response probability to construct the response weight variable for each IHPS adult household member that was interviewed in private; (2) winsorize the response weights at the top 3 percent to account for potential outliers; and (3) set it equal to 1 for all adults in the IHS4 sample. Henceforth, all statistics are weighted using the response weight.

Table 1 presents the descriptive statistics on selected individual and household attributes. Individuals in the IHS4 are slightly older, more likely to be the household head or spouse, female and less educated, and they live in smaller households. Although these are statistically significant differences, the magnitude of the differences is negligible.<sup>12</sup>

**<u>Table 1. Descriptive Statistics by Survey Approach</u>**

|IHPS<sup>(1)</sup>|IHS4<sup>(2)</sup>|T-test<br>(1)–(2)|
|---|---|---|
|Age (years)<br>33.01|33.46|**|
|Female<br>0.52|0.53|**|
|Never attended school<br>0.09|0.13|***|
|No primary degree<br>0.52|0.51||
|Primary degree<br>0.12|0.12||
|Lower secondary degree<br>0.12|0.12||
|Higher secondary degree<br>0.15|0.12|*|
|Married<br>0.68|0.66||
|Household head or spouse<br>0.73|0.76|**|
|Log household size<br>1.61|1.52|***|
|Dependency ratio<br>0.89|0.93||
|Wealth index<br>0.10|0.16||
|Observations<br>4,377<br>**Notes:**IHPS = individual interviews; IHS4 =|17,433<br>business-as-usual|survey|

**<u>Notes:</u>** IHPS = individual interviews; IHS4 = business-as-usual survey approach. Significant differences are indicated with * (p<0.1), ** (p<0.05) and *** (p<0.01). Estimates are weighted with the response weight.

Table 2 presents the descriptive statistics for labor market outcomes of interest, by gender. The estimates are coupled with the results from the tests of mean differences across the two surveys.

identifying females; a series of dichotomous variables on educational attainment; dichotomous variables identifying whether the individual is currently married, and separately, whether he/she is head/spouse of head; and individual’s number of months living away from the household over the past year; and (iii) household covariates, including household size, dependency ratio, and wealth index. The latter is a factor analysis-based index that is composed of (i) a series of dichotomous variables that capture the ownership of mortar, bed, table, chair, fan, air conditioner, radio, radio with flash drive/micro CD, TV, VCR, sewing machine, kerosene/paraffin stove, electric/gas stove, refrigerator, washing machine, bicycle, motorcycle, car, minibus, lorry, beer-brewing drum, sofa, coffee table, cupboard/drawers, lantern, desk, clock, iron, computer, satellite dish, solar panel and generator, and (ii) a series of dwelling covariates, including number of dwelling rooms per capita and categorical variables that identify construction material (permanent; semi-permanent; traditional); roof type (grass; iron sheets; clay tiles/concrete/plastic sheeting/other); floor type (sand; smoothed mud; smooth cement/wood/tile/other); water source (piped/well; borehole; other), and toilet facility (flush/VIP toilet; traditional latrine; other/none).

12 These differences are due to the survey setting, as the IHS4 aims to represent the national population of Malawi in 2016, while the IHPS is based on the national population in 2010.

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