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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.

In Africa, most development strategies include efforts to improve the productivity of staple crops grown on smallholder farms. An underlying premise is that small farms are productive in the African context and that smallholders do not forgo economies of scale-a premise supported by the often observed phenomenon that staple cereal yields decline as the scale of production increases. This paper explores a research design conundrum that encourages researchers who study the relationship between productivity and scale to use surveys with a narrow geographic reach in order to produce more reliable results, even though results are better suited for policy decisions when they are based on data that are broadly representative. Using a model of endogenous technology choice, we explore the relationship between maize yields and scale using alternative data. Since rich descriptions of the decision environments that farmers face are needed to identify the applied technologies that generate the data, improvements in the location specificity of the data should reduce the likelihood of identification errors and biased estimates. However, our analysis finds that the inverse productivity hypothesis holds up well across a broad platform of data, despite obvious shortcomings with some components. It also finds surprising consistency in the estimated scale elasticities.

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

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