Structural transformation and the gender pay gap in Sub-Saharan Africa.

The focus of this study is the implications of structural transformation for gender equality, specifically equal pay, in Sub-Saharan Africa. While structural transformation affects key development outcomes, including growth, poverty, and access to decent work, its effect on the gender pay gap is not clear ex-ante. Evidence on the gender pay gap in sub-Saharan Africa is limited, and often excludes rural areas and informal (self-)employment. This paper provides evidence on the extent and drivers of the gender pay gap in non-farm wage- and self-employment activities across three countries at different stages of structural transformation (Malawi, Tanzania and Nigeria). The analysis leverages nationally-representative survey data and decomposition methods, and is conducted separately among individuals residing in rural versus urban areas in each country. The results show that women earn 40 to 46 percent less than men in urban areas, which is substantially less than in high-income countries. The gender pay gap in rural areas ranges from (a statistically insignificant) 12 percent in Tanzania to 77 percent in Nigeria. In all rural areas, a major share of the gender pay gap (81 percent in Malawi, 83 percent in Tanzania and 70 percent in Nigeria) is explained by differences in workers' characteristics, including education, occupation and sector. This suggests that if rural men and women had similar characteristics, most of the gender pay gap would disappear. Country-differences are larger across urban areas, where differences in characteristics account for only 32 percent of the pay gap in Tanzania, 50 percent in Malawi and 81 percent in Nigeria. Our detailed decomposition results suggest that structural transformation does not consistently help bridge the gender pay gap. Gender-sensitive policies are required to ensure equal pay for men and women.

Representativeness of individual-level data in COVID-19 phone surveys: Findings from Sub-Saharan Africa.

The COVID-19 pandemic has created urgent demand for timely data, leading to a surge in mobile phone surveys for tracking the impacts of and responses to the pandemic. Using data from national phone surveys implemented in Ethiopia, Malawi, Nigeria and Uganda during the pandemic and the pre-COVID-19 national face-to-face surveys that served as the sampling frames for the phone surveys, this paper documents selection the biases in individual-level analyses based on phone survey data. In most cases, individual-level data are available only for phone survey respondents, who we find are more likely to be household heads or their spouses and non-farm enterprise owners, and on average, are older and better educated vis-a-vis the general adult population. These differences are the result of uneven access to mobile phones in the population and the way that phone survey respondents are selected. To improve the representativeness of individual-level analysis using phone survey data, we recalibrate the phone survey sampling weights based on propensity score adjustments that are derived from a model of an individual's likelihood of being interviewed as a function of individual- and household-level attributes. We find that reweighting improves the representativeness of the estimates for phone survey respondents, moving them closer to those of the general adult population. This holds for both women and men and for a range of demographic, education, and labor market outcomes. However, reweighting increases the variance of the estimates and, in most cases, fails to overcome selection biases. This indicates limitations to deriving representative individual-level estimates from phone survey data. Obtaining reliable data on men and women through future phone surveys will require random selection of adult interviewees within sampled households.

Viewpoint: High-frequency phone surveys on COVID-19: Good practices, open questions.

Following the onset of the COVID-19 pandemic, face-to-face survey data collection efforts came to a halt due to lockdowns, limitations on mobility and social distancing requirements. What followed was a surge in phone surveys to fulfill rapidly evolving needs for timely and policy-relevant microdata for understanding the socioeconomic impacts of and responses to the pandemic. Even as the face-to-face survey data collection efforts are resuming in different parts of the world with COVID-19 safety protocols, the rapidly-acquired experience with phone surveys on the part of national statistical offices and survey practitioners in low- and middle-income countries appears to have formed the foundation for phone surveys to be more commonly implemented in the post-pandemic era, in response to other shocks and as complementary efforts to face-to-face surveys. Informed by the practical experience with the high-frequency phone surveys that have been implemented with support from the World Bank Living Standards Measurement Study (LSMS) to monitor the socioeconomic impacts of the COVID-19 pandemic, this paper provides an overview of options for the design and implementation of phone surveys to collect representative data from households and individuals. Further, the discussion identifies the requirements for phone surveys to be a mainstay in the toolkits of national statistical offices and the directions for future research on the design and implementation of phone surveys.

Socioeconomic impacts of COVID-19 in low-income countries.

The emergence of SARS-CoV-2 and attempts to limit its spread have resulted in a contraction of the global economy. Here we document the socioeconomic impacts of the pandemic among households, adults and children in low-income countries. To do so, we rely on longitudinal household survey data from Ethiopia, Malawi, Nigeria and Uganda, originating from pre-COVID-19 face-to-face household surveys plus phone surveys implemented during the pandemic. We estimate that 256 million individuals-77% of the population-live in households that have lost income during the pandemic. Attempts to cope with this loss are exacerbated by food insecurity and an inability to access medicine and staple foods. Finally, we find that student-teacher contact has dropped from a pre-COVID-19 rate of 96% to just 17% among households with school-aged children. These findings can inform decisions by governments and international organizations on measures to mitigate the effects of the COVID-19 pandemic.

Physical activity and sedentary time in a rural adult population in Malawi compared with an age-matched US urban population.

OBJECTIVES: This study was designed to assess patterns of objectively measured physical activity (PA) and sedentary behaviour in a sample of adults in a rural setting from a low-income Sub-Saharan African country (Malawi). The patterns of PA and sedentary behaviour in Malawi were compared with US data collected and analysed using the same methodology. METHODS: The Malawi PA data were collected as part of a survey experiment on the measurement of agricultural labor conducted under the World Bank Living Standards Measurement Study program. ActiGraph accelerometers (model GT3X) were worn on the right hip in a household-based sample of 414 working-age adults (15-85 years). RESULTS: Mean total and 95% CIs for PA by category in min/day for Malawi adults were: sedentary 387.6 (377.4-397.8), low-light 222.1 (214.7-229.5), high-light 136.3 (132.7-139.9), moderate 71.6 (68.8-74.5), vigorous 1.1 (0.5-1.8) and moderate-to-vigorous physical activity (MVPA) 72.8 (69.7-75.9). Mean of PA and sedentary behavior (min/day) summed across age and sex groups are compared between Malawi and US samples: sedentary behaviour, 387.6 vs 525.8 (p<0.001); low-light, 222.1 vs 217.0 (p=ns); high-light, 136.3 vs 45.6 (p<0.001); moderate, 71.6 vs 28.0 (p<0.001); vigorous, 1.1 vs 2.5 (p<0.001); MVPA, 72.8 vs 30.5 (p<0.001). Compared with the USA, Malawi participants averaged consistently less sedentary time/day and more minutes/day in all intensity levels of PA, except for low-light and vigorous PA. CONCLUSION: Overall, levels of MVPA and high-light activity in adults in Malawi were substantially higher and sedentary time was substantially lower than those observed in US samples using near identical data collection, scoring and analysis.

Composition of Household Income and Child Nutrition Outcomes Evidence from Uganda.

This study targets the empirical space between cross-country analyses exploring links between income and nutrition without insights on micro-level determinants, and relevant microeconomic studies hindered by small sample size and/or incomplete data. We use the rural samples of the three waves of the Uganda National Panel Survey, and estimate panel regressions of child height-for-age z-scores (HAZ) controlling for time-invariant child-level heterogeneity. On the whole, we find no impact of short-term changes in total gross income on HAZ but document small positive correlations for younger children. Sector-differentiated analyses indicate that compared to wage earnings, only share of income from non-farm self-employment correlates positively with HAZ. Within agriculture, shares of income from consumption of own crop production and from low-protein crop production underlie the negative effect of share of income from crop production. While we cannot claim causal relationships, our findings suggest the possibility of "stickiness" of crop production to own consumption.

How much of the labor in African agriculture is provided by women?

The contribution of women to labor in African agriculture is regularly quoted in the range of 60-80%. Using individual, plot-level labor input data from nationally representative household surveys across six Sub-Saharan African countries, this study estimates the average female labor share in crop production at 40%. It is slightly above 50% in Malawi, Tanzania, and Uganda, and substantially lower in Nigeria (37%), Ethiopia (29%), and Niger (24%). There are no systematic differences across crops and activities, but female labor shares tend to be higher in households where women own a larger share of the land and when they are more educated. Controlling for the gender and knowledge profile of the respondents does not meaningfully change the predicted female labor shares. The findings question prevailing assertions regarding substantial gains in aggregate crop output as a result of increasing female agricultural productivity.