5. Industry contributions to aggregate labour productivity growth

This chapter builds upon the research presented in the 2023 edition of the Compendium of productivity indicators, on within-industry labour productivity developments and between-industry reallocation of hours worked during the first years of the COVID-19 pandemic. It incorporates information up to 2022.

The aggregate productivity growth in this chapter refers to the growth of the total economy, excluding real-estate, public administration and defense, education, and health activities. Labour productivity developments at the industry level are broken down into between-industry reallocation and within-industry productivity developments (within-industry effect).

Between-industry reallocations of hours worked are the sum of reallocations between industries with different productivity levels (static reallocation effect) and between industries with different productivity growth rates (dynamic reallocation effect). The static effect usually dominates the dynamic effect.

The within-industry effect reflects labour productivity developments that are not the result of reallocation of hours worked between industries. It is measured by the labour productivity growth in each industry weighted by the industry share in total value added. It can be affected by a variety of factors, including changes in the intensity with which industries use skilled labour and capital, their capacity to innovate, and their exposure to competition and knowledge sharing through their participation in international trade and global value chains. Even though the within industry effect can also potentially result from resource reallocation on a more disaggregated level, between firms, the aggregation level of data used in this chapter does not make it possible to infer the extent of this more disaggregated reallocation.

  • In ‘normal’ times outside large contractions of the economy, reallocations of hours worked between industries only play a limited role in explaining aggregate labour productivity growth. A more significant and positive reallocation effect on labour productivity growth is usually observed during recessions (Figure 5.1).

  • The COVID-19 recession was no exception and the scale of the overall reallocation effect between industries in 2020 was unprecedented. It largely contributed to the rebound in aggregate labour productivity growth that was observed in most countries in 2020.

  • Information from 2021 and 2022 suggests that the impact of the pandemic-induced disruptions was temporary. In most countries with data, the absolute contribution of the within-industry effect to labour productivity growth gained weight relative to the between-industry reallocation effects. Both effects often reduced productivity growth in 2022. The between-industry reallocation effect shrank or even turned negative. The within-industry effect mostly evolved in the same direction as labour productivity growth, so that it was negative in many countries.

  • The limited overall reallocation of hours worked between industries during normal economic circumstances is often the result of contributions with opposite signs (Figure 5.2). A positive (resp. negative) reallocation effect happens when resources move from industries with lower (resp. higher) productivity towards more (resp. less) productive ones.

  • Between-industry reallocations of hours worked during the COVID-19 pandemic were unusually high compared to the pre-pandemic era. However, these effects started to dissipate and, in some instances, even turned negative in several OECD countries over 2021-22.

  • In most countries for which the data is available in 2022, reallocation of hours worked contributed negatively to labour productivity growth. Belgium experienced the most significant decline in the overall reallocation effect as compared with the COVID-19 period, followed by Czechia and Sweden. On the other hand, the reallocation effect was positive, though small in Estonia, Greece and Portugal.

  • The decline in the contribution of between-industry reallocation of hours worked to productivity partly stems from the post-COVID economic recovery. Industries hardest hit by the COVID-19 recession – such as accommodation and restaurants or personal services typically characterised by lower productivity – have recovered, leading to reallocation of hours worked to these sectors. On the other hand, reallocation to high-productivity sectors that grew rapidly in 2020, such as financial and insurance activities and ICT, was small or even negative in 2022.

  • In 2022, within-industry contribution to productivity growth declined and even turned negative in many OECD countries, after the strong rebound experienced in 2021 from the COVID-19 crisis.

  • The within-industry effect varied across industries. While in several countries positive growth persisted in information and communication sector and in business services, this was surpassed by the negative contribution of low-productivity industries (Figure 5.3). The largest decline in the within-industry effect was observed in Norway, followed by Estonia and Costa Rica, while the most substantial increase in the within-industry effect was experienced in Croatia, Sweden, and Portugal.

  • The relative contributions of different industries to overall within-industry effect varied across countries, reflecting differences in countries’ industrial structure and business environment. For example, some countries experienced an expansion of mining and utility activities, such as electricity, gas and water supply, which is traditionally a low-productive sector. This could be a response to the demand pressure for energy in European countries since early 2022, prompted by Russia’s cut in supplies. Norway experienced the most pronounced decline in this sector’s within-industry contribution to overall labour productivity growth in 2022, as their oil and gas production increased by around 8%. (OECD, 2023[1]). Similarly, in Estonia, oil shale electricity generation increased considerably due to high electricity prices in 2022 (IEA, 2023).

  • Industries, which were most severely impacted by the COVID-19 pandemic, gradually recovered, albeit at varying paces across countries. The rebound was almost complete in some countries by 2022, such as the United States or Nordic countries, marked by the rapid increase in employment and hours worked within these industries. This resurgence, however, has mechanically lowered labour productivity growth, as the influx of new hires is often associated with low-skilled workers and less productive activities (Garnier, 2023[2]) (Jobs and Skills Australia, 2023[3]) (Fernald and Li, 2022[4]). Construction, wholesale and retail sectors experienced negative labour productivity growth in 2022 in many countries. The contribution of the accommodation, restaurants and personal services to the overall labour productivity growth varied, being negative in countries such as the United States and Australia, while positive in others.

  • The labour productivity growth increase in hospitality and personal services in some countries in 2022 could potentially be tied to the ongoing digital transformation, such as the contactless mobile payment, digital menu accessible through QR codes, service robots or food delivery (Esposito et al., 2022[5]). The swift integration of technology and innovation in these industries not only responds to the challenges triggered by the pandemic but may also be reinforced by the prevailing labour shortages, which in some industries can be attributed to various factors, including the potential rise in workers bargaining power (Bachmann et al., 2021[6]) and the shifts in workers’ preference, in particular in low-pay and low-quality jobs (Causa et al., 2022[7]) (Duval et al., 2022[8]).

The decomposition of aggregate labour productivity growth that is used in this chapter includes three main terms, each of them corresponding to a sum of industry contributions:

  • A within-industry effect, where labour productivity growth in each industry is weighted by the industry share in total value added in year t-1.

  • A static reallocation effect, accounting for changes between t-1 and t in the share of total hours worked of industries with different productivity levels. Industries with an increasing share in total hours worked contribute positively to aggregate labour productivity growth if they have an above-average labour productivity level.

  • A dynamic reallocation effect, accounting for changes between t-1 and t in the share of total hours worked of industries with different productivity growth rates. An increase in the total hours worked share of industries with positive productivity growth has a positive effect on aggregate labour productivity growth. This effect is all the more significant if the industry value added is high.

For additional information on this decomposition of aggregate labour productivity growth, see the methodological note.

This chapter focuses on a subset of the total economy that excludes real-estate, public administration and defence, education, and health activities (i.e. total economy less industries L, O, P, Q in the ISIC rev. 4 classification). Real-estate activities are excluded because their value added is largely imputed (it includes the value of both actual and imputed housing rents in the economy) and disproportionate as compared to the corresponding work force in national accounts (mostly real-estate agents and employees of notary offices are attached to the real-estate industry in national accounts). Public administration and defence, education and health services are excluded because they are largely non-market. Hence, their output value is measured as the sum of input costs, and in several countries their output volume is measured by deflating input costs, thus conventionally excluding any productivity gains.

For most countries, the above decompositions of aggregate labour productivity growth rely on breakdowns of value added and hours worked into economic sectors at the 2-digit level of the NAICS 2017 classification (for Canada, Mexico, and the United States) or the ISIC rev. 4 classification. Due to data limitations, the decompositions for France, Germany, Italy, and the United Kingdom rely on a mix of 1-digit and 2-digit level data corresponding to the A38 level of the ISIC rev.4 classification, and the decomposition for Australia relies on 1-digit level data according to the ANZSIC 2006 classification. This corresponds to between 20 and 64 industries, depending on data availability in different countries. Except for a few cases, this is the most granular industry data publicly available in national accounts, but it might not be sufficient to fully capture the heterogeneity of economic activities. Therefore, it cannot be excluded that part of the within-industry effects presented above correspond to resource reallocations between firms or economic activities belonging to the same 2-digit industry. A complete assessment of the contribution of reallocations and business dynamism (entries and exits of firms) to aggregate labour productivity growth would require firm-level data.

Even though a more granular breakdown is used for all calculations, the following breakdown by industry is used to visualise the contributions of reallocation and within-industry effects to aggregate labour productivity growth in the figures included in this Chapter:

  • Agriculture and mining: industries A and B in the ISIC rev. 4 classification; industries 11 and 21 in the NAICS 2017 classification

  • Manufacturing and utilities, excluding manufacturing of ICT: industries C, D and E except C26-27 in the ISIC rev. 4 classification; industries 22 and 31-33 except 3361MV and 3364OT in the NAICS 2017 classification

  • Construction: industry F in the ISIC rev. 4 classification; industries 23 in the NAICS 2017 classification

  • Trade: industry G in the ISIC rev. 4 classification; industries 42 and 44RT in the NAICS 2017 classification

  • Transport, accommodation, and personal services: industries H, I and R to U in the ISIC rev. 4 classification; industries 48TW, 71, 72 and 81 in the NAICS 2017 classification

  • Finance and insurance: industry K in the ISIC rev. 4 classification; industry 52 in the NAICS 2017 classification

  • Business services: industries M and N in the ISIC rev. 4 classification; industries 54 to 56 in the NAICS 2017 classification.

Macroeconomic data for recent years can be subject to revisions, especially in the years covering the COVID-19 pandemic.

OECD National Accounts Statistics (database), https://doi.org/10.1787/na-data-en.

References and further reading

[6] Bachmann, R. et al. (2021), “Worker churn in the cross section and over time: New evidence from Germany”, Journal of Monetary Economics, Vol. 117, pp. 781-797, https://doi.org/10.1016/j.jmoneco.2020.05.003.

[7] Causa, O. et al. (2022), The post-COVID-19 rise in labour shortages, OECD Publishing.

[8] Duval, R. et al. (2022), “Labor Market Tightness in Advanced Economies”, Staff Discussion Notes, Vol. 2022/001, p. 1, https://doi.org/10.5089/9798400204340.006.

[5] Esposito, B. et al. (2022), “Service innovation in the restaurant sector during COVID-19: digital technologies to reduce customers’ risk perception”, The TQM Journal, Vol. 34/7, pp. 134-164, https://doi.org/10.1108/TQM-01-2022-0016.

[4] Fernald, J. and H. Li (2022), “The Impact of COVID on Productivity and Potential Output”, Federal Reserve Bank of San Francisco, Working Paper Series, Vol. 2022/19, pp. 01-52, https://doi.org/10.24148/wp2022-19.

[2] Garnier, O. (2023), Une mesure de l’efficacité dans l’utilisation des ressources en main d’oeuvre : au-delà de la productivité, Banque de France.

[3] Jobs and Skills Australia (2023), Skills Shortage Quarterly, Australian Government, https://www.jobsandskills.gov.au/publications/skills-shortage-quarterly-march-2023 (accessed on 11 January 2024).

[1] OECD (2023), Nordic Lessons for an Inclusive Recovery? Responses to the Impact of COVID-19 on the Labour Market, OECD Publishing, Paris, https://doi.org/10.1787/2aa7bcc1-en.

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