Since the middle of the 1990s productivity growth in southern Europe has been much lower than in other developed countries. Figure 1 shows this by plotting aggregate productivity, measured as real GDP per hour worked (net of non-IT capital deepening), for six OECD countries.1 Between 1995 and 2015, productivity grew by 1.1% per year in Germany, and by 1.4% per year in the US, but by 0.5% per year in Portugal and only 0.1% per year in Italy and Spain.
These trends represent a challenge for the survival of the monetary union. A common currency can function well when there are geographical differences in productivity levels, but it is much harder to accommodate persistent differences in productivity growth, particularly when inflation is low.
Figure 1 Productivity growth across the OECD, 1995-2015
Source: Schivardi and Schmitz (2019), using data from OECD and EU KLEMS.Possible explanations
It is therefore not surprising that, in recent years, researchers have proposed explanations for this divergence. Some papers argue that the large capital inflows that southern Europe received during the first decade of the euro have mostly been captured by low-productivity firms, depressing aggregate productivity through a composition effect (Gopinath et al. 2017, Garcia-Santana et al. 2019). Others claim that inefficient management practices have kept southern European firms from taking full advantage of the IT revolution (Bloom et al. 2012, Pellegrino and Zingales 2017).
We have investigated the second claim – in particular its main mechanisms – in greater detail (Schivardi and Schmitz 2019), to determine the quantitative importance of these mechanisms and their implications for policy.
We note that southern Europe's divergence coincided with the diffusion of IT in the mid-1990s. IT was a major driver of productivity growth in leading economies (Fernald 2014, Gordon 2016) but, in southern Europe, this IT revolution made relatively little headway. Figure 2 indicates that between 1995 and 2014, the real stock of IT capital increased by a factor of 4.6 in the US, by a factor of 4 in Germany, but only by a factor of 1.5 in Italy, 2.6 in Portugal, and 3.7 in Spain.
Figure 2 Growth in the real IT capital stock, 1995-2014
Source: Schivardi and Schmitz (2019), using data from OECD and EU KLEMS.
Thus, IT diffusion in southern Europe was limited, and even in countries that had faster growth in IT capital (such as Spain), IT had a negligible impact on productivity. Why was this the case?
It may be how you use it
An extensive empirical literature documents that IT adoption requires changes in firm organisation (Brynjolfsson and Hitt 2000), and that it induces higher productivity gains in better-managed firms (Garicano and Heaton 2010, Bloom et al. 2012), because management practices and IT are complements.
Southern European firms perform systematically worse in terms of management efficiency. Figure 3 illustrates this by using data from the World Management Survey (WMS), developed by Nick Bloom, Raffaella Sadun and John Van Reenen. The WMS is an innovative survey that allows to score firms in terms of the quality of their managerial practices. It has been applied to more than 20,000 firm in 35 countries. The figure plots country (standardised) averages of this measure for industrialised economies, showing that southern European countries such as Italy, Spain, Portugal and Greece have much lower scores than northern European countries, the US, Canada, and Japan.
Figure 3 Management efficiency in OECD countries
Source: Schivardi and Schmitz (2019), based on WMS data.
Figure 3 provides some evidence that this matters. Panel A shows that, before the IT revolution, there was no correlation between management scores and productivity growth. Panel B shows that this changed radically around 1995, and a strong positive correlation emerged. At the beginning of the IT revolution, inefficient management practices started to become a drag on growth. This supports the idea that efficient management practices and IT are complementary.
Figure 4 Management scores and productivity growth before and after the IT revolution, 1985-2008
Source: Schivardi Schmitz (2019) using data from OECD and WMS. Productivity growth is growth in real GDP per hour worked net of non-IT capital deepening. The graphs omit Greece (which has no productivity data) and Ireland (where the role of multinational companies makes national accounting difficult).
Management during the IT revolution
We analysed these developments using a simple model, with two fundamental assumptions: efficient management and IT are complements, and southern European countries have worse management practices. Our model predicts that inefficient management had lowered southern European income and productivity levels (but not growth rates) already before the IT revolution. Inefficient management implied that the best southern firms remained smaller than their northern counterparts. This allowed less-productive firms to remain in the market, depressed the demand for high-skilled labour, lowered the skill premium and led some high-skilled workers to emigrate. Thus, many salient long-run features of southern European economies can be explained by a single factor: inefficient management.
The arrival of the IT revolution amplified this north-south divide through three channels:
- Productivity. As efficient management and IT are complements, southern firms adopting IT experienced lower productivity gains than northern firms. This obviously lowered the aggregate impact of IT in the south. And fewer southern firms adopted IT in the first place – precisely because they did not benefit much from it.
- Employment. IT increases the employment share of firms relying on formal management. Southern firms were as efficient as northern firms for basic technologies, but less efficient for management. Thus, the southern disadvantage became more salient through a composition effect.
- Wages. The IT revolution increased northern high-skilled wages more than southern high-skilled wages. This encouraged highly skilled workers to move north, and the south thus lost exactly the workers it would need to adopt IT.
We calibrated our model to determine the quantitative importance of these channels, assuming that a country’s management efficiency was given by its WMS score. We also parameterised production functions so that their coefficients corresponded to our estimates (computed using a large firm-level dataset) for the impact of management and IT on firm-level productivity.
In our baseline calibration, between 1995 and 2008, the IT revolution increased productivity by 11.1% in Germany, 5.9% in Italy, 2.5% in Spain, and 3.4% in Portugal.2 Comparing these numbers to the actual productivity divergence observed in the data shows that we account for 35% of the Italian, 47% of the Spanish, and 81% of the Portuguese divergence from Germany. Divergence is mainly driven by lower firm-level productivity gains from IT adoption, compounded by lower adoption rates. High-skilled emigration's impact on aggregate productivity is small.
We have also analysed southern Europe's policy interventions. Subsidising IT adoption actually lowers southern productivity even further. Likewise, subsidising education has negative effects, as it is effectively becomes a transfer to the north through high-skilled migration. These surprising results are due to the fact that, in our model, low IT adoption and low education are a symptom, rather than the cause, of low productivity growth in southern Europe.
Indeed, given management efficiency, southern workers and firms behave optimally. There is no further room for improvement.
Of course, these results should be taken with a grain of salt. Our model abstracts from market failures that might cause suboptimal IT adoption, or education choices. Nevertheless, it suggests that policies should focus on the underlying cause of southern Europe’s divergence, namely, inefficient management.
How to improve management practices? Research on the subject is still in its infancy, but some lessons can already be drawn. The ownership structure of firms is important. Family ownership and management, particularly common in southern Europe, tend to be associated with lower-quality management compared to widely-held firms, firms controlled by private equity, or those that have foreign owners. A counterfactual shows that increasing the presence of foreign multinationals could substantially improve the quality of management in southern Europe directly, because subsidiaries of foreign multinationals are well managed, and indirectly, as there is evidence that good practices in one firm tend to diffuse locally as managers change jobs.
Bloom, N, R Sadun, and J Van Reenen (2012), "Americans Do IT Better: US Multinationals and the Productivity Miracle", American Economic Review 102(1): 167–201.
Brynjolfsson, E and L M Hitt (2000), "Beyond Computation: Information Technology, Organizational Transformation and Business Performance", Journal of Economic Perspectives 14(4): 23–48.
Fernald, J (2014), "Productivity and Potential Output Before, During, and After the Great Recession", NBER Macroeconomics Annual 29.
Garcia-Santana, M, E Moral-Benito, J Pijoan-Mas, and R Ramos (2019), "Growing like Spain: 1995-2007", forthcoming in International Economic Review.
Garicano, L and P Heaton (2010), "Information Technology, Organization, and Productivity in the Public Sector: Evidence from Police Departments", Journal of Labor Economics 28(1): 167–201.
Gopinath, G, S Kalemli-Ozcan, L Karabarbounis, and C Villegas-Sanchez (2017), "Capital Allocation and Productivity in South Europe", Quarterly Journal of Economics 132(4): 1915–1967.
Gordon, R J (2016), The Rise and Fall of American Growth: The US Standard of Living since the Civil War, Princeton University Press.
Pellegrino, B and L Zingales (2017), "Diagnosing the Italian Disease", NBER working paper 23964.
Schivardi, F and T Schmitz (2019), "The IT Revolution and Southern Europe’s Two Lost Decades", forthcoming in Journal of the European Economic Association.
 The data comes from the OECD Productivity Database, which decomposes growth in real GDP per hour worked into changes in total factor productivity, IT capital deepening, and non-IT capital deepening. Our measure of productivity growth is the sum of the first two components. This abstracts from changes in the non-IT capital stock, while still taking into account the effect of IT capital.
 We stop in 2008, as the subsequent financial crisis may have amplified divergence for reasons not captured in our model. We show in our paper that a calibration based on 1995-2015 yields similar results.