OECD Compendium of Productivity Indicators 2021

Productivity and the COVID-19 pandemic

The impact of the COVID-19 crisis on productivity in 2020 and beyond

Physical distancing, lockdowns and restrictive measures put in place worldwide to contain the COVID-19 pandemic triggered the most severe and abrupt global recession since the end of the Second World War. Admittedly, GDP declines recorded in 2020 were heterogeneous across OECD countries, reflecting the uneven impact of the pandemic throughout the economy, differences in economic specialisation, variations in the nature and timing of restrictions, and differences in fiscal and monetary policy across countries. However, (quarterly) GDP declines exceeded almost everywhere those recorded at the time of the 2007-09 financial crisis, often referred to as the Great Recession.

As of mid-2021, prospects for a path out of the crisis continue to improve, as shown by recent upward revisions in economic forecasts, but they remain uncertain and unequal across countries (OECD, 2021a). The brighter outlook is mainly related to the gradual deployment of effective vaccines, strengthened macroeconomic policy support, especially in the United States, and signs that economies are coping better with measures to contain the virus. Global economic activity has now returned to its pre-pandemic level, but at the end of 2022, it would still remain weaker than expected before the pandemic. There is also marked variation in the pace of recovery across countries. While swift policy actions have paved the way for the health and economic recovery, the risks of new virus outbreaks, with the appearance of variants in different places, and the challenges in deploying vaccines on such a scale, in particular in emerging and low-income economies, may weigh down on the recovery.

Beyond its aggregate impact, the recession affected economic sectors in different ways, both in terms of output and hours worked, reflecting the uneven effects of the temporary restrictions put in place to contain the propagation of the virus. In addition to the uneven impact on sectoral productivity, the crisis also induced reallocation of activity across sectors, with a positive effect on aggregate productivity in the short term. While there are exceptions, most of the hardest hit sectors indeed correspond to activities with low labour productivity levels (e.g. accommodation and restaurants, and household services). In the short term, this implied changes in the relative weights of economic sectors, which contributed to limit declines in aggregate labour productivity.

The widespread implementation of job retention schemes in most countries led to a disconnection between the number of persons employed and the number of hours worked during the COVID-19 crisis. For the purpose of economic analysis and to maximise the comparability of statistical series across countries (see below), it is better to focus on labour productivity per hour worked. Overall, the data available so far show significant cross-country discrepancies in labour productivity (per hour worked) developments between 2019 and 2020, with for example large increases in Canada, Italy and the United States, and overall stability in France and Germany. Looking ahead, the sectoral developments underlying these aggregate evolutions will need to be carefully analysed.

 

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In the longer term, the main risk to productivity depends on whether the crisis will have long-lasting effects on the productive capacity of the economy by triggering a surge in bankruptcies, not only of the least productive firms as in the usual creative destruction process, but also of the more productive ones due to falling revenues and short-term insolvencies. Even though financial measures put in place by governments to support firms and temporary regulations on insolvency largely contributed to avoid a wave of bankruptcies in 2020, there are risks of debt build-ups that may lead to significant increases in bankruptcies as support measures are unwound, with potentially long-lasting effects on the economy. Governments will need to implement policies to address this issue. These policies include timely debt restructuring for viable firms, and the implementation of efficient liquidation procedures to ensure that resources are reallocated from non-viable to viable businesses (OECD, 2021b). In addition, despite the government actions to mitigate the crisis, the pandemic may also have an effect on human capital accumulation. All countries have suffered from a deterioration in the employment situation, which has aggravated existing inequalities and risks of “scarring” effects on workers, in particular women, youth and low-income workers (ILO, 2021a; OECD, 2021a). While in normal circumstances, young people facing high unemployment risks may decide to remain in school, this decision may have been affected by disruptions in the provision of educational services during the pandemic, thus increasing the risk to drop out from school and weighing down on human capital accumulation (ILO, 2021b).

On a more positive note, the crisis may accelerate the adoption of digital technologies by firms. Indeed, early evidence from business surveys conducted worldwide in the course of 2020 points to the majority of firms, including smaller ones, having intensified their use of digital technologies during the pandemic. Nevertheless, smaller firms consistently report that costs, and lack of skills and awareness of digital tools, remain concerns for investing in digital technologies (OECD, 2021b). A wide diffusion of digital technologies across firms is key to avoid the widening of the productivity gap within economies and to ensure a sustained rebound of aggregate productivity after the crisis (Andrews et al. 2016; McKinsey 2021).

Monitoring the dynamics and composition of investment, with a focus on assets such as research and development (R&D) and information and communication technologies (ICT), will also be key to assessing the potential for a rebound in productivity after the crisis. The volume of gross fixed capital formation (GFCF) declined by 6% on average across OECD countries in 2020, with large cross-country differences. A common feature across all countries is the substantial drop in investment in transport equipment, which is likely related to the mobility restrictions implemented to limit the propagation of the virus, as well as to the overall reduction in economic activity. Nevertheless, it is still too early to assess the effect of the crisis on R&D and ICT investment. In this respect, the crisis has underlined the need for more timely data to monitor short-term developments in investment and economic activity more generally.

Statistical measurement challenges and cross-country comparability issues during the crisis

Measuring non-market output

Contrary to market output, non-market output is provided for free or at prices that are not economically significant. Therefore, the value of non-market output is imputed in the national accounts and calculated as the sum of the underlying costs of production. These costs include intermediate consumption, compensation of employees, consumption of fixed capital, and taxes less subsidies on production. Compensation of employees represents by far the largest share of non-market value added in current prices (around 80% on average across OECD countries). In countries where governments maintained the normal compensation of their employees during the crisis even though they may have worked longer or shorter hours than usual, the value added of non-market activities at current prices in the national accounts remained largely unaffected.

When it comes to the volume measurement of non-market output, National Statistics Offices (NSOs) tend to use different methods in the absence of observable market prices to deflate output at current prices (Schreyer, 2010; ONS, 2021). A few of them, such as the Office for National Statistics (ONS) in the United Kingdom, rely on direct indicators of the volume of output (e.g. number of students for education services, or number of patients treated for health services) to estimate how the volume of non-market services evolves over time. However, most NSOs rely on indicators of the volume of inputs (e.g. number of teachers for education services) or deflate input costs based on appropriate price indices (e.g. price indices capturing wage increases in the public sector). Overall, countries relying on output methods are likely to show more variability in non-market output during the crisis than countries relying on input methods.

In practice, even though non-market activities (public administration, education and health services provided by both government and other non-market producers) make up around 20% of GDP on average across OECD countries, differences in non-market output account for only a small part of cross-country variation in annual GDP growth in 2020 (OECD, 2021a). In other words, differences in measuring non-market output across countries play a much more limited role than other factors (e.g. economic specialisation and stringency of restrictions put in place to limit the propagation of the virus) in explaining cross-country differences in overall GDP growth during the crisis.

Measuring labour input

The COVID-19 pandemic occurred at a time when employment rates, i.e. ratios of employment to working age population, were at historic highs across OECD countries (OECD, 2019). According to the OECD Labour Market Statistics, the COVID-19 crisis induced a decline in the OECD employment rate of 2.7 percentage points, from 68.8% in 2019 to 66.1% in 2020. While the total number of persons employed declined by more than 1% in most OECD countries, the situation varied substantially across countries, with Canada and the United States recording a drop in total employment of 5.2% and 6.2% respectively between 2019 and 2020, and the Euro area recording a decline of 1.6%.

While these cross-country differences are partly related to differences in macroeconomic conditions and labour market institutions, they mostly reflect differences in the treatment of workers on temporary lay-off in official labour statistics (Arnaud, 2020).

According to the International Labour Organisation (ILO) guidelines, temporarily laid-off or furloughed workers are persons “employed” who, in their present job, are “not at work” due to economic reasons for a short duration but maintain a job attachment during their absence (ILO, 2013 and 2020). These guidelines treat furloughed workers as being employed when:

• the expected total duration of the absence is up to three months (or more if the return to employment in the same economic unit is guaranteed), or

• workers continue to receive a remuneration from their employer, including partial pay, even if they also receive support from other sources, including government schemes.

In turn, furloughed workers not satisfying the above criteria are classified as either unemployed, if they are actively looking for a job and available for work, or as outside of the labour force (i.e. neither employed nor unemployed).

In practice, departures from these guidelines in national practices do exist. In the United States for example, persons on temporary lay-off are classified as “unemployed” even if they expect to be recalled to their job within six months. As stated by the US Bureau of Labor Statistics (BLS), “people who were effectively laid off due to pandemic-related closures [are] counted among the unemployed on temporary lay-off” without further testing for their return to their previous job (BLS, 2020). In Canada, persons on temporary lay-off are also classified as “unemployed” even if they have a date of return or an indication that they will be recalled by their employer. On the contrary, in Europe, only those furloughed workers that do not have an assurance to return to work within three months and receive less than half of their salary are treated as unemployed, if they are available to start working in the next two weeks.

In normal times, these differences only have a marginal impact on the international comparability of employment and unemployment measures, as furloughed workers typically account for a relatively insignificant share of the population. However, the confinement measures put in place to contain the spread of the virus have significantly increased their number. Prior to the pandemic, furloughed workers represented 0.5% of the labour force in the United States and less than 0.2% in the European Union, but in the second quarter of 2020, these shares jumped to 9.3% and 9.6% respectively (Arnaud, 2020).

International differences in the treatment of temporarily laid-off workers are likely to be less relevant when labour input is measured as the total number of hours worked, as furloughed workers work by definition zero hours while being in temporary lay-off. Preliminary national accounts for 2020 reveal a decline in total hours worked of 6.4% and 7.7% in the European Union and the Euro area, respectively, against a drop of 1.5% and 1.6% in total employment. This stresses the importance of using total hours worked as a measure of labour input, as opposed to job- and head-counts labour input measures, in particular when analysing the impact of the COVID-19 outbreak on productivity.

Measuring investment and capital utilisation

Although capital stock estimates are not yet available for 2020, capital services during the crisis and beyond are expected to reflect the shortfall in investment. Nevertheless, measures of capital services should capture the reduced rates of capital utilisation during the crisis whenever possible. Difference in containment measures and in teleworking capacities across countries resulted in different patterns of capital usage across economic activities. For instance, many offices and commercial buildings were closed, in full or in part, during lockdowns, with much of the capital equipment being unused. This has certainly caused a fall in capital utilisation rates that is more or less pronounced across assets and industries. In productivity analysis, it is typically assumed that capital services are a time-invariant proportion of the productive capital stock, an assumption that is difficult to maintain in 2020. While estimating capital utilisation rates is far from trivial (OECD, 2001), adjusting measured capital services for the reduced rates of capital utilisation can certainly provide a more accurate estimate of multifactor productivity (MFP) growth and the contribution of capital services to GDP growth in 2020.

Data sources

OECD National Accounts Statistics (database), https://doi.org/10.1787/data-00017-en.

OECD Labour Market Statistics (database), https://doi.org/10.1787/data-00046-en.

OECD Productivity Statistics (database), http://dx.doi.org/10.1787/pdtvy-data-en.

References and further reading

Andrews D., Criscuolo C. and Gal P.N. (2016), “The Best versus the Rest: The Global productivity Slowdown, Divergence across Firms and the Role of Public Policy”, OECD Productivity Working Papers, 2016-05, OECD Publishing, Paris, https://doi.org/10.1787/63629cc9-en.

Arnaud B. (2020), “Has COVID-19 Distorted International Comparability of Unemployment Rates?”, in The Statistics Newsletter, Issue No. 73, December 2020, https://www.oecd.org/sdd/theoecdstatisticsnewsletter-allissues.htm.

BLS, Bureau of Labor Statistics (2020), “The impact of the coronavirus (COVID-19) Pandemic on the Employment Situation for March 2020”, U.S. Bureau of Labor Statistics, March 2020, Washington DC. https://www.bls.gov/cps/employment-situation-covid19-faq-march-2020.pdf.

ILO (2013), “Resolution Concerning Statistics of Work, Employment and Labour Underutilization”, 19th International Conference of Labour Statisticians (ICLS), Geneva. https://www.ilo.org/wcmsp5/groups/public/---dgreports/---stat/documents/normativeinstrument/wcms_230304.pdf.

ILO (2020), “COVID-19: Guidance for Labour Statistics Data Collection”, International Labor Organisation (ILO), Geneva. https://www.ilo.org/wcmsp5/groups/public/---dgreports/---stat/documents/publication/wcms_741145.pdf.

ILO (2021a), “World Employment and Social Outlook: Trends 2021”, Geneva, 2021, https://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/---publ/documents/publication/wcms_795453.pdf.

ILO (2021b), “An Update on the Youth Labour Market Impact of the COVID-19 Crisis”, Statistical Brief, June 2021, https://www.ilo.org/wcmsp5/groups/public/---ed_emp/documents/briefingnote/wcms_795479.pdf.

McKinsey (2021), “Will Productivity and Growth Return after the COVID-19 Crisis?”, McKinsey Global Institute.

OECD (2001), “Measuring Productivity - OECD Manual: Measurement of Aggregate and Industry-level Productivity Growth”, OECD Publishing, Paris, https://doi.org/10.1787/9789264194519-en.

OECD (2019), “OECD Compendium of Productivity Indicators 2019”, OECD Publishing, Paris, https://doi.org/10.1787/b2774f97-en.

OECD (2021a), “OECD Economic Outlook”, Volume 2021, Issue 1 (June), OECD Publishing, Paris, https://doi.org/10.1787/edfbca02-en.

OECD (2021b), “OECD SME and Entrepreneurship Outlook”, OECD Publishing, Paris, https://doi.org/10.1787/97a5bbfe-en.

ONS, Office for National Statistics (2021), “International Comparisons of GDP during the Coronavirus (COVID-19) Pandemic”, article published on the ONS website on February 1, 2021, https://www.ons.gov.uk/economy/grossdomesticproductgdp/articles/internationalcomparisonsofgdpduringthecoronaviruscovid19pandemic/2021-02-01.

Schreyer, P. (2012), “Output, Outcome, and Quality Adjustment in Measuring Health and Education Services”, Review of Income and Wealth, Series 58, Number 2, June 2012, https://doi.org/10.1111/j.1475-4991.2012.00504.x.