Denmark: Productivity

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. Insights on Productivity and Business Dynamics

December 2020

Denmark has traditionally enjoyed high living standards and low inequality. The Danish economy is a frontrunner in green growth and digitalisation. Denmark’s manufacturing has remained strong, with labour productivity at the macro-sector level averaging 3.5% annual growth in the period 2000-19, above the average of other Nordic countries, 2.6%. Labour productivity in Danish private services sector averaged 1.5%, slightly behind the Nordic countries’ average of 1.7%. Because individual firms drive aggregate outcomes and there exist large productivity disparities across firms, even within the same country and narrowly defined industry, it is crucial to look behind the aggregate figures. This issue of OECD Insights on Productivity and Business Dynamics investigates within-industry productivity patterns in manufacturing and non-financial market services. The analysis relies on data from the OECD MultiProd project to help understand the micro-drivers of aggregate productivity in Denmark (Box 1). It is based on long-term patterns and trends over the period 2000-12. The MultiProd data point to Denmark’s relatively high level of labour productivity in manufacturing across the entire productivity distribution. Productivity levels in services are average or slightly lower compared to other OECD countries. Within-industry productivity growth has followed a similar trend to the benchmark countries, with an increase in manufacturing and stagnation in services over the period 2000-12. Disparities in productivity levels across Danish firms are less pronounced than in the benchmark countries. Top firms have not pulled away from the rest in Denmark, unlike in many other countries. However, the least productive firms have fallen behind. This evidence from the MultiProd project provides insights on knowledge and technology diffusion in Denmark and contributes to informing policymaking related to productivity growth.

Highlights

 Danish manufacturing firms have a high level of labour productivity compared with other OECD countries, especially at the very top of the firm distribution.  In services, Danish firms are very close in productivity levels to firms in other OECD countries, except among the most productive firms where they noticeably underperform.  Productivity dispersion within industries is relatively low compared with other OECD countries.  Top performers have not increased their productivity substantially faster than the median firm, but laggards are falling further behind.

An open and competitive business environment that encourages investment and business dynamism enables experimentation with new ideas. In that respect, Danish framework conditions for businesses consistently rank at the top among OECD countries and firms are close to the technological frontier (OECD, 2019). The most recent OECD Product Market Regulation indicators show that Denmark is similar to the top five best performing OECD

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countries (OECD, 2018). Boosting productivity remains an important challenge for Danish policymakers, especially in services, to maintain the high living standards and wellbeing of the population. Recently, Denmark has introduced initiatives that will help tackle this challenge, including the development of a national productivity board in 2017 and easing of rules concerning shop size and location, as well as production location (OECD, 2019). Further improvements in policy that supports innovation and an improved institutional framework for competition could benefit Denmark’s productivity performance (OECD, 2015). Beyond these, addressing skill mismatch could accelerate the catch-up of laggard firms.

Productivity level

Overall, Danish manufacturing firms have a high level of productivity and service firms have a productivity level comparable to other OECD countries. However, these aggregate measures hide large disparities between firms. To address this heterogeneity, MultiProd separates the population of firms into performance groups, i.e. it groups firms according to their productivity. Going beyond the aggregate offers a more accurate picture of the level of firm productivity in Denmark (Figure 1). In manufacturing, labour productivity –defined as value added per worker– is higher in Denmark than in the benchmark group of countries across the entire distribution over the period 2000-12. That good performance mostly comes from the top of the distribution, where Danish average productivity is substantially higher than in the benchmark group. In contrast, Danish services firms are very close to the benchmark group except at the very top, where they noticeably underperform. Figure 1. Average labour productivity in 2005 USD PPP by productivity performance groups Manufacturing and non-financial market services Denmark vs benchmark countries, 2000-12

DNK Benchmark

Manufacturing Market services 2005 USD

160 000 160 000

120 000 120 000

80 000 80 000

40 000 40 000

0 0 Bottom Med.-low Medium Med.-high Top Bottom Med.-low Medium Med.-high Top

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Box 1. The MultiProd project

MultiProd provides a unique comprehensive overview of within-industry productivity patterns across countries over the last two decades. It extends productivity analyses beyond aggregate industry performance and focuses on the underlying dynamics and developments within industries. The MultiProd project relies on a distributed microdata approach to access representative firm-level data while respecting the confidentiality of the underlying data sources, in collaboration with experts from National Statistical Offices within the MultiProd network. The resulting micro-aggregated database is harmonised across countries and over time, hence suitable for international comparisons. MultiProd focuses on manufacturing and non-financial market services (“services” for brevity) in order to enhance cross-country comparability. The definition of these two macro-sectors (“sectors” for brevity) follows a customised 7- sector aggregation of ISIC Rev.4/NACE Rev.2 industrial classification. Detailed industries within sectors (“industries” for brevity) follow the SNA A38 classification. The analysis excludes the Coke and Refined Petroleum industry and the Real Estate industry. The present analysis compares Denmark to a “benchmark” group of countries for which MultiProd data are available, namely Australia, Austria, Belgium, Canada, Chile, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Italy, Japan, Luxembourg, the Netherlands, Norway, New Zealand, Portugal, Slovenia, Sweden and Switzerland. Figures are for the period for which data are available for Denmark, namely 2000-12. Results presented here are from the MultiProd database as of February 2020. The underlying data source for Denmark is the Accounts Statistics for Non-Agricultural Private Sector from Statistics Denmark merged with the General Enterprise Statistics. Owing to methodological differences, figures may deviate from officially published national statistics. See Desnoyers-James, Calligaris and Calvino (2019) for further details on the MultiProd data; see Berlingieri et al. (2017) for details on the methodology.

Productivity growth

Denmark’s productivity growth has declined since the mid-1990s, a common trend in many OECD countries partly due to the shift away from manufacturing and towards the typically less productive services sector (Adalet McGowan and Jamet, 2012; OECD, 2019). Calculated based on statistics from the OECD Structural Analysis Database (STAN), in 2016, about 40% of Danish employees worked in non-financial market services, an increase from around 36% in 2005. In contrast, the share of employees in manufacturing decreased to about 10% in 2016 from around 13% in 2005.1 On top of this compositional effect, productivity growth has stagnated in services, particularly in less knowledge-intensive services including trade, transport, and food and accommodation (OECD, 2019). Against this backdrop, addressing productivity in the Danish services sector is increasingly vital. MultiProd allows the analysis to go beyond compositional effects by focusing on within-industry trends. Consistent with the aggregate picture, the analysis shows that the average cumulative change in within-industry labour productivity in Denmark is very similar to the benchmark in both manufacturing and services (Figure 2). Over the period 2000-12, productivity growth in manufacturing was about 2% a year in both Denmark and benchmark countries. Growth was positive in most years. In stark contrast, within-industry productivity in services stagnated over the period, falling slightly during the 2008/09 recession and failing to fully recover by 2012. Recently, the Government has introduced initiatives to foster productivity growth. This has included support for entrepreneurship and innovation, as well as further improvements to framework conditions for businesses (OECD, 2019). Denmark has developed these and other policy initiatives in collaboration with business CEOs and expert panels, including the Entrepreneurship Panel and the Digital Growth Panel (OECD, 2019). While current business expenditure on R&D is high in Denmark, it is concentrated in a few large firms, especially within pharmaceuticals. Recent policy initiatives include increases in tax incentives for R&D expenditures. Well-designed R&D grants can promote innovation across more companies, namely those in services where innovation is needed. Providing more grants and less tax incentives can better meet the needs of young firms, versus favouring incumbents. Further, shifting taxation away from capital and labour income can increase incentives for investment and innovative business models (OECD, 2019). In addition, policies that promote training and human resources for science and technology can increase innovation, as well as prepare workers for the digital economy. Although in the short-run

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the supply of workers in science, technology, engineering and mathematics (STEM), is relatively inelastic, incentives to encourage students to complete graduate and postgraduate degrees in these fields can foster innovation. This is especially the case in Denmark where student grants are generous, yet the share of graduates in these fields is comparatively low (OECD, 2019).

Figure 2. Cumulative change in within-industry labour productivity Manufacturing and non-financial market services Denmark vs benchmark countries, 2000-12

DNK Benchmark

% Manufacturing Market services 30 30

20 20

10 10

0 0

-10 -10 2000 2002 2004 2006 2008 2010 2012 2000 2002 2004 2006 2008 2010 2012

Productivity dispersion and diffusion

There are large disparities in productivity between firms across OECD countries, even within narrowly defined industries. Denmark has a lower level of labour productivity dispersion than the benchmark in nearly all industries (Figure 3). Measured by the 90-10 productivity ratio, which compares the productivity level at the 90th percentile of the distribution (“the top”) to the productivity level at the 10th percentile (“the bottom”) manufacturing productivity dispersion is lower in all industries excepting textiles, wearing apparel and leather.2 In services, productivity dispersion is lower in all industries excepting Scientific research and development, Advertising and market research, and Accommodation and food service. Productivity dispersion increased across OECD countries since the early 2000s, even within country-industry pairs (Andrews, Criscuolo and Gal, 2016; Berlingieri, Blanchenay and Criscuolo, 2017). In principle, a rise in productivity dispersion can come from (i) improving performance at the top, due e.g. to augmented knowledge and technology adoption, or (ii) worsening performance at the bottom, due e.g. to the weakening of technology diffusion.

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Figure 3. Within-industry labour productivity dispersion Manufacturing and non-financial market services Denmark vs benchmark countries, 2000-12

DNK Benchmark

Manufacturing Market services

20 20

15 15

10 10

5 5

0 0

While productivity levels vary across Danish firms, top firms do not appear to have pulled away from the rest and there is no indication that innovation only benefits top performers (Kristoffersen, Spange and Malthe-Thagaard, 2017, Danish Economic Councils 2017). The MultiProd data indicate that productivity divergence between the 90th (“top”) percentile and the 50th (“median”) percentile of the labour productivity distribution has not increased substantially in Denmark, in either manufacturing or services (Figure 4). The data also reveal that productivity divergence between the median and the 10th (“bottom”) percentile has increased, i.e. the least productive firms are falling behind. Moreover, the data show that the median manufacturing firm has – to a large extent – kept up with the innovative frontier in Denmark. In services, innovation appears to be lacking altogether, as even the most productive service firms have experienced persistently slow productivity growth (OECD, 2019). Some researchers argue that the overall “diffusion machine” –the process of disseminating existing knowledge and technology from frontier firms to laggard firms– has not weakened as much in Denmark as in many other OECD countries, possibly thanks to high job turnover that contributes to the diffusion of knowledge within and between industries (Kristoffersen, Spange and Malthe-Thagaard, 2017). In any case, the MultiProd data provides evidence that firms at the 10th (“bottom”) percentile of the labour productivity distribution are falling behind in Denmark. This suggests that implementing policies that accelerate the catch-up of laggard firms can play a role in fostering aggregate productivity growth. In particular, recent OECD research shows that addressing skill shortages and mismatch has the potential to increase the speed of catch-up, especially in industries that are more digital or skill intensive (Berlingieri et al., 2020). This is particularly relevant for Denmark, where the share of STEM graduates is low compared to many other OECD countries, while businesses increasingly report shortages in these fields (OECD, 2019).

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Figure 4. Cumulative change in within-industry labour productivity at different parts of the distribution Manufacturing and non-financial market services Denmark vs benchmark countries, 2000-12

Top Median Bottom

Manufacturing Market services % 40 40

30 30

20 20

10 10

0 0

-10 -10

-20 -20 2000 2002 2004 2006 2008 2010 2012 2000 2002 2004 2006 2008 2010 2012

Notes

1 Calculations based on SNA A38 industry classification. 2 The 90-10 productivity ratio is an intuitive measure of the spread of the productivity distribution. It is defined as the ratio between the 90th and the 10th percentile of the productivity distribution. A ratio of X is interpreted as follows: firms at the top of the productivity distribution, proxied by firms at the 90th percentile, are X times as productive as firms at the 10th percentile.

References

Adalet McGowan, M. and S. Jamet (2012), “Sluggish Productivity Growth in Denmark: The Usual Suspects?”, OECD Economics Department Working Papers, No. 975, OECD Publishing, Paris, https://doi.org/10.1787/5k962hj88txt- en. Andrews, D., C. Criscuolo and P. Gal (2016), “The Best versus the Rest: The Global Productivity Slowdown, Divergence across Firms and the Role of Public Policy”, OECD Productivity Working Papers, No. 5, OECD Publishing, Paris, http://doi.org/10.1787/6. Berlingieri, G., et al. (2020), “Laggard firms, technology diffusion and its structural and policy determinants”, OECD Science, Technology and Innovation Policy Papers, No. 86, OECD Publishing, Paris, https://doi.org/10.1787/23074957. Berlingieri, G., et al. (2017), “The Multiprod project: A comprehensive overview”, OECD Science, Technology and Industry Working Papers, No. 2017/04, OECD Publishing, Paris, https://doi.org/10.1787/2069b6a3-en. Berlingieri, G., P. Blanchenay and C. Criscuolo (2017), “The Great Divergence(s)”, OECD Science, Technology and Innovation Policy Papers, No. 39, OECD Publishing, Paris, https://doi.org/10.1787/953f3853-en. Danish Economic Councils (2017), Productivity Report 2020, De Økonomiske Råd, https://dors.dk/english/list-of- reports. Desnoyers-James, I., S. Calligaris and F. Calvino (2019), “DynEmp and MultiProd: Metadata”, OECD Science, Technology and Industry Working Papers, No. 2019/03, OECD Publishing, Paris, https://doi.org/10.1787/3dcde184-en. Kristoffersen, M. S., M. Spange and S. Malthe-Thagaard (2017), “Diffusion of new knowledge benefits firms’ productivity”, Analysis, No. 18, Danmarks Nationalbank, Copenhagen, www.nationalbanken.dk/en/publications/Documents/2017/09/Analysis_Diffusion%20of%20new%20knowledge %20benefits%20firms%27%20productivity.pdf. OECD (2019), OECD Economic Surveys: Denmark 2019, OECD Publishing, Paris, https://doi.org/10.1787/eco_surveys-dnk-2019-en. OECD (2018), Indicators of Product Market Regulation, OECD Publishing, Paris, https://doi.org/10.1787pmr- data-en. OECD (2015), Competition Law and Policy in Denmark. A Peer Review, OECD Publishing, Paris, www.oecd.org/daf/competition/COMP_A%20Peer%20Review_Denmark__web_2015.pdf.

OECD Insights on Productivity and Business Dynamics

The global productivity slowdown and the simultaneous decline in business dynamism has prompted widespread policy concern. Productivity is the ultimate driver of living standards improvements in the long run, whereas a dynamic business environment is key in enabling job creation. Persisting negative trends can increase earnings inequalities and exacerbate pressures on governments’ budgets, thus threatening social cohesion and political stability. While most existing analysis of productivity and business dynamics rely on macro-aggregated data, the OECD MultiProd and DynEmp projects utilise a distributed microdata methodology to construct unique sets of harmonised micro-aggregated statistics from confidential firm-level data. The resulting databases allow studying the role of individual firms in driving aggregate outcomes and explaining the observed macro trends across countries and over time. OECD Insights on Productivity and Business Dynamics is a series of country profiles with a focus on the microdrivers of aggregate productivity and job creation. It makes available, to wider audiences, analytical material from the MultiProd and DynEmp databases that was prepared for use within the OECD. Comment on this country profile is invited, and may be sent to OECD, 2 rue André Pascal, 75775 Paris Cedex 16, France, or by e-mail to [email protected]. Please cite this country profile as: OECD (2020), “Denmark: Productivity”, OECD Insights on Productivity and Business Dynamics, December 2020.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 811181.

The findings, recommendations and conclusions expressed in this paper are those of the authors. Neither the OECD nor the European Commission are responsible for any use that may be made of the information contained herein.

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