However, in addition to estimating specification (1), this article also presents estimates of the simple difference in Sana’a following the capture of Sana’a to demonstrate the results are being driven by changes in Sana’a as opposed to changes in the rest of Yemen: where all variables are the same as above.<sup>19</sup> Specification (2) is restricted to households from the city of Sana’a, and the coefficients of interest are _βj_ , which represent the percentage point change in a variety of outcomes following the capture of the city relative to the three months before the capture.

As an additional robustness check, this article also estimates specifications that allow the outcome to vary by month to better demonstrate when the changes in expenditure and coping strategies only occurred: where _Month j_ are indicators equaling one if the household was interviewed during the j’th month following the first month used in the base period<sup>20</sup> , and all other variables are the same as above.<sup>21</sup> The coefficients of interest are _βj_ , which represent how much larger the percentage point change was in Sana’a for a variety of outcomes month-by-month, including the two months leading up to the survey and the three months after. In order to attribute the decline in expenditure to the capture of the city, it is important to verify that expenditure was not trending differently leading up the capture. In such a scenario, it is possible that the expenditure declines could be uncovering the response to a shock that actually led to rebels capturing the city, as opposed to uncovering the response to the capture.

# **5a. Decline in Expenditure Following the Capture of the Capital**

Table 2 presents estimates of how annualized expenditure changed following the capture. Estimates of specification (1) are presented in columns (1)-(2). Column (1) reports a sparse specification including only lower-order terms and not the control variables; and column (2) adds control variables to absorb unobserved heterogeneity and increase the precision of the

> are qualitatively identical regardless of which months are used to construct the pre-period.

> 19Control variables are identical, but the rural indicator is omitted given that all households in Sana’a are urban.

> 20Specifically, _Month_ ~~1~~ - _Month_ ~~5~~ are month indicators for August-December respectively.

> 21The appendix also investigates specifications that can better account for seasonality. Specifically, Appendix 4 estimates a difference-in-difference specification comparing the change in Sana’a in 2014 to the change in Sana’a in 2005; and Appendix 5 also estimates a triple difference specification that compares the differencein-difference in Sana’a (between 2005 and 2014) to the difference-in-difference for the rest of Yemen. All results from those specifications are qualitatively identical to the baseline specification. However, given the long time period between the 2005 and 2014 surveys and the numerous events that happened between- political transition and food price shock- this article focuses on estimates from specification (1) that compare the change in household outcomes in the city of Sana’a to the rest of Yemen using only data from the 2014 survey.

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