somewhat reduced by their price sensitivity<sup>49</sup> . However, the fact that poor households are still more affected (and substantially so) remains – the gain to poor households is equivalent to an increase in their overall expenditure of more than 1 percent. The right hand panel of Figure 8 plots the estimated gains (including substitution effects) separately for urban and rural households<sup>50</sup> - showing very similar results. We see very slightly lower impact on the urban population here – driven by both lower shares in sugar relative to income and (in the case of the urban poor) higher estimated elasticities. The vertical lines on the figure indicate the rural (left) and urban (right) poverty lines – giving a sense of how the poor and non-poor are differentially affected.

**Lower prices that could be achieved by removal of trade barriers and more efficient domestic production would have a significant effect on poverty.** We estimate that just over 40,000 families would cross the poverty line (out of poverty) as a consequence of a 20 percent price decrease in sugar – an approximate 1.5 percent decrease in poverty for Kenya overall. We use the estimated equivalent change in real income<sup>51</sup> added to current household expenditure to estimate ‘post-reform income’.  Comparison of the post reform income with the thresholds of the rural/urban poverty lines in Kenya produces the welfare estimate.  Even though the equivalent income effects of the sugar price on households are relatively small compared to total expenditure (mean of 0.9 percent, median of 1 percent), the effects are higher on poorer households, many of which sit very close to the poverty line.  This striking result is indicative of (a) the inelasticity of sugar demand (people do not easily change their consumption of sugar), (b) high average consumption of sugar, and (c) the vulnerability of poorer households to price changes<sup>52</sup> .

**Lower sugar prices** **_might_ affect the welfare of sugar smallholders, but even if there is complete price pass-through, the net welfare impacts are still positive.** We are focusing on consumers, rather than producers in this analysis. Producers are difficult to incorporate into the analysis as we lack information about the pass-through between sugar and sugar cane prices. Chisanga et al (2014) argue that the majority of rents in the value chain lie at the level of the miller, rather than the farmer.  The fact that sugar factories in Kenya are generally operating below capacity due to cane shortage suggests that even if some sugar factories closed their doors, there would still be excess demand for cane, and as such cane prices would be unlikely to fall.  Nevertheless, we can stress test our results by making two very simplistic assumptions: (a) cane prices move in lockstep with sugar prices, and (b) the elasticity of substitution of cane farmers is zero.  Both of these are extreme (worst case) assumptions, but they provide us with an upper bound of the potential effects on smallholders.  Under these

> 49 The welfare impact including household substitution effects is given by the compensating variation.  This is estimated using a second order Taylor series expansion of the derivate of the expenditure function with respect to own-price, dropping the effect of curvature.  See Porto (2010) and Mghenyi et al (2011) for derivation.  Elasticities of demand are estimated using simple log-log regressions for four groups defined by the categories or poor/nonpoor and rural/urban.  Estimation using the method of Deaton (1989) found these elasticities to be high, suggesting that if anything we are understating the impact here (through overstating substitution).  See appendix for the estimated elasticites from both methods.

> 50 Again, we have truncated the plot on the left hand side to remove the bottom 1 percent of households. 51 The technical term for this is the compensating variation.

> 52 There are a very large number of Kenyan households that have consumption levels that are very close to the poverty line (KIHBS, 2005/06).  Thus small changes income can generate large changes in poverty as measured by the national poverty line.  The annual per adult equivalent poverty lines for rural and urban areas at the time of the survey were KSH 18,746 (USD256) and KSH 34,954 (USD477) respectively.

16