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Labor productivity and employment gaps in Sub-Saharan Africa

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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.


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Figure (a) (top) shows a global cross-section of agricultural labor and employment shares graphed against a log transformation of each country’s per capita GDP. Figure (b) (bottom) shows agricultural labor productivity gaps graphed against the log of GDP per capita (Source: Gollin et al., 2014a, Gollin et al., 2014b). The horizontal dashed line represents inter-sectoral parity in labor productivity (value = 1).
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f0005: Figure (a) (top) shows a global cross-section of agricultural labor and employment shares graphed against a log transformation of each country’s per capita GDP. Figure (b) (bottom) shows agricultural labor productivity gaps graphed against the log of GDP per capita (Source: Gollin et al., 2014a, Gollin et al., 2014b). The horizontal dashed line represents inter-sectoral parity in labor productivity (value = 1).

Mentions: The premise of higher returns to labor outside of agriculture is quite central to structural change. Are these productivity differentials really as high as national accounts data suggest? I use a new micro-level dataset to measure key structural change parameters – sector participation, time use, and labor productivity – from a micro perspective. This paper draws on the Integrated Surveys on Agriculture from the Living Standards Measurement Study group at the World Bank (LSMS-ISA datasets), which explicitly collect information about respondents’ time use across sectors. Particular attention is paid to farm labor, which is often neglected in large scale, multi-topic surveys because of the challenges involved in collecting detailed agricultural data. The analysis includes surveys from Ethiopia, Malawi, Tanzania and Uganda.1 The countries comprising the LSMS-ISA dataset exhibit considerable heterogeneity with respect to GDP per capita, agriculture’s share of the labor force and economy, and productivity gaps (Fig. 1).


Labor productivity and employment gaps in Sub-Saharan Africa
Figure (a) (top) shows a global cross-section of agricultural labor and employment shares graphed against a log transformation of each country’s per capita GDP. Figure (b) (bottom) shows agricultural labor productivity gaps graphed against the log of GDP per capita (Source: Gollin et al., 2014a, Gollin et al., 2014b). The horizontal dashed line represents inter-sectoral parity in labor productivity (value = 1).
© Copyright Policy - CC BY
Related In: Results  -  Collection

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

f0005: Figure (a) (top) shows a global cross-section of agricultural labor and employment shares graphed against a log transformation of each country’s per capita GDP. Figure (b) (bottom) shows agricultural labor productivity gaps graphed against the log of GDP per capita (Source: Gollin et al., 2014a, Gollin et al., 2014b). The horizontal dashed line represents inter-sectoral parity in labor productivity (value = 1).
Mentions: The premise of higher returns to labor outside of agriculture is quite central to structural change. Are these productivity differentials really as high as national accounts data suggest? I use a new micro-level dataset to measure key structural change parameters – sector participation, time use, and labor productivity – from a micro perspective. This paper draws on the Integrated Surveys on Agriculture from the Living Standards Measurement Study group at the World Bank (LSMS-ISA datasets), which explicitly collect information about respondents’ time use across sectors. Particular attention is paid to farm labor, which is often neglected in large scale, multi-topic surveys because of the challenges involved in collecting detailed agricultural data. The analysis includes surveys from Ethiopia, Malawi, Tanzania and Uganda.1 The countries comprising the LSMS-ISA dataset exhibit considerable heterogeneity with respect to GDP per capita, agriculture’s share of the labor force and economy, and productivity gaps (Fig. 1).

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