Sources of Productivity Growth

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

in Sub-Saharan Africa was double that of China and India in 1960, while it was slightly lower than Brazil’s (figure 1.2, panel b). The region’s boom-bust cycles in labor productivity led it to gradually diverge from these other countries. By 2017, labor in India was nearly twice as productive, China more than 2.5-fold, and Brazil more than triple that of Sub-Saharan Africa.

Drawing on firm-level census data, this report evaluates the sources of firm productivity growth. Productivity gains within each sector of economic activity are primarily the outcome of increased dynamism within production units. Resource reallocation from less- to more-productive firms and activities also contributes to industry-level productivity growth in any market economy—especially in lowincome economies with greater distortions.

Broadly speaking, the sources of productivity growth at the firm level (for countries either pushing the production possibility frontier or catching up to the productivity leaders) are as follows (Cusolito and Maloney 2018): • The within component, which accounts for the productivity growth within firms.

It depends on changes in the efficiency and intensity with which inputs are used in production (that is, to upgrade firms) owing to increased firm capabilities (including improved managerial skills, labor skills, innovation, and technology adoption capacity). • The between component, which reflects the role of factor reallocation across firms in aggregate productivity growth. Increases in the “between” component imply that the most-productive firms would command the most resources—thus rendering the largest output and productivity gains.

However, multiple distortions may limit the productivity gains arising from this component. • The selection component, which accounts for the gains arising from the entry of high-productivity firms (relative to the industry average) and the exit of low-productivity firms (relative to the industry average). It captures the aggregate effect of firm churning (or turnover) on productivity growth.

A growing strand of the literature investigates aggregate productivity as the result of firm-level decision-making processes, whereby firms are assumed to have different levels of productivity even within narrowly defined economic activities. (See, for instance, Bartelsman, Haltiwanger, and Scarpetta 2013; Foster, Haltiwanger, and Krizan 2001; and Syverson 2011.) In this context, the seminal work by Restuccia and Rogerson (2008) and Hsieh and Klenow (2009) has argued that the microstructure of production establishments in different economic sectors can help explain the development gap between rich and poor countries. In their framework, the production units exhibit different levels of productivity and hence size. Aggregate TFP is, in turn, influenced by the distribution of productivity across production units, those units’ corresponding allocation of resources, and the number of firms per capita.6

Role of Resource Misallocation

This report will focus on resource misallocation as a potential explanation of low productivity (levels and growth) in Sub-Saharan Africa.7 Resource misallocation refers to distortions in the allocation of inputs (such as capital, land, and labor) across production units of varying sizes. In other words, it occurs when different production establishments are taxed at different rates. This focus on misallocation is grounded in the following dimensions: • First, the increasing role of TFP differences in explaining the labor productivity gap between African countries and both the global efficiency and aspirational development benchmarks. • Second, the limited availability of firm-level census data that would primarily permit the testing of the static effects of misallocation on aggregate productivity. In the few

b oostin G Pro D u C tivity in s ub- sA h A r A n Afri CA 7

countries with longitudinal data from firmlevel censuses (for example, Côte d’Ivoire and Ethiopia), there will be an exploration of the static and dynamic implications of misallocation (which includes not only reallocation among incumbents but also reallocation by churning). • Third, the prevalence of policies and institutions (including social norms) in

Sub-Saharan African countries that drive production units away from efficiency benchmarks.

Framework of Resource Allocation–or Misallocation

This strand of the literature on resource misallocation assumes that aggregate output is produced by several producers (N) that have different (individual) levels of productivity (Ai). Firm i’s technology is summarized by a production function (f) that is strictly increasing and strictly concave. There is a fixed cost of operation (c) for any producer. Given an aggregate demand of labor (H) and capital (K), there is a unique allocation of labor and capital across producers that maximizes total output net of fixed operating costs.

Theoretically, inefficiencies in the allocation of labor and capital across heterogeneous producers will affect aggregate output and productivity through three different channels: • The technology channel reflects the level of productivity of each producer. If technological changes increase the productivity of all producers, output will be greater. • The selection channel reflects the choices of producers that would operate in a given industry, given the costs of entry and their levels of productivity. • The misallocation channel reflects the allocation of capital and labor among the operating producers.

These three channels are not independent: any policy or institution that misallocates resources across producers will potentially generate additional effects through both the selection and technology channels (figure 1.3).

FIGURE 1 .3 Sources of Resource Misallocation That Reduce Total Factor Productivity

Productivity levels Factor utilization Firm capabilities

Market failures

Technology channel Operating environment

Statutory provisions Discretionary provisions

Selection channel Misallocation channel

Total factor productivity losses