6 productivity,<sup>8</sup> nontradable) services in urban areas, consistent with the emergence of consumption cities following Africa’s resource boom (Gollin, Jedwab, Vollrath, 2016), and premature deindustrialization (Rodrik, 2016). Nonetheless, a glance at the national accounts would suggest that huge gains can still be reaped from an accelerated reallocation of labor out of agriculture. Also using macro data, Gollin, Lagakos, and Waugh (2014b) estimate that non-agricultural labor is 6 times more productive than agricultural labor in Africa, relative to 4.5 times in other developing countries, 3.4 times in middle income countries, and 2.2 in high income countries.

Yet measuring the potential gains from intersectoral labor reallocation is wrought with measurement challenges, and the national accounts and macro data routinely overstate the prospective gains from leaving agriculture. When adjusting their macro estimates for sectoral differences in human capital and hours worked, the agricultural labor productivity gap declines by half, to 3.3 for SSA and 2.2 for developing countries (Gollin, Lagakos and Waugh, 2014b). Also correcting for differences in human capital, but using micro income data and indirect proxies for differences in sectoral time use shares instead, Vollrath (2013) finds that the misallocation of labor effort between sectors explains only 12 percent of cross-country income variation, compared to 30 percent when using unadjusted macro data from the national accounts.

Important new work by McCullough (2016) using household income and individual hourly labor input data by sector collected through nationally representative household surveys in four countries under the World Bank-led Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMSISA) initiative points in the same direction. Once one accounts for inter-sectoral differences in time worked, which is particularly important due to the seasonal nature of agricultural work as well as the often-diversified income portfolios of rural households, the productivity differentials commonly found in less detailed data sets nearly disappear. The powerful implications are that what is commonly understood as an intersectoral labor productivity gap may be more an employment gap and that the commonly used agricultural productivity gap measures drawn from the national accounts should not be taken as proof of agriculture as an intrinsically less productive sector. The lower-than-expected domestic migration observed in Africa (De Brauw, Mueller and Lee 2014) is consistent with this perspective.

Furthermore, important labor productivity gaps appear _within_ sectors. Bringing those operating at the 25<sup>th</sup> percentile in the net labor productivity distribution to the 75<sup>th</sup> percentile would increase net agricultural labor productivity 4.5 times in Uganda and 7.8 times in Côte d’Ivoire (Christiaensen and Kaminski 2015, World Bank 2016). Substantial scope for intrasectoral labor productivity gains have been similarly observed within the nonagricultural sectors. Finally, while the drivers of structural change are hard to properly identify econometrically, McMillan and Harttgen (2014) and Gollin Lagakos and Waugh (2014b) both report important correlations with proxies of agricultural productivity.

These findings signal (i) the continued importance of focusing on agricultural productivity growth as a vehicle for ushering in structural transformation – rather than prematurely shifting workers to other sectors – and (ii) the substantial scope for improving labor productivity and employment within sectors. Agricultural transformation based on productivity growth, improved market functioning and growth in the rural non-farm economy, remains essential to achieve the goal of inclusive growth and prosperity in SSA.

# **3 Structural features of African food systems that impede a structural transformation**

Several key structural features of the region heavily condition the available paths for structural transformation and the policies most likely to help stimulate sustainable transformation. First, **_<u>land</u>_** is an emerging problem in SSA even though as a continent it remains relatively land-abundant. Nearly half of the world’s uncultivated arable land is in SSA (Deininger and Byerlee 2012), making it the world’s primary remaining agricultural frontier. Yet, as much as 90 percent of SSA’s unutilized arable land is

> 8 While low productive, labor productivity may still be higher than in agriculture. The key question is whether adoption of these activities only entails a one-time productivity shift, or whether they also offer opportunities for further productivity growth.