This paper quantifies the gains in gross domestic product per capita from closing gender employment gaps in the Middle East and North Africa, using three neoclassical growth models. The paper starts with baseline impacts from the Gender Employment Gap Index, which suggests that in the long run, gross domestic product per capita would be around 50 percent higher in the typical economy in the region if gender employment gaps were closed (mean 54 percent, median 49 percent). However, the gains are heterogeneous, ranging from less than 10 percent in Qatar to more than 80 percent in the Republic of Yemen. The paper then explores short-term gains, when capital is fixed (or adjusts slowly), and gains in the medium-term, with sluggish implementation of reforms using the Long Term Growth Model, which roughly halves the gains (and lowers the gains by more than half in resource-rich countries). Finally, the paper incorporates the effects of changes in the skill distribution in a model incorporating capital-skill complementarities in production. Because gender employment gaps in the Middle East and North Africa tend to be larger among the unskilled, closing these gaps reduces average skill levels, moderating long-term gains by 5-10 percentage points. However, if women in the Middle East and North Africa continue the current trend toward greater educational attainment, the gains will be greater than in the baseline. All three models—the Gender Employment Gap Index, the Long Term Growth Model, and capital-skill complementarities—point to large increases in gross domestic product per capita from closing gender employment gaps.
Repository name | URI |
---|---|
Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
The code was reproduced on a computer with the following specifications:
– OS: Windows 11 Enterprise
– Processor: Intel(R) Core(TM) i5-1145G7 CPU @ 2.60GHz
– Memory available: 11.7 GB
– Software version: Stata version 18
~20-minutes runtime
To run the script, new users only need to change the directory of the Main do file (MasterDoFileFigures) and run the code.
All datasets utilized in this research are publicly accessible and have been included in this reproducibility package.
Author | Affiliation | |
---|---|---|
Federico Fiuratti | World Bank | ffiuratti@worldbank.org |
Steven Pennings | World Bank | spennings@worldbank.org |
Jesica Torres | World Bank | jtorrescoronado@worldbank.org |
2024-01
Location | Code |
---|---|
Middle East and North Africa | MNA |
The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.
Name | URI |
---|---|
Modified BSD3 | https://opensource.org/license/bsd-3-clause/ |
Name | Affiliation | |
---|---|---|
Steven Pennings | World Bank | spennings@worldbank.org |
Reproducibility WBG | World Bank | reproducibility@worldbank.org |
Name | Abbreviation | Affiliation | Role |
---|---|---|---|
Reyes Retana | MRR | World Bank | Junior Data Scientist |
2024-01-22
1