_et al._ , 2020; FAO _et al._ , 2020). Taken together, this implies that future work should focus on measuring the extent of heterogeneity in the effect of the coronavirus pandemic on food security in a variety of contexts around the world. Understanding this heterogeneity is important for understanding how to best design, implement, and target policies and programs aimed at assisting those harmed most by the pandemic.

# **5.3 Robustness**

We conduct several robustness checks to test the sensitivity of our results. First, in Table A4 in the Supplemental Appendix, we show results where the raw FIES score is not standardized to have a mean of zero and standard deviation of one in each survey wave. Although we prefer the results using the standardized dependent variable, this robustness check shows that our core findings are not driven by our standardization procedure. Specifically, the difference-in-differences estimates shown in the last four columns of Table A4 are qualitatively similar to the core results reported in Panel A of Table 1.

Second, in Table A5 in the Supplemental Appendix, we show results that do not control for missing observations. This tests if our results are driven by the systematic non-response to specific survey questions. We find results that are qualitatively consistent with those reported in 1.

Third, in Table A6 in the Supplemental Appendix, we show results that exclude households in Bamako from the sample. This tests if our results are strictly driven by the effect of the pandemic within Bamako. To the contrary, we find qualitatively similar results outside Bamako, although the difference-in-difference estimates are not robust to the inclusion of household fixed effects, largely due to limited statistical power. We continue to find evidence of worsening food security outcomes, on average and at every level of severity, in urban areas relative to rural areas outside Bamako.

The analysis in this paper is not without limitations. First, and most generally, although the coronavirus pandemic has disrupted life in every country around the world, we study only one country. The effects of the pandemic on welfare may vary substantially across countries, largely due to the specific non-pharmaceutical policy response of each country. We argue, however, that the situation in Mali may resemble that in many other parts of Sub-Saharan Africa where public health measures intended to slow the spread of the virus are difficult to implement effectively, but were generally more disruptive in urban areas. The work of Amare _et al._ (2020) in Nigeria and Mahmud and Riley (2020) in Uganda provide complementary analysis highlighting the substantial effect of the pandemic on food security in Sub-Saharan Africa.

Second, and specifically relating to our empirical strategy, our difference-in-difference estimates likely underestimate the effect of the coronavirus pandemic on food security in urban Mali. The lack of a truly unaffected comparable population challenges our ability to estimate an unbiased effect. Although we show that pandemic-related disruptions in Mali’s urban areas likely outweigh disruptions in rural areas, the pandemic likely had non-negligible disruptions in rural areas. Nevertheless, these challenges likely bias 15