Foto omschrijving: Naftakraker 4 van chemieconcern Sabic op het Chemelotcomplex

Scroll naar Executive summary

Executive summary

The Internationalisation Monitor describes trends in globalisation and the consequences thereof for the Dutch economy and society. It is published quarterly as part of the Globalisation research agenda at Statistics Netherlands (CBS), commissioned by the Dutch Ministry of Foreign Affairs.

A few decades ago, a bakery on the corner of a street could bake at most a few hundred biscuits a day, whereas a team of bakers in a factory now deliver tens of thousands a day thanks to machine mixers, kneaders, industrial ovens and thanks to the optimal use of employees based on their skills and expertise. It is clear that technological progress leads to an increase in labour productivity. However, growth in productivity per hour worked has been declining for years, in our country and in other developed economies. And this trend continues, despite the emergence of new innovations and advancing digitalisation.

Productivity is one of the most important factors for economic success and wealth. The more productive firms in a country are, the more value they can add to the economy. In this Internationalisation Monitor, productivity is not only considered at the macro level, but also at industry and firm level. This provides a wealth of additional information, such as where productivity growth in the Netherlands comes from and how it develops over time. In addition, we place the productivity developments in a globalisation perspective: what are the differences between trading and non-trading firms and whether or not multinationals? And does international trade increase productivity?

Productivity can be measured in different ways. The two most common measures are labour productivity and multifactor productivity. In this Internationalisation Monitor we use both measures at macro, industry and firm level.

Listed below is a summary of the main findings presented in this edition:

Chapter 1: The productivity paradox from a Dutch perspective

  • Productivity growth is key to raising wages and living standards, helping to increase consumer purchasing power and then re-increasing demand for goods and services without necessarily requiring a greater commitment of labour and capital.
  • Productivity measures how efficiently production inputs, such as labour and capital, are used in an economy to produce a given level of output. In recent years, productivity growth in the Netherlands and many other countries around the world has stagnated, if not decreased.
  • This decline came at a time of rapid technological change, increasing firm and national participation in global value chains and rising education levels among the labour force, all of which are generally associated with higher productivity growth. This apparent contradiction is referred to as the productivity paradox.
  • A number of possible causes of slowing productivity growth are identified in the scientific literature, including:
    • the effect of the Great Recession;
    • recent innovations such as ICT, while also revolutionary, were adopted faster and had a shorter impact on productivity growth;
    • shifts in the economic structure and servicification of the economy;
    • the next wave of productivity growth driven by technological breakthroughs in e.g. artificial intelligence, robotics, big data, 3D printing, nanotechnology, biotechnology may lag behind innovations;
    • many of the new technologies, especially those related to the digital economy, play a different transformative role than previous technological innovations.
  • It is difficult to put a finger on the faltering productivity growth, also because measuring productivity is not easy. The question therefore arises whether the existing techniques to measure output are still sufficient to capture these fast-growing trends.
  • Multifactor productivity (MFP) is that part of the volume development of the output which is not caused by changes in the use of inputs. MFP is a measure of the improvement of efficiency in the production process thanks to technological progress, economies of scale, changes in utilisation rates, but also incidental factors such as weather conditions.
  • The development of labour productivity growth in the Netherlands over the period 1996-2019 is comparable to that in Germany, the UK and the EU-27. Productivity growth has been slowing down over the past two decades. The contribution of MFP to the growth in Dutch value added is lower over the period 2010-2019 than for our main European trading partners or the US.
  • Annual economic growth in the Dutch commercial sector was on average 2.1% between 1996 and 2021. Increased MFP contributed 0.6 percentage point, the rest of the growth was generated by increased use of capital and labour. However, this contribution from MFP diminished over time, from 1.5% in the period 1996-2001, to 0.4% in 2002-2011 and 0.1% in 2012-2021.
  • Financial services is the most productive sector compared to the commercial sector as a whole. Trade, business services and manufacturing are also above-average productive sectors. Furthermore, sectors with high MFP are also often export and R&D intensive. Agriculture, water supply and waste management firms and health care are the least productive sectors.
  • On average, manufacturing and trade contribute the most to MFP growth in the Dutch commercial sector. The largest growth in MFP is due to the ‘within component’: productivity growth within a sector, not due to shifting of inputs between sectors (‘between component’). Import and export intensive industries contribute mainly positively to MFP growth.

Chapter 2: Productivity of Dutch firms

  • This chapter examines firm productivity on a micro level and focuses on differences between groups of firms in terms of how productive they are.
  • Productivity can be measured in several ways. In this chapter we consider two measures, namely average labour productivity and multifactor productivity (MFP). Average labour productivity is easy to compute, but only captures one aspect of the production process, namely labour. MFP takes all inputs of the production process into account and is therefore more time consuming to calculate.
  • Dutch data show that average labour productivity and MFP follow the same trends and are strongly correlated for most groups of firms. The correlation between the two measures is significantly lower amongst capital intensive firms, indicating the importance of a more comprehensive measure of productivity for that group of firms.
  • Comparing the productivity of different groups of firms confirms many of the stylised facts already established in the economic literature. Firms that invest in innovation and R&D are more productive than firms that do not do so. Multinationals are more productive than domestic firms.
  • Exporters are significantly more productive than non-exporters. Differences also extend to the various subgroups of exporters, where perennial exporters are more productive than occasional exporters.
  • However, differences in productivity by export status depend on whether or not the firm forms part of an international enterprise group. The difference in productivity between exporters and non-exporters is greater and more apparent within the group of domestic firms compared to multinationals.

Chapter 3: More than the sum of its parts: the productivity premium of market share allocation and business dynamics

  • The dynamics of the business population and the distribution of the market shares among enterprises in an industry (allocative efficiency) are important factors in the total productivity growth, besides the average productivity growth of enterprises. This chapter presents a breakdown of productivity in terms of their average productivity and allocative efficiency at industry level and looks at the role of business dynamics.
  • Since 2007 there has been a marked decrease in dynamism, measured by the proportion of enterprise births and deaths in the population concerned, especially micro-enterprises.
  • Exporters are the main contributors to average productivity growth within an industry.
  • All industries achieve a productivity premium as a consequence of allocative efficiency, with an average of about 25% in 2019 (28% when weighted by industry size) and varying from 12 to 53%.
  • This premium can mainly be attributed to exporting firms and has remained fairly constant over time.
  • In the manufacturing sector, there is a somewhat varied picture per industry with regard to the increase or decrease in allocative efficiency, while in the trade sector there is only a slight decrease.
  • The results also indicate that there is a substantial role of business dynamics in determining productivity growth, beyond the mere productivity growth of firms in a particular industry.
  • The components of productivity growth are also mainly determined by exporters. Furthermore, the results indicate a relatively strong role for mergers and acquisitions in the process of creative destruction through the entry and exit of firms, in which exporters in particular appear to be involved.
  • The results in this chapter indicate that in addition to familiar determinants of productivity such as innovation, the use of ICT and new technology, management quality, there is also an important role for the process of creative destruction in relation to business dynamics and market allocation.
  • However, average productivity growth is lagging somewhat, and growth derived from allocative efficiency appears to be fairly constant. There appears to be room for improvement in both components to avoid the slowdown in productivity growth.
  • To that end, macro-economic productivity growth benefits from an efficiently operating market mechanism that, on the one hand, leaves room for innovative new firms that can challenge and possibly displace incumbent firms, and, on the other hand, allows labour and capital to be deployed by well-performing firms to increase their market share. The productivity benefits that can be achieved from exports are even more substantial from a macroeconomic perspective when exporters are able to grow, which offers scope for policy at the intersection of competition and trade policy.

Chapter 4: Do firms learn from exporting?

  • Internationally active firms are typically larger, more productive, more innovative and more capital intensive. In addition, they also tend to pay higher wages and have a higher chance of survival.
  • What remains unclear, however, is how this relationship works exactly. Broadly speaking, there are two possibilities. First, firms may self-select into exporting. Since an export start is a costly undertaking, only the most productive firms are able to make this move. In this scenario, it is the higher productivity that allows firms to internationalise.
  • An alternative hypothesis is that firms actually learn from the internationalisation process. By exporting to a new market, firms are confronted with different customers, tastes, competitors, regulations and procedures which may spur process and product innovation.
  • While the learning hypothesis is typically assumed and also nurtured by e.g. policy makers, academic evidence has typically been in favour of the self-selection mechanism. However, recent literature has shown that the relative lack of evidence for the learning hypothesis may be due to the econometric methodology used.
  • In this chapter, we examine whether there is a learning effect for Dutch firms from their importing and/or exporting activities. Following the latest research methodology, we show that after controlling for self-selection effects, Dutch firms still gained 4.4% in productivity from exporting.
  • The learning effects of importing are also significant, albeit with 2.2% less than the learning effects from exporting. This may be due to the distinct learning opportunities from importing and exporting. By importing, firms may learn by getting in contact with superior technology. Dutch firms more likely learn from entering a new market via the export channel only.
  • Learning effects are most evident in the food and tobacco industries as well as the wood and paper industry. In other industries, such as textiles, there is no significant learning effect present.
  • Independent SMEs show the smallest learning effects. This may be due to their limited absorptive capacity or the fact that their export spells may be limited in duration or intensity.
  • Future research could look more into the dynamic learning effects. How fast do they emerge and, in the case of an export exit, dissolve again? In addition, it could be worthwhile to explore the difference in learning between exporting goods and services.

Chapter 5: Innovation in small firms

  • For the first time, we use web-scraped data to enrich information about innovation at enterprises.
  • 42% of firms in our dataset are classified as being innovative.
  • 40% of small firms (2 to 10 persons employed) are innovative, 44% of firms have between 10 and 50 persons employed, over half of firms have between 50 and 250 persons employed and 57% of large firms (250 or more persons employed).
  • The information and communication sector is especially innovative.
  • Exporters are generally more innovative than non-exporters. Exporters of both goods and services have a higher share of innovative enterprises than non-exporters (9 percentage points).
  • Highly productive enterprises have a higher share of innovative businesses (44%) than enterprises with low productivity (40%).
  • Dutch multinationals have the largest share of innovative firms across all size classes.
  • Large firms—(more than 250 employees) are 16.2% more likely to be innovative than comparable small firms with 2 to 10 employees.
  • Firms that export both goods and services are almost 4% more likely to be innovative compared to similar firms which do not have any exports.
  • There is a positive correlation between innovation and labour productivity. A 1-percentage point increase in labour productivity is associated with a 0.8-percentage point increase in the likelihood of being innovative. For firms with 50 employees or more, these effects are magnified. For these firms specifically, a 1-percentage point increase in labour productivity is associated with a 1.9-percentage point increase in the likelihood to be innovative.
  • Foreign-owned firms are less likely to be innovative than Dutch firms. Being a subsidiary of a foreign-owned multinational is associated with a 2.9-percentage point lower likelihood of innovativeness compared to similar non multinational firms. Dutch multinationals, on the other hand, are more likely to be innovative, more specifically 3.5 percentage points, compared to similar non-multinational Dutch firms.
  • When we take labour productivity as the dependent variable, we find that innovative firms are associated with a 2 to 4% greater productivity compared to non-innovative firms, controlled for background characteristics such as the sector they operate in, the fact whether they are a multinational or not, and information on their trade in goods or services.


Deze website is ontwikkeld door het CBS in samenwerking met Textcetera Den Haag.
Heb je een vraag of opmerking over deze website, neem dan contact op met het CBS.

Disclaimer en copyright


CBS maakt op deze website gebruik van functionele cookies om de site goed te laten werken. Deze cookies bevatten geen persoonsgegevens en hebben nauwelijks gevolgen voor de privacy. Daarnaast gebruiken wij ook analytische cookies om bezoekersstatistieken bij te houden. Bijvoorbeeld hoe vaak pagina's worden bezocht, welke onderwerpen gebruikers naar op zoek zijn en hoe bezoekers op onze site komen. Het doel hiervan is om inzicht te krijgen in het functioneren van de website om zo de gebruikerservaring voor u te kunnen verbeteren. De herleidbaarheid van bezoekers aan onze website beperken wij zo veel mogelijk door de laatste cijfergroep (octet) van ieder IP-adres te anonimiseren. Deze gegevens worden niet gedeeld met andere partijen. CBS gebruikt geen trackingcookies. Trackingcookies zijn cookies die bezoekers tijdens het surfen over andere websites kunnen volgen.

De geplaatste functionele en analytische cookies maken geen of weinig inbreuk op uw privacy. Volgens de regels mogen deze zonder toestemming geplaatst worden.

Meer informatie:


Verklaring van tekens

niets (blanco) een cijfer kan op logische gronden niet voorkomen
. het cijfer is onbekend, onvoldoende betrouwbaar of geheim
0 (0,0) het cijfer is kleiner dan de helft van de gekozen eenheid
* voorlopige cijfers
** nader voorlopige cijfers
- (indien voorkomend tussen twee getallen) tot en met
2016–2017 2016 tot en met 2017
2016/2017 het gemiddelde over de jaren 2016 tot en met 2017
2016/’17 oogstjaar, boekjaar, schooljaar, enz. beginnend in 2016 en eindigend in 2017
2004/’05-2016/’17 oogstjaar enz., 2004/’05 tot en met 2016/’17

In geval van afronding kan het voorkomen dat het weergegeven totaal niet overeenstemt met de som van de getallen.

Over het CBS

De wettelijke taak van het Centraal Bureau voor de Statistiek (CBS) is om officiële statistieken te maken en de uitkomsten daarvan openbaar te maken. Het CBS publiceert betrouwbare en samenhangende statistische informatie, die het deelt met andere overheden, burgers, politiek, wetenschap, media en bedrijfsleven. Zo zorgt het CBS ervoor dat maatschappelijke debatten gevoerd kunnen worden op basis van betrouwbare statistische informatie.

Het CBS maakt inzichtelijk wat er feitelijk gebeurt. De informatie die het CBS publiceert, gaat daarom over onderwerpen die de mensen in Nederland raken. Bijvoorbeeld economische groei en consumentenprijzen, maar ook criminaliteit en vrije tijd.

Naast de verantwoordelijkheid voor de nationale (officiële) statistieken is het CBS ook belast met de productie van Europese (communautaire) statistieken. Dit betreft het grootste deel van het werkprogramma.

Voor meer informatie over de taken, organisatie en publicaties van het CBS, zie


Met vragen kunt u contact opnemen met het CBS.



Marcel van den Berg

Sarah Creemers

Dennis Cremers

Loe Franssen

Marjolijn Jaarsma

Angie Mounir

Michael Polder

Rik van Roekel

Janneke Rooyakkers

Iryna Rud

Mark Vancauteren

Christiaan Visser


Sarah Creemers

Daniël Herbers

Marjolijn Jaarsma

Janneke Rooyakkers


Sarah Creemers

Janneke Rooyakkers


We danken de volgende personen voor hun constructieve bijdrage aan deze editie van de Internationaliseringsmonitor:

Piet Daas

Daan Freeman (CPB)

Rogier Goedhart

Rick de Kruijf

Tim Peeters

CBS CCN Logistiek

CBS CCN Redactie en Visualisatie

CBS Vertaalbureau