2.11 Dispersion in Labor Productivity Is Higher in Services Than in Manufacturing

FIGURE 2.11 Dispersion in Labor Productivity Is Higher in Services Than in Manufacturing

Labor productivity dispersion in selected sectors, Sierra Leone and Kosovo

a. Kosovo, 2014

8

Labor productivity relative to manufacturing median 7

6

5

4

3

2

1

0 Manufacturing All services Hotels and restaurantsVehicles trade Administrative and support ICTRetail TransportationProfessionalWholesale

b. Sierra Leone, 2016

30

Labor productivity relative to manufacturing median 25

20

15

10

5

0 ManufacturingAll services ICT Transportation Administrative and supportHotels and restaurantsProfessionalRetail Vehicles tradeWholesale

10th percentile 75th percentile Median 25th percentile 90th percentile

Source: Calculations using administrative firm-level data (detailed in annex 2A). Note: Dispersion in labor productivity is measured as the ratio between the 10th and 90th percentiles (p10 and p90), relative to the manufacturing median. Wholesale sector results do not display p90 markers (or the p75 marker for Kosovo), those percentiles being outliers beyond the maximum values shown. ICT = information and communication technology.

In practice, many factors other than dispersion—including measurement issues— likely confound productivity dispersion, meaning that high dispersion cannot always be interpreted as higher misallocation. Some of these confounding factors might be even more important for services than for manufacturing.

Many of the potentially confounding factors result from using revenue-based productivity measures (such as value added per worker, or revenue total factor productivity [TFPR]) instead of quality-adjusted and quantity-based productivity measures (such as quantity total factor productivity [TFPQ]). As highlighted in this book’s “Spotlight” on data, the heterogeneity and intangibility of services—as well as limited data coverage—create additional challenges in constructing quantity-based productivity measures. Revenue-based productivity measures reflect not only production but also prices. Such measures are particularly sensitive to the prices that firms charge, which in turn are determined by factors like quality and market power.

Differences in market power can lead to dispersion in revenue-based measures of productivity (De Loecker, Eeckhout, and Unger 2020). Firms with more market power can

charge higher prices and will therefore likely appear more productive. An open question is whether services firms have higher market power than manufacturing firms. This likely depends on the subsector. Measures of competition restrictions, such as the OECD–World Bank Indicators of Product Market Regulation, suggest that restrictions can be high in certain services subsectors—for example, regulated occupations in professional services (Dauda and Drozd 2020; Sorbe, Gal, and Millot 2018). In Colombia and Ecuador, markups tend to be lower overall in services than in manufacturing, but services subsectors are considerably heterogeneous in this regard, with higher markups found in real estate, transportation, and ICT services (Alfaro and Eslava 2020).

These factors are in addition to other reasons why dispersion can arise, including differences in technology (David and Venkateswaran 2019) and adjustment costs (Asker, Collard-Wexler, and De Loecker 2014) as well as differences between average and marginal products (Bils, Klenow, and Ruane 2017). Risk and experimentation could be another source of dispersion. Investing in quality upgrading can be risky, and not all upgrading will be successful, which in turn can drive dispersion (Krishna, Levchenko, and Maloney 2020). This result could be particularly relevant to services, which tend to have lower start-up costs, which facilitates experimentation.

Dispersion matters, not only from the perspective of allocative efficiency but also in terms of economic inclusion. High productivity dispersion points toward the presence of a group of firms that are much less productive than the frontier firms. This dispersion is likely an underestimation and would be even larger if informal firms were included, since many informal enterprises operate at the lower end of the productivity distribution. Low-productivity firms are economically vulnerable (as low productivity usually also implies low earnings) and where economically more vulnerable groups (such as low-skilled workers or women) are disproportionally represented (see Aga et al. 2021 regarding Mozambique). Raising the productivity of these firms at the lower end of the productivity distribution, rather than just focusing on the better-performing upper end, would still raise aggregate productivity and, importantly for development, raise the earnings of the poor.

Stylized Fact 6: Services Firms’ Employment Growth Is Lower Than in Manufacturing Firms

The next question concerns how firms contribute to jobs and productivity dynamics. Manufacturing firms exhibit a well-documented pattern of expanding their employment as they age—a sign that firms are investing in technology, markets, and product quality, hence enabling themselves to grow and hire more workers (Atkeson and Kehoe 2005). A firm’s lack of employment growth could be a sign that distortions are creating a barrier against growth (Hsieh and Klenow 2014). However, the features of services themselves— for example, the simultaneity of production and consumption and the size of the local market—could be limiting the benefits of expanding in the same location.

Analysis from eight LMICs with suitable panel data confirms that services firms tend to have lower employment growth rates than manufacturing firms in their initial years (figure 2.12, panel a). Across these countries, a manufacturing firm expands employment by an average of 26 employees, tripling in size, while a retail firm on average added only 3 employees, only doubling in size (figure 2.12, panel b). Within the services sector, ICT, administrative and support, and transportation services tend to expand employment the most, while retail and wholesale services tend to expand employment the least.

Studies in other countries have shown similar patterns. In Brazil, the relationship between a firm’s age and its employment size is weaker in services than in manufacturing (Brolhato de Oliveira et al. 2021). An analysis of new entrants in the Dutch services sector also showed little growth of services enterprises after they reached five employees (Audretsch, Klomp, and Thurik 1998). Services firms’ relative lack of employment growth might well have to do with the sector’s earlier-identified lower economies of scale in terms of establishment size. This would be in line with results from manufacturing firms, whose subsectors with lower scale economies also exhibit lower employment growth rates (Audretsch 1995).

This finding has implications for policy. Services firms’ smaller size overall means that government programs likely would need to include more beneficiaries to cover the same amount of employment or economic activity as in manufacturing firms. In addition, focusing solely on firm employment growth as a policy outcome might make less sense for some services, since experiences from HICs have shown that a firm’s employment growth by itself is not a necessary condition for achieving higher productivity (Berlingieri, Calligaris, and Criscuolo 2018).

Stylized Fact 7: But Firms Do Grow in Productivity over Their Life Cycles

Services firms’ more limited employment growth and their weaker relationship between size and productivity raise the question of the importance of the traditional scale economies that emphasize establishment size. Yet such characteristics do not mean that firms are not growing in other respects. In fact, the firm-level data highlight that services firms in their initial years often show productivity growth like that of manufacturing firms (figure 2.13) despite not expanding employment as much.

Their growth in productivity—although employment growth is more stagnant—is an indication that services firms can expand their revenue throughout their life cycles. This implies that services firms have been able to either provide more services (expand the quantity of output) or charge a higher price. This higher price can reflect an increase in market power but can also reflect the increasing quality of the service.9

Quality is an important dimension for many services. The simultaneity of consumption and production as well as the importance of customization mean, for many