Dimensions of the Productivity Assessment

8 b oostin G Pro D u C tivity in s ub- sA h A r A n Afri CA

According to this framework, lower values of Ai reflect either slow adoption or inefficient use of technology. The efficient allocation in this economy maximizes final output and is characterized by two decisions: (a) the number of operating establishments (that is, establishments that can pay the fixed cost, c); and (b) the allocation of capital and labor across the operating establishments. If either of these decisions is distorted, the economy will have lower output and hence lower aggregate TFP—as aggregate factor inputs (K and H) in the industry are constant.

An allocation of inputs that maximizes output across production units (say, either firms or farms) takes place when, conditional upon their operation, the marginal (and average) products are equal across all production units. In this equilibrium, no output gains would be obtained by reallocating inputs of production (such as capital, land, and labor) from production units with low marginal products to those with high marginal products. In the efficient allocation, the most productive operating establishments will demand more inputs. In other words, a production unit’s productivity and size are positively associated in the efficient allocation. In addition, production units with similar productivity levels command the same amount of inputs and are of identical size.

Deviations from the efficient allocation of resources across firms may have implications for aggregate output and productivity. Input choices that differ from the efficiency model, even if they allocate more factors to the more-productive production units, will generate lower aggregate output. Given the constant aggregate amount of inputs (such as capital, land, and labor), the output loss associated with an inefficient allocation is also an aggregate TFP loss. In this context, misallocation refers to situations where resources are not allocated efficiently across production units, and the cost of misallocation is typically measured in terms of aggregate output or TFP losses.

If the misallocation of resources across these different producers helps explain cross-country differences in aggregate productivity levels, it is then crucial to investigate the sources of misallocation. Resource misallocation across different production units might reflect the following (Restuccia and Rogerson 2017): • Statutory provisions, including some features of the tax code and regulations—for instance, tax code provisions that vary with firm characteristics (say, age or size); tariffs targeting certain groups of goods; employment protection measures; and land regulations, among others • Discretionary government (or bank) provisions that favor or penalize specific firms— for instance, subsidies, tax breaks, or low-interest loans granted to specific firms; preferential market access; and unfair bidding practices for government contracts, among others • Market imperfections such as monopoly power; market frictions (for example, in credit and land markets); and enforcement of property rights.

The main objective of this report is to characterize the evolution of output and productivity in Sub-Saharan Africa. To accomplish this task, the report documents the region’s (labor and multifactor) productivity trends on an international, regional, and country basis. It benchmarks productivity levels and growth in Sub-Saharan Africa in relation to countries in other regions as well as in various African country groups, classified by their degree of natural-resource abundance and condition of fragility.8 Overall, the analysis of productivity trends is conducted for three different levels of data aggregation: aggregate, sectoral, and establishment.

Aggregate Level

First, the report estimates the level and growth of labor and multifactor productivity in Sub-Saharan Africa (for the region as

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a whole as well as across countries) and the extent and nature of productivity gaps in relation to international benchmarks at the aggregate level. Labor productivity is measured by the ratio of real GDP to the number of persons employed.

The report not only illustrates the region’s labor productivity trends but also identifies the sources of the persistent differences in labor productivity between Sub-Saharan Africa and benchmark countries or regions. To that end, the development accounting framework is used to decompose the differences in the level of labor productivity into (a) differences in input intensity (such as capital-use intensity and land-use intensity); and (b) differences in production efficiency (Hsieh and Klenow 2010).

In addition, the growth accounting framework is used to examine the sources of growth of African economies. In other words, it quantifies the proportion of growth attributed to factor accumulation and TFP growth (Solow 1957). The analysis of the sources of variation of labor productivity using these two frameworks is fully presented in chapter 2.

Sectoral Level

Second, the report depicts labor productivity trends at the sectoral level in Sub-Saharan Africa. Current research typically classifies economic activity into three broad sectors: agriculture, industry, and services (see, for instance, Duarte and Restuccia 2010; Herrendorf, Rogerson, and Valentinyi 2014). This classification has been broadly used to analyze the role of structural change—captured by the reallocation of labor from low- to high-productivity sectors—in explaining the differences in labor productivity in low- and middle-income countries (Diao, McMillan, and Rodrik 2017; Gollin, Lagakos, and Waugh 2014; McMillan, Rodrik, and Verduzco-Gallo 2014) and particularly in African countries (McMillan and Harttgen 2014; McMillan, Rodrik, and Sepulveda 2017).

The report uses input-output data, the United Nations National Accounts Database, and International Labour Organization statistics to unbundle the industry and services sectors. Within the industry sector, it distinguishes manufacturing from nonmanufacturing activities (such as construction; mining and quarrying; and electricity, water, and gas). In the services sector, it classifies the different activities as either market or nonmarket services. (Market services include wholesale and retail trade; hotels and restaurants; transportation, storage, and communications; financial intermediation; and real estate. Nonmarket services comprise public administration and defense; education; health and social work; and other community, social, and personal service activities.) Using data on labor productivity and labor shares, this report examines the shifts of resources across sectors over the recent decades.

Establishment Level

Third, the report presents evidence on (labor and multifactor) productivity at the establishment level. Using the World Bank’s Living Standards Measurement Studies–Integrated Surveys on Agriculture (LSMS–ISA) and manufacturing firm-level censuses of select Sub-Saharan African countries, the report calculates quantity and revenue productivity (TFPQ and TFPR, respectively) at the farm level in agriculture and at the firm level in manufacturing. The coverage of countries in the region as well as time periods depends on the availability of microeconomic data.

The core analysis of this report will rest upon the assessment of the implications of aggregate productivity of production decisions across agricultural farms and manufacturing firms in Sub-Saharan Africa. Using farm- and firm-level data, it will assess the performance of production units in terms of their productivity levels across African establishments relative to an efficiency benchmark by computing the extent of resource misallocation. This calculation will provide information on the