the following were your household’s sources of livelihood?” Options included: 1) Family farming, livestock or fishing; 2) Non-farm family business, including family business; 3) Wage employment of household members; 4) Remittances from abroad; 5) Assistance from family within the country; 6) Assistance from other non-family individuals; 7) Income from properties, investments or savings; 8) Pension; 9) Assistance from the Government; 10) Assistance from NGOs / charitable organization/religious bodies; 11) Other income source. A household is assigned a one if it reports “yes” to the question and zero if it reports “no.” Our variable of interest in our analysis consists of a series of indices measuring income diversification. Following methodology from Michler and Josephson (2017), we use two measures to evaluate household income diversification: (1) a simple fractional index (FI) and (2) a HerfindahlHirschman Index (HHI).<sup>4</sup> HHI scores are negatively related to diversification. That is, they are larger for less diversified households and smaller for more diversified households. For consistency, we adjust the fractional index to maintain this negative relationship. Both indices can be interpreted as specialization indices that are inversely related to diversification. Table 2 summarizes the characteristics of each index.

The simple fractional index is calculated using the count of the income sources each household is engaged in ( _m_ ) at time _t_ given the total number of income-generating opportunities ( _n_ ) in their region ( _j_ ) over the entire time series: The fraction is subtracted from one so that a higher score is associated with fewer income-generating activities, while a lower score indicates a more diversified income portfolio. The fractional index is calculated for both pre- and post-COVID-19 data. To generate the index, we collapse multiple income categories into seven categories standardized across the three countries: (1) farm, (2) wage, (3) pension, (4) remittances, (5) non-farm enterprises, (6) income from properties, savings, and investment, and (7) other, which includes asset sales, income from NGOs, and other government assistance. This index accounts for geographic area to capture livelihood specialization relative to regional diversification opportunities. We count the total number of income sources households participate in for all geographic areas available in the data (e.g., region, zone, district, postal code, ward). We then determine the smallest geographic area with at least 10 available observations. The count of income sources households are engaged in within that smallest geographic area with sufficient observations then serves as the denominator ( _nj_ ) in the index calculation for households residing in that area.<sup>5</sup>

> 4We also generate four variations of these indices, following our pre-analysis plan, that differ in if they standardize income categories across countries and/or across time. Summaries of these additional indices are presented in Online Appendix A.

> 5Our final results are robust to changes in this benchmark: if we include a control for the size of the benchmark or standardize the geographic region that is the benchmark for diversification, we see no difference in how diversification

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