We showed that the potential of women under equality of opportunities was considerable and that their current contribution is undervalued. The highest return of single-variable convergences to GDP was given by closing the gap in education, which would increase GDP by 8.3 percent. Most of the increase would be due to an increased share of (more educated) women in the higher-paying modern sector and a shift out of the lower-paid traditional sectors. A reduction of fertility rates to the net reproduction rate of 1.0 would increase GDP by 3.1 percent, due to the impacts of lower fertility on higher female educational attainment, increased female labor supply, and an increased allocation of women to the modern sector (though men’s modern sector employment would also grow).

While individual convergences in labor are limited, simultaneously closing gender gaps in laborrelevant domains would have led to an increase in output equivalent to 11.5 percent of GDP. Closing the gender labor force participation rate would have increased GDP by 2.3 percent, the modest value is attributable to the small difference in women’s and men’s labor force participation rates in 2020. Closing the gender pay gap within sectors would have increased GDP by 4.8 percent and women’s contribution to GDP would have risen to 30.1 percent. If men and women were equally represented in each sector, GDP would have increased by 2.48 percent once accounting for the change in wages due to a changing sector size.

If we considered all convergences simultaneously, GDP would have increased by 23.7 percent, reaching USD 5 billion. Given the endogenous relationships between the sub-modules developed, it was not appropriate to simply sum the effects of the individual convergences. However, the macrosimulation model allowed the convergences to simultaneously work through various channels, which reduced the chance of double- or under-counting. Women would have been responsible for 1.87 billion or 37.4 percent of GDP and 50.2 percent of the aggregate production of labor.

When adding non-tradable production to the full gender convergence estimates, GDP would equal USD 5.89 billion. With such addition, women’s potential would be maximized in the Liberian economy as their contribution to GDP would rise to 41.4 percent while the value added to the labor market would be 52.8 percent.

The predictions found in this study are comparable to studies that have attempted to estimate the economic losses due to gender inequality on employment and productivity. The 11.5 percent increase in GDP (and GDP-per-capita) that was generated by eradicating labor-relevant inequalities between men and women in our model closely resembles the estimated 8.9 percent increase found in estimates from Niger (World Bank, 2019) and the 19 percent increase in GDP-per-capita found in a multi-country study on employment and productivity (Pennings, 2022). On the other hand, our estimate of an 8.3 percent increase in output per capita from closing the gender gap in education was almost three times larger than the increase found by Devadas & Kim (2020) even though our study estimated similar average losses from the difference in labor force participation rates between men and women; the Devadas & Kim (2020) study estimated a 1.4 percent loss from gender gaps in labor force participation, which is about 0.9 percentage points lower than the 2.3 percent loss that we estimated for Liberia.

Our approach is not without its limitations, many of which have been discussed throughout this paper as well as in prior studies that have used macrosimulation models for inference. A key constraint of our model is in its limited ability to infer general equilibrium effects that are not explicitly incorporated through our identified channels of interest.<sup>30</sup> While there may be value added to modeling these relationships more

> 30 An example of this limitation can be observed in our conceptualization of the labor market in which labor supply allocations across sectors by gender may in turn have dynamic impacts on wages by gender and by sector, to the extent that wages in the formal sector may fall over time as more skilled women enter the labor market and are allocated to that sector.

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