Official statistics in sub-Saharan Africa do not tend to support the idea that it is common for poor people to work for other people on a casual basis. Standard labour force surveys (LFS), household income and expenditure surveys, and population censuses – with variations between individual country contexts – normally underestimate the significance of wage employment in rural areas (Mwamadzingo 2003; Oya 2013; Sender et al. 2005). This phenomenon, as the World Bank has recently acknowledged, stems from the fact that: ‘data that classify workers by their main activity typically miss large numbers of casual wage earners’ (World Bank 2007, 205). Data on population, size, density, and various indicators of socio-economic development (e.g. GDP per capita, literacy, child mortality and malnutrition) show the existence of significant differences between Ethiopia and Rwanda (see Table 7.1). However, by comparing the results of official statistics with those of other (often micro) studies on rural poverty, a similar story emerges from the two case studies: it is evident that there are two contrasting pictures of rural poverty in both countries. The official story depicts small, independent farmers as constituting the bulk of the poor. By contrast, micro-studies suggest that very poor individuals, while retaining access to small plots of land, critically rely on casual earnings in the labour market for their livelihoods.
The policy neglect of rural wage employment: The cases of Rwanda and Ethiopia / Rizzo, M; Petit, N. - (2015), pp. 171-204.
The policy neglect of rural wage employment: The cases of Rwanda and Ethiopia
Rizzo M;
2015
Abstract
Official statistics in sub-Saharan Africa do not tend to support the idea that it is common for poor people to work for other people on a casual basis. Standard labour force surveys (LFS), household income and expenditure surveys, and population censuses – with variations between individual country contexts – normally underestimate the significance of wage employment in rural areas (Mwamadzingo 2003; Oya 2013; Sender et al. 2005). This phenomenon, as the World Bank has recently acknowledged, stems from the fact that: ‘data that classify workers by their main activity typically miss large numbers of casual wage earners’ (World Bank 2007, 205). Data on population, size, density, and various indicators of socio-economic development (e.g. GDP per capita, literacy, child mortality and malnutrition) show the existence of significant differences between Ethiopia and Rwanda (see Table 7.1). However, by comparing the results of official statistics with those of other (often micro) studies on rural poverty, a similar story emerges from the two case studies: it is evident that there are two contrasting pictures of rural poverty in both countries. The official story depicts small, independent farmers as constituting the bulk of the poor. By contrast, micro-studies suggest that very poor individuals, while retaining access to small plots of land, critically rely on casual earnings in the labour market for their livelihoods.| File | Dimensione | Formato | |
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