Duration Analysis using Household Surveys
Nicole Vellios
Emerging Research Programme
22-26 June 2015
www.tobaccoecon.org
Research question
• Do cigarette prices affect smoking onset? Evidence from South Africa
using duration analysis
• Substantial body of literature conclusively shows that there is an
inverse relationship between tobacco prices and tobacco
consumption (International Agency for Research on Cancer 2011).
• Existing literature on smoking onset is dominated by studies
performed in high-income countries while only 5 studies consider
determinants of smoking initiation in low & middle-income countries.
Duration Analysis using Household Surveys
24 June 2015
Research question
• Relatively large increases in cigarette prices over nearly 20
years allow one to investigate the relationship between
cigarette prices and smoking initiation.
• We chose data from SA since it is at the forefront of middleincome countries in using excise tax increases as a tobacco
control measure.
• Investigate individual & household variables that influence
smoking onset decision.
Duration Analysis using Household Surveys
24 June 2015
Literature review
• Guindon (2012) reviewed 27 studies that examine impact of
tobacco prices on smoking onset and concludes that existing
studies do not provide strong evidence that tobacco prices impact
smoking onset. He points to serious methodological issues (e.g.
price not treated as a time-varying covariate), as well as data and
measurement issues (e.g. current location may not match location
at time of decision).
• Useful studies include: Douglas and Hariharan (1994), Forster and
Jones (2001), Kidd and Hopkins (2004) Grignon (2007), López
Nicolás (2002) and Madden (2007).
• Grignon (2007), Kidd and Hopkins (2004) and Guindon (2009) find
large and significant effects.
Duration Analysis using Household Surveys
24 June 2015
Survival / Duration Analysis
•Duration analysis focuses not only on the probability of the
event taking place, but also on the time to the event.
•Two related probabilities form the basis of duration analysis:
Hazard rate: subject’s risk of experiencing an event, given
that he/she has not yet experienced the event.
Survival rate: probability of not having experienced the
event at particular times. Survive: Does not start smoking
•Duration analysis of smoking behaviour requires data on year of
smoking initiation, which is linked to the prices of cigarettes in
that year.
Duration Analysis using Household Surveys
24 June 2015
Data on smoking behaviour
• We use 3 waves of the National Income Dynamic Study data
(2008, 2010, 2012).
• Although data is longitudinal, we did not use the longitudinal
characteristics of the data, since the change in the real price
between waves was modest (only 4% per year between 2008 2012)
• Instead, we combined data from all three waves to increase sample
size
• W1:9844, W2:4520, W3:3327. Master sample: n= 17 691
Duration Analysis using Household Surveys
24 June 2015
Survey questions on smoking
• NIDS has five smoking-related questions, of which three are
relevant for this study.
– “Do you smoke cigarettes?”
– “Did you ever smoke cigarettes regularly?”
– “How old were you when you first smoked cigarettes regularly?”
• This information, together with information on the year of birth,
is used to determine the year in which the person started
smoking.
• Based on smokers’ declared age of smoking initiation, a
pseudo-panel is created.
Duration Analysis using Household Surveys
24 June 2015
Price Data
• Data on average cigarette prices are derived from two sources.
– Price data for 1970 to 1989 taken from Central Statistical Services’ (CSS)
Report on Prices
– Price data for 1990 to 2012 came from Statistics South Africa (MPPC)
• The data used in the analysis refer to the average price of cigarettes in the
MPPC range (which comprises about 70% of the market).
• Nominal prices were deflated by the CPI to remove the impact of inflation
(base = December 2010).
• We did not explore the effect of price variation by province/other
georgraphical region, but this could have been done with more detailed
price data
Duration Analysis using Household Surveys
24 June 2015
Aggregate cigarette consumption and
price of cigarettes, 1970 - 2012
Source: Van Walbeek 2005, Statistics South Africa (various issues)
Duration Analysis using Household Surveys
24 June 2015
Cigarette prices
• SA has achieved significant success with its tobacco contol
policy.
– Since 1990s, price of cigarettes increased sharply, resulting in a
substantial decrease in smoking prevalence.
• Between 1994 and 2012 the real excise tax increased by
407% and the real price of cigarettes increased by 229%.
• Over this period aggregate legal consumption decreased by
38%, per capita consumption decreased by 52% and smoking
prevalence decreased from about 31% to 18.2%.
Duration Analysis using Household Surveys
24 June 2015
Descriptive stats
Race
White and Asian
Coloured
African
Urban/rural
Urban
Rural
Either parent’s highest education
Primary or less (including no education)
Incomplete secondary school
Complete secondary school (grade 12)
Tertiary (including incomplete tertiary)
Literate
Mother died before age 15
Ever smoker (i.e. current smoker or former smoker)
Mean age of initiation
Mean age of full sample (range 15 – 48 years)
Either parent ever a smoker (males n=1732, females n=1986)
Male (n=7771)
Female (n=9920)
4.51%
12.56%
82.93%
4.11%
12.63%
83.26%
46.65%
53.35%
45.91%
54.09%
55.72%
27.84%
9.72%
6.72%
82.41%
5.44%
39.09%
18.17 (sd: 4.08)
27.24 (sd: 9.78)
61.20%
59.49%
25.96%
8.57%
5.99%
82.04%
5.54%
10.22%
18.33 (sd: 4.87)
28.67 (sd: 10.06)
61.83%
Source: NIDS wave 1 (2008), wave 2 (2010) and wave 3 (2012), Van Walbeek 2005, Statistics South Africa (various issues)
Duration Analysis using Household Surveys
24 June 2015
Expanding the data
An artificial panel is created from cross-sectional data. Cross-section
information is transformed into a multiple record for each individual.
Person
ID
Year
Age
Period
(t)
Event
(start)
Gender
Price
(R)
Person
ID
Year
Age
Period
(t)
Event
(start)
Gender
Price (R)
x
x
x
x
x
x
x
x
x
x
x
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
10
11
12
13
14
15
16
17
18
19
20
1
2
3
4
5
6
7
8
9
10
11
0
0
0
0
0
0
0
0
0
0
1
M
M
M
M
M
M
M
M
M
M
M
8.45
7.93
7.27
6.79
6.97
6.60
6.61
6.46
6.06
6.09
6.04
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
F
8.45
7.93
7.27
6.79
6.97
6.60
6.61
6.46
6.06
6.09
6.04
5.95
6.23
5.59
6.38
6.68
6.81
7.68
7.96
9.41
10.78
12.31
12.83
13.30
14.19
15.20
16.63
17.56
18.39
19.26
19.17
•
Individual x aged 40 years in 2008. Born 1968. Starts
smoking at age 20 (in 1988). A separate observational
record is created for each year that individual x is known
to be at risk. Starts smoking in year 11 (1988) 
“failure”. The event time is known so this person is not
considered censored. Once the event is experienced,
person drops out of the risk set.
•
Individual y  also aged 40 in 2008 but has not started
smoking by 2008. Individual y is censored after 31 years
(last time period when the event could have occurred).
“Failure” or transition to smoking is not observed.
Final sample
• 96 448 person-period observations for males and 161 071
person-period observations for females (based on 7771 males
and 9920 females).
• In 2008, smoking prevalence in SA was 36% for males and
9% for females. Given these large gender differences,
separate models for smoking initiation were estimated for
males and females.
Duration Analysis using Household Surveys
24 June 2015
Logit Model using discrete time to estimate
determinants of smoking initiation for Male & Females
(odds ratios)
Covariates
Price of cigarettes
Rural
Urban
Parents: Primary / no education
Parents: Incomplete secondary edu
Parents: Complete secondary edu
Parents: At least some tertiary edu
Illiterate
Literate
Mother alive when respondent was 15
Mother died before respondent was 15
Controls for age and race group
Controls for age-race group interactions
Observations
Pseudo R-squared
Duration Analysis using Household Surveys
Male
Female
0.983*** (0.004) 0.991 (0.007)
1.000
1.000
1.228*** (0.051) 1.501*** (0.129)
1.000
1.000
1.048 (0.049)
1.087 (0.088)
0.968 (0.075)
1.098 (0.138)
0.778*** (0.073) 1.291* (0.177)
1.000
1.000
0.626*** (0.030) 0.617*** (0.052)
1.000
1.000
1.072 (0.099)
1.350** (0.206)
Yes
Yes
Yes
Yes
96 320
159 818
0.0994
0.232
24 June 2015
Smoking initiation hazard rates for males, using
discrete and continuous age specifications, by race
•
•
•
Source: NIDS wave 1 (2008), wave 2 (2010) and Wave 3 (2012) data
Duration Analysis using Household Surveys
↑ cigarette
prices
significantly ↓
smoking
initiation.
Coloureds have
a higher
probability of
initiating
smoking
compared to
other population
groups
Africans initiate
later and at
lower rates than
other population
groups.
24 June 2015
Smoking initiation hazard rates for females, using
discrete and continuous age specifications, by race
•
•
•
Smoking
initiation among
males ↑ than
among females.
We find that an
↑ in cigarette
prices does not
significantly ↓
smoking
initiation
Africans females
have a very low
uptake of
smoking
compared to
other
populations
groups.
Source: NIDS wave 1 (2008), wave 2 (2010) and Wave 3 (2012) data
Duration Analysis using Household Surveys
24 June 2015
Results
•
•
•
•
•
•
•
Smoking initiation in SA takes place in late teenage years and
early twenties.
For both males and females, probability of starting smoking is
highest amongst the Coloured population.
Being literate reduces the risk of smoking initiation for both males
and females.
Males are more responsive to price changes than females.
Females whose mother died before the respondent was aged 15
are more likely to start smoking. The same effect was not found for
males.
Children of non-smoking parents are substantially less likely to
initiate smoking than those who have at least one parent who
smokes.
Children with more educated parents are less likely to initiate
smoking than those with less educated parents.
Duration Analysis using Household Surveys
24 June 2015
Conclusion
• Findings from this study provide additional evidence of the
effectiveness of tobacco prices in reducing tobacco use.
• Tobacco taxation should remain a major public policy
instrument to discourage smoking.
• Further increases in the excise tax on cigarettes are likely to
discourage smoking habit and to delay onset for those who
decide to start.
• Paper is currently under review at the Journal of
Contemporary Economic Policy.
Duration Analysis using Household Surveys
24 June 2015