Steady-state EWAPs are fairly homogeneous for men, but vary widely for women. Only 21 EMDEs have significantly above- or below-average EWAPs for men (and those are mostly in SubSaharan Africa)—less than half the number of EMDEs (59 EMDEs) with significant deviations from the same average for women’s EWAPs. More than three-quarters of the EMDEs in the Middle East and North Africa and South Asia are converging to significantly below-average EWAPs for women (see also World Bank 2024). The deviation is considerable: it averages 34 and 19 percent of the female working-age population, respectively. In contrast, two-thirds of the EMDEs in East Asia and the Pacific are converging towards above-average steady-state EWAPs for women.

The _aggregate_ steady-state EWAPs that deviate statistically significantly from the EMDE average reflect pockets of weakness in countries’ labor markets.<sup>4</sup> In Sub-Saharan Africa, these deviations in aggregate steady-state EWAPs seem to be significantly correlated with deviations in agricultural steady-state EWAPs (Figure 3). A linear regression of the steady-state EWAPs in aggregate on the steady-state EWAP in agriculture or non-agriculture illustrates the correlation (Table 3). In the steady state, for every 1 percentage point higher _agricultural_ EWAP, the _aggregate_ EWAP is also higher by 0.67 percentage point (broadly in line with the share of agricultural employment of 75 percent during 2000-19). Meanwhile, higher non-agricultural EWAPs are not associated with higher aggregate EWAPs in Sub-Saharan Africa.

In other EMDEs, the opposite is the case: for every 1 percentage point higher _non-agricultural_ steady-state EWAP, the _aggregate_ steady-state EWAP is 0.72 percentage point higher—almost twice as much as might be expected arithmetically, based on the share of non-agricultural employment in this group of countries (39 percent during 2000-19). In EMDEs outside SubSaharan Africa, agricultural and aggregate steady-state EWAPs are much less closely linked than in Sub-Saharan Africa and also less closely linked than non-agricultural and aggregate ratios outside Sub-Saharan Africa.

For the vast majority of EMDEs (i.e., those outside Sub-Saharan Africa), this is consistent with the assumption that aggregate steady-state EWAPs are, in the long-run, determined by the nonagricultural sector. In the remainder of this paper, we therefore focus on the correlates of nonagricultural EWAPs.

# **3.3 Robustness**

These regression results for the first stage are robust to using different samples. Table 4 compares the results between the baseline sample (Column I) and alternative samples, including: a sample of all countries including both advanced economies and EMDEs since 1960 (Column II), for all EMDEs including small states since 1960s (Column III), and for a trimmed sample of all EMDEs that excludes countries whose real output growth or EWAP growth is in the top or bottom 1 percent (Column IV).

In addition, some studies in the growth literature have used 10-year average changes instead of year-over-year changes as the dependent variable (e.g., Kremer, Willis, and You 2022). This alternative calculation would smooth out variations across years within the decade. Column V

> 4 While there is a significant difference between the correlations of non-agricultural and agricultural steady-state employment ratios with aggregate ones, there is no material difference between correlation between men’s and women’s steady-state employment ratios and aggregate ratios.

10