Since the middle of the 1990s, productivity growth in Southern Europe has been substantially lower than in other developed countries. Panel A of Figure 1 illustrates this by plotting aggregate productivity, measured as real GDP per hour worked (net of non-IT capital deepening), for six OECD countries. The data comes from the OECD Productivity Database, which decomposes growth in real GDP per hour worked into changes in total factor productivity (TFP), IT capital deepening and non-IT capital deepening. Our preferred measure of productivity growth is the sum of the two former components. This measure has the advantage to abstract from changes in the non-IT capital stock, while still taking into account the effect of IT capital. Between 1995 and 2015, productivity grew by only 0.1% per year in Italy and Spain and by 0.5% per year in Portugal, while it grew by 1.1% per year in Germany and by 1.4% per year in the United States.

 

Figure 1: Productivity growth and IT capital across the OECD

Source: OECD and EU KLEMS. See Schivardi and Schmitz (2019).

These trends represent a challenge for the survival of the monetary union. While a common currency can function well with geographical differences in productivity levels, it is much harder to accommodate persistent differences in productivity growth, particularly when inflation is low.  A line of research 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).  In a recent paper (Schivardi and Schmitz, 2019), we investigate this argument in greater detail. In particular, we seek to identify its main mechanisms, to determine their quantitative importance, and to discuss some policy implications.

We note that the striking divergence of Southern Europe coincides with the diffusion of information technology (IT) in the mid-1990s, which was a major driver of productivity growth in the leading economies. In Southern Europe, this IT Revolution made relatively little headway. Panel B of Figure 1 indicates that between 1995 and 2014, the real stock of IT capital increased by a factor of 4.6 in the United States and 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. Thus, IT diffusion in Southern Europe was limited, and even in countries that had somewhat faster growth in IT capital (such as Spain), IT had a negligible impact on productivity. Why was this the case?

An extensive empirical literature documents that IT adoption requires changes in firm organization and that it induces higher productivity gains in better-managed firms, because management practices and IT are complements. However, Southern European firms perform systematically worse in terms of management efficiency. Figure 2 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 that 20.000 firm in 35 countries . Figure 2 plots country (standardized) averages of this measure for industrialized economies, showing that Southern European countries such as Italy, Spain, Portugal and Greece have substantially lower scores than Northern European countries, the United States, Canada and Japan.

 

Figure 2: Management efficiency in OECD countries

Source: Authors’ calculations based on WMS data. See Schivardi and Schmitz (2019).

 

Do these differences in management practices matter for Southern Europe’s divergence? Figure 3 provides some evidence suggesting that they do. Panel A shows that before the IT Revolution, there was no correlation between management scores and productivity growth. However, Panel B shows that this changed radically around 1995, and a strong positive correlation emerged. Thus, inefficient management practices started to become a drag on growth with the beginning of the IT Revolution, in line with the idea that efficient management practices and IT are complementary.

 

Figure 3: Management scores and productivity growth before and after the IT Revolution

Source: OECD, WMS. Productivity growth is growth in real GDP per hour worked net of non-IT capital deepening. These graphs omit Greece (which has no productivity data) and Ireland (where the role of multinational companies makes national accounting difficult). See Schivardi and Schmitz (2019).

 

In our paper, we analyse these developments though the lens of a simple model built on two fundamental assumptions: efficient management and IT are complements, and Southern European countries have worse management practices. Our model predicts that inefficient management lowered Southern European income and productivity levels (but not growth rates) already before the IT Revolution. The arrival of the IT Revolution amplifies these differences between the North and the South. In fact, as efficient management and IT are complements, Southern firms adopting IT experience lower productivity gains than Northern firms. Furthermore, fewer Southern firms adopt IT in the first place, precisely because they do not benefit much from it. In addition, the IT Revolution increases Northern high-skilled wages more than Southern ones. This fosters high-skilled emigration, and the South thus loses exactly the workers it would need to adopt IT.

To determine the quantitative importance of these channels, we calibrate our model using various data sources.  In our baseline calibration, the IT Revolution increases productivity by 11.1% in Germany, 5.9% in Italy, 2.5% in Spain, and 3.4% in Portugal between 1995 and 2008. (We stop in 2008, as the subsequent financial crisis may have amplified divergence for reasons not captured in our model. However, we show in our paper that a calibration for the whole period 1995-2015 yields very similar results). 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 with respect to Germany. Divergence is mainly driven by lower firm-level productivity gains from IT adoption, compounded by lower adoption rates. High-skilled emigration triples as a consequence of the IT Revolution, but its impact on aggregate productivity is small.

Finally, we analyse a series of Southern European policy interventions. We show that subsidizing IT adoption would actually lower Southern productivity even further. Likewise, subsidizing education would also have negative effects, as it is effectively a transfer to the North, which reaps its benefits through high skilled migration.  This is because these policies cure the symptoms of Southern Europe malaise (low IT adoption or low education), but not the cause (inefficient management). Of course, these results should be taken with a grain of salt, as our model abstracts from market failures that might well result in suboptimal IT adoption or education choices. Nevertheless, this suggests that policies should focus on the underlying cause of Southern Europe’s divergence: inefficient management.

The final question is how to improve managerial practices. While the literature on the subject is still in its infancy, some lessons can already be drawn. An important factor is the ownership structure of firms. Family ownership and family management, particularly common in Southern Europe, tend to be associated with managerial practices of lower quality compared to widely held firms or firms controlled by private equity funds or by foreign owners. Consequently, we perform a final counterfactual, where we show that increasing the presence of foreign multinationals could substantially improve the quality of managerial practices in Southern Europe both 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 through managerial mobility.

 

References

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Brynjolfsson, Erik and Lorin M. Hitt (2000). “Beyond Computation: Information Technology, Organizational Transformation and Business Performance.” Journal of Economic Perspectives, 14(4), 23–48.

Fernald, John (2014). “Productivity and Potential Output Before, During, and After the Great Recession.” In NBER Macroeconomics Annual 2014, Volume 29.

Garcia-Santana, Manuel, Enrique Moral-Benito, Josep Pijoan-Mas, and Roberto Ramos (2019). “Growing like Spain: 1995-2007.” International Economic Review, Forthcoming.

Garicano, Luis and Paul Heaton (2010). “Information Technology, Organization, and Productivity in the Public Sector: Evidence from Police Departments.” Journal of Labor Economics, 28(1), 167–201.

Gopinath, Gita, Sebnem Kalemli-Ozcan, Loukas Karabarbounis, and Carolina Villegas-Sanchez (2017). “Capital Allocation and Productivity in South Europe.” The Quarterly Journal of Economics, 132(4), 1915–1967.

Gordon, Robert J. (2016). The Rise and Fall of American Growth: The U.S. Standard of Living since the Civil War. Princeton University Press.

Pellegrino, Bruno and Luigi Zingales (2017). “Diagnosing the Italian Disease.” Working Paper 23964, National Bureau of Economic Research.

Schivardi, Fabiano and Tom Schmitz (2019). “The IT Revolution and Southern Europe’s Two Lost Decades.” Journal of the European Economic Association, Forthcoming.