Notes

Needed: Boosti N g the Co N tri B utio N of t o tal f a C t or Produ C tivit y 37

(Burundi, the Central African Republic, and Malawi), whereas the share exceeds 40 percent in another three countries (the Gambia, Mauritius, and South Africa).

Sectoral Labor Productivity

Sectoral labor productivity exhibits large swings over time in most Sub-Saharan African countries. However, it has improved in most of the region’s countries since the mid1990s (Duarte and Restuccia 2018). Labor productivity experienced sharp upswings in agriculture (averaging 4.5 percent per year) and manufacturing (averaging 3 percent per year) from 1990 to 2016. Productivity growth in market and nonmarket services was less dynamic (with annual average growth rates of 1.6 percent and 1.1 percent, respectively).

In spite of its faster growth, labor productivity is lower in agriculture than in the region’s nonagricultural activities—namely, manufacturing, nonmanufacturing, and market and nonmarket services. By 2016, the ratio of value added per worker relative to that of agriculture was 2.9 in market services, 5.7 in manufacturing, and 10.4 in nonmanufacturing activities (figure 2.9).

The region’s sectoral productivity gaps relative to agriculture have remained slightly invariant or have declined at a sluggish pace over the past quarter century. However, among the non-resource-rich countries, these gaps have been declining steadily. In contrast, among resource-rich countries, they have declined at a slower pace in all sectors but manufacturing.

Overall, sectoral labor productivity growth in Sub-Saharan Africa is consistent with the process of structural change and aggregate performance. However, there is substantial heterogeneity across countries and over time. A standard structural transformation model shows that low growth in agricultural productivity translates into weak structural change—although faster productivity growth since 1995 has almost doubled the pace of reallocation out of agriculture. The presence of medium-term cycles in trended productivity across countries and over time may reflect either frictions in labor allocation or issues in measurement and specification (Duarte and Restuccia 2018).

Notes

1. Productivity data and ratios for Malaysia and

Senegal are the author’s calculations using

Penn World Table (PWT) data. 2. The capital-output ratio is the amount of capital needed to produce each extra unit of output. As such, it is an indicator of how efficiently new investment contributes to economic growth. 3. The human capital index is calculated from the average years of schooling and an assumed rate of return to education, on the basis of

Mincer equation estimates, around the world.

For a detailed explanation on how the data are compiled and used to construct the index, see “Human Capital in PWT 9.0” (https:// www.rug.nl/ggdc/docs/human_capital_in _pwt_90.pdf). 4. Throughout the “Development Accounting” section, the sample of Sub-Saharan African countries varies by the type of productivity, ratio, or index being measured because of the countries’ varying data availability. For example, a TFP calculation requires complete information on output, inputs, and shares of labor in output, which several countries did not have, resulting in a relatively low total sample (37 countries) for that measurement. 5. Relative to the aspirational development benchmark (represented by the EAP5 countries), the output per worker in 35 (out of 45) countries in Sub-Saharan Africa is less than half the EAP5 average—and less than one-fifth the EAP5 average among 24 of those countries. 6. The HCI has three components: probability of survival, expected learning-adjusted years of school, and health. It reflects the human capital of the next generation given the risks of inadequate education and health in the country where they live (World Bank 2019). 7. Outside Sub-Saharan Africa, only 11 countries had such low relative TFP—although US

TFP is, on average, no more than eight times that of this group. 8. Appendix B of this report, “Country Productivity Analysis of Sub-Saharan Africa,” presents a visual analysis of the development accounting exercises for all countries in the region, with data available on output,