Even if there is a connection between information and communication technology (ICT) and growth in the European economy has been understood, specific policy measures describing how ICT can power growth are often too generic. While much of the debate has zoomed in on the level of digital investments, this policy brief offers a framework for considering more tailored policy recommendations. Countries need to focus on exploiting their comparative advantages in the data economy and everyone cannot be a leader in the endowment of data. Policy attention is also needed for so-called intermediating policy factors that can improve economic performance through ICT in non-digital sectors. Increasing a country’s digital investment is one thing, but much of the factors that will have a real impact on the link between ICT capital and economic growth is country-specific and requires careful analysis and tailored policy reforms.
A Framework for Analysis
In order to show the need for a framework, I will take the publication of Hofheinz and Mandel (2015) as a starting point, but modify their results a bit. Their paper provides a chart in which an indicator called “digital density” in 2010 (which is the within-country data traffic) is put in relation with intangible investments as a share of GDP in 2014. Intangible investments cover a wide spectrum of new types of investments that help to determine the competitiveness of an economy. Standard economics used to treat physical capital such as machines as the only type of existing capital. Then came a greater understanding of the role of human capital. Now there is also intangible capital which is seen as important for economic performance. Obviously, the two variables are strongly connected with each other as shown in Hofheinz and Mandel (2015): a greater level of investments in intangibles is associated with greater digital density.
Figure 1 replicates their graph, but with a few alterations. First, it does not take the wider definition of intangibles into account but only one, namely “computerized information”. This is because computerized information is really at the core of digital investments, and much more so than other components of intangible capital. Computerized information covers both software and databases. Moreover, digital investments are really what is actually discussed in the two other publications that will be discussed below.
Second, on a more technical note, rather than plotting the nominal value of investments I am using the corrected real value use of investment accumulated over the years, i.e. capital. Ultimately, what matters for economists is the amount of accumulated capital stock in an economy. This capital stock in Figure 1 also corrects for any depreciation over time and as such can only then be compared with other determinants of growth, or other factors of production such as traditional physical capital and human capital. Once this is done, it is possible to compare how well-endowed a country is with these factors and to determine whether a country has a comparative advantage or not.
Third, the two axis are swapped: placing digital investments on the horizontal axis in the graph below implies that the amount of digital investments (or stocks in my case) determines the extent to which a country produces and makes use of data, not the other way around. It is true that the authors talk about correlations and not causation so that none of the factors actually has an effect on the other. The two items are indeed highly inter-linked, and one can debate if greater data production and usage of data (i.e. data density) stimulate greater investments in software – or if greater investments in software create a greater level of data density? Somehow, the way this relationship works remains yet unclear.
However, in my view, and as pointed out in Christensen and Etro (2013), data can also be seen as a factor of production, next to the previously discussed intangible, physical and human capital. As with labour, generating higher skills in an economy comes on the heels of greater levels of investment in education. In such a scenario, a greater level of investments in software (per worker) in 2010 would generate greater data production and usage (per worker) four years later (i.e. 2014). Therefore, if anything, it would make more sense to plot our variables of data density on the vertical axis and investment in intangibles on the horizontal axis.
If we follow such approach, what is the result? Figure 1 below shows the result for only six European countries (without the United States) because these are the overlapping countries for which two variables are available. Again, a clear correlation appears suggesting that software stock and data traffic are highly associated with each other. This was to be expected as both proxy for the same factor of production. However, some differences among countries do appear in this graph. For one, countries such as Sweden and the United Kingdom, placed in the upper-right corner, show much higher data traffic and level of software capital stock than Spain, Italy or Germany, which are placed in the lower-left corner.
The question is: should the latter group of countries be concerned with their position? Not necessarily. These differences could just as well point to different comparative advantages across European economies. By way of example, in the past Sweden made a lot of investment in computerized information, which has now translated into many economic activities using data, such as Spotify. Other countries have not made the same amount of investment and therefore Germany, Spain and Italy are just better at producing other things in their respective economies that use less data. Therefore, not all countries need to be equally endowed with “digital stock” and as a consequence not all countries need to be entirely specialized in providing services that use data.However, the differences across countries might become a problem if we think that the introduction of software and ICT serves as a “general purpose technology” in the wider economy and is associated with greater economic performance or simply economic growth. It is commonly accepted now that the extent to which ICT becomes embedded in other non-digital sectors is strongly associated with greater efficiency gains, and therefore economic performance across the wider non-digital economy. Based on such analysis, Figure 1 also tells us something else: some countries are doing better than others in terms of producing and using data compared to how these countries are endowed with ICT, or in our case software.
Consider France, for instance. Based on its stock of software, it generates a lower than expected activity in data traffic (or data density) since France is placed below the trend line, which in this figure runs diagonally from the bottom left to the upper right corner. Similarly, Spain is also placed below the trend line indicating that even though it has low software stocks, it demonstrates even lower activities in data than what otherwise could be reasonably expected. Germany, UK, and Sweden on the other hand show greater levels of data density compared to what one could expect based on these countries’ respective accumulated software stocks.