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Evan Blecher School of Economics, University of Cape Town The Economics of Tobacco Control in South Africa.

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Presentation on theme: "Evan Blecher School of Economics, University of Cape Town The Economics of Tobacco Control in South Africa."— Presentation transcript:

1 Evan Blecher School of Economics, University of Cape Town evan.blecher@uct.ac.za The Economics of Tobacco Control in South Africa

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3 Tobacco control in South Africa Pre 1993 –No tobacco control policy/strategy 1993 Legislation –Banned smoking on public transport –Introduced warning labels on packaging and advertising –Coupled with consistent increases in excise taxes –Strongly opposed by tobacco industry

4 Tobacco control in South Africa Percentage changes in smoking indicators (1993 to 2000) Real price per pack↑ 92.7 % Aggregate consumption↓ 26.0 % Per capita consumption↓ 37.1 % Smoking prevalence↓ 16.9 % Number of smokers↓ 2.2 % Average consumption per smoker↓ 24.2 % Source: van Walbeek (2002)

5 Can increases in tax reduce government revenue?

6 Prices & consumption

7 Who gets what?

8 Industry revenue: shouldn’t it have been falling?

9 Input costs: raw tobacco

10 Input costs: paper

11 Employment: why has it been falling? Peak employment Peak consumption Merger

12 Tobacco control in South Africa 1999 Legislation –Bans smoking in workplaces & other public places –Bans all advertising, promotion & sponsorship of tobacco –Bans sale of tobacco products to persons younger than 16 –Bans free distribution of products –Limits the maximum yield on tar, nicotine & other ingredients What did the 1999 legislation do? –Public debate raised the awareness about tobacco risks –Transferred the property rights of clean air to non-smokers –Non-smokers now have the right to demand clean air

13 Tobacco control in South Africa Percentage changes in smoking indicators (1993 to 2003) Real price per pack↑ 115.6 % Aggregate consumption↓ 32.9 % Per capita consumption↓ 46.0 % Smoking prevalence↓ 26.4 % Number of smokers↓ 5.5 % Average consumption per smoker↓ 28.9 % Source: van Walbeek (2005)

14 Restaurant restrictions Two options: become entirely smoke free or separated areas Original proposal was for a blanket ban –International Hotel & Restaurant Association Cape Town Survey: Revenue would fall 32% High compliance without police crackdowns despite difficulty in enforcing –Federated Hospitality Association of South Africa 85% non-compliance & sales down 37% –Saloojee & Ucko: “How can a law, that according to them, is being widely ignored result in a loss of more than a third of sales?”

15 Literature Scollo et al (2003) –Studies that do not meet Siegel’s criteria generally find that legislation has had negative impacts in terms of financial performance; customer satisfaction & employment –Studies that meet criteria find little impact or positive impact –Scollo & Lal (2004) support this with updated data Siegel’s (1992) methodological criteria –Control for economic conditions –Use of independent funding sources –Publication subject to peer review –Measurement of actual events rather than predicted outcomes or assessments

16 A model for South Africa Real per capita revenue is a function of –Real per capita income –Effect of the legislation –Efficiency of tax collection Fixed effects panel model –Aggregate data → no sample selection problem –Provinces (nine) as cross sections –1995 to 2003

17 Data Real per capita revenue (dependent variable) –Output VAT (sales tax) data from SARS –“Restaurant/Tearoom Selling Food – Consumption Mainly on Premises” –37 regional offices aggregated to provinces –Regional CPI & population converts to real & per capita Real per capita GDP –No other provincial specific income series available Tax collection efficiency variable

18 Survey Database included –1431 restaurants –1011 completed (70.6 %) –230 established after the implementation (20.7 %) Conducted by telephone during November 2004 & January 2005 Sit down restaurants only, excluded takeaways & bars Some problems –Sample is not random –Biased towards urban, tourist & business centres Positives –Perceptions corroborates VAT data

19 Results Estimated CoefficientsExcluding Ratio Including Ratio Ln Real Per Capita GDP0.6590.789 (1.359)(1.714)*** Ban Dummy0.2270.063 (5.917)*(0.962) VAT Collection Ratio33.034 (3.051)* R 2 adjusted0.980.99 Dependent variable: Ln Real Per Capita Aggregate Revenue

20 Survey results Changes to restaurant layout –Prior 54% had specific smoking sections → 74% after 75% had specific non-smoking sections → 97% after A quarter have become entirely smoke free –Occupancy not significantly different –Compliance: 92% believe they are in compliance –In retrospect 52% indicate they would not change the status quo 23% entirely smoke free 25% ignore

21 Survey results Financial Impact –Capital expenditure Mean = R 67 000 ($ 9 571) Median = R 25 000 ($ 3 571) Malls & franchises spent more than independents Linked to restaurant size –Revenues Generally no significant impact Franchises: generally positive Independents: slightly negative –Interesting: greater capital expenditure resulted in greater positive impact (franchises)

22 Change in revenues

23 Acceptance by customers Non smokers Smokers

24 International evidence Studies using objective measures to assess economic impact of smoke-free policies in the hospitality industry: studies funded from sources other than the tobacco industry No effect, positive effect Negative effect Taxable sales receipts250 Sales data other30 Employment levels80 Number of establishments20 Number of restaurant/bar permit applications10 Bankruptcy data20 Number of employment insurance claims20

25 International evidence Studies using objective measures to assess economic impact of smoke-free policies in the hospitality industry: studies funded from sources with links to the tobacco industry or by the industry itself No effect, positive effectNegative effect Taxable sales receipts04 Sales data other02 Employment levels02 Number of establishments01

26 International evidence Studies using subjective measures to assess economic impact of smoke-free policies in the hospitality industry: studies funded from sources other than the tobacco industry No effect, positive effect Negative effect Public self-reported intentions or actual patronage of restaurants/bars180 Proprietor predictions/perceptions of sales changes140 Proprietor predictions/perceptions of costs30 Estimated number of overseas visitors10

27 International evidence Studies using subjective measures to assess economic impact of smoke-free policies in the hospitality industry: studies funded from sources with links to the tobacco industry or by the industry itself No effect, positive effect Negative effect Public self-reported intentions or actual patronage of restaurants/bars25 Public self-reported spending/time spent02 Proprietor predictions/perceptions of sales changes124 Proprietor estimates of impact on employment09 Proprietor predictions/perceptions of costs01

28 Conclusion: smoke free Legislation has had, if any, a small positive impact on restaurant revenues No systematic harm done to restaurant industry Smoking & non-smoking customers have accepted the policy well Inline with international evidence Implications –Supports the current legislation –May support further legislation –Supports the implementation in other developing countries which do not yet have such policies

29 The options: taxes No evidence that illicit trade is a problem of excise Illicit trade may be a function of the retail price → but the retail price is a function of industry price as well Industry is attempting to profit from declining consumption Illicit trade is part of a broader organised crime issue


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