**Table 2 – Tobacco Price Elasticities, by Decile**

|_Price Elasticity_|_1_|_2_|_3_|_4_|_De_<br>_5_|_ciles_<br>_6_|_7_|_8_|_9_|_10_|
|---|---|---|---|---|---|---|---|---|---|---|
|Lower bound|−0.16|−0.06|−0.04|−0.11|−0.14|−0.03|−0.04|−0.01|0.07|−0.02|
|Medium bound|−0.36|−0.26|−0.24|−0.31|−0.34|−0.17|−0.24|−0.21|−0.13|−0.22|
|Upper bound|−0.56|−0.46|−0.44|−0.51|−0.54|−0.37|−0.44|−0.41|−0.33|−0.42|

_Source:_ Estimates based on harmonized datasets by World Bank staff of the National Income Dynamics Study, waves 1–4, 2008–15. _Note_ : Lower- and upper-bound elasticities show on average differences of −0.2 and +0.2, respectively, with the medium-bound elasticity. Random effects estimates reported using near balanced panel data, where only individuals present in all four waves are kept but some are dropped due to missing observations in the relevant tobacco expenditure questions.

Lastly, in South Africa, because the wealth distribution does not vary substantially across the bottom deciles, which largely rely on government subsidies and transfers, price elasticities were also estimated for quintiles as a robustness check (Inchauste et al. 2017) (figure 2, panel b).

**Figure 2 – Tobacco Price Elasticity, South Africa**

<!-- Start of picture text --> a. Deciles b. Quintiles<br>0.1<br>0.20<br>0<br>0.00 -0.1<br>-0.2<br>-0.20<br>-0.3<br>-0.40 -0.4<br>-0.5<br>-0.60<br>-0.6<br>1 2 3 4 5 6 7 8 9 10<br>1 2 3 4 5<br>Deciles<br>Quintiles<br>Medium Bound Upper Bound Lower Bound<br>Price elasticity of demand<br>Price elasticity of demand<br><!-- End of picture text --> _Source:_ Estimates based on the National Income Dynamics Study, waves 1–4, 2008–15. _Note_ : Deciles and quintiles were created using per capita household expenditure. Lower- and upper-bound elasticities show differences of −0.2 and +0.2, respectively, with the medium-bound elasticity. Random effects estimates reported using near balanced panel data, where only individuals present in all four waves are kept but some are dropped due to missing observations in the relevant tobacco expenditure questions.

# **Mortality and morbidity**

Statistics South Africa has information on mortality and causes of death in South Africa in 2015. The data are disaggregated according to the smoking status of the deceased (table 3), where a smoker is defined as someone who had smoked any form of tobacco on average for more than six months a year or four or more days a week five years previously. Approximately 36 percent of all deaths in 2015 (173,241) were associated with tobaccorelated diseases.<sup>23</sup> Of these, over 7,000 were women and nearly 25,000 were men (tables 3 and 4). Though a large share of deaths in South Africa (46 percent) are recorded with the smoking status unknown, the incidence of tobacco-related deaths appears to be higher among smokers. For instance, in 2015, even though there were roughly the same number of cases of chronic obstructive pulmonary disease among smokers (4,348) and nonsmokers (4,270), smokers represented fewer than 20 percent of the South African population. Pillay-van Wyk et al. (2016) find that mortality by disease is severely underreported in the South African data; the results presented using these numbers will thus provide lower-bound estimates of tobacco-related deaths.

> 23 If only individuals with known smoking status are considered (32,767), the share drops to 7 percent.

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