Our main outcome of interest is mental health, which was measured in the baseline and third waves of the survey. All adult respondents responded to the PHQ-9 in the baseline, but only the main respondent answered the MHI-5 questions in wave 3. Another difference is that in the baseline wave, the Patient Health Questionnaire (PHQ-9) was used, but in wave 3, the Mental Health Inventory 5 (MHI-5) was used instead. As we describe in section A.1, although the instruments are different, both of these measures can be used to categorize a respondent as having severe depression, moderate depression, mild depression, or no/minimal depression. We therefore use indicators for different categories of depression as our outcome variables. This has the added advantage of avoiding the cardinal use of an ordinal variable, shown to be problematic by Bond and Lang (2019).

We use several other variables in our analysis. Food security questions were included in waves 1 to 4 of the survey. Because only one question was asked in wave 1 (“In the past 7 days, did you or any other family member eat fewer meals in a day because of lack of food?”), we restrict our attention to this question in all waves, even though waves 2 through 4 included a more detailed set of food security questions (described in section A.2). Income and employment (for which we report baseline levels in Table 1) were collected in all waves of the survey. We also examine an indicator for whether the household reported receiving remittances. This is obtained from the wave 3 survey, during which respondents are asked two separate questions: whether they were receiving remittances before the lockdown in March, and whether they had received any remittances since the lockdown in March. We assign the answer to the first question to the baseline wave and the answer to the second question to the third wave.

Because we will be examining changes in depression rates over time, we restrict our sample to households with mental health information in both the baseline and wave 3 surveys. This ensures that any change in average depression across waves is not driven by changes in the composition of the sample due to attrition. In Table A2, we show that attrition from the sample (which was 10%) was largely unrelated to household characteristics, which indicates that our restricted sample is fairly representative of the original sample. Specifically, when we relax our sample restriction to include all households with baseline mental health measures and regress a dummy for household attrition on baseline household characteristics, only one coefficient is statistically significant at the 10% level (primary education). With the exception of this variable and the severe depression variable (which measures the share of household respondents with severe depression at baseline), all other coefficients are small in magnitude. The large positive (but statistically insignificant) coefficient on severe depression suggests households with severely depressed individuals were more likely to attrit from the sample. However, because all of our analysis restricts to households found in both waves, as noted above, differential attrition by household characteristics does not affect the internal validity of the results described in the next section.

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