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The impact of market regulations on intra-European real exchange rates

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Abstract

We study the contribution of market regulations to the dynamics of the real exchange rate within the European Union. Based on a model proposed by De Gregorio et al. (Rev Int Econ 2(3):284–305, 1994a), we show that both product market regulations in nontradable sectors and employment protection tend to raise the real exchange rate. We then carry out an econometric estimation for European countries for 1985–2006 to quantify the contributions of the pure Balassa–Samuelson effect and those of market regulations on real exchange-rate variations. Based on this evidence and on a counter-factual experiment, we conclude that the relative evolutions of product market regulations and employment protection across countries play a very significant role for real exchange-rate variations within the European Union and especially within the euro area, through their impacts on the relative price of nontradable goods.

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Notes

  1. See Sect. 2.

  2. The nontradable sector includes: electricity, gas and water supply, construction, wholesale and retail trade, hotels and restaurants. In turn, the tradable sector covers manufacturing, transport, storage, communication, and all primary sectors. Unfortunately the data do not extend consistently beyond 2006 (see Sect. 4).

  3. Within the EU single market, changes in trade tariffs are no longer an issue.

  4. See Bahmani-Oskooee and Nasir (2005) for a review.

  5. We simplify the model by omitting government expenditures, the impact of which has been shown either neutral or ambiguous in the literature, (see De Gregorio et al. 1994b).

  6. Here we drop time subscripts for the sake of clarity.

  7. The first-order Taylor approximation of (24) around w 0 is given by \(L^d(w)=L^d(w_0)+(w-w_0)\partial L^d(w_0)/\partial w=L_0+\epsilon w\) where \(\partial L^d(w)/\partial w=\frac{1}{(1-\alpha)w}\left(\frac{\alpha a^T p^T}{pw}\right)^{1/(1-\alpha)}-\frac{(1-\gamma)Y^T}{\gamma(1+\beta)p w^2}, L_0=L^d(w_0)-w_0\partial L^d(w_0)/\partial w\) and \(\epsilon= -\partial L^d(w_0)/\partial w\). Like De Gregorio et al. (1994a), we neglect here the effect of labor demand parameters on \(\epsilon\).

  8. Only the level of significance can be affected. We have checked the robustness of our results by changing the reference country. The results are available from the authors.

  9. Using the last updated OECD databases, the PMR index is available from 1975 to 2007 for 29 OECD countries, while EP index is available for the period 1985–2013 for 43 countries (34 OECD countries and 9 emerging economies). Therefore, our sample starts in 1985. Due to missing values for the PMR index in 2007 and in order to get a balanced panel that is required by our estimation procedure (panel DOLS procedure of Mark and Sul 2003), our data cover the period 1985–2006.

  10. Intermediate years are available but skipped here to save space.

  11. Cross-sectional dependence in panel data settings results in nuisance parameter problems in the first-generation panel unit root tests (which assume cross-sectional independence). The Pesaran test relies on the cross-sectional augmented Dickey–Fuller (CADF, see below).

  12. In contrast to the second-generation panel unit root tests, the third-generation panel unit root tests allow consideration of both cross-sectional dependency and structural breaks.

  13. See http://epp.eurostat.ec.europa.eu/portal/page/portal/excessive_imbalance_procedure/imbalance_scoreboard.

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Acknowledgments

This paper was written while both authors were researchers at CEPII. We are thankful to Gunther Capelle-Blancard, Benjamin Carton, Jacques Melitz and Valérie Mignon for their remarks on a preliminary version. The usual disclaimer applies.

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Correspondence to Agnès Bénassy-Quéré.

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Bénassy-Quéré, A., Coulibaly, D. The impact of market regulations on intra-European real exchange rates. Rev World Econ 150, 529–556 (2014). https://doi.org/10.1007/s10290-014-0185-6

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