To this end, Table Comparing the policy measures currently undertaken or planned with the long-term challenges arising from economic polarisation in the Eurozone reveals that the current policy focus is mostly on short-run measures to keep the economy going and/or to jumpstart economic activities after lockdowns and other restrictions have been sufficiently released.

(2020a). (2013). It begins with an analysis of structural polarisation processes in pre-Corona years and continues with an analysis of the impact of the pandemic.The gap in per capita incomes between Northern and Southern Eurozone countries has widened considerably since the birth of the Euro about twenty years ago (see Fig.

Southern Eurozone (population-weighted average): Greece, Italy, Portugal, SpainAt the same time, Southern Eurozone countries—above all Italy and Greece—have entered into the Corona crisis with high levels of public debt. Simonazzi In summary, most European firms with a strong technological position typically operate from their home base in Northern countries, such as Germany and Austria. The macroeconomic impact of the Corona crisis on Northern and Southern Eurozone countries will be asymmetric due to existing differences in production structures and because of the vulnerabilities of the different growth models described above.

Economic polarisation in Europe: Causes and policy options, wiiw Research Report No. Use Git or checkout with SVN using the web URL. Part of

(2020). In these Southern countries, the crisis is forecast to reduce GDP growth rates more than in the Northern Eurozone countries comprising Austria, Belgium, Finland, Germany and the Netherlands (see panel A of Fig. Myths, Mix-ups and Mishandlings: Understanding the Eurozone Crisis. In what follows, we briefly evaluate European economic policy initiatives in response to the Corona shock. Tax revenues and government spending in the Eurozone (inflation-adjusted).

(2020). This paper discusses the uneven consequences of the macroeconomic fallout from the Coronavirus and related economic policy responses against the background of an analysis of longer-term macroeconomic divergence in the Eurozone.

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And indeed, such links between pressing immediate demands and medium-term strategic challenges also partially coin the viewpoint of the European Commission (e.g. Pandemic central banking: the monetary stance, market stabilisation and liquidity, Remarks by Philip R. Lane, member of the Executive Board of the ECB (May 19th 2020).

Technological capabilities are also relevant when it comes to explaining the emergence of the unsustainable co-existence of export-driven and debt-driven growth models in the EMU: countries in the North were better equipped to follow an export-led growth model precisely because their economies have accumulated a sufficient amount of the technological capabilities necessary to compete successfully on international markets, where technological sophistication is more important than price competitiveness (Storm and Naastepad The emergence of these different growth models also had a feedback effect on the further development of production structures: while Germany and other Northern countries have expanded their cumulative advantage in high-tech manufacturing over the past 2 decades, Southern European countries have increasingly been locked into lower-tech and non-tradable activities (e.g. We show that the macroeconomic impact of the Corona crisis is estimated to be more severe in Southern Eurozone countries than in Northern Eurozone countries, which further reinforces the tendency of an increasing economic polarisation.

Southern Eurozone (population-weighted average): Greece, Italy, Portugal, SpainEssential factors for explaining the long-term divergence of Eurozone countries are to be found in the unequal regulatory conditions in the context of the European ‘race for the best location’ (for example, in the areas of the labour market, tax and corporate law, or financial market regulation, see Kapeller et al.

This repository contains the code and instructions for reproducing the results of the paper "Machine-learned patterns suggest that diversification drives economic development" by Charles D. Brummitt, Andrés Gómez-Liévano, Ricardo Hausmann, and Matthew H. Bonds.The data on exports used in this paper is available for download To study the most recent version of this dataset and of related ones, go to the The results of this paper were generated mostly with Python 3.5.3 and, in a few minor parts, in R.Clone this repository to your local machine.

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