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Convergence in Central and Eastern Europe: Can All Get to EU Average?

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Abstract

This note examines recent evidence on the convergence of per capita incomes in Central and Eastern Europe. The motivation for revisiting this topic is a revival of interest among policymakers in speeding up the convergence process, after it apparently stalled during the financial crisis of 2008–2012 and the subsequent slow recovery. There are two main findings. First, the choice of benchmarks can make a significant difference for assessments of convergence. Most studies seem to ignore this “fine print” of data. Second, despite disappointments, the goal of convergence remains a useful anchor for economic policy in CEE. Going forward, it would be important to recognise that convergence is a slow process, but nevertheless requires sustained reforms to avoid prolonged periods of stagnation or pronounced booms and busts.

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Fig. 1

Sources: IMF, World Economic Outlook; author’s calculations

Fig. 2

Sources: IMF, World Economic Outlook, October 2017; author’s calculations

Fig. 3

Sources: IMF, World Economic Outlook, 2017; author’s calculations

Fig. 4

Sources: IMF, World Economic Outlook, 2017; author’s calculations

Fig. 5
Fig. 6

Sources: IMF, World Economic Outlook; author’s calculations

Fig. 7

Sources: ECB; Datastream

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Notes

  1. Social psychologists have well documented the notion of “illusory superiority”, a tendency of individuals to overestimate their capabilities and performance (see e.g. Gilovich 1991). This tendency is also known as the Lake Wobegon effect, named after a fictional town from a long-running radio broadcast Prairie Home Companion “where all the women are strong, all the men are good-looking, and all the children are above average” (Keillor 1985).

  2. See e.g. Borsi and Metiu (2013), ECB (2015), Vujčić (2017), the IMF conference “Reaccelerating convergence in central eastern and Southeastern Europe” (Dubrovnik, 10–11 July 2017), and the ECB conference “Institutional quality and sustainable economic convergence” (Frankfurt, 5 October 2017).

  3. Calculated as β = − (1/T) ln(1 + α1T), where T is the length of the sample period (21 years) and α is the slope coefficient from the regression in Fig. 1 (− 0.018). For a derivation of the formula, see e.g. Šikić (2013) or Dobrinsky and Havlik (2014).

  4. Calculated as τ = − ln(0.5)/β.

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  1. BIS, Basel, Switzerland

    Dubravko Mihaljek

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  1. Dubravko Mihaljek
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Correspondence to Dubravko Mihaljek.

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This note is based on my introductory remarks to the panel How much catching-up is still out there? at the 23rd Dubrovnik Economic Conference. The views expressed are those of the author and not necessarily those of the BIS. I would like to thank Paul Wachtel and participants of a seminar at Croatian National Bank for helpful comments.

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Mihaljek, D. Convergence in Central and Eastern Europe: Can All Get to EU Average?. Comp Econ Stud 60, 217–229 (2018). https://doi.org/10.1057/s41294-018-0063-7

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