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Labor productivity and employment gaps in Sub-Saharan Africa

View Article: PubMed Central - PubMed

ABSTRACT

Drawing on a new set of nationally representative, internationally comparable household surveys, this paper provides an overview of key features of structural transformation – labor allocation and labor productivity – in four African economies. New, micro-based measures of sector labor allocation and cross-sector productivity differentials describe the incentives households face when allocating their labor. These measures are similar to national accounts-based measures that are typically used to characterize structural change. However, because agricultural workers supply far fewer hours of labor per year than do workers in other sectors in all of the countries analyzed, productivity gaps shrink by half, on average, when expressed on a per-hour basis. Underlying the productivity gaps that are prominently reflected in national accounts data are large employment gaps, which call into question the productivity gains that laborers can achieve through structural transformation. Furthermore, agriculture’s continued relevance to structural change in Sub-Saharan Africa is highlighted by the strong linkages observed between rural non-farm activities and primary agricultural production.

No MeSH data available.


Related in: MedlinePlus

Figure (a) (top) shows average annualized output per worker per year by month of household interview (and the 95% confidence interval for each productivity measure). The horizontal line shows the annual mean for each productivity measure, with the dashed lines above and below depicting their 95% confidence intervals. And the share of observations per month is plotted at the bottom of the figure along the right hand axis. Figure (b) (bottom) shows sectoral output per hour of labor supplied, along with the annual mean for output per hour worked.
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f0040: Figure (a) (top) shows average annualized output per worker per year by month of household interview (and the 95% confidence interval for each productivity measure). The horizontal line shows the annual mean for each productivity measure, with the dashed lines above and below depicting their 95% confidence intervals. And the share of observations per month is plotted at the bottom of the figure along the right hand axis. Figure (b) (bottom) shows sectoral output per hour of labor supplied, along with the annual mean for output per hour worked.

Mentions: I demonstrate how the per-worker-per-year and per-hour labor productivity measures vary by month of survey visit in Fig.8.9 Each diamond represents a monthly mean productivity measure, and the bar it sits within depicts 95% confidence intervals for the mean. The horizontal solid line represents the annual survey-weighted average for the survey, along with dashed lines above and below representing its 95% confidence intervals. If more surveys are conducted during high or low productivity times within the year, then annual productivity aggregates would be biased. This is especially concerning if different sectors have different seasonality patterns within a country. According to Fig. 8, there are some months with especially high or low productivity measures, but there does not seem to be a major pattern of over- or under-representing these months.


Labor productivity and employment gaps in Sub-Saharan Africa
Figure (a) (top) shows average annualized output per worker per year by month of household interview (and the 95% confidence interval for each productivity measure). The horizontal line shows the annual mean for each productivity measure, with the dashed lines above and below depicting their 95% confidence intervals. And the share of observations per month is plotted at the bottom of the figure along the right hand axis. Figure (b) (bottom) shows sectoral output per hour of labor supplied, along with the annual mean for output per hour worked.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5384442&req=5

f0040: Figure (a) (top) shows average annualized output per worker per year by month of household interview (and the 95% confidence interval for each productivity measure). The horizontal line shows the annual mean for each productivity measure, with the dashed lines above and below depicting their 95% confidence intervals. And the share of observations per month is plotted at the bottom of the figure along the right hand axis. Figure (b) (bottom) shows sectoral output per hour of labor supplied, along with the annual mean for output per hour worked.
Mentions: I demonstrate how the per-worker-per-year and per-hour labor productivity measures vary by month of survey visit in Fig.8.9 Each diamond represents a monthly mean productivity measure, and the bar it sits within depicts 95% confidence intervals for the mean. The horizontal solid line represents the annual survey-weighted average for the survey, along with dashed lines above and below representing its 95% confidence intervals. If more surveys are conducted during high or low productivity times within the year, then annual productivity aggregates would be biased. This is especially concerning if different sectors have different seasonality patterns within a country. According to Fig. 8, there are some months with especially high or low productivity measures, but there does not seem to be a major pattern of over- or under-representing these months.

View Article: PubMed Central - PubMed

ABSTRACT

Drawing on a new set of nationally representative, internationally comparable household surveys, this paper provides an overview of key features of structural transformation – labor allocation and labor productivity – in four African economies. New, micro-based measures of sector labor allocation and cross-sector productivity differentials describe the incentives households face when allocating their labor. These measures are similar to national accounts-based measures that are typically used to characterize structural change. However, because agricultural workers supply far fewer hours of labor per year than do workers in other sectors in all of the countries analyzed, productivity gaps shrink by half, on average, when expressed on a per-hour basis. Underlying the productivity gaps that are prominently reflected in national accounts data are large employment gaps, which call into question the productivity gains that laborers can achieve through structural transformation. Furthermore, agriculture’s continued relevance to structural change in Sub-Saharan Africa is highlighted by the strong linkages observed between rural non-farm activities and primary agricultural production.

No MeSH data available.


Related in: MedlinePlus