this survey is that one may detect the price paid by consumers and account for promotions, sales, or even the purchases of illicit cigarettes.

Nonetheless, the NIDS suffers from nonresponse and attrition as most surveys do. Similarly, the sample size is also reduced when using a balanced panel.<sup>18</sup> In addition, Kacker (2016) finds that the NIDS data do not match information from other South African surveys and appear to oversample rural areas, the less well educated, and college-educated individuals. Despite these limitations, Kacker (2016) recognizes that the survey is clearly internally consistent and that there is no reason to doubt the reliability of the data. Caution is recommended in drawing conclusions from the survey because the NIDS appears to be biased toward the part of South Africa that has improved the most.<sup>19</sup> Although several models have been tested to estimate decile-level elasticities, the random effects in a near balanced panel is the preferred model. (See annex A for more on the methodology and the various iterations of the estimation of tobacco price elasticities by decile.) The estimated average tobacco price elasticity in South Africa is −0.25, which is lower in absolute terms than the elasticities found in the literature for developing countries (−0.4 and −0.8), as well as those previously estimated for South Africa (−0.5 and −0.87) (Boshoff 2008; Chaloupka et al. 2000; Reekie 1994; van der Merwe and Annett 1998; van Walbeek 2000).<sup>20</sup> Nonetheless, all models tested for this study estimate an average elasticity between −0.23 and −0.28 (see annex A, table A2). Moreover, as noted above, to the best of our knowledge, previous estimates of tobacco price elasticities in South Africa have not relied entirely on data on households or individuals, and few rely on income groups. In addition, most of these estimates have been calculated in years prior to the more profound changes in tobacco policy in South Africa. Previous elasticities were also estimated at a time when smoking prevalence was significantly higher in South Africa; as of 2015, fewer than a fifth of the households interviewed reported spending money on cigarettes, relative to over 40 percent in 1995.<sup>21</sup> As expected, lower income deciles exhibit higher elasticities relative to richer deciles. For instance, the poorest decile has a medium-bound elasticity of −0.36, whereas the richest has an elasticity of −0.22 (table 2). The standard error of these estimates is approximately 0.10, producing a 95 percent confidence interval of −0.20, +0.20.<sup>22</sup> To show the effect of a tax increase under different scenarios, we simulate a lower- and an upperbound elasticity for each decile. The former tends to reflect income groups that would not change consumption patterns, such as rural residents or older individuals, while the latter tends to show a longer-term scenario, reflecting the effect the tobacco tax would have on younger individuals. After a few decades, only these would still be alive; the total average effect of the price increase would therefore be approximated more accurately by the upper-bound price elasticity.

> 18 The NIDS was first undertaken in 2008 among approximately 28,000 individuals in around 7,000 households. The aim of the survey is to collect repeated information over a wide range of social and economic behaviors among the same set of households. Over time, approximately 17,264 individuals consistently responded during all four waves.

> 19 As per official data from Stats SA, GDP per capita is stagnant, unemployment rate is constant, labor force participation and employment rate falls: these are all opposite to what the NIDS data shows.

> 20 Lower price elasticities are likely a result of using reported tobacco prices (expenditure on tobacco). Thus, the price elasticities in this paper are conditional elasticities. Kechia-Mukong and Ngeh (2018) estimate total tobacco price elasticity of 0.52 to 0.61 by merging annual price data to the NIDS data set.

> 21 Estimates using the 1995 and 2015 Income and Expenditure Surveys in South Africa.

> 22 In order to maintain comparability with similar studies, the same average upper and lower-bounds has been applied to all deciles. Applying individual bounds by decile resulted in minimal changes to the results.

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