Access to jobs is essential for economic growth. In Africa, unemployment rates are notably high. This paper reexamines the relationship between transport mobility and labor market outcomes, with a particular focus on the direct and indirect effects of transport connectivity. As predicted by theory, wages are influenced by the level of commuting deterrence. Generally, higher earnings are associated with longer commute times and/or higher commuting costs. Local accessibility is also important especially for individuals with time constraints. Both direct and indirect impacts are found to be significant in South Africa, where job accessibility has been challenging since the end of apartheid. For the direct impact, the wage elasticity associated with commuting costs is significant. Returns on commute are particularly high for women. Local accessibility to socioeconomic facilities, such as shops and health services, is also found to have a significant impact, consistent with the concept of mobility of care. To enhance employment, therefore, it is crucial to connect people not only to job locations but also to various socioeconomic points of interest, such as markets and hospitals, in an integrated manner. This integration will enable individuals to spend more time working and commuting longer distances.
| Repository name | URI |
|---|---|
| Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
Paper exhibits were reproduced on a computer with the following specifications:
• OS: Windows 11 Enterprise
• Processor: Intel(R) Xeon(R) Gold 6226R CPU @ 2.90GHz
• Memory available: 5.7 GB
Runtime: 10 minutes.
1. Access the data: Some data used in the reproducibility package are accessible but not redistributable with the package. These data need to be obtained for the code to run. See the Datasets section for details.
2. Download and place the data: Once all data are obtained, copy it to the "data" folder.
3. Run the Stata code: Adjust the folder path in line 5 of the do-file "SouthAfrica_Travel_Analysis_2025sep30_OpenData.do" and run the code.
4. Open the Excel file: Open the Excel file "SouthAfrica_Excel_Data.xlsx" to display figures 2-5. All of these use data included in the reproducibility package and are already generated in the Excel file.
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| Author | Affiliation | |
|---|---|---|
| Atsushi Iimi | World Bank | aiimi@worldbank.org |
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| Location | Code |
|---|---|
| South Africa | ZAF |
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 | |
|---|---|---|
| Atsushi Iimi | World Bank | aiimi@worldbank.org |
| Reproducibility WBG | World Bank | reproducibility@worldbank.org |
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Reproducibility WBG | DECDI | World Bank - Development Impact Department | Verification and preparation of metadata |
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