Leaving No Women Behind: Evaluating the Impact of the COVID-19 Pandemic on Livelihood Outcomes in Kenya and Ethiopia
Abstract
:1. Introduction
2. SARS-CoV-2 Pandemic, Gender, and Outcomes
3. Materials and Methods
3.1. Data
3.2. Measures
3.2.1. Food Insecurity during the SARS-CoV-2 Pandemic
3.2.2. Income and Consumption Losses during the SARS-CoV-2 Pandemic
3.3. Empirical Strategy
3.4. Identifying the Impact of the SARS-CoV-2 Pandemic
4. Results
4.1. Summary Statistics
4.2. SARS-CoV-2 Pandemic and the Vulnerability of Women within the Household
4.3. What Explains the Vulnerability of Female-Headed Families in Kenya and Ethiopia during the SARS-CoV-2 Pandemic?
5. Discussion
6. Recommendations
7. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Ethiopia | Kenya | |||
---|---|---|---|---|
Variables | N | Mean (%) | N | Mean (%) |
Age (years) | 3249 | 39.01 | 10,374 | 35.30 |
Female-headed family | 995 | 24.38 | 2733 | 30.09 |
Able to read and write | 2440 | 58.18 | n/a | |
Never married | 536 | 13.62 | n/a | |
Married | 2120 | 71.98 | n/a | |
Divorced/widowed | 547 | 14.40 | n/a | |
Number of children in the household | ||||
None | 1107 | 22.24 | 3014 | 31.55 |
1–2 children | 1459 | 45.33 | 4346 | 41.33 |
3–4 children | 533 | 24.36 | 2305 | 21.89 |
5 or more children | 150 | 8.07 | 709 | 5.22 |
pre-COVID-19 household wealth | ||||
asset quintile 1 (poorest) | 220 | 16.69 | 2912 | 26.88 |
asset quintile 2 | 217 | 18.60 | 1746 | 14.54 |
asset quintile 3 | 373 | 19.30 | 5082 | 52.10 |
asset quintile 4 | 649 | 22.45 | n/a | |
asset quintile 5 | 1751 | 22.96 | 634 | 6.47 |
Rural resident | 966 | 66.89 | 34,759 | 66.52 |
Observations | 3249 | 10,374 |
Went Hungry | Adult Skipped Meals | Child Skipped Meals | Worry over Inadequate Food | |||||
---|---|---|---|---|---|---|---|---|
Specification | β | Std. Error | β | Std. Error | β | Std. Error | β | Std. Error |
Female-headed family | 0.0396 *** | 0.0048 | 0.0342 *** | 0.0047 | 0.0333 *** | 0.0037 | 0.0341 *** | 0.0104 |
Number of children | ||||||||
1–2 children | 0.0648 *** | 0.0053 | 0.0719 *** | 0.0052 | 0.1517 *** | 0.0037 | 0.0637 *** | 0.0114 |
3–4 children | 0.1126 *** | 0.0064 | 0.1218 *** | 0.0063 | 0.2140 *** | 0.0050 | 0.1009 *** | 0.0132 |
5 or more children | 0.1433 *** | 0.0105 | 0.1443 *** | 0.0104 | 0.2559 *** | 0.0095 | 0.0818 *** | 0.0209 |
Lost a job during COVID-19 | 0.1092 *** | 0.0134 | 0.1459 *** | 0.0133 | 0.0991 *** | 0.0122 | 0.0708 *** | 0.0188 |
pre-COVID-19 household wealth | ||||||||
asset quintile 1 (poorest) | 0.1633 *** | 0.0098 | 0.1575 *** | 0.0094 | 0.1016 *** | 0.0070 | 0.2450 *** | 0.0206 |
asset quintile 2 | 0.1863 *** | 0.0101 | 0.1434 *** | 0.0097 | 0.1007 *** | 0.0072 | 0.1762 *** | 0.0216 |
asset quintile 3 | 0.0994 *** | 0.0098 | 0.0951 *** | 0.0095 | 0.0516 *** | 0.0073 | 0.1661 *** | 0.0196 |
asset quintile 4 | 0.1325 *** | 0.0102 | 0.1114 *** | 0.0098 | 0.0626 *** | 0.0068 | 0.0000 | . |
Rural resident | 0.0418 *** | 0.0046 | 0.0130 ** | 0.0045 | 0.0189 *** | 0.0036 | −0.0218 * | 0.0094 |
Age-fixed effects | Yes | Yes | Yes | Yes | ||||
Region-fixed effects | Yes | Yes | Yes | Yes | ||||
Survey-fixed effects | Yes | Yes | Yes | Yes | ||||
Mean of the dependent variable | 0.394 | 0.346 | 0.194 | 0.535 | ||||
Number of observations | 46,129 | 46,134 | 46,134 | 11,292 |
Sold Livestock | Took a Loan | Borrowed from Friends | Business Closed | Credited Purchases | Reduced Food Consumption | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Specification | β | Std. Error | β | Std. Error | β | Std. Error | β | Std. Error | β | Std. Error | β | Std. Error |
Female-headed family | −0.0240 *** | 0.0025 | 0.0120 ** | 0.0044 | 0.0249 *** | 0.0042 | 0.0651 * | 0.0298 | 0.0388 *** | 0.0064 | 0.0303 *** | 0.0077 |
Age-fixed effects | Yes | Yes | Yes | Yes | Yes | Yes | ||||||
Region-fixed effects | Yes | Yes | Yes | Yes | Yes | Yes | ||||||
Survey-fixed effects | Yes | Yes | Yes | Yes | Yes | Yes | ||||||
Mean of the dependent variable | 0.075 | 0.083 | 0.071 | 0.262 | 0.210 | 0.456 | ||||||
Observations | 46,134 | 21,596 | 21,596 | 1097 | 21,596 | 21,596 |
Went Hungry | Adult Skipped Meals | Worry Inadequate Food | Food Ran Out | |||||
---|---|---|---|---|---|---|---|---|
Specification | β | SE | β | SE | β | SE | β | SE |
Female-headed family | 0.0207 *** | 0.0062 | 0.0442 *** | 0.0092 | 0.0721 *** | 0.0106 | 0.0536 *** | 0.0083 |
Number of children | ||||||||
1–2 children | 0.0219 *** | 0.0059 | 0.0419 *** | 0.0085 | 0.0794 *** | 0.0099 | 0.0570 *** | 0.0077 |
3–4 children | 0.0393 *** | 0.0082 | 0.0495 *** | 0.0116 | 0.0705 *** | 0.0132 | 0.0673 *** | 0.0102 |
5 or more children | 0.0784 *** | 0.0155 | 0.0714 *** | 0.0201 | 0.1586 *** | 0.0213 | 0.0969 *** | 0.0174 |
Lost a job during COVID-19 | 0.0861 *** | 0.0226 | 0.1071 *** | 0.0288 | 0.1951 *** | 0.0305 | 0.1327 *** | 0.0187 |
Able to read and write | −0.0444 *** | 0.0075 | −0.1203 *** | 0.0107 | −0.1405 *** | 0.0113 | −0.0660 *** | 0.0088 |
pre-COVID-19 household wealth | ||||||||
asset quintile 1 (poorest) | 0.0777 *** | 0.0123 | 0.2054 *** | 0.0187 | 0.1693 *** | 0.0199 | 0.0575 *** | 0.0143 |
asset quintile 2 | 0.1072 *** | 0.0133 | 0.1788 *** | 0.0187 | 0.1790 *** | 0.0199 | 0.1053 *** | 0.0154 |
asset quintile 3 | 0.1243 *** | 0.0109 | 0.2084 *** | 0.0144 | 0.2175 *** | 0.0153 | 0.1338 *** | 0.0124 |
asset quintile 4 | 0.0882 *** | 0.0077 | 0.1561 *** | 0.0105 | 0.1485 *** | 0.0116 | 0.1174 *** | 0.0091 |
Marital status | ||||||||
never married | −0.0336 *** | 0.0079 | −0.0585 *** | 0.0113 | −0.1017 *** | 0.0133 | −0.0678 *** | 0.0100 |
divorced/separated/widowed | 0.0074 | 0.0085 | 0.0474 *** | 0.0123 | 0.0343 * | 0.0137 | 0.0164 | 0.0110 |
Rural resident | −0.0712 *** | 0.0079 | −0.0894 *** | 0.0108 | −0.0651 *** | 0.0121 | −0.0660 *** | 0.0095 |
Age-fixed effects | Yes | Yes | Yes | Yes | ||||
Region-fixed effects | Yes | Yes | Yes | Yes | ||||
Survey-fixed effects | Yes | Yes | Yes | Yes | ||||
Mean of the dependent variable | 0.085 | 0.234 | 0.404 | 0.201 | ||||
Observations | 14,278 | 14,285 | 14,281 | 17,479 |
Lost Household Income | Lost Business Income | Lost Farm Income | Lost Remittances | |||||
---|---|---|---|---|---|---|---|---|
Specification | β | SE | β | SE | β | SE | β | SE |
Female-headed family | 0.0273 ** | 0.0095 | 0.0129 *** | 0.0031 | −0.0035 | 0.0197 | 0.0141 *** | 0.0032 |
Age-fixed effects | Yes | Yes | Yes | Yes | ||||
Region-fixed effects | Yes | Yes | Yes | Yes | ||||
Survey-fixed effects | Yes | Yes | Yes | Yes | ||||
Mean of the dependent variable | 0.388 | 0.024 | 0.353 | 0.019 | ||||
Observations | 17,453 | 17,479 | 4279 | 17,479 |
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Makate, M.; Makate, C. Leaving No Women Behind: Evaluating the Impact of the COVID-19 Pandemic on Livelihood Outcomes in Kenya and Ethiopia. Int. J. Environ. Res. Public Health 2023, 20, 5048. https://doi.org/10.3390/ijerph20065048
Makate M, Makate C. Leaving No Women Behind: Evaluating the Impact of the COVID-19 Pandemic on Livelihood Outcomes in Kenya and Ethiopia. International Journal of Environmental Research and Public Health. 2023; 20(6):5048. https://doi.org/10.3390/ijerph20065048
Chicago/Turabian StyleMakate, Marshall, and Clifton Makate. 2023. "Leaving No Women Behind: Evaluating the Impact of the COVID-19 Pandemic on Livelihood Outcomes in Kenya and Ethiopia" International Journal of Environmental Research and Public Health 20, no. 6: 5048. https://doi.org/10.3390/ijerph20065048