coffee prices (note that Zone is a higher level administrative unit than Kebele/Village).<sup>10</sup> An alternative way of capturing this is using zone-specific time trend, which gives very similar estimates. _C_ denotes consumption. ESS data reports household level adult-equivalent per capita consumption expenditures disaggregated into food and non-food. _LandShareCoffee_ is the share of household land allocated to coffee. _Price_ is the average international coffee price in the four quarters before the consumption survey month.<sup>11</sup> Identification comes from large variations in the fraction of farmland allocated to coffee across households within a zone and massive swings in the international coffee prices over time. Table A.2 shows that about 82% of variation in adult equivalent consumption and about 61% variation in fraction of land allocated to coffee are within-zone variation. The identification assumptions are: (i) households cannot endogenously adjust the fraction of their farmland allocated to coffee in response to coffee price (at least in the short run); (ii) international coffee price change is exogenous to Ethiopia; and (iii) coffee price movement does not have any significant effect on non-coffee producers.

To rule out any concern about households endogenously adjusting the fraction of land allocated to coffee in response to coffee price change, I use the share of land allocated to coffee at the beginning of the panel, i.e., the year 2011. The lumpy nature of coffee production by itself rules out any endogenous adjustment of coffee production in the short run. Coffee plants take about 5 years to grow into trees and bear fruit. Hence, it is unlikely that farmers would adjust the share of their land allocated to coffee following fluctuations in coffee prices. Moreover, variation in the fraction of farmland allocated to coffee is largely attributed to geographic variation in agro-climatic suitability to grow coffee (see figure 3 and table A.2). Table A.2 decomposes the variation in consumption, landholding, and the share of land allocated to coffee. It shows that about 72% of the variation in landholding is within a village, but only 32% of variation in the share of land allocated to coffee is within a village.<sup>12</sup> The remaining 68% of variation in the share of land allocated to coffee is across villages, implying the importance of agro-climatic

> 10Ethiopia is administratively divided into 10 Regions which are divided into 70 Zones, which are further divided into 683 Woredas/districts and the Woredas are divided into over 15,000 Kebeles/Villages, about 10,000 which are rural villages. Hence, even after including zone-year fixed effects, there is sufficient variation in the data to precisely estimate the parameters of interest. See table A.2.

> 11 Using average prices over one, two, or three quarters before the consumption survey month has no significant effect on the estimates.

> 12While the 32% within-village variation is surprisingly high (given that there is little agro-climatic variation within a village – the average village size is about 25km square), there are a number of potential factors that might explain this variations including risk attitude (risk averse farmers might like to diversify their crop portfolio), variation in forest coverage, family labor supply constraints, size of farmland, etc.

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