Tobacco taxes in China InHEA
Tobacco taxes in China: impacts on
smokers’ health and finance
Dr. Rachel A. Nugent, Vice President, Global NCDs
Indonesia Health Economics Association
July 29, 2016
Yogyakarta, Indonesia
1
RTI International is a registered trademark and a trade name of Research Triangle Institute.
www.rti.org
Outline
Background
A new perspective on the economic evaluation of health
policies: Extended Cost-Effectiveness Analysis (ECEA)
ECEA case study
Tobacco tax in China
Conclusions
Application of ECEA to global health priority setting
2
Background
A new perspective on the economic
evaluation of health policies: Extended
Cost-Effectiveness Analysis (ECEA)
Disease Control Priorities History
• 1993 World Development
Report
• Disease Control Priorities in
Developing Countries, Second
Edition 2006 (DCP2)
• Disease Control Priorities, 3rd
Edition 2015-2016 (DCP3)
4
Disease Control Priorities, 3rd Edition
DCP3 Volume Topics
1. Essential Surgery - 2015
2.
Reproductive, Maternal, Newborn and Child Health -2016
3.
Cancer - 2015
4.
Mental, Neurological, and Substance Use Disorders - 2015
5. Cardiovascular, Respiratory, Renal and Endocrine Disorders 2016
6.
HIV/AIDS, STIs, Tuberculosis and Malaria - 2016
7.
Injury Prevention and Environmental Health - 2016
8.
Child and Adolescent Development - 2016
9. Disease Control Priorities: Improving Health & Reducing Poverty 2016
@dcpthree | #dcp3
5
Motivation: from HTA to HPA?
From: Health Technology Assessment (HTA)
Cost-effectiveness of technical interventions targeting
specific diseases (e.g. ART for AIDS)
To: Health Policy Assessment (HPA)
Resources allocated across different delivery platforms:
e.g. routine immunization vs. mass immunization
campaigns
Governments use distinct instruments of policy:
e.g. public finance, taxation, legislation
Multiple criteria involved in decision-making:
e.g. burden, costs,
effectiveness, equity, medical impoverishment
6
Objective: Health Policy Assessment, with dimensions of
equity & medical impoverishment
Extended Cost-Effectiveness Analysis (ECEA)
(1)
Distributional consequences across
distinct strata of populations
(e.g. socio-economic status, geographical setting,
gender)
(2)
7
Financial risk protection: quantify
household medical impoverishment
averted by policy
Verguet, Laxminarayan & Jamison. Health Economics
2015
Extended Cost-effectiveness
Analysis (ECEA) Approach
Inclusion of the efficient purchase of equity & nonhealth benefits into economic evaluations
8
ECEA Approach
Examine specific health policy
(e.g. public finance for rotavirus vaccine)
Health gains
(e.g. diarrhea-related
deaths averted)
Poorest
9
Poor
Household
expenditure
averted
(e.g. private diarrhea
treatment averted)
Middle
Financial risk
protection
benefits
(e.g. household
impoverishment
averted)
Rich
Richest
Financial risk protection: prevention of medical
impoverishment
Medical impoverishment
When confronted with expensive medical expenditures, poor
people can face high out-of-pocket (OOP) payments and fall
into poverty
10
Measures of financial risk protection
Threshold-based measures
Number of cases of poverty averted
–
Estimate number of individuals no longer crossing poverty line
because of medical expenses
Catastrophic expenditures averted
–
Estimate number of individuals no longer crossing catastrophic
threshold (medical expenditures > 0.40 subsistence income)
Money-metric value of insurance
provided
11
Estimate a ‘risk premium’
Verguet, Laxminarayan & Jamison. Health Economics 2015
ECEA case study – Tobacco
tax in China
Verguet S, Gauvreau CL, Mishra S, et al. The
consequences of tobacco tax on household health
and finances in rich and poor smokers in China: an
extended cost-effectiveness analysis. Lancet Global
Health 2015; 3:e206-216.
12
Tax is the single most effective tobacco control policy
Tobacco tax is
vastly underused
in LMICs
(e.g. China, India,
Indonesia,
Russia)
France: cigarette consumption & inflation-adjusted price
(Hill et al. 2010)
13
One specific policy issue with tobacco tax: it is often
regarded as regressive
Most assessments to date assume individuals with different
income to be responsive to tax increase in the same way!
Use ECEA to examine regressivity of increase
in tobacco tax
14
Tobacco in China (1)
Tobacco prevalence (males)
50%; 300 million smokers
15 cigarettes per day; varies slightly by socioeconomic
status
Tobacco-related mortality
15
Risk of premature mortality from smoking = 50%
1M annual deaths (out of 6M globally)
Stroke (46%); heart disease (23%); neoplasm (20%);
COPD (11%)
Sources: GATS (2010); Jha and Peto (2014); GBD 2010
Tobacco in China (2)
Out-of-pocket expenditures
Only 50% of inpatient healthcare costs (e.g. cancer,
stroke costs) reimbursed by insurance schemes
Stroke ($2,000), heart disease ($11,000), cancer
($14,000)
Price elasticity of cigarette
consumption (assumed based on reviews)
16
- 0.40 on average
- 0.50 (poorest) to - 0.30 (richest)
Youth (under 25 year-olds) are twice as price elastic
Sources: Yip et al. (2012); Hu et al. (2010); IARC (2010)
Price hike scenario
Increase by 50% retail price of tobacco
Price of cigarette pack: $0.74 -> $1.11
Health
benefits
Poorest
< $1700
17
Generation
of excise
tax
revenues
Poor
$1700 < < $3100
Changes in
household
cigarette
expenditure
Middle
$3100 < < $4900
OOP
tobaccorelated
disease
expenditure
averted
Rich
$4900 < < $7600
Financial
risk
protection
benefits
Richest
> $7600
Decrease in smokers & health benefits
Follow up over 50 years
Future
newborns
Future
(< 15)
Smokers
Poorest
Youth (1524)
Smokers
Poor
Price hike
Future (< 15) & Youth (15-24)
quitters
•
18
• Twice as responsive
97-100% risk reduction premature mortality
Middle
Adult (> 25)
Smokers
Rich
Future
Premature
dead
Richest
Health benefits estimated from quitting:
Participation elasticity ~ ½ price elasticity
•
Sources: IARC (2010); Hu et al. (2010); Jha et al. (2012)
Adult (> 25) quitters
85% (25-44) to 25% (> 65) risk reduction premature
mortality depending on age at quitting
Excise tax revenues & changes in household cigarette
expenditures
Follow up over 50 years
Future
(< 15)
Smokers
Future
newborns
Poorest
Price hike
Youth (1524)
Smokers
Poor
Rich
Future
premature
dead
Richest
Price elasticity of cigarette consumption
(future (< 15) & youth (15-24) smokers twice as responsive)
Added excise tax
revenues
19
Middle
Adult (> 25)
Smokers
Sources: IARC (2010), Jha et al. (2012)
Changes in household
cigarette expenditures
OOP expenditures averted & financial risk protection
Follow up over 50 years
Future
newborns
Future
(< 15)
Smokers
Poorest
Youth (1524)
Smokers
Poor
Price hike
Future (< 15) & Youth (15-24)
quitters
•
20
• Twice as responsive
97-100% risk reduction of tobacco
OOP expenditures
Middle
Adult (> 25)
Smokers
Rich
Future
premature
dead
Richest
FRP benefits estimated from quitting:
Participation elasticity ~ ½ price elasticity
•
Adult (> 25) quitters
85% (25-44) to 25% (> 65) risk reduction of
tobacco OOP expenditures
Sources: IARC (2010); Hu et al. (2010); Jha et al. (2012); Jha et al. (2013); Doll et al. (2004); Yip et al. (2012)
Results (1): premature deaths averted
3
2
1
0
Total: 13 million
(95% UI: 11-15)
Deaths averted (million)
4
5
Premature deaths averted
I
II
III
Income quintile
21
IV
V
Results (2): additional excise tax revenues
Additional tax revenues (% of income)
4
5
150
2
3
%
100
50
Revenues (US$ billion)
6
7
200
Additional tax revenues
0
0
1
Total: 700 $ billion
(95% UI: 600-800)
I
II
III
Income quintile
22
IV
V
I
II
III
Income quintile
IV
V
Results (3): changes in household tobacco expenditures
Changes in cigarette expenditures (% of income)
6
4
0
I
II
III
Income quintile
23
2
%
100
50
IV
-2
Total: 370 $ billion
(95% UI: 230-500)
0
Expenditures (US$ billion)
150
Changes in cigarette expenditures
V
I
II
III
Income quintile
IV
V
Results (4): financial risk protection
Financial risk protection
1
0.5
Insurance (US$ billion)
6
2
4
Total: 1.5 $ billion
(95% UI: 1.0-2.1)
0
Total: 23 $ billion
(95% UI: 19-28)
0
Expenditures averted (US$ billion)
8
1.5
Tobacco-related disease treatment expenditures averted
I
II
III
Income quintile
24
IV
V
I
II
III
Income quintile
IV
V
Pro-poor angles of tobacco tax
50% tobacco price increase,
China
95% uncertainty
contours
500
1000
1500
I
II
III
IV
V
0
Financial risk protection ($ million)
2000
I = Bottom income quintile
0
1
2
3
Premature deaths averted (millions)
25
4
5
Conclusions
Application of ECEA to global health priority setting
26
7
8
Rotavirus vaccine (1)
Pneumococcal conjugate vaccine (2)
Measles vaccine (3)
Diarrhea treatment (4)
Pneumonia treatment (5)
Malaria treatment (6)
Cesarean section (7)
Tuberculosis treatment (8)
Hypertension treatment (9)
80
9
4
5
6
60
1
40
($1 per dose)
2
($1 per dose)
1
20
ECEA for:
priority setting
within the
health sector
(1)
Number of poverty cases averted
100
Financial risk protection afforded & health gains, per $100,000 spent
($2.5 per dose)
2
3
0
($3.5 per dose)
0
100
200
300
Number of deaths averted
27
Verguet, Olson, Babigumira, et al. Lancet Global Health 2015
400
Priority setting beyond the health sector
Estimate efficient purchase of poverty reduction
benefits by health policies i.e. poverty cases
averted per health policy $ invested
Poverty
averted
per health
policy
$1M
invested
1
0
0
0
Poverty
averted per
education
policy
$1M invested
8
0
0
Poverty
averted per
transport policy
$1M invested
Intersectoral comparison by Ministry of Finance &
Development
28
6
0
0
More Information
Rachel A. Nugent
Vice President of Global Non-communicable Diseases
rnugent@rti.org
29
smokers’ health and finance
Dr. Rachel A. Nugent, Vice President, Global NCDs
Indonesia Health Economics Association
July 29, 2016
Yogyakarta, Indonesia
1
RTI International is a registered trademark and a trade name of Research Triangle Institute.
www.rti.org
Outline
Background
A new perspective on the economic evaluation of health
policies: Extended Cost-Effectiveness Analysis (ECEA)
ECEA case study
Tobacco tax in China
Conclusions
Application of ECEA to global health priority setting
2
Background
A new perspective on the economic
evaluation of health policies: Extended
Cost-Effectiveness Analysis (ECEA)
Disease Control Priorities History
• 1993 World Development
Report
• Disease Control Priorities in
Developing Countries, Second
Edition 2006 (DCP2)
• Disease Control Priorities, 3rd
Edition 2015-2016 (DCP3)
4
Disease Control Priorities, 3rd Edition
DCP3 Volume Topics
1. Essential Surgery - 2015
2.
Reproductive, Maternal, Newborn and Child Health -2016
3.
Cancer - 2015
4.
Mental, Neurological, and Substance Use Disorders - 2015
5. Cardiovascular, Respiratory, Renal and Endocrine Disorders 2016
6.
HIV/AIDS, STIs, Tuberculosis and Malaria - 2016
7.
Injury Prevention and Environmental Health - 2016
8.
Child and Adolescent Development - 2016
9. Disease Control Priorities: Improving Health & Reducing Poverty 2016
@dcpthree | #dcp3
5
Motivation: from HTA to HPA?
From: Health Technology Assessment (HTA)
Cost-effectiveness of technical interventions targeting
specific diseases (e.g. ART for AIDS)
To: Health Policy Assessment (HPA)
Resources allocated across different delivery platforms:
e.g. routine immunization vs. mass immunization
campaigns
Governments use distinct instruments of policy:
e.g. public finance, taxation, legislation
Multiple criteria involved in decision-making:
e.g. burden, costs,
effectiveness, equity, medical impoverishment
6
Objective: Health Policy Assessment, with dimensions of
equity & medical impoverishment
Extended Cost-Effectiveness Analysis (ECEA)
(1)
Distributional consequences across
distinct strata of populations
(e.g. socio-economic status, geographical setting,
gender)
(2)
7
Financial risk protection: quantify
household medical impoverishment
averted by policy
Verguet, Laxminarayan & Jamison. Health Economics
2015
Extended Cost-effectiveness
Analysis (ECEA) Approach
Inclusion of the efficient purchase of equity & nonhealth benefits into economic evaluations
8
ECEA Approach
Examine specific health policy
(e.g. public finance for rotavirus vaccine)
Health gains
(e.g. diarrhea-related
deaths averted)
Poorest
9
Poor
Household
expenditure
averted
(e.g. private diarrhea
treatment averted)
Middle
Financial risk
protection
benefits
(e.g. household
impoverishment
averted)
Rich
Richest
Financial risk protection: prevention of medical
impoverishment
Medical impoverishment
When confronted with expensive medical expenditures, poor
people can face high out-of-pocket (OOP) payments and fall
into poverty
10
Measures of financial risk protection
Threshold-based measures
Number of cases of poverty averted
–
Estimate number of individuals no longer crossing poverty line
because of medical expenses
Catastrophic expenditures averted
–
Estimate number of individuals no longer crossing catastrophic
threshold (medical expenditures > 0.40 subsistence income)
Money-metric value of insurance
provided
11
Estimate a ‘risk premium’
Verguet, Laxminarayan & Jamison. Health Economics 2015
ECEA case study – Tobacco
tax in China
Verguet S, Gauvreau CL, Mishra S, et al. The
consequences of tobacco tax on household health
and finances in rich and poor smokers in China: an
extended cost-effectiveness analysis. Lancet Global
Health 2015; 3:e206-216.
12
Tax is the single most effective tobacco control policy
Tobacco tax is
vastly underused
in LMICs
(e.g. China, India,
Indonesia,
Russia)
France: cigarette consumption & inflation-adjusted price
(Hill et al. 2010)
13
One specific policy issue with tobacco tax: it is often
regarded as regressive
Most assessments to date assume individuals with different
income to be responsive to tax increase in the same way!
Use ECEA to examine regressivity of increase
in tobacco tax
14
Tobacco in China (1)
Tobacco prevalence (males)
50%; 300 million smokers
15 cigarettes per day; varies slightly by socioeconomic
status
Tobacco-related mortality
15
Risk of premature mortality from smoking = 50%
1M annual deaths (out of 6M globally)
Stroke (46%); heart disease (23%); neoplasm (20%);
COPD (11%)
Sources: GATS (2010); Jha and Peto (2014); GBD 2010
Tobacco in China (2)
Out-of-pocket expenditures
Only 50% of inpatient healthcare costs (e.g. cancer,
stroke costs) reimbursed by insurance schemes
Stroke ($2,000), heart disease ($11,000), cancer
($14,000)
Price elasticity of cigarette
consumption (assumed based on reviews)
16
- 0.40 on average
- 0.50 (poorest) to - 0.30 (richest)
Youth (under 25 year-olds) are twice as price elastic
Sources: Yip et al. (2012); Hu et al. (2010); IARC (2010)
Price hike scenario
Increase by 50% retail price of tobacco
Price of cigarette pack: $0.74 -> $1.11
Health
benefits
Poorest
< $1700
17
Generation
of excise
tax
revenues
Poor
$1700 < < $3100
Changes in
household
cigarette
expenditure
Middle
$3100 < < $4900
OOP
tobaccorelated
disease
expenditure
averted
Rich
$4900 < < $7600
Financial
risk
protection
benefits
Richest
> $7600
Decrease in smokers & health benefits
Follow up over 50 years
Future
newborns
Future
(< 15)
Smokers
Poorest
Youth (1524)
Smokers
Poor
Price hike
Future (< 15) & Youth (15-24)
quitters
•
18
• Twice as responsive
97-100% risk reduction premature mortality
Middle
Adult (> 25)
Smokers
Rich
Future
Premature
dead
Richest
Health benefits estimated from quitting:
Participation elasticity ~ ½ price elasticity
•
Sources: IARC (2010); Hu et al. (2010); Jha et al. (2012)
Adult (> 25) quitters
85% (25-44) to 25% (> 65) risk reduction premature
mortality depending on age at quitting
Excise tax revenues & changes in household cigarette
expenditures
Follow up over 50 years
Future
(< 15)
Smokers
Future
newborns
Poorest
Price hike
Youth (1524)
Smokers
Poor
Rich
Future
premature
dead
Richest
Price elasticity of cigarette consumption
(future (< 15) & youth (15-24) smokers twice as responsive)
Added excise tax
revenues
19
Middle
Adult (> 25)
Smokers
Sources: IARC (2010), Jha et al. (2012)
Changes in household
cigarette expenditures
OOP expenditures averted & financial risk protection
Follow up over 50 years
Future
newborns
Future
(< 15)
Smokers
Poorest
Youth (1524)
Smokers
Poor
Price hike
Future (< 15) & Youth (15-24)
quitters
•
20
• Twice as responsive
97-100% risk reduction of tobacco
OOP expenditures
Middle
Adult (> 25)
Smokers
Rich
Future
premature
dead
Richest
FRP benefits estimated from quitting:
Participation elasticity ~ ½ price elasticity
•
Adult (> 25) quitters
85% (25-44) to 25% (> 65) risk reduction of
tobacco OOP expenditures
Sources: IARC (2010); Hu et al. (2010); Jha et al. (2012); Jha et al. (2013); Doll et al. (2004); Yip et al. (2012)
Results (1): premature deaths averted
3
2
1
0
Total: 13 million
(95% UI: 11-15)
Deaths averted (million)
4
5
Premature deaths averted
I
II
III
Income quintile
21
IV
V
Results (2): additional excise tax revenues
Additional tax revenues (% of income)
4
5
150
2
3
%
100
50
Revenues (US$ billion)
6
7
200
Additional tax revenues
0
0
1
Total: 700 $ billion
(95% UI: 600-800)
I
II
III
Income quintile
22
IV
V
I
II
III
Income quintile
IV
V
Results (3): changes in household tobacco expenditures
Changes in cigarette expenditures (% of income)
6
4
0
I
II
III
Income quintile
23
2
%
100
50
IV
-2
Total: 370 $ billion
(95% UI: 230-500)
0
Expenditures (US$ billion)
150
Changes in cigarette expenditures
V
I
II
III
Income quintile
IV
V
Results (4): financial risk protection
Financial risk protection
1
0.5
Insurance (US$ billion)
6
2
4
Total: 1.5 $ billion
(95% UI: 1.0-2.1)
0
Total: 23 $ billion
(95% UI: 19-28)
0
Expenditures averted (US$ billion)
8
1.5
Tobacco-related disease treatment expenditures averted
I
II
III
Income quintile
24
IV
V
I
II
III
Income quintile
IV
V
Pro-poor angles of tobacco tax
50% tobacco price increase,
China
95% uncertainty
contours
500
1000
1500
I
II
III
IV
V
0
Financial risk protection ($ million)
2000
I = Bottom income quintile
0
1
2
3
Premature deaths averted (millions)
25
4
5
Conclusions
Application of ECEA to global health priority setting
26
7
8
Rotavirus vaccine (1)
Pneumococcal conjugate vaccine (2)
Measles vaccine (3)
Diarrhea treatment (4)
Pneumonia treatment (5)
Malaria treatment (6)
Cesarean section (7)
Tuberculosis treatment (8)
Hypertension treatment (9)
80
9
4
5
6
60
1
40
($1 per dose)
2
($1 per dose)
1
20
ECEA for:
priority setting
within the
health sector
(1)
Number of poverty cases averted
100
Financial risk protection afforded & health gains, per $100,000 spent
($2.5 per dose)
2
3
0
($3.5 per dose)
0
100
200
300
Number of deaths averted
27
Verguet, Olson, Babigumira, et al. Lancet Global Health 2015
400
Priority setting beyond the health sector
Estimate efficient purchase of poverty reduction
benefits by health policies i.e. poverty cases
averted per health policy $ invested
Poverty
averted
per health
policy
$1M
invested
1
0
0
0
Poverty
averted per
education
policy
$1M invested
8
0
0
Poverty
averted per
transport policy
$1M invested
Intersectoral comparison by Ministry of Finance &
Development
28
6
0
0
More Information
Rachel A. Nugent
Vice President of Global Non-communicable Diseases
rnugent@rti.org
29