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Rose effect and the euro: is the magic gone?

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Abstract

This paper presents an updated meta-analysis of the effect of currency unions on trade, focusing on the euro area. Using meta-regression methods such as the funnel asymmetry test, evidence for strong publication bias is found. The estimated underlying effect for currency unions other than the eurozone reaches more than 60%. However, according to the meta-regression analysis, the euro’s trade promoting effect corrected for publication bias is insignificant. The Rose effect literature shows signs of the economics research cycle: reported t-statistic is a quadratic concave function of the publication year. Explanatory meta-regression (robust fixed effects and random effects), that can explain about 70% of the heterogeneity in the literature, suggests that results published by some authors might consistently differ from the mainstream output and that study outcomes are systematically dependent on study design (usage of panel data, short- or long-run nature, number of countries in the data set).

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Notes

  1. For an excellent introduction to the methodology of meta-analysis and its application in economics, see Stanley (2001).

  2. There is an obvious trade-off between the representativeness and the robustness of the data: selecting representative estimates increases the threat of mistakes and data contamination. For this reason, we employ robust estimation methods wherever possible.

  3. The exact search query used in RePEc was (((currency | monetary) + union) | euro) + trade + (effect | rose) + estimate, abstract search since 2002. The “old” Rose and Stanley (2005) data were updated—for example, many of the then working papers have been published in a journal since 2005 and their estimates might have slightly changed.

  4. Note that “fixed” and “random” effects estimators in meta-analysis do not correspond to the standard use of these terms in panel data econometrics. For a more detailed explanation, see Abreu et al. (2005) and Sutton et al. (2000).

  5. As Rabe-Hesketh and Skrondal (2008, p. 159) note, the LR test is conservative in this case and the correct p-value can be obtained by dividing the original LR p-value by 2.

  6. Other robustness checks are available from the author upon request or in the working paper version of this article.

  7. A predictable pattern of novelty and fashion in economics; initial path-breaking results are confirmed by other highly significant estimates, but as the time passes, skeptical results become preferable (Goldfarb 1995; Stanley et al. 2008).

  8. However, because these are weighted least squares versions of the original equation, R 2s have to be recomputed to reflect the actual determination of the estimates of γ. For example, in the case of the robust specification, the corrected R 2 reaches 0.68.

  9. Monte Carlo experiments suggest that random effects MRA is preferable if heterogeneity is caused by non-constant effect size variance or differences in the true underlying effect across studies. However, when heterogeneity arises due to omitted variable bias—which is realistic in economics—fixed effects estimators should be relied upon (Koetse et al. 2010). For this reason, fixed effects MRA is interpreted here as well along with random effects.

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Acknowledgments

This work was supported by the IES Research Institutional Framework 2005–2010 (MSMT 0021620841). I thank Roman Horváth, Zuzana Iršová, Tom Stanley, Katerina Šmídková, and participants of the ETPM seminar at the Charles University in Prague for valuable comments. I am especially grateful to an anonymous referee of this journal for very useful suggestions that led to a substantial improvement in the quality and readability of the article. All remaining errors and omissions are mine. The views expressed are those of the author and do not necessarily reflect the views of the Czech National Bank.

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  1. Economic Research and Financial Stability Department, Czech National Bank, Na Prikope 28, 115 03, Prague 1, Czech Republic

    Tomáš Havránek

  2. Institute of Economic Studies, Charles University in Prague, Opletalova 26, 110 00, Prague 1, Czech Republic

    Tomáš Havránek

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Correspondence to Tomáš Havránek.

Appendix

Appendix

Tables 4, 5 and Figs. 4, 5

Table 4 Studies used in the meta-analysis
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Table 5 Acronyms of regression variables
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Fig. 4
figure 4

Forest plot of individual estimates of γ, non-euro studies

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Fig. 5
figure 5

Funnel plot corrected for publication bias, all studies

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Havránek, T. Rose effect and the euro: is the magic gone?. Rev World Econ 146, 241–261 (2010). https://doi.org/10.1007/s10290-010-0050-1

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