Patterns of Convergence and Divergence in the Euro Area


This article studies the extent of macroeconomic convergence/divergence among euro area countries. The analysis focuses on four variables (unemployment, inflation, relative prices, and the current account), and seeks to uncover the role played by monetary union as a convergence factor by using noneuro developed economies and the pre-European Monetary Union period as control samples.

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  1. 1.

    Our focus is on macroeconomic convergence. For an overview of the impact of EMU on trade and financial integration see, for example, Lane (2006), Santos-Silva and Tenreyro (2010), and Kalemli-Ozcan and others (2010).

  2. 2.

    Mundell (1961) and Kenen (1969) were among the first to emphasize the importance of those factors in order to determine whether the costs of a currency union (associated to the lack of a country-specific monetary policy) would more than offset the benefits (associated with greater trade and financial integration).

  3. 3.

    See, for example, Giannone and others (2010) and the references therein for evidence on the role of monetary unification as a potential source of greater synchronization of business cycles.

  4. 4.

    Excluding these three countries, the regression coefficient becomes negative, although nonstatistically significant at standard levels.

  5. 5.

    See Lane (2006) and Mongelli and Wyplosz (2009) for further discussion of inflation differentials and their implications.

  6. 6.

    See Caselli (2009) for a related view. Ball and Sheridan (2005) and Mishkin and Schmidt-Hebbel (2007) provide evidence of a generalized decline in inflation among developed economies over the past quarter century.

  7. 7.

    See Alesina and Barro (2002) for a discussion of the role played by currency unions in overcoming the inflationary bias associated with the time inconsistency problem.

  8. 8.

    A precondition for EMU membership was that inflation could not be higher than 1.5 percentage points the unweighted average of the three EU member states with the lowest inflation rates.

  9. 9.

    Excluding these two countries form the regression, the convergence parameter becomes negative, although nonstatistically significant at standard levels.

  10. 10.

    See Lane (2006), Engel and Rogers (2004) and Allington and others (2005) for an analysis of price convergence within the euro area using more disaggregated data.

  11. 11.

    Lane (2006) emphasizes the differential impact on the competitiveness of different euro area countries of changes in the external value of the euro, due to the diversity in the composition of trade partners.

  12. 12.

    Blanchard (2007) constitutes an early analysis on the different options that an euro area country like Portugal had to recover losses of competitiveness.

  13. 13.

    Several regulation indices elaborated by the OECD could be used to assess the link between labor market regulation and good market regulations and external imbalances. The Doing Business indicators elaborated by the World Bank can also be used for this purpose. As we discuss below, these aspects constitute key elements of the index elaborated by the World Economic Forum and some of them are assessed to analyze the robustness of our conclusions.

  14. 14.

    This index was elaborated by Xavier Sala-i-Martin and Elsa Artadi and published by the World Economic Forum, and it expands on two previously considered indices: The Growth Competitiveness Index and Business Competitiveness Index. For more details, see

  15. 15.

    A brief description of the “pillars” is presented in the Appendix.


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Additional information

*Ángel Estrada is advisor in the International Affairs Associate Directorate General at the Banco de España. Jordi Galí is Director of Centre de Recerca en Economia Internacional (CREI) at Universitat Pompeu Fabra, and Research Professor at the Barcelona Graduate School of Economics. David López-Salido is Deputy Associate Director in the Monetary Affairs Division at the Board of Governors of the Federal Reserve System. Prepared for the IMF Thirteenth Jacques Polak Annual Research Conference, November 8−9, 2012. The authors thank Pierre-Olivier Gourinchas, Ayhan Kose, and two anonymous referees and conference participants for their comments. The views expressed in this paper are those of the authors alone and do not necessarily reflect the views of the Banco de España or the Board of Governors of the Federal Reserve Systems or its staff.

Appendix I

Appendix I

Data Sources and Description of the Variables

Most of the data used in this paper has been obtained from the statistical office of the European Union (Eurostat), at the website: In some cases the time series were forward extended using other data basis, such as AMECO (ECFIN European Commission):

  • In particular, the European unemployment rates were obtained from the Labor Force Survey, using the conventional definitions (population aged 15–64): its side, the US unemployment rate corresponds to the household data of the Bureau of Labor Statistics:

  • The European and other countries inflation rates were obtained from AMECO, and they correspond to the harmonized or domestic concept as available:

  • GDP, value added and their deflators, employment (heads and hours, total employment and wage earners) and compensation of employees correspond to their National Accounts definitions. These time series were obtained from Eurostat at the website: /data/database. In this respect, the tradable sector corresponds to the NACE activities A to E; the nontradable sector to F to E.

  • The source of the purchasing power parities (PPP) used in the construction of the price levels is also Eurostat and the International Monetary Fund WEO database: For the euro area countries, the tradable sector is identified with total goods and the nontradable sector with total services. For other developed countries, relative prices of the tradable sector in the base year correspond to those of the

  • Information on the current account was also obtained from the balance of payments compiled by Eurostat and the International Monetary Fund WEO balance_of_payments/data/database.

Unit labor costs are defined as the ratio between wages and labor productivity. Wages are obtained by dividing compensation of employees on hours worked by employees. Finally, labor productivity corresponds to GDP (Value added) divided on hours worked by total employment.

The GCI corresponds to the elaboration of the World Economic Forum: A brief description of the GCI 12 pillars is provided in the main report.

First pillar: Institutions. The institutional environment is determined by the legal and administrative framework within which individuals, firms, and governments interact to generate wealth. Government attitudes toward markets and freedoms and the efficiency of its operations are also very important: excessive bureaucracy and red tape, overregulation, corruption, dishonesty in dealing with public contracts, lack of transparency and trustworthiness, inability to provide appropriate services for the business sector, and political dependence of the judicial system impose significant economic costs to businesses and slow the process of economic development.

Second pillar: Infrastructure. A well-developed transport and communications infrastructure network is a prerequisite for the access of less-developed communities to core economic activities and services. Effective modes of transport—including quality roads, railroads, ports, and air transport—enable entrepreneurs to get their goods and services to market in a secure and timely manner and facilitate the movement of workers to the most suitable jobs.

Third pillar: Macroeconomic environment. A proper management of public finances is also critical to ensuring trust in the national business environment. This pillar includes indicators capturing the quality of government management of public finances. Running persistent fiscal deficits limits the government’s future ability to react to business cycles and to invest in competitiveness-enhancing measures. It is important to note that this pillar evaluates the stability of the macroeconomic environment, so it does not directly take into account the way in which public accounts are managed by the government.

Fourth pillar: Health and primary education. Poor health leads to significant costs to business, as sick workers are often absent or operate at lower levels of efficiency. In addition to health, this pillar takes into account the quantity and quality of the basic education received by the population.

Fifth pillar: Higher education and training. This pillar measures secondary and tertiary enrollment rates as well as the quality of education as evaluated by the business community. The extent of staff training is also taken into consideration because of the importance of vocational and continuous on-the-job training—which is neglected in many economies—for ensuring a constant upgrading of workers’ skills.

Sixth pillar: Goods market efficiency. Healthy market competition, both domestic and foreign, is important in driving market efficiency and thus business productivity by ensuring that the most efficient firms, producing goods demanded by the market, are those that thrive. The best possible environment for the exchange of goods requires a minimum of impediments to business activity through government intervention. Market efficiency also depends on demand conditions such as customer orientation and buyer sophistication. For cultural or historical reasons, customers may be more demanding in some countries than in others.

Seventh pillar: Labor market efficiency. The efficiency and flexibility of the labor market are critical for ensuring that workers are allocated to their most effective use in the economy and provided with incentives to give their best effort in their jobs. Efficient labor markets must also ensure a clear relationship between worker incentives and their efforts to promote meritocracy at the workplace, and they must provide equity in the business environment between women and men.

Eighth pillar: Financial market development. An efficient financial sector allocates the resources saved by a nation’s citizens, as well as those entering the economy from abroad, to their most productive uses. A thorough and proper assessment of risk is therefore a key ingredient of a sound financial market. In order to fulfill all those functions, the banking sector needs to be trustworthy and transparent, and—as has been made so clear recently—financial markets need appropriate regulation to protect investors and other actors in the economy at large.

Ninth pillar: Technological readiness. The technological readiness pillar measures the agility with which an economy adopts existing technologies to enhance the productivity of its industries, with specific emphasis on its capacity to fully leverage information and communication technologies in daily activities and production processes for increased efficiency and enabling innovation for competitiveness.

Tenth pillar: Market size. Therefore, we continue to use the size of the national domestic and foreign market in the Index. Thus exports can be thought of as a substitute for domestic demand in determining the size of the market for the firms of a country.

Eleventh pillar: Business sophistication. The quality of a country’s business networks and supporting industries, as measured by the quantity and quality of local suppliers and the extent of their interaction, is important for a variety of reasons. Individual firms’ advanced operations and strategies (branding, marketing, distribution, advanced production processes, and the production of unique and sophisticated products) spill over into the economy and lead to sophisticated and modern business processes across the country’s business sectors.

Twelfth pillar: Innovation. The final pillar of competitiveness focuses on technological innovation. In particular, it means sufficient investment in research and development (R&D), especially by the private sector; the presence of high-quality scientific research institutions that can generate the basic knowledge needed to build the new technologies; extensive collaboration in research and technological developments between universities and industry; and the protection of intellectual property, in addition to high levels of competition and access to venture capital and financing that are analyzed in other pillars of the Index.

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Estrada, Á., Galí, J. & López-Salido, D. Patterns of Convergence and Divergence in the Euro Area. IMF Econ Rev 61, 601–630 (2013).

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