The macroeconomic impacts of diet-related fiscal policy for NCD prevention: A systematic review

Economics and Human Biology 37 (2020) 100854

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The macroeconomic impacts of diet-related fiscal policy for NCD prevention: A systematic review Sarah Mounseya,* , Lennert Veermanb , Stephen Janc , Anne Marie Thowa a b c

Menzies Centre for Health Policy, University of Sydney Australia School of Medicine, Griffith University Australia The George Institute for Global Health Australia

A R T I C L E I N F O

A B S T R A C T

Article history: Received 11 August 2019 Received in revised form 19 January 2020 Accepted 20 January 2020 Available online 1 February 2020

Background: Diet-related fiscal policies are effective interventions to address non-communicable disease. However, despite these being economic policy instruments, there is little public health attention given to the evidence of macroeconomic impacts. This review aims to assess the global evidence for the macroeconomic impact of diet-related fiscal policies for non-communicable disease prevention on industry revenue, government revenue and employment. Methods: For this systematic review we comprehensively searched the bibliographic databases MEDLINE, OvidSP, EMBASE, Global Health, SCOPUS, CINAHL and ECONLIT, and Google Scholar for English peerreviewed studies or grey literature, with no date cut-off. Global interventions with a focus on diet-related fiscal strategies were assessed for the outcomes of industry revenue, gross domestic product, government revenue and employment. We excluded non-English papers. Findings: Eleven studies met the inclusion criteria. All studies were on sugar sweetened beverage taxation and one also included an energy-dense food tax. Nine were modelling studies and two used interrupted time series analysis based on empirical evidence. One study found potential employment increases because of taxation; two found no significant job losses and eight found reduced employment. Taxes reduced sales volume and revenue within the sugar/beverage industry. Government revenue generation was positive in all studies. One study considered redistribution of consumer and government spending to other goods and services; Interpretation: We found no robust evidence for negative macroeconomic impacts of diet-related fiscal policies, likely a reflection of the limited methodology used in the analyses. This review suggests that there is a need for more high-quality research into the macroeconomic impacts of diet related fiscal measures and similar to tobacco taxation, government should consider directing revenue generated towards complementary measures to generate employment and/or provide livelihood training for those affected. © 2020 Published by Elsevier B.V.

JEL classification: E62 H23 H25 H27 Keywords: Non-Communicable disease Fiscal policy Macroeconomic impact Diet Sugar-Sweetened beverages (SSBs)

1. Introduction The World Health Organization (WHO) has recommended fiscal policies as part of comprehensive intervention packages to improve diets and reduce non-communicable disease (NCD) risk (World Health Organization, 2011; Sassi et al., 2013; World Health Organization, 2015a). There is now a significant body of evidence indicating that unhealthy food and beverage taxes and subsidies on healthy food and beverages can improve diets and health and are likely to generate substantial revenue (World Health Organization,

* Corresponding author at: University of Sydney Camperdown Campus, City Road Sydney NSW 2006 Australia. E-mail address: [email protected] (S. Mounsey). http://dx.doi.org/10.1016/j.ehb.2020.100854 1570-677X/© 2020 Published by Elsevier B.V.

2015a, b; Thow et al., 2014, 2018; Cobiac et al., 2017; Lal et al., 2017; Manyema et al., 2016). Existing evidence for the impacts of fiscal measures has primarily focused on health, consumption, consumer behavior and revenue generation. However, potential economic impacts are also critical considerations for fiscal policy. Manufacturing, production and employment are likely to be affected by fiscal policies on food as well as employment in other parts of the food supply chain (Stiglitz, 2000). Industry actors have consistently resisted proposals for taxation with claims that this will negatively affect employment and other economic indicators. In Australia, for example, the Australian Beverage Council has successfully lobbied against a proposed tax on sugar-sweetened beverages (SSBs), bolstered by the claim, ‘Mexico’s 2014 taxes on unhealthy drinks and energy dense foods have been a failure: jobs have been lost,

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sales have rebounded, and the poorest families are experiencing the burden of the tax’ (Anand et al., 2015). Also, in response to job loss concerns, the Government of South Africa halved their proposed 20 % SSB tax to just 11 % (Hofman and Tugendhaft, 2017). Similar concerns were raised by the tobacco industry in the face of public health intervention – including taxes – to reduce tobacco consumption. However, provision of Articles 17 and 18 within the Framework Convention on Tobacco Control (FCTC) specifically addressed alternative and sustainable livelihoods for farmers still producing significant tobacco as well as protecting the health of those involved in tobacco, particularly in low- and middle-income (LMIC) countries. These provisions were critical to overcoming concerns about loss of employment (World Health Organization, 2005; Kulik et al., 2017). Evidence of wider economic implications of diet-related fiscal policy to improve dietary behaviors and health outcomes will thus provide a rounded perspective and understanding to help policy makers make informed decisions in a cross-sectoral policy context (Box 1). 2. Methods 2.1. Search strategy and selection criteria In this systematic review we followed Cochrane guidelines for systematic reviews (Higgins et al., 2019). We used the search terms ‘sugar sweetened beverage* OR SSB* OR fat OR diet AND tax* OR subsid* OR fiscal policy, together with specific terms for each outcome variable: employment impacts “employment OR job* OR unemployment OR work”; industry impacts “industry OR manufacture*”; agriculture impacts “agriculture”. We searched MEDLINE via Ovid SP (1946-present), EMBASE via OvidSP (1946present), Global Health via OvidSP (1910-present), SCOPUS, CINAHL, and ECONLIT. We completed a Google Scholar and hand search through reference lists of included papers, because grey literature has featured as an important contribution to the evidence. Finally, we reached out to experts for any papers in submission for publication. Inclusion criteria: 1. Study design: Either primary data from randomized control trials (RCTs), cross-sectional studies, case studies, modelling studies or econometric analyses; 2. Time frame for studies: All years were included; 3. Interventions: Global interventions with a focus on diet-related fiscal strategies; 4. Outcome variables: changes to sales, government revenue, GDP, industry productivity, and employment; 5. Published in English. In total, we identified 2922 citations, of which 10 studies met the

inclusion criteria (Fig. 1); one additional study, recently published online, was identified via an expert recommendation. Exclusion criteria: 1. Articles not published in English; 2. Systematic reviews, opinion papers, editorials and narrative reviews or papers without primary data; 3. Qualitative studies; and 4. Duplicate publications from the same study (the most comprehensive and recent to be included). 2.2. Data extraction and analysis We conducted the searches and extracted records to EndnoteTM, deleting duplicates. Each author independently reviewed the titles, abstracts and full papers, and crosschecked full papers. We sought any missing information of eligible papers through communication with the study’s authors. We then extracted information on the study characteristics, design and quality, together with data for the primary outcome variables. In line with recommendations from the Cochrane Quality Assessment Tool for Quantitative Studies (Bennett and Manue, 2012; Hamilton, 2008) we reviewed the design and quality criteria using a modelling-specific checklist developed by Bennet and Manue (2012). The checklist assesses the methodological quality of the variables and the validity of the data. We extracted information from each paper on 69 quality criteria aggregated into seven domains: structure, data, uncertainty analysis, consistency, validity, transparency, and sponsorship. 3. Results Of 2922 records identified, 85 remained after eliminating duplicates or those failing to meet the inclusion criteria. After assessing the full texts, and based on selection criteria, a further 74 papers were excluded (Fig. 1). Eleven studies met our inclusion criteria, of which eight were reports published in the grey literature (Table 1). Of these, soft drink industry actors commissioned four (Oxford Economics 2016a, 2016b, 2017; Theron et al., 2016). All involved modelling analysis of SSB taxation or levies based on sugar content. One study also included an energy-dense food tax (Powell et al., 2014). Seven used input-output analysis (IOA) (Oxford Economics 2016a, 2016b, 2017; Balbinotto and Cardoso, 2016; Cantu et al., 2015; Gabe, 2008; Fairhead, 2016), one used the Regional Economics Model Inc. (REMI),(Powell et al., 2014) one used the Computable General Equilibrium (CGE) model (Theron et al., 2016) and two used empirical evidence for Interrupted Time Series Analysis (ITSA) (Guerrero-López et al., 2017; Lawman et al., 2019). Box 2 describes the different methodologies.

Box 1. Research in context. Evidence before this study Before initiating this review, we did a thorough search of the literature to detect any existing systematic reviews or prevalence studies relating to the macroeconomic impacts of diet-related fiscal policies. We found reviews on tobacco- and alcohol-related fiscal policies and their impacts on economic indicators, which showed similar industry bias and no robust evidence of negative macroeconomic outcomes. Added value of this study This is the first review to bring together global evidence about the macroeconomic impacts of diet-related fiscal policies from different disciplines including nutrition, economics, industry, health policy and medicine. It provides and synthesizes evidence of industry’s efforts to influence policy making in the form of commissioned reports. Finally, it provides solid direction for future research in this area. Implications of all the available evidence This review shows there is no robust, valid evidence showing negative macroeconomic impacts from diet-related fiscal policies. Public health policy and decision makers must acknowledge the limited evidence is largely industry-funded economic reports that fail to show overall impacts to the country’s economy. Indeed, alternative studies indicate no significant changes to employment and even gains. This review also highlights the need for more non-industry funded research in this area that incorporates the indirect effects of reduced product consumption towards other goods and services.

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Fig. 1. Search strategy used for identifying studies on impacts of fiscal policy on the food supply chain.

3.1. Sales revenue Of the eleven papers in this review, five modelled the sales revenue impact of SSB taxes, with predicted reductions in sales revenue generation (Oxford Economics 2016a, 2016b, 2017; Cantu et al., 2015; Gabe, 2008). Three reported the dollar value of sales revenue reductions (between $US13.3 and $US779 million), but not the total revenue prior to the tax, and one reported the percentage reduction in total revenue (23.5 %) (Table 2). Price elasticity of demand estimates appeared to be consistent across all studies at around negative one (range 0.92 to -1.3). However, assumptions regarding the products taxed, wage fixing, the pass-through rate and substitution availability varied between papers, which have significant implications for the outcome of the models. For example, choosing to limit the foods/beverages targeted (Oxford Economics, 2016b; Gabe, 2008); would underestimate impact across outcome variables; assuming wages remained constant (Cantu et al., 2015) would overestimate loss to sales revenue and over-shifting the pass-through rate (Powell et al., 2014) is likely to overestimate the loss of sales revenue. In contrast, including the impacts on industries that produce substitutes enables assessment of economy-wide impacts, and thus provides a more balanced perspective on national economic impact (Powell et al., 2014). Furthermore, by focusing only on the impact on sugar industry revenue, in isolation from substitute beverage industries which would likely benefit from consumption shifts (eg. milk/dairy, diet drinks or alcohol industry), studies are

likely to overestimate sales revenue losses on industry. For example, one study excluded the milk sector (despite reporting a likely increase in consumer purchases of 3.7 % due to substitution) because milk did not fall within their definition of the ‘soft drinks industry’ (Oxford Economics, 2016b). 3.2. Aggregated industry output and impact on GDP Four studies modelled estimated impacts for industry output and/or GDP impacts of SSB taxes (Table 2) (Oxford Economics 2016a, 2016b, 2017; Cantu et al., 2015). These GDP impacts were also a consequence of the sales revenue impacts, and therefore, similar issues around assumptions were evident. For example, the projections for reductions of approximately US$173 million and US $1 billion to GDP contributions from Oxford Economics’ UK (Oxford Economics, 2016b) and South Africa (Oxford Economics, 2016a) analyses, respectively, were likely overestimated because of (World Health Organization, 2011) failure to incorporate milk and other substitutions across sectors, and (Sassi et al., 2013) for South Africa, the over-shifting of the pass-through rate.(Oxford Economics, 2017) It was also clear from the studies reviewed that the PE selected for modelling had a significant impact on the potential GDP effects of a tax. For example, Theron et al’s analysis across the alternative PE scenarios (-0.79, -0.97 and -1.299) saw differences of up to R0.56 billion (US$40million) in GDP reductions over the five years and across scenarios.(Theron et al., 2016) These results were lower than expected and likely due to substitution of other goods and services (Fig. 2).

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Table 1 Studies on the macroeconomic impacts of diet-related fiscal policy. Paper (Year)

Country

Study design

Data source

Tax imposed

Balbinotto & Cardoso (2016): Measuring the impact of SSB taxes in Brazil: An inputoutput analysis

Brazil

Input-Output Analysis (IOA)

Brazilian Tables of Resources and Uses, 2009; Annual Industrial Survey, 2009; Consumer Expenditure Survey, 2008– 2009.

Hypothetical 10 % SSB excise tax

Mexico Cantu, Curiel and Valero (2015): The Non-Alcoholic Beverage Industry in Mexico

Report/ Autonomous University of Nuevo Leon (UANL)

Input-Output Analysis (IOA)

National HIES (INEGI, 2007–2014, and the Monthly Survey of the Manufacturing Industry (EMIM). Years not given.

Actual 11 % SSB excise tax 8 % energy-dense food ad valorem tax (>275 kcal/ 100 gm)

UK Fairhead H (2016) An estimate of the effect of the Soft Drinks Industry Levy on employment Gabe T (2008): Fiscal Maine, US and economic impacts of beverage excise taxes imposed by Maine public law 629

Report/ Taxpayers’ Alliance

Modelling analysis

British Soft Drinks Industry Actual

Not discussed

Report/ 'Fed up with Taxes' coalition

Input-output Analysis (ie. Maine IMPLAN model)

Maine Office of Fiscal and Program Review, US Bureau of Labor Statistics, US Census Bureau, American Beverage Association. Years not given.

Hypothetical excise tax equivalent to 11.9 % and 8.1 % of the pretax average prices of softdrinks and sports drinks, respectively.

Peer-reviewed/ n/a

Interrupted Time Series Analysis (ITSA)

Monthly Surveys of Manufacturing Industry (EMIM), 2007–2016); Monthly Surveys of the Commercial Establishments (EMEC), 2011–2015; National Occupation and Employment Survey (ENOE), 2007 to 2016.

Actual 11 % SSB excise tax 8 % energydense food ad valorem tax (>275 kcal/ 100gm)

1. Figures reported include alcoholic beverages and exclude many nonalcoholic beverages. Included soft-drinks were Pepsi, Powerade, Gatorade and Coke. 2. Average prices based on current retail prices in Maine. Not discussed however n/a noted the SSB tax was associated with a price increase of nearly 11 % and a 7.3 % decrease in sales of SSBs in 2014/ 2015 compared to the pre-tax period. NEDF noted a 5% reduction in purchases.

Economic report/ Beverage

Nielsen, Bai, BevSA and Input-Output Analysis(IOA) Three Statistics South Africa scenarios modelled (2012 - 2016)

Guerrero-Lopez et al Mexico (2017): Employment changes associated with the introduction of taxes on sugar-sweetened beverages and nonessential energy-dense food in Mexico Oxford Economics (2016). The economic impact of

South Africa

Hypothetical 20 % levy (R 0.0229/g

Price elasticity estimation source Not discussed

Analyst’s own estimate: 1.0 for soft drinks

Previously published academic literature assumed to be an average of -0.40.

Manyema et.al's systematic review and meta-analysis of

Key assumptions

Outcome variables of interest Employment 1. The increase in prices comes from a Government full transfer of the revenue tax increase. 2. Families do not change drink preferences and wages remain constant. Sales revenue GDP Assumptions for Industry impact the two Employment simulations: 1. Price elasticities of demand are equal to one. 2. Simulation 1: nominal wage is exogenous and fixed. 3. Simulation 2: nominal wages indexed to Consumer Price Index (CPI). Sales revenue GDP Analysis based on Mexico's data from Employment the Non-Alcoholic Beverage Industry Sales revenue Government revenue Employment

Employment Unemployment

1. The pass-on rate Sales revenue GDP to consumers is 100 Government %. 2. Diet drinks do revenue Industry

Key conclusions A 10 % SSB tax would generate a 4 % increase in the price of drinks and result in an approximately 4 % contraction of the SSB sector. Overall, the tax would have a negative impact on the economy but would reduce consumption in the short term. The NAB industry is linked to many sectors of the economy and contributes to almost 1.1 % of the gross output in the country. It was estimated that the impact of the SSB tax lead to a drop in sales, production and jobs in Mexico, with the NAB industry and agricultural sectors most severely affected.

If the sugar tax had the same effect in the UK as it did in Mexico, there would be a reduction in employment and employment taxes. The economic impacts of Maine's Public Law 629 on 9 beverages indicates loss of sales revenue and associated jobs. Additional government revenue would be gained. The biggest impact on sales reductions were from the two soft drinks, Coke and Pepsi.

The results showed no employment reductions with the associated fiscal policies implemented in 2014.

On average, the tax will increase the price of SSBs by 25 %, reduce the sales of SSBs,

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Type of paper and funding Currently under review for publication

taxation of sugar sweetened beverages in South Africa

Association of South Africa

for different retail types

UK Oxford Economics (2016). The economic impact of the soft drinks levy Final report.

Economic report/ British Soft Drinks Association (BSDA)

Input-Output Analysis (IOA) Three scenarios modelled for different retail types

Canadean, Kantar World Panel, Agriculture and Horticulture Dairy Board (AHDB), previous Oxford Economics research for BSDA

US (Philadelphia)

Economic report/ American Beverage Association

Input-output model (IMPLAN model)

City of Philadelphia tax receipts, Bottler sales data, Information Resources Inc. (IRI)

Powell, LM, et al. (2014)." Employment impact of sugarsweetened beverage taxes."

USA (Berkeley/ Illinois)

Peer-reviewed/ n/a

Macroeconomic simulation modelling (Regional Economic Models, Inc. or REMI)

Beverage Marketing Corporation, Census Bureau's 2009 retail industry study, Health and Nutrition Examination Survey, 2009-2010

studies done in USA, France, Mexico and Brazil: -1.3 for SSBs

impact not increase in price in response to Employment the tax. 3. VAT is liable on the value of the SSB levy.

which could reduce the industry's total contribution to the GDP by approximately R15 billion and reduce employment by up to 71,000 across the industry's economic footprint. The net tax revenue generated would be approximately R4.3 billion. The tax can expect to raise £504 million in tax revenue however it could result in 4000 job losses. The industry's total contribution to the UK GDP could be reduced

Actual levy based on sugar content: 5–8 g m/ 100 mL ₤0.18/liter ($0.25) >8gm/ 100 mL ₤0.24/liter ($0.34) An actual ad valorem tax of 1.5c/ounce

Briggs et al

1. The pass-on rate to consumers is 100 %. 2. Diet drinks do not increase in price in response to the tax.

Sales revenue GDP Government revenue Industry impact Employment

Oxford Economic’s own estimates: Carbonated drinks: 0.90; sports drinks: 0.92

Sales revenue GDP Government revenue Industry impact Employment

Overall, the results indicate reduced employment and a decline in economic activity in the form of GDP and labour income.

Hypothetical 20 % SSB excise tax

Powell et.al's systematic review on prices, demand and body weight outcomes (2013). PE used: -1.2.

1. 1 % point decline in output in a given industry will result in a 1 % point decline in that industry’s employment and value-added contribution to GDP. 2. Only the bottling establishments within Philadelphia (2/3 from total sales data) were included in the estimates. 1. Beverages were manufactured by 'soft drinks and ice manufacturing' (exceptions were milk and juice who had their own industry category). 2. Tap water was considered free. 3. The 20% tax was fully passed on to consumers and all purchases were subject to the same tax. 4. Average beverage prices were constant within and across states and prices of the non-SSBs did not change because of the tax. 5. The own-price

Government revenue Employment

The industry's total contribution to the UK GDP could be reduced.

S. Mounsey et al. / Economics and Human Biology 37 (2020) 100854

Oxford Economics (2017). The economic impact of Philadelphia's beverage tax.

sugar) ($0,0015/g sugar)

5

Report Beverage Association of S.Africa

A dynamic computable general equilibrium (CGE) model with three different scenarios based on different PE estimates of -0.79, -0.97 and -1.299 and projected from 2017 to 2021.

Lawman HG et al (2019) Unemployment claims in Philadelphia one year after implementation of the sweetened beverage tax

Philadelphia

Peer-reviewed

Interrupted Time Series Analysis (ITSA)

The Enormous Regional Model for SA (SA-TERM) model database based on a 2012 Social Accounting Matrix (SAM7) of the South African economy, aggregated to 31 industries and products. For the baseline forecast, which shows the macroeconomic projections for the main components of GDP, Econex uses IMF (2016), National Treasury (2016) and CEPII (2012) estimates. Pennsylvania Dept of Labour

Actual 20 % SSB excise tax

n/a Actual 1.5cents/ ounce excise tax on sugarand artificially sweetened beverages 1 January 2017.

Unemployment Soft drink claims manufacturers: 1.56 claims (β = -0.13, SE = 4.59, p = 0.98) Potentially affected industries: -118.47 claims (β = 9.16, SE = 253.80, p = 0.97) Total industries: -268.15 claims (β = -445.85, SE = 1952.35, p = 0.82))

The 20 % SSB tax will have a significant and adverse effect on the value added coefficients and domestic output in the SSB products sector. However, it may also be beneficial to other sectors in the economy. The net impact is, however, still negative.

No statistically significant changes to monthly unemployment claims in Philadelphia compared to neighboring counties following the implementation of the beverage tax (1 January 2017). The following is the average difference between claims 2 years before and 14 months after the tax implementation: Supermarkets: -55.86 claims Soft drink manufacturers: -1.11 claims Potentially affected industries: -241.53 claims Total industries: -926.31 claims Mean differences in unemployment claims between Philadelphia and neighboring counties: Supermarkets: -11.77 claims (β = -9.45, SE = 45.24, p = 0.84)

S. Mounsey et al. / Economics and Human Biology 37 (2020) 100854

South Africa

6

Theron N, R. R., Fourie H, (2016). Economy-wide implications of the proposed tax on sugar sweetened beverages (SSBs) Research Note 42, ECONEX

elasticity of demand for SSB was -1.2, reducing consumption by 24%. 6. Cross-price elasticity of 0.1, implying a 10% increase in taxed beverages would increase non-taxed beverage consumption by 1%. 7. Individuals would substitute with other beverages on a full volume replacement. GDP Employment 1. Baseline Three sources: projections paint a (World Health business-as-usual Organization, 2011) (BAU) picture. 2. 80 Manyema et.al (-1.299); (Sassi et al., % of the soft drinks industry is SSBs. 3. 2013) Bayes (-0.97); The policy scenario (World Health Organization, 2015a) a tax increase that translates to a 25.1 Author's own % price increase is calculations from used. 4. The passNeilsen data on volume and sales data on of the tax is 100%. (-0.79).

S. Mounsey et al. / Economics and Human Biology 37 (2020) 100854

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Box 2. Modelling methods explained. Input-Output Analysis (IOA) IOA is based on all monetary flows to (inputs) and from (outputs) discrete economic sectors for all traditional economic activity in a nation’s economy. In other words, as a result of input of materials from other sectors, the (beverage) industry can sell its output, as an intermediate input product to another industry, or as a final product to families, to the government or to the external sector. The most commonly used IOA assumes a demand-driven market economy (as opposed to a centrally planned economy) and relies on National Accounts to give the snapshot of an economy at a specific time. In addition, IOA forms the core of most economic models, like computable general equilibrium models (CGE) and Regional Economics Model Inc. (REMI) (Foran et al., 2005; Zhang, 2002). Computable general equilibrium (CGE) CGE combines economic theory with real economic data to quantify the economic impact of a policy change scenario (in this review, an increased price of SSBs). It can take into account a reduction in demand or a substitution between products. Here, comparison between no tax (baseline) and the increased tax (policy simulation) estimated what the effect of this demand change would be on the main macroeconomic variables and its sub-components as well as those on the industry level components of the economy (Gretton, 2013). Regional Economic Models Inc. (REMI) REMI modelling incorporates four major modelling approaches: (1. IOA, 2. CGE, 3. Econometric, and 4. Economic geography. It is useful for addressing what effects policies have on an economy or which projects may warrant tax incentives. Impacts assessed are economic (ie. employment, general and GDP).(Bonn and Harrington, 2008) Interrupted time series analysis (ITSA) ITSA is a statistical method useful for determining the initial effects of an interventions or policy when random controlled trials (RCTs) are impractical or premature. The process involves taking multiple, repeated observations at regular intervals before and after an intervention (in this review, SSB taxes). Changes in trends after the intervention are then determined through statistical analysis (Guerrero-Lopez et al., 2017; Bernal et al., 2017).

3.3. Government revenue Five studies estimated government revenue generated from SSB taxation (Oxford Economics, 2016a, 2016b; Balbinotto and Cardoso, 2016; Gabe, 2008; Powell et al., 2014). Estimates ranged from between US$31 million to US$940 million, translating to per capita values of between US$1.05 to US$43.39 (Table 2). The most significant impacts on the magnitude of revenue were the tax levels imposed and onto what products, PE and substitution estimates. Similarly, as for sales revenue, underestimates of government revenue are likely if only sub-sets of products taxed were analysed (Gabe, 2008). 3.4. Cross-border shopping One study reported the cross-border shopping impact of the Philadelphia SSB tax on both beverages and non-beverage items and showed a gross loss from the local sales tax revenue that should have been collected (Oxford Economics, 2017). 3.5. Employment All eleven studies estimated the impact of either actual or hypothetical diet-related taxes on employment (Table 3). One study predicted a net increase of 4870 and 5887 jobs for two US jurisdictions (Powell et al., 2014); two studies indicated no significant change to either employment or unemployment claims (Guerrero-López et al., 2017; Lawman et al., 2019), and eight studies estimated net job loss, ranging from 1190 to 71,000 jobs (Oxford Economics 2016a, 2016b, 2017; Theron et al., 2016; Balbinotto and Cardoso, 2016; Cantu et al., 2015; Gabe, 2008; Fairhead, 2016). 3.6. Quality of the evidence Table 4 summarises the findings for the quality assessment. We used 69 criteria covering seven domains as outlined by Bennett and Manue (2012): structure, data quality, uncertainty analysis, consistency, validity, transparency and sponsorship. We found that overall, while all studies in this review gave adequate details around the aims and data sources as well as funding sources, most lacked adequate uncertainty analyses, validity and transparency. In particular, we

found the studies using IOA were limited in terms of their validity, because this method is unable to consider all relevant aspects of the economic situation considered important by end-users of the reports (eg. substitution to other goods and services). 4. Discussion This is the first systematic review of the macroeconomic impacts of diet-related fiscal policy and addresses important implications of the global push for fiscal policy to address NCDs. We found no robust, high-quality evidence for a negative macroeconomic impact from implementing diet-related fiscal policies. Policy makers must be aware that the majority of the limited evidence available for the macroeconomic impact of diet-related taxes was from industryfunded reports. Similar to the introduction of tobacco and alcohol taxes, we question if industry has sought to influence health-related fiscal policies through the sponsorship of studies. This is because we found their reports to be based on selected outcomes providing partial measures of the gross economic impact across sectors and based on questionable assumptions such as over-shifting of pass through rate or the products used in the analysis. In contrast, the three non-industry supported peer-reviewed academic studies found none of the significant job losses industry reports suggested, but found instead, no significant net decline in employment and job creation (Powell et al., 2014; Guerrero-López et al., 2017; Lawman et al., 2019). Similarly, econometric studies for economic impacts of tobacco and alcohol taxation contradict the taxed industry’s persistent arguments for lost jobs and negative economic growth. In most countries, increased government spending of revenue generated and/or the extra spending on other goods and services by consumers (as a result of decreased consumption of the good), served to either offset job loss or generate employment (Jernigan et al., 2011; Chaloupka Frank et al., 2019). For example, estimates of two hypothetical alcohol taxes by Wada et.al (2017) showed net job creation across five US states: 653–4583 jobs due to a 5-cent drink excise tax ranged; and 621–4493 jobs from a 5 % sales tax increase (Wada et al., 2017).Similarly, several econometric studies from around the world in the 1990s saw the majority of countries gain jobs as a direct result of tobacco taxation, often the tens of thousands (World Health Organization, 2016).

z


3.7 to -4.3 -3.7 to -4.3 -3.5 to -4.4
211 to -247 millionz -213 to -246 millionz -216 to -251 millionz n/a
0.79–0.97 -1.30 20 % SSB ta

Based on estimated reductions in sales of 3.2 million/172,582 gallons at an average retail price of $3.88/5.16 per gallon for soft drinks and sports drinks, respectively. Based on full-volume replacement with non-SSB sales (e.g. Non-taxes substitutes: diet drinks, milk, water, juice). Estimates are from 2017 to 2021. †

n/a n/a n/a n/a (net†) -364 million (net†) -540 million n/a n/a
1.2
1.2

1,580,863 Philadelphia, US

Illinois, US 12,768,300 Berkeley, California 39,776,830 US Theron et al (Econex) South Africa 57,400,000

*


50.6
80 million n/a n/a 0.90/0.92

n/a


2.62
173 million n/a
0.81 to -0.92
1.3 %

5–8 g m/100 mL - ₤0.18/ liter ($0.25) SSB tax >8gm/ 100 mL - ₤0.24/liter ($0.34) SSB tax Ad valorem tax of 1.5c/ ounce SSB tax 20 % SSB tax 20 % SSB tax Oxford Economics (2016) Powell et al (2014)

South Africa

Oxford Economics (2016) Oxford Economics (2016)

66,000,000


1.1 billion
1.3


4.8 %/ -3.2 % (soft/sports drinks)
25.0 %
0.4 Maine, US Gabe (2008)

United Kingdom


19.2

n/a


337 million


779/-678 million (fixed/indexed wage) 12.4 million/890,523 (soft drink/sports drinks)*
23.5 % 123,500,000 11 % SSB tax 8 % energydense food 1,300,000 11.9 %/8.1 % (soft drinks/ sports drinks) 57,400,000 20 % SSB tax Cantu et al (2015)

Mexico

1.0

Sales volume reduction (%) PE Tax Population Country/State Author

Table 2 Sales revenue and GDP impact of a diet-related fiscal policy.

n/a

Overall GDP change (US$) Sales revenue change (US$)/(%)


2.73

S. Mounsey et al. / Economics and Human Biology 37 (2020) 100854 GDP per capita (SU $)

8

The evidence for economic impacts of diet-related fiscal policy is largely based on projection econometric modelling. Although modelling studies can synthesize data from various sources and provide valuable information where empirical studies are infeasible, for this review, the majority of modelled studies were unable to factor in substitution effects, which generally moderate these macroeconomic impacts. Substitution is critical for robust, valid estimates of sales revenue impact. While it is impossible to determine or standardise exact substitution effects, omitting this fundamental component in modelling analyses creates unrealistic, distorted conclusions. Only one study in this review considered substitution to other goods and services as well as to increased government spending as a result of decreased consumption of the taxed product (Powell et al., 2014). Concerns raised by industry about declining employment levels may be occurring due to, or exacerbated by, declines or diversification in the sugar industry. For the SSB industry, in addition to the previously mentioned substitution effects, these may include factors relating to declining employment or sales volume/revenue from soft drinks. For example, in 2015, the South African sugar industry (the world’s second largest), recorded its lowest production in 15 years and is now shifting focus into emerging markets on the continent, building gated communities and developing tourist resorts (Myers et al., 2017). The Mexican sugar industry (the world’s seventh largest), is facing serious environmental and climatic challenges, which have resulted in smaller and poorer quality units of production, limited investment and improvements, and in turn, poorer efficiency in the sugar mills (Aguilar-Rivera et al., 2012). Finally, the US beverage industry reported the number of paid employees fell by 30 % between 1992 and 2007 because of improved automation processes, unrelated to tax impacts (Powell et al., 2014). These examples highlight a serious limitation of the studies in this review: all failed to take into account external, underlying trends, particularly around the sugar industry and overall product consumption. Given that diet-related fiscal policies are globally recognised as effective public health interventions for reducing NCDs (World Health Organization, 2015a; Thow et al., 2014; Cobiac et al., 2017) there are also likely to be significant savings to the health system associated with such improved population-wide health outcomes. Studies have shown that these are likely to have economic benefits in terms of direct health carerelated savings to consumers and the government, as well as improvements in productivity (Cobiac et al., 2017; Lal et al., 2017; Manyema et al., 2016; Powell et al., 2014; Nomaguchi et al., 2017). If some of the revenue generated from the tax was ‘earmarked’ for health promotion and health insurance as well as towards employment-generating programs and/or livelihood training for those affected, there would be further improvement to both health and economic outcomes (Cecchini et al., 2010; Jensen and Smed, 2007; Jan et al., 2018). This is particularly relevant for lower socioeconomic groups in middle- and high-income countries and marginalized populations from low-income countries where consumption of the taxed unhealthy products is likely to be higher. Although we have not included these studies in our review as to keep it focused on the macroeconomic perspective, policy makers should also consider these cost-savings. 4.1. Strengths and limitations The strengths of this review include the comprehensive search strategy of both peer-reviewed literature and grey literature, given that both inform policy, across multiple disciplines. The study also has limitations. First, because of heterogeneity of methods and outcome variables, we were unable to provide a quantitative synthesis through a meta-analysis of the results. In addition, there were only 11 studies identified, which limits the scope of

S. Mounsey et al. / Economics and Human Biology 37 (2020) 100854

9

Fig. 2. Summary of per capita impacts on GDP and Government revenue.

Table 3 Employment/unemployment impact of diet-related fiscal policy. Authors

Study design

Balbinotto et al Input-output analysis (IOA) Input-output Cantu et al analysis (IOA) GuerreroLopez et al Oxford Economics Fairhead (Taxpayers Alliance) Oxford Economics Theron et al (Econex) Gabe Oxford Economics Lawman et al

Powell et al

Powell et al

Interrupted time series analysis (ITSA) Input-output analysis (IOA) Input-output analysis (IOA) Input-output analysis (IOA) Computable general equilibrium (CGE) Input-output analysis (IOA) Input-output analysis (IOA) Interrupted time series analysis (ITSA) Regional Economic Models Inc Regional Economic Models Inc

Country

Population

Tax

Employment/Unemployment change

Employment impact breakdown Direct Indirect/ impact induced impact

Retail outlets –

Brazil

209,000,000 10 % SSB


14699 jobs

23 %

Mexico

123,500,000


10,815 jobs (Fixed wages) -16,406 jobs (CPI-indexed wages) No significant change in employment

39 %

UK

South Africa

66,000,000

57,400,000

11 % SSB 8 % energy-dense food

5–8 g m/100 mL - ₤0.18/ liter ($0.25) SSB >8gm/ 100 mL ₤0.24/liter ($0.34) SSB 20 %

62 % (food services) 35 % ( Agriculture)

–

–

–

–


4000 jobs

66 %

34 %z

–


5624 jobs

–

–

–


61,000 to -71,000 jobs

8%

92 % (sector wide*)


27,088 to -28,130 jobs

21%– 25%

n/a


18786 to -28,886 jobs† –


395 full- and part-time jobs –

–

–

1,580,863

11.9 %/8.1 % (soft drinks/ sports drinks) 1.5cents/ounce


1190 jobs

5%

68 %

Philadelphia, US

1,580,863

1.5cents/ounce

No significant change in unemployment claims

–

27 % (beverage trade & transport) –

–

Illinois, US

12,768,300

20 %

Net 4406 jobs

–

–

Berkeley, California US

39,776,830

20 %

Net 6654 jobs

–

–

Maine, US

1,300,000

Philadelphia, US

–

This is for Philadelphia bottling manufacturers, which is what this analysis is partially estimating. * Sector wide: Agriculture, mining, manufacturing (excluding soft drinks), utilities, construction, wholesale, retail, hotels and catering, transport and communications, financial services, public administration, health and education and ‘others.’. † Retail sectors: large, modern retail stores, small formal retail stores and Spaza stores. There is uncertainty around double counting, hence the variation in estimate. z No sector breakdown given. Depending on price elasticity estimate scenario: -0.79, -0.97 and -1.3.

10

S. Mounsey et al. / Economics and Human Biology 37 (2020) 100854

Table 4 Quality of the evidence in studies on the economic, employment and industry impacts of diet-related fiscal. Quality criteria

Structure Problem/objective outlined Rationale for model structure Data source given Assumptions clearly stated Is the comparator stated Data Data identification methods transparent and appropriate Is the data pooled? Is the data context-specific Has the quality of the data been assessed Is the data modelling based on justifiable, statistical and epidemiological techniques Is the choice of baseline data described Have alternative assumptions been explored through sensitivity analysis Has the data been described and referenced in sufficient detail Is the process of data incorporation transparent Uncertainty analysis Has uncertainty analysis been addressed Have methodological uncertainties been addressed Have structural uncertainties been addressed with sensitivity analysis Do point estimates have ranges Which sensitivity analysis was carried out Consistency Is there evidence the logic of the model has been tested before use? Are any counterintuitive results explained and justified? Has the model be calibrated? Validity Face validity: model structure or data sources or results pres ented? Was the predictive validity of the model tested and described? Transparency Is the model available to the reader Is there a detailed document available describing the model’s methods Have relevant appendices included Sponsorship Is disclosure of sponsorship given * † z

Balbinotto et al. (2016)

Cantu et al (2015)

Fairhead (2016)

Gabe Guerrero(2008) Lopez et al (2017)

Oxford Economics* (2016)

Oxford Economics† (2016)

Oxford Powell Economicsz et al (2014)

Theron (Econex) (2016)

Lawman et al (2019)

U U U U n/a

U U U U U

U U U U n/a

U X U U n/a

U X U U n/a

U X U U n/a

U X U U n/a

U U U U U

U U U U U

U X U n/a U

U

U

U X U X n/a X X

U

U

U

U

U

U

U

U

X U X

X U X

X X X

U U X

X U X

X U X

X U X

X U X

X U X

X U X

X U X

U

U

X

U

U

U

U

U

U

U

U

U

U

n/a

U

U

n/a

n/a

n/a

U

U

U

X

X

X

X

U

X

X

X

U

U

U

U

U

X

U

U

U

U

U

U

U

U

U

U

X

U

U

U

U

U

U

U

U

X

X

X

X

X

X

X

X

X

X

U

X

X

X

X

X

X

X

X

X

X

U

X

X

X

X

X

X

X

X

X

X

U

X X

X X

X X

X X

X X

X X

X X

X X

X X

X X

U n/a

U

U

U

U

U

U

U

U

U

U

U

n/a

n/a

n/a

n/a

U

n/a

n/a

n/a

n/a

X

U

X

X

n/a

X

X

X

X

X

X

U

U

U

U

U

U

U

U

U

U

U

n/a

n/a

X

n/a

X

n/a

n/a

n/a

X

X

n/a

X U

X U

X X

X X

X X

X X

X X

X X

X X

X X

U U

U

U

X

X

U

U

U

U

X

X

U

n/a

U

X

X

U

U

U

U

U

U

U

n/a

Oxford Economics, South Africa. Oxford Economics, UK. Oxford Economics, Philadelphia.

conclusions that can be drawn. Finally, we may have excluded some relevant papers from non-English language countries. 5. Conclusion This review aligns with similar studies done for the introduction of tobacco taxes and found there is no valid, high quality evidence showing overall negative economic impacts from dietrelated fiscal policies on production, sales revenue reductions or

employment. Similar to tobacco studies, we found the minimal, mixed evidence was largely from industry-funded economic reports whose analyses hinged upon partial analyses and which may overstate the negative impacts to sales revenue, GDP, employment and industry. Finally, and also similar to studies on tobacco, we found papers using more appropriate methodologies, which incorporated substitution to other goods and services (because of decreased unhealthy food and beverage consumption), saw compensatory effects, with overall outcomes of no significant

S. Mounsey et al. / Economics and Human Biology 37 (2020) 100854

change, or even increases, to employment in addition to significant government revenue generated. CRediT authorship contribution statement Sarah Mounsey: Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Validation, Visualization, Writing - original draft. Lennert Veerman: Methodology, Writing - review & editing. Stephen Jan: Methodology, Writing review & editing. Anne Marie Thow: Conceptualization, Methodology, Writing - review & editing. Declaration of Competing Interest None. Acknowledgements We would like to express our thanks and gratitude to those who supported the development of this systematic review: Ms Bernie Carr, whose data searching expertise in systematic reviews was invaluable and Dr Helen Trevena for her contributions and guidance towards the final version. As first author, I would like to thank and acknowledge the co-authors for their input, guidance and expertise throughout the research process. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.ehb.2020.100854. References Aguilar-Rivera, N., Rodríguez, L.D.A., Enríquez, R.V., Castillo, M.A., Herrera, S.A., 2012. The mexican sugarcane industry: overview, constraints, current status and long-term trends. Sugar Tech 14 (3), 207–222. Anand, S.S., Hawkes, C., De Souza, R.J., Mente, A., Dehghan, M., Nugent, R., et al., 2015. Food consumption and its impact on cardiovascular disease: importance of solutions focused on the globalized food system: a report from the workshop convened by the World Heart Federation. J. Am. Coll. Cardiol. 66 (14), 1590–1614. Balbinotto, G., Cardoso, L., 2016. Measuring the economic impact of SSB Taxes in Brazil: an input-output analysis. Value Health 19 (3), A101. Bennett, C., Manue, D.G., 2012. Reporting guidelines for modelling studies. BMC Med. Res. Methodol. 12 (168), 7. Bernal, J.L., Cummins, S., Gasparrini, A., 2017. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int. J. Epidemiol. 46 (1), 348–355. Bonn, M.A., Harrington, J., 2008. A comparison of three economic impact models for applied hospitality and tourism research. Tour. Econ. 14 (4), 769–789. Cantu, J,, Curiel, D., Valero, L., 2015. The non-alcoholic beverage industy in Mexico. [cited 12 May 2018] Available from: https://semepul-aieplac.com.mx/docs/libro04_soft_drinks. pdf. Mexico: Centro de Investigaciones Economicas [Internet]. Cecchini, M., Sassi, F., Lauer, J.A., Lee, Y.Y., Guajardo-Barron, V., Chisholm, D., 2010. Tackling of unhealthy diets, physical inactivity, and obesity: health effects and cost-effectiveness. Lancet 376 (9754), 1775–1784. Chaloupka Frank, J., Powell Lisa, M., WK, E., 2019. The use of excise taxes to reduce tobacco, alcohol and sugary beverage consumption. Annu. Rev. Public Health 40, 187–201. Cobiac, L.J., Tam, K., Veerman, L., Blakely, T., 2017. Taxes and subsidies for improving diet and population health in Australia: a cost-effectiveness modelling study. PLoS Med. 14 (2) e1002232. Fairhead, H., 2016. An Estimate of the Effect of the Soft Drinks Industry Levy on Employment.. . Foran, B., Dey, C., Lenzen, M., 2005. Balancing Act - a Triple Bottom Line Analysis of the Australian Eocnomy. Commonwealth of Australia, Australia. Gabe, T., 2008. Fiscal and Economic Impacts of Beverage Excise Taxes Imposed by Maine Public Law 629. University of Maine Contract No.: 575.

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