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

Evan BlecherSchool of Economics, University of Cape Town

[email protected]

The Economics of Tobacco Control in South Africa

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

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)

Can increases in tax reduce government revenue?

0

100

200

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19

61

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65

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69

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73

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77

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81

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89

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93

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Re

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Real excise rate Real excise revenue

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120019

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4006008001000

120014001600

18002000

Cig

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(m

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pac

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Real price of cigarettes Consumption of cigarettes

Prices & consumption

Who gets what?

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Industry price Excise tax Sales tax

Industry revenue: shouldn’t it have been falling?

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cig

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Excise revenue (R million, constant 2000 prices, left-hand scale)

Industry revenue (R million, constant 2000 prices, left-hand scale)

Cigarette consumption (millions of packs, right-hand scale)

Input costs: raw tobacco

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66/6

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Marketing year

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Flue-cured (AAS) Flue-cured (TB) Dark air-cured (AAS) Dark air-cured (TB)

Flue-cured (TB)

Flue-cured (AAS)

Dark air-cured (TB) Dark air-cured (AAS)

Input costs: paper

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Real producer price of paper and paper products (index value, 2000 = 100, left-hand scale)

Real industry price of cigarettes (cents/pack, base 2000, right-hand scale)

Employment: why has it been falling?

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Number of employees (left-hand scale)

Average monthly wage bill (R millions, constant 2000 prices, 3-year moving average, right-hand scale)

Peak employment

Peak consumption

Merger

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

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)

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?”

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

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

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

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

Results

Estimated Coefficients Excluding Ratio

Including Ratio

Ln Real Per Capita GDP 0.659 0.789

(1.359) (1.714)***

Ban Dummy 0.227 0.063

(5.917)* (0.962)

VAT Collection Ratio 33.034

(3.051)*

R2 adjusted 0.98 0.99

Dependent variable: Ln Real Per Capita Aggregate Revenue

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

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)

Change in revenues

4.5%6.1%

8.3%

59.3%

4.3%

12.2%

5.2%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

Decreased by morethan 20 %

Decreased bybetween 10-20 %

Decreased by lessthan 10 %

No change Increased by lessthan 10 %

Increased bybetween 10-20 %

Increased by morethan 20 %

Acceptance by customers

56.2%

31.0%

7.1%4.9%

0.9%

76.7%

18.0%

3.7%1.1% 0.5%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Very Well Fairly Well Not Very Well Not Well At All Don't Know

No

n

smo

kers

Sm

oke

rs

International evidenceStudies 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 receipts 25 0

Sales data other 3 0

Employment levels 8 0

Number of establishments 2 0

Number of restaurant/bar permit applications 1 0

Bankruptcy data 2 0

Number of employment insurance claims 2 0

International evidenceStudies 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 effect Negative effect

Taxable sales receipts 0 4

Sales data other 0 2

Employment levels 0 2

Number of establishments 0 1

International evidenceStudies 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/bars 18 0

Proprietor predictions/perceptions of sales changes 14 0

Proprietor predictions/perceptions of costs 3 0

Estimated number of overseas visitors 1 0

International evidenceStudies 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/bars 2 5

Public self-reported spending/time spent 0 2

Proprietor predictions/perceptions of sales changes 1 24

Proprietor estimates of impact on employment 0 9

Proprietor predictions/perceptions of costs 0 1

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

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