very prevalent, the 19<sup>th</sup> ICLS standards may have a larger effect on the sectoral distribution of the employed population than on the employment-to-population ratio.

To illustrate the effects of the adoption of the 19<sup>th</sup> ICLS standards on headline labor indicators, we rely on nationally representative household surveys from the two early adopters, i.e. the Nigeria GHS Panel Wave 3 (activity-level operationalization) and the Malawi IHS-4 (product-level operationalization).<sup>32</sup> Since the Malawi IHS-4 only collected the intended use of output for crops, we assume that livestock products are for sale, even though we know from the previous section that some livestock (especially chicken) are often reared for own consumption. In Nigeria, the analysis is based on the end-of-season survey, which, as discussed in the previous section, shows a higher share of farmers producing for sale than the start-ofseason survey. The estimates in this section should therefore be seen as a lower bound of the implications of the 19<sup>th</sup> ICLS standards on measures of employment.

Table 5 shows that in both countries, there is a large reduction in male and female employment-topopulation ratios in rural areas under the 19<sup>th</sup> ICLS standards, and a much smaller reduction in urban areas. In Malawi, employment declines disproportionately among women, while in Nigeria, the decline is larger for men. The latter result may be surprising, given that Table 5 is based on the same end-of-season data for Nigeria used in Table 1, which shows women farmers being more likely to be classified as own-use production workers than male farmers. However, there is also a comparatively higher incidence of nonfarm household enterprise work among Nigerian women, while more men than women work on the farm, which mitigates the impact of the 19<sup>th</sup> ICLS standards on female (relative to male) employment. Conversely, in Malawi, women are less likely than men to work in the non-farm household enterprise and wage sectors, which is one of the factors explaining a disproportionate decline in female employment (Palacios-Lopez and Lopez 2015).

Besides these changes in employment-to-population ratios, there is a large drop in the measured share of agricultural employment in total rural employment, which declines by about 50 percent in Nigeria and by about 10 percent in Malawi.<sup>33</sup> This is a considerable change, especially for Nigeria, which, if taken at face value, would paint the picture of a rural population that is much less reliant on agricultural activities

> 32 We do not report data from the Ghana and Malawi agricultural survey experiments in this section, because neither data set is nationally representative, and the samples include only rural households.

> 33 The change in Malawi is most likely underestimated, since a substantial share of workers in Malawi is primarily engaged in casual or ganyu labor. We assigned these workers to the agricultural sector, since their sector of work is not recorded in the data. This increases the share of agricultural employment in total employment under both definitions, but also affects the difference between the two. Of the roughly 10,000 sample individuals who mainly farm for own use (and are therefore in agriculture by the previous standards), about 40 percent are no longer employed by the new standards, while almost 10 percent are reclassified as casual/ganyu workers. Some of these would likely be reclassified as non-agricultural workers if their sector of work had been recorded in the data.

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