Duration Analysis using Household Surveys Nicole Vellios Emerging Research Programme June

Duration Analysis using Household Surveys 24 June 2015 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 middle- income 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 ) Instead, we combined data from all three waves to increase sample size W1:9844, W2:4520, W3:3327. Master sample: n=

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, 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 Male (n=7771)Female (n=9920) Race White and Asian4.51%4.11% Coloured12.56%12.63% African82.93%83.26% Urban/rural Urban46.65%45.91% Rural53.35%54.09% Either parent’s highest education Primary or less (including no education)55.72%59.49% Incomplete secondary school27.84%25.96% Complete secondary school (grade 12)9.72%8.57% Tertiary (including incomplete tertiary)6.72%5.99% Literate82.41%82.04% Mother died before age %5.54% Ever smoker (i.e. current smoker or former smoker)39.09%10.22% Mean age of initiation18.17 (sd: 4.08)18.33 (sd: 4.87) Mean age of full sample (range 15 – 48 years)27.24 (sd: 9.78)28.67 (sd: 10.06) Either parent ever a smoker (males n=1732, females n=1986)61.20%61.83% Source: NIDS wave 1 (2008), wave 2 (2010) and wave 3 (2012), Van Walbeek 2005, Statistics South Africa (various issues)

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 YearAge Period (t) Event (start) Gender Price (R) x M8.45 x M7.93 x M7.27 x M6.79 x M6.97 x M6.60 x M6.61 x M6.46 x M6.06 x M6.09 x M6.04 Person ID YearAge Period (t) Event (start) GenderPrice (R) y F8.45 y F7.93 y F7.27 y F6.79 y F6.97 y F6.60 y F6.61 y F6.46 y F6.06 y F6.09 y F6.04 y F5.95 y F6.23 y F5.59 y F6.38 y F6.68 y F6.81 y F7.68 y F7.96 y F9.41 y F10.78 y F12.31 y F12.83 y F13.30 y F14.19 y F15.20 y F16.63 y F17.56 y F18.39 y F19.26 y F19.17 Individual x  aged 40 years in Born 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 Individual y is censored after 31 years (last time period when the event could have occurred). “Failure” or transition to smoking is not observed.

Duration Analysis using Household Surveys 24 June 2015 Final sample person-period observations for males and 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 The Logit model

Duration Analysis using Household Surveys 24 June 2015 Logit Model using discrete time to estimate determinants of smoking initiation for Male & Females (odds ratios) CovariatesMaleFemale Price of cigarettes0.983*** (0.004)0.991 (0.007) Rural1.000 Urban1.228*** (0.051)1.501*** (0.129) Parents: Primary / no education1.000 Parents: Incomplete secondary edu1.048 (0.049)1.087 (0.088) Parents: Complete secondary edu0.968 (0.075)1.098 (0.138) Parents: At least some tertiary edu0.778*** (0.073)1.291* (0.177) Illiterate1.000 Literate0.626*** (0.030)0.617*** (0.052) Mother alive when respondent was Mother died before respondent was (0.099)1.350** (0.206) Controls for age and race groupYes Controls for age-race group interactionsYes Observations Pseudo R-squared

Duration Analysis using Household Surveys 24 June 2015 males Smoking initiation hazard rates for males, using discrete and continuous age specifications, by race ↑ 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. Source: NIDS wave 1 (2008), wave 2 (2010) and Wave 3 (2012) data

Duration Analysis using Household Surveys 24 June 2015 females Smoking initiation hazard rates for females, using discrete and continuous age specifications, by race Source: NIDS wave 1 (2008), wave 2 (2010) and Wave 3 (2012) data 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.

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.