicit tobacco trade [3]. For example, in 2024, the newly elected National Party-led coalition New Zealand (NZ) government quickly repealed the previous government’s world-leading ‘Smokefree Environments and Regulated Products (Smoked Tobacco) Amendment Act’, citing, in justification, claims of an increase in the availability of illicit tobacco based on industry-funded studies that estimate that the illicit trade was increasing [4,5]. However, independent analyses using consumption gap analysis (CGA) indicated a fluctuating but downward trend in illicit tobacco in NZ between 2012 and 2023 [6]. According to data collected from NZ Customs, many different types of illicit tobacco were seized during this period – illicit cigarettes, illicit loose tobacco imported from other countries (especially Tonga), chewing tobacco, water pipe tobacco, and domestically grown and produced loose tobacco [7]. Under the NZ Customs and Excise Act 2018, adults are permitted to cultivate up to 5 kg of tobacco annually for personal use, but the sale or distribution of home-grown tobacco is prohibited and illegal [8].

One reason for the different estimates of the size of the illicit tobacco trade is that it is inherently difficult to measure [9]. Researchers and international organisations, such as the World Bank and Tobacconomics, have recommended various methods to measure the illicit tobacco market. These methods range from surveys of people who smoke tobacco (with or without examination of cigarette packs), discarded pack surveys, interviews with key stakeholders (e.g., Customs officials), CGA, and economic modelling (using econometric analysis) [10–12].

CGA examines the difference between estimated tobacco consumption and legal sales [11]. Econometrics uses economic theory, math, and statistics to quantify economic phenomena [13], enabling estimates of how price changes impact illicit tobacco demand. Furthermore, such methods were used to analyse the link between legal sales and factors influencing tobacco demand and smuggling [14].

Economic methods have been widely used in tobacco control research for various purposes, including examining the relationships among taxation, price, consumption, and health outcomes [15,16].These approaches have also been applied to model nicotine addiction within a framework of rational economic behaviour [15,17].In addition, economic models can be used to assess how cigarette taxation may shift demand for other tobacco and nicotine products through substitution effects by estimating cross-price elasticities and relative price responses [15,16]. Furthermore, economic methods are widely used to evaluate the impact of tobacco control policies on tobacco demand and use [16]. Finally, economic analyses—such as cost–benefit and economic impact analyses—have been employed to assess the overall economic contribution of tobacco [15].In the context of illicit tobacco trade, econometric modelling is used to estimate tax avoidance and evasion by comparing predicted tax-paid sales with observed sales, with the difference interpreted as illicit consumption; this approach has been applied to measure legal cross-border shopping, direct low-tax purchases, and illegal bootlegging in a specific country and to a more limited extent in global and regional estimates [9,15]Generally, it is recommended that multiple methods are used to better understand the scale of, or changes in, the illicit tobacco trade [9].

It remains unclear which economic or econometric methods or models are most appropriate for measuring illicit tobacco trade or use in NZ, an island nation where overall smoking prevalence has declined but substantial inequities persist across population groups [18], particularly in the context of potential implementation of nicotine reduction policy. It is important to examine whether such methods and models consider health equity while measuring illicit tobacco [19].

We undertook a scoping review to identify economic or econometric methods that could be applicable for measuring changes in the extent of the illicit tobacco trade and how these methods could be used to measure differences among various sub-groups of the population, thus promoting a health equity perspective [20]. The focus was particularly relevant in the NZ context and other similar contexts, where the prevalence of tobacco use varies significantly among different ethnic groups and socio-economic strata.

Methodology

The scoping review protocol was developed in June 2023 and registered with the Open Science Framework (OSF) [21]. The review followed the scoping review guided by the University of South Australia and the Joanna Briggs Institute (JBI) manual for evidence synthesis [22]. We used the criteria outlined in the PRISMA extension for scoping reviews for reporting the review findings [23]. In July 2023, the protocol’s literature search strategy was revised, followed by a further revision in May 2024 that integrated feedback from peer reviewers.

Research questions

The research questions were:

What economic or econometric methods should be used to measure the size of the illicit tobacco trade?What strengths and limitations do these methods have when measuring illicit tobacco use from a health equity perspective?Can these methods be used to assess the size and impact of the illicit tobacco market in priority populations (e.g., subpopulations with higher smoking prevalence than the general population, such as Indigenous peoples, and people with low education)?

Search strategy

The research question followed the population-concept-context framework to determine relevant search terms:

Population: Active tobacco usersConcept: Economic or econometric methodsContext: Global and New Zealand.

The initial search strategy was tested in PubMed, followed by a preliminary screening of studies. The Boolean operator ‘AND’ was used to link the main search concepts. A ‘NOT’ operator was then added to refine the results and remove irrelevant articles. An overview of the final search strategy is provided in Table 1.

Table 1: Search strategy.

Five databases (PubMed, CINAHL, EMBASE, EconLit, and ABI/Inform) were searched using the search terms (S1 File, Table A2). Grey literature was searched using Google, following the methods suggested by the University of Otago, New Zealand [24]. The first search was conducted in July-August 2023 and was extended in April 2024 to include Medline and two economic working paper platforms (SSRN and IDEAS) recommended by experts in economics at the University of Auckland (S1 File, Table A3).

Study selection

Studies were identified, screened, and selected in accordance with PRISMA guidelines [25] (Fig 1) was conducted using the free version of Rayyan Software [26] that allowed multiple researchers to participate online by using the eligibility criteria in Table 2. All five authors screened study titles. Abstracts were then screened by at least three authors, with the final selection made after reviewing the full papers and related appendices. Discussions were held when reviewers disagreed, with a resolution reached by consensus (based on the inclusion criteria (Table 2)).

Table 2: Inclusion and exclusion criteria for the scoping review.

Flow chart for the study selection using the PRISMA flow diagram.

Data extraction

Data extraction was undertaken by the first author using Microsoft Excel. The studies were grouped into two categories: those that applied CGA methods and those that used non-CGA methods. Two co-authors reviewed the extracted data. The titles for data extraction and synthesis are presented in Table 3.

Table 3: Data extraction and synthesis format.

Critical appraisal from a health equity perspective

We examined the strengths and limitations of these methods through a health equity lens, emphasising their relevance to subpopulations, including priority or vulnerable populations, rather than the quality of individual models. Priority populations included, but were not limited to, analyses focusing on specific ethnic groups, gender, socioeconomic status, and mental or physical health characteristics associated with increased vulnerability to tobacco use. Based on Huang et al.‘s proof-of-concept quality assessment framework for tobacco models [27], a checklist was used to assess whether studies evaluated the target population, included baseline and policy scenarios, conducted demand analysis, ensured model transparency, and examined equity approaches (S1 File, Table A5). Studies that used CGA were included as a single category in the critical appraisal, as they utilised the same methodological approach.

Results

Selection of sources of evidence

Overall, 759 papers were identified, of which 247 were subsequently removed as duplicates. A further 458 articles were excluded after the initial screening because they did not meet the inclusion criteria, leaving 512 records. Another 19 studies were removed during the second screening phase: 17 were excluded because they did not use the CGA method or economic or econometric models, one was excluded because it was not published in English, and one was excluded because it was published prior to 2010. Overall, 35 articles underwent full review (Fig 1). Additional searches in MEDLINE, IDEAS, and SSRN yielded four additional papers, bringing the total to 39 studies (Fig 1).

Characteristics of the studies

Of all studies, 38 were original papers, and one was the editorial. The studies were divided into two groups: CGA-related studies and studies using economic and econometric methods. Sixteen studies used the CGA method. Of these, ten studies were conducted in Asia, three in Africa, two in South America, and one in North America. Twenty-three studies used economic or econometric methods, 12 conducted in North America, five in Europe, three in Oceania, two in South America, and one in Asia.

Studies using CGA methods

Of the 16 studies using the CGA method (see Table 4 for a detailed synthesis of these studies). All monitored trends in the illicit tobacco trade and estimated its size within a specific country. The CGA method was applied with and without considering tobacco policy changes, allowing the researchers to evaluate trends in consumption patterns under varying conditions. The CGA method served to monitor the extent of the current and past illicit tobacco trade, which was ultimately useful to assess the trends of illicit tobacco trade over the past years, rather than estimating future trends in the illicit trade. CGA is grounded in a simple mathematical model: the estimated amount of illicit tobacco trade or consumption gap, representing the difference between the estimated amount of tobacco consumption and legal sales.

Table 4: Summary of characteristics of studies that applied CGA methods.

Nine of the 16 studies exclusively employed the CGA method [28–36]. Four other studies [37–40] incorporated the trade deficit method in their research and used both CGA and the trade deficit method. Trade deficit methods involved calculating tax avoidance by summing the reported volumes of tobacco exported from various countries to a specific country and cross-referencing them with the country’s importation records. One study [41] used the price threshold method. This method involved applying a price threshold on the last purchased tobacco of participants to distinguish legal tobacco from illegal tobacco. Another study analysed survey responses regarding smuggled cigarettes [42] and one study [43] estimated revenue loss due to the trade in illicit tobacco.

CGA methods require two major sources of data: demand data and supply data. Demand or estimated consumption data were primarily calculated using national survey data (12 of the 16 studies, Table 3). Supply or legal sales data were predominantly obtained from the customs and revenue sector (10 of the 16 studies, Table 4) or other government agencies, such as the Ministry of Trade (n = 1), Ministry of Health (n = 1), or Ministry of Finance (n = 1) of the respective countries (Table 4). In one study (40), researchers utilised data from Euromonitor International because country-level data were unavailable [44]. The study acknowledged that Euromonitor International’s illicit trade estimates were inconsistent; however, it relied on Euromonitor International’s registered sales data for certain countries, assuming that there are fewer incentives to manipulate data on tobacco production or legal sales.

An important aspect of correctly estimating demand or consumption data is the consideration of under-reporting. Under-reporting of cigarette consumption can cause issues when using the CGA method. To compensate for the under-reporting, two of the 16 studies utilised an ‘uplift factor’ (Table 4) [28,35]. The ‘uplift factor’ was calculated using the formula of legitimate consumption divided by total consumption for a particular year. Researchers multiply the estimated consumption by the uplift factor to achieve the final estimated consumption, which is more than the estimated consumption [9].

As part of sensitivity analyses, eight studies also used the ‘different percentages’ method, which assumes under-reporting from 0% to 40% (Table 4) [32–35,38–40,45], while one study [30] employed both the ‘uplift factor’ and ‘different percentages’ methods.

The CGA method was used to estimate the amount of, or trends in, illicit tobacco at a national level; however, it was not applied to specific regions within a country or sub-populations due to the method’s limitations and the limited availability of quality data. Therefore, equity aspects were not reflected in any CGA study.

Non-CGA related studies

Twenty-three studies that applied other economic or econometric methods were reviewed. All 23 studies focused on demand: 22 on tobacco and one on illicit cannabis [46]. Nine studies examined the illicit tobacco trade [42,47–54], either past or existing demand, or the potential demand for certain illicit products in the event of future policy changes. A summary of the models, their purposes, strengths, and limitations is presented in Table 5.

Table 5: Summary of non-CGA-based economic and econometric analysis with the purposes, strengths, and limitations of the models.

The Hursh and Silberberg’s exponentiated model was used in six of the 23 studies [48,49,55–58]. This behavioural economic model was used in these studies to analyse the price elasticity of various tobacco products, including illicit tobacco, by examining how changes in price, availability, and taxation policies influence consumer behaviour, product substitution, and demand shifts.

Five studies used discrete choice models [45,46,59–61]. Like the behavioural economic model, discrete models were used to assess the demand and preference for different tobacco products and marijuana and to test the preference for different smoking warning signs.

Another approach, the extended cost-benefit analysis, included the public health impacts and was holistic; it required extensive data and several assumptions. Static partial equilibrium was a focused model for tax and price simulation for cigarettes. In the case of tobacco, the scope was narrowed, and, with other potential market interactions apart from the illicit tobacco trade, such as substitution with other tobacco products, cross-border shopping, health care system implications, and macroeconomic effects, were not considered [62].

Acknowledging the strengths and weakness of different models, Tarantilis et al. applied three consumption models for comprehensive analysis of smoking behaviours: 1) conventional demand (simple to be applied, but ignores the role of addiction in driving behaviour, and time-dependent behaviours); 2) myopic addiction (accounts for addiction, but neglects the future potential consequences of current smoking behaviour, such as health deterioration or economic costs), and 3) rational addiction (considers both past and future consumption, but was based on the assumption that consumers behaved with perfect rationality) [63].

Risk prediction models were used to predict consumer behaviour under different tax policy scenarios, including illicit tobacco. However, such a model depended on several assumptions, such as a direct relationship between cigarette tax levels and smuggled cigarette consumption, minimal influence of tax changes on smoking initiation or cessation, and the adequacy of self-reported survey data as a proxy for illicit tobacco use because data on the illicit tobacco market were limited [51]. Similarly, a forward-looking behaviour model could help capture time-inconsistent (present-biased) preferences. However, the model involved complex parameter estimation and assumed rational decision-making, an assumption that may not be applicable to tobacco addiction [64].

The integrated micro–macro demand model developed by Tuchman (2019) incorporated addiction and persistence effects through a state-dependent framework, where past consumption increased the likelihood of current consumption. However, the model assumed rational behaviour and may omit unobserved influences on demand [65]. An endogenous switching regression model was useful for capturing tax avoidance behaviour and, therefore, could inform policy, including tax policy. However, it was methodologically complex and required detailed individual-level data on purchasing behaviour and tax avoidance. It also relied on several assumptions, such as the accuracy of self-reported cross-border purchases, the strong responsiveness of tax avoidance to price differentials, the rationality of consumer behaviour, and the absence of unobserved confounders once observable factors were accounted for [47].

Multiple and non-linear regression models captured complex, non-linear relationships and were used in policy evaluations on retail tobacco product display bans on smoking rates. The models required high-quality data, did not establish causality, and were sensitive to model specification [66]. Another model that could be used for policy evaluation was the dynamic projection model, which was used to evaluate whether regular tax increases would suffice for NZ to achieve its Smokefree 2025 goal. This model forecasted future smoking prevalence based on current trends and policy interventions. However, it oversimplified factors, assumed consistent trends [67].

A demand-driven analytical model was used to comprehensively analyse the impact of tax and price changes on the composition of the cigarette market, with particular focus on the shift between legal and illegal cigarette consumption [50]. The model’s limitations included the inability to accurately measure illegal cigarette consumption, which relied on simplifying assumptions and static analysis.

Econometric regression models (time-series and panel data regression techniques) provided comprehensive trend analysis, informed policy effectiveness, and assessed trends in the illicit market [53]. However, the model was limited by data accuracy, especially regarding the illicit cigarette market, and by static assumptions underlying the data-generating processes(58).Econometric modelling developed by Stoklosa (2020), using pooled time-series data and fixed-effects models, integrated temporal and cross-sectional data, controlling for unobserved heterogeneity, and provided policy-relevant insights for cross-border cigarette purchasing in the European Union countries. However, the model did not fully capture cross-border purchases, based on the assumptions of rational behaviour, and had limited external validity [52]. The two-way fixed effects model was used to analyse cigarette tax compliance using data from the first nationwide littered cigarette pack collection in the USA, and it informed the nationwide scope and policy on tax compliance. Since the model was based on discarded pack survey data (i.e., single time-point cross-sectional survey data), the packs may not represent the consumption patterns of the population, and the model assumed constant unobserved factors [54].

Finally, data were collected through a wide range of sources, including experiments (n = 9), surveys (including discarded pack surveys, n = 6), sales databases (n = 6), and various data sources, such as budgeted and actual revenue, prices, tax rates, and littered cigarette packs (n = 2). Table 6 provides details on the studies’ characteristics, including their objectives, scenarios, and data sources.

Table 6: Summary of the characteristics of studies using non-CGA-based economic or econometric methods.

Critical appraisal of the studies from health equity perspectives

Given their shared methodology and national-level geographical coverage, the CGA studies were collectively considered a single study for critique. Among the 23 studies using economic/econometric models, most (n = 17, 74%) also performed policy scenario analyses. All studies conducted demand analysis, with most (n = 17, 74%) providing supplementary materials. Only six (26%) of the 23 studies investigated the equity implications of the assessed policies (Table 7).

Table 7: Critical appraisal of strengths and limitations of the economic or econometric models from the health equity perspective.

Discussion

Overview of economic and econometric methods used

This review found that current literature about estimating the size of the illicit tobacco trade used one of two perspectives: 1) estimating the amount and trends of illicit tobacco trade using the CGA method, or 2) estimating or predicting illicit tobacco use using non-CGA-based economic models and econometric analyses to estimate the demand.

Strengths, limitations, and equity considerations of identified methods

The CGA method has been utilised to estimate both the current extent of illicit trade and historical trends, depending on the availability of data. However, the method has several limitations. It cannot be used to estimate future illicit tobacco trade. Although the method can generate state- or subpopulation-level estimates when sufficient data exist, limited data availability has resulted in its predominant use at the national level. These limitations mean that data for specific population subgroups are not available, which limits the method’s applicability whenconsidering health equity. One possible reason for this limitation is the nature of the demand and supply data, which are typically available only at the national level. In contrast, behavioural economic models (like Hursh and Silberberg’s exponentiated model) are used to analyse the price elasticity of various tobacco products, including illicit tobacco, to test whether changes in price, product availability, and taxation policies can significantly influence consumer behaviour, including patterns of product substitution and shifts in demand for illicit tobacco. Such models can be applied to analyse the past or existing demand for illicit tobacco and predict the future demand for illicit tobacco on policy changes. Discrete choice models could also be used to assess the past or existing demand for illicit tobacco and predict future demand. Including examining consumer preferences regarding various tobacco control policies [45,46,59–61]. Both behavioural economic and discrete choice models can be used to conduct sub-population analyses for priority populations; however, only a limited number of studies have taken such an equity perspective.

Cost-benefit analysis and partial equilibrium models [62] were useful for simulating tax policy changes’ fiscal and consumption effects, including estimates of the illicit market share. However, since they were generally not designed to provide estimates for specific population subgroups, health equity perspectives cannot be applied.

Consumption Models such as the Rational Addiction Model incorporated behavioural responses to price and income changes, helping to project shifts in legal and illicit consumption. The models could be adapted to estimate the responses of specific populations if the disaggregated data were available. Risk Prediction Models [51]and Forward-looking Behavioural Models [64]captured consumer responses to changing tax environments, including transitions to illicit products. These models could be applied to specific populations, provided relevant individual-level data were available.

Econometric Regression Models, including Time-Series, Panel Data, and Fixed Effects Models [52–54] provided statistical frameworks for evaluating long-term trends, cross-border effects, and tax compliance, which were indirect indicators of the illicit tobacco trade. These models effectively analysed trends over time and across regions or demographic groups; however, the data for specific populations were limited due to the availability and quality of data at the population-specific level.

An integrated micro-macro model of demand [65] was used to assess product substitution and could be applied to estimate the substitution between legal tobacco and illicit products. Such a model could be applied to specific populations, given that the model used both market and individual-level data. However, the models were data-intensive, and the availability of representative data for specific populations is often limited.

Switching regression models [47] and non-linear regression approaches [66] could identify the determinants and outcomes of tax avoidance behaviours, including the decision to engage in illicit purchasing. Such models could assess illicit purchasing behaviour among specific populations if disaggregated individual-level data were available.

Dynamic projection models [67] were employed for policy simulations, including investigating long-term goals (e.g., achieving national smoke-free targets). By integrating assumptions about the prevalence and growth of illicit trade, these models could estimate the extent to which illicit consumption may undermine progress toward smoke-free targets or reduce the effectiveness of taxation policies. Such models may also be used to assess smoke-free targets for disadvantaged or high-risk groups.

Implications for research, practice, and methodological advancement for illicit tobacco

In NZ, Phyo and Bullen (2025) applied CGA to assess the proportion of illicit tobacco in overall tobacco use, from 2012 to 2023 [6]. The trade comparison method could also be applied to this research to validate the estimates of the illicit tobacco market in NZ. If tobacco import and export data (from the concerned countries) to NZ are available from national and international data sources, the trade comparison method could be applied in the NZ context. However, since NZ’s smoking prevalence is very inequitable among different socioeconomic groups [18],it is crucial to supplement this method with other methods to estimate the illicit tobacco trade more accurately in NZ. Furthermore, NZ’s tobacco control policies are evolving in response to political efforts to achieve smoke-free goals [68]. Therefore, it is essential to anticipate potential changes in illicit tobacco use while accounting for forthcoming tobacco control measures.

Non-CGA-based economic or econometric models that assessed or predicted tobacco users’ behaviour in engaging with illicit tobacco could be very useful for filling the gap in estimating future illicit tobacco use among all tobacco users and specific populations in NZ. Behavioural economic models, discrete choice models, consumption models, risk predictions, and forward-looking behavioural models could be used to estimate behaviours related to illicit tobacco use. Econometric analyses to quantify tax avoidance behaviour could also be applied to the NZ context. However, cross-border shopping may not always be applicable in island nations like NZ.

Researchers collected data to assess future behaviours through experiments, such as tobacco market experiments, discrete-choice experiments, and simulated cigarette purchase tasks. Similar experiments or data collection under hypothetical policy scenarios could be applied to the NZ context, given that the Smokefree Environments and Regulated Products Amendment Regulations Act 2023 (to mandate a very low nicotine content standard for all tobacco, retailer reduction, and a smoke-free generation) has been recently repealed [69].

The behavioural economic models were mainly driven by product availability and price. Two such studies were conducted in NZ [57,58]. However, the studies did not assess potential illicit tobacco use. A similar experiment from a public health perspective using other potential factors influencing the behaviour of people who smoke, e.g., product availability and health knowledge, would be useful to investigate illicit tobacco use.

Overall, this review highlights that most economic models used to assess illicit tobacco trade have applied limited equity dimensions. The six studies that included subpopulation analyses conducted limited subgroup analyses based on selected sociodemographic and smoking-related characteristics, including age, sex, ethnicity, income, and smoking status. To strengthen future applications, the studies that applied economic or econometric models should incorporate disaggregated datasets, subgroup analyses, and equity-weighted parameters to better reflect the distributional impacts of tobacco control policies across vulnerable or priority populations. Integrating these approaches would enhance the capacity of existing models to assess not only overall effectiveness but also the fairness and inclusiveness of policy outcomes, thereby advancing a health equity perspective in tobacco control research.

The inclusion criteria for the review enabled identification of studies examining other forms of illicit trade, such as illicit alcohol or drugs, while the PCC framework focused specifically on active tobacco users. The use of broader inclusion criteria was intentional and enabled the identification of methodological approaches that could be transferable to illicit tobacco research. However, because the primary focus of this review was illicit tobacco, the search strategy excluded studies centred solely on illicit drugs. Although these additional studies primarily contributed to methodological insights rather than direct evidence on illicit tobacco markets, they were valuable in identifying adaptable analytical techniques—such as behavioural and econometric models—that could be refined and applied within illicit tobacco contexts.

Strengths and limitations

This review clarified the best available options for measuring the illicit tobacco trade from a market perspective and outlined the strengths and limitations of specific economic or econometric methods used for assessing current and potential behaviours related to the demand for illicit tobacco from an equity perspective. Strengths of the review included: 1) the broad literature search (that included grey literature), helping to ensure the review was comprehensive; 2) assessment of the application of economic and econometric methods assessing illicit tobacco use from a health equity perspective, and 3) our selection criteria meant studies on economic and econometric methods applied not only to illicit tobacco but also to other tobacco and nicotine products, and in one case, to other illicit goods such as marijuana. Several limitations should be acknowledged. First, no assessment of the individual models employed was undertaken. Further, due to resource limitations, only studies published in English were included. However, we extensively searched the key public health and economics databases, as well as added expert-suggested articles and grey literature. By doing this, we are confident there is minimal selection bias. Future reviews could address language bias by engaging multilingual collaborators or by targeted searches for key non-English studies.

Conclusion

Estimating the extent of the illicit tobacco trade presents challenges, not only because of its illicit nature but also because of the limitations of current methods for measuring it (and the often-limited availability of high-quality data). The choice of the most suitable economic and econometric methods for measuring the illicit tobacco trade is ultimately dependent on the research question. If the aim is to understand the current national illicit tobacco trade from the market side (and past trends), a CGA is most appropriate. However, CGA is not suitable for assessing illicit tobacco use in specific subpopulations due to limited data availability and for predicting the impact of future policy scenarios. If the aim is to assess the past, existing, and potential behaviours of tobacco users in engaging with the illicit tobacco market, economic models (e.g., behavioural economics, discrete choice, consumption, risk prediction, and forward-looking models) are best utilised, especially if a health equity perspective is required. Given the above, triangulation of data (i.e., CGA and other non-CGA-based economic or econometric models, alongside surveys of people who smoke tobacco and discarded pack surveys) remains the best pathway forward. However, consideration of health equity perspectives is essential.

Supporting information

S1 FileReview protocol.Full review protocol describing the objectives, inclusion criteria, search strategy, and methods used for data charting and synthesis, developed in accordance with the Joanna Briggs Institute framework for scoping reviews.(DOCX)

S2 FilePRISMA-ScR Checklist.Completed Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist outlining the reporting items addressed in this review.(DOCX)