Skip to main content

Advertisement

SpringerLink
Log in

Exchange Rate Regimes and Business Cycle Synchronization

  • Research Article
  • Published:
Open Economies Review Aims and scope Submit manuscript

Abstract

This paper studies the effect of seven types of exchange rate regimes on business cycle synchronization, by using a new dataset on bilateral de-facto exchange rate regimes for the 1973-2016 period. Using the extreme bounds analysis (EBA) methodology, we find that the exchange rate regime is a robust determinant of business cycle synchronization. We find that, compared to country pairs with freely floating arrangements, (i) the correlation coefficient measuring business cycle synchronization is higher by approximately 0.07-0.12 points in countries with no separate legal tenders; (ii) the effect does not always linearly decrease with increasing exchange rate regime flexibility, since the effects of crawling pegs and crawling bands turn out to be insignificant, whereas that of moving bands as a more flexible type of exchange rate regime is positive and significant; and (iii) the effect is stronger for countries with a high degree of financial openness and good institutional quality. The second finding suggests that the role of intermediate exchange rate regimes is more complicated than previously recognized in the literature and deserves more attention. In addition, we find that (iv) the positive effect of interest is more prominent for countries from the high-income group, in contrast to the occasionally negative effect of some regimes for other country pairs, and that (v) specialization and fiscal policy integration are factors that influence the effect of exchange rate regimes on business cycle synchronization.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. See for example Klein and Shambaugh (2006) for the effect of exchange rate regimes on international trade, Harms and Knaze (2021) for the effect on FDI or Ghosh et al. (2014) for the effect on inflation. Further, exchange rate regimes have been found to significantly affect GDP growth (Levy-Yeyati and Sturzenegger 2003), terms of trade (Broda 2004) or other policy variables [e.g.][onmonetarypolicy] (Obstfeld et al. 2005).

  2. The dataset with further description is available at: https://www.international.economics.uni-mainz.de/data-on-bilateral-exchange-rate-regimes/ In some part of the analysis, we also test the specification by including the \(Regime_{FF}\) dummy that takes a value of one if at least one country from a given country pair had a freely falling exchange rate regime at a given period.

  3. Another approach would be to use an average value of the exchange rate regime measure for each period. However, taking averages would leave us with non-integer values. For example, if a country had a crawling peg (Regime 4) and later on adopted a crawling band (Regime 5). To circumvent this, we conduct analysis based on yearly data of all relevant variables. The results are part of the robustness check to alternative indicators, which we mention again later.

  4. We follow Levine and Renelt (1992) and Sala-I-Martin (1997) to choose 3 as the number of variables for combinations in EBA regressions. Techniqually, it is also fine to choose a bigger number as the criteria. However, to our understanding of the method, this number should not matter too much for the results since we make ultimately all combinations in the rolling windows. In results not reported in the paper, we tried to use 4 as the number of explanatory variables, the coefficients of ERR dummies stay rather similar. The results are available upon request.

  5. In one of our robustness checks, we will replace country-specific variables by time-variant country fixed effects in line with Harms and Knaze (2021). Note, however, that we do not include country-pair fixed effects since our main variable of interest — the bilateral de-facto exchange rate regime — exhibits little time variation.

  6. In addition, we find that our dummy variable \(Regime_{FF}\) dummy has an EBA robust negative coefficient: country pairs where at least one country’s regime is classified as freely falling have substantially less synchronised business cycles compared to the country pairs with free floating regimes. This is in line with our intuition: if countries with freely falling exchange rate regime suffer severe financial and economic crisis, then the business cycles get significantly out of synchronization compared to countries that are currently not in crisis. We have conducted further analysis on \(Regime_{FF}\). Results are available upon request.

  7. We perform the sample split by defining a threshold of 0.5 in the range 0 to 1, where countries with an index of 0.5 or higher are understood as having an open financial account. Results are available upon request.

  8. Our EBA estimation included both different measures of trade intensity as well as the principal component of four different measures to estimate parameters of principal-component model following Inklaar et al. (2008). Since all variables were found to be EBA robust, we use the principal component of the variables in the benchmark results.

  9. We note a difficulty in comparing the strength of the effects between individual determinants: the dummy coefficients for exchange rate regimes are non-standardized, whereas the other variables have standardized coefficients. Despite the standardization, bilateral variables constructed as bilateral correlations such as trade specialisation are difficult to compare with aggregate measures such as trade openness. Therefore, our paper focuses on the relative importance between individual exchange rate regimes for business cycles synchronization.

  10. We have conducted analysis when observations of “Free Falling” regime is included for both the EBA analysis and the reduced model. Results are available upon request.

  11. Note that from cca. 27.000 observations available, the large majority are the freely floating regimes.

  12. We are grateful to two anonymous referees for motivating us to conduct analysis for this section.

References

  • Alesina A, Wagner AF (2006) Choosing (and reneging on) exchange rate regimes. J Eur Econ Assoc 4(4):770–799

    Article  Google Scholar 

  • Anderson HM, Kwark NS, Vahid F et al (1999) Does international trade synchronize business cycles? Monash University, Department of Econometrics and Business Statistics, Tech. rep.

    Google Scholar 

  • Arkolakis C, Ramanarayanan A (2009) Vertical specialization and international business cycle synchronization. Scandinavian J Econ 111(4):655–680

    Article  Google Scholar 

  • Barro R, Tenreyro S (2007) Economic effects of currency unions. Econ Inq 45(1):1–23

    Article  Google Scholar 

  • Baxter M, King RG (1999) Measuring business cycles: Approximate band-pass filters for economic time series. Rev Econ Stat 81(4):575–593. https://ideas.repec.org/a/tpr/restat/v81y1999i4p575-593.html

  • Baxter M, Kouparitsas MA (2005) Determinants of business cycle comovement: A robust analysis. J Monet Econ 52(1):113–157

    Article  Google Scholar 

  • Belke A, Heine JM (2006) Specialisation patterns and the synchronicity of regional employment cycles in Europe. IEEP 3(2):91–104

    Article  Google Scholar 

  • Belke A, Domnick C, Gros D (2017) Business cycle synchronization in the EMU: Core vs. periphery. Open Econ Rev 28(5):863–892

  • Bleaney MF, Tian M, Yin L (2017) De facto exchange rate regime classifications: An evaluation. Open Econ Rev 28(2):369–382

    Article  Google Scholar 

  • Broda C (2004) Terms of trade and exchange rate regimes in developing countries. J Int Econ 63(1):31–58

    Article  Google Scholar 

  • Burstein A, Kurz C, Tesar L (2008) Trade, production sharing, and the international transmission of business cycles. J Monet Econ 55(4):775–795

    Article  Google Scholar 

  • Calderon C, Chong A, Stein E (2007) Trade intensity and business cycle synchronization: Are developing countries any different? J Int Econ 71(1):2–21

    Article  Google Scholar 

  • Campos NF, Fidrmuc J, Korhonen I (2019) Business cycle synchronisation and currency unions: A review of the econometric evidence using meta-analysis. Int Rev Fin Anal. http://www.sciencedirect.com/science/article/pii/S1057521918301650

  • Cerqueira P (2013) A closer look at the world business cycle synchronization. Int Econ Econ Policy 10(3):349–363. https://EconPapers.repec.org/RePEc:kap:iecepo:v:10:y:2013:i:3:p:349-363

  • Cerqueira PA, Martins R (2009) Measuring the determinants of business cycle synchronization using a panel approach. Econ Lett 102(2):106–108. https://www.sciencedirect.com/science/article/pii/S0165176508003182

  • Chang R, Velasco A (2000) Financial fragility and the exchange rate regime. J Econ Theo 92(1):1–34

    Article  Google Scholar 

  • Chinn MD, Ito H (2006) What matters for financial development? Capital controls, institutions, and interactions. J Dev Econ 81(1):163–192. https://ideas.repec.org/a/eee/deveco/v81y2006i1p163-192.html

  • Christiano LJ, Fitzgerald TJ (2003) The band pass filter. Int Econ Rev 44(2):435–465. https://onlinelibrary.wiley.com/doi/pdf/10.1111/1468-2354.t01-1-00076

  • Darvas Z, Szapáry G (2008) Business cycle synchronization in the enlarged EU. Open Econ Rev 19(1):1–19

    Article  Google Scholar 

  • De Grauwe P, Ji Y (2017) The international synchronisation of business cycles: The role of animal spirits. Open Economies Review 28(3), 383–412

    Article  Google Scholar 

  • Dées S, Zorell N (2012) Business cycle synchronisation: Disentangling trade and financial linkages. Open Econ Rev 23(4):623–643

    Article  Google Scholar 

  • Di Giovanni J, Levchenko AA (2010) Putting the parts together: Trade, vertical linkages, and business cycle comovement. Am Econ J Macroecon 2(2):95–124

    Article  Google Scholar 

  • Dorn S, Egger P (2015) On the distribution of exchange rate regime treatment effects on international trade. J Int Money Fin 53:75-94. http://www.sciencedirect.com/science/article/pii/S0261560614002198

  • Duval R, Li N, Saraf R, Seneviratne D (2016) Value-added trade and business cycle synchronization. J Int Econ 99:251–262. https://www.sciencedirect.com/science/article/pii/S0022199615001555

  • Ehrmann M, Fratzscher M (2009) Global financial transmission of monetary policy shocks. Oxford Bull Econ Stat 71(6):739–759

    Article  Google Scholar 

  • Fleming JM (1962) Domestic financial policies under fixed and under floating exchange rates. Staff Papers 9(3):369–380

    Article  Google Scholar 

  • Ghosh AR, Qureshi MS, Tsangarides CG (2014) On the value of words: Inflation and fixed exchange rate regimes. IMF Econ Rev 62(2):288–322. https://doi.org/10.1057/imfer.2014.14

  • Harms P, Knaze J (2021) Bilateral de-jure exchange rate regimes and foreign direct investment: A gravity analysis. J Int Money Financ 117

  • Ilzetzki E, Reinhart CM, Rogoff KS (2019) Exchange Arrangements Entering the Twenty-First Century: Which Anchor will Hold? Quarterly J Econ 134(2):599–646. https://doi.org/10.1093/qje/qjy033

  • Imbs J (2004) Trade, finance, specialization, and synchronization. Rev Econ Stat 86(3):723–734

    Article  Google Scholar 

  • Imbs J (2006) The real effects of financial integration. J Int Econ 68(2):296–324. https://www.sciencedirect.com/science/article/pii/S002219960500053X

  • Inklaar R, Jong-A-Pin R, De Haan J (2008) Trade and business cycle synchronization in OECD countries A re-examination. Eur Econ Rev 52(4):646–666

    Article  Google Scholar 

  • Itskhoki O, Mukhin D (2019) Mussa Puzzle Redux. Society for Economic Dynamics 2019 Meeting Papers(1434). https://ideas.repec.org/p/red/sed019/1434.html

  • Kalemli-Ozcan S, Sørensen BE, Yosha O (2001) Economic integration, industrial specialization, and the asymmetry of macroeconomic fluctuations. J Int Econ 55(1):107–137

    Article  Google Scholar 

  • Kalemli-Ozcan S, Papaioannou E, Peydro JL (2013) Financial regulation, financial globalization, and the synchronization of economic activity. J Financ 68(3):1179–1228

    Article  Google Scholar 

  • Klein MW, Shambaugh JC (2006) Fixed exchange rates and trade. J Int Econ 70:359–383

    Article  Google Scholar 

  • Klein MW, Shambaugh JC (2010) Exchange Rate Regimes in the Modern Era, MIT Press Books, vol 1. The MIT Press.  https://ideas.repec.org/b/mtp/titles/0262013657.html

  • Laeven L, Valencia F (2012) Systemic banking crisis database: An update. Working paper, International Monetary Fund

  • Leamer EE (1983) Let’s take the con out of econometrics. Am Econ Rev 73(1):31–43

    Google Scholar 

  • Leamer EE (1985) Sensitivity analyses would help. Am Econ Rev 75(3):308–313. http://www.jstor.org/stable/1814801

  • Levy-Yeyati E, Sturzenegger F (2003) To float or to fix: evidence on the impact of exchange rate regimes on growth. Am Econ Rev 93(4):1173–1193

    Article  Google Scholar 

  • McKinnon RI (2004) Optimum currency areas and key currencies: Mundell I versus mundell II. JCMS: Journal of Common Market Studies 42(4):689–715. https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.0021-9886.2004.00525.x

  • Mundell RA (1963) Capital mobility and stabilization policy under fixed and flexible exchange rates. Canadian Journal of Economics and Political Science/Revue canadienne de economiques et science politique 29(4):475–485

    Article  Google Scholar 

  • Obstfeld M, Shambaugh JC, Taylor AM (2005) The trilemma in history: Tradeoffs among exchange rates, monetary policies, and capital mobility. Rev Econ Stat 87(3):423–438

    Article  Google Scholar 

  • Pentecôte JS, Poutineau JC, Rondeau F (2015) Trade integration and business cycle synchronization in the emu: The negative effect of new trade flows. Open Econ Rev 26(1):61–79

    Article  Google Scholar 

  • Reinhart C, Rogoff KS (2004) The modern history of exchange rate arrangements: A reinterpretation. Quart J Econ 119:1–48

    Article  Google Scholar 

  • Rey H (2016) International channels of transmission of monetary policy and the mundellian trilemma. IMF Econ Rev 64(1):6–35

    Article  Google Scholar 

  • Sala-I-Martin (1997) I just ran two millions regressions. Am Econ Rev 87:178–183

  • Sturm J, Haan J (2005) Determinants of long-term growth: New results applying robust estimation and extreme bounds analysis. Emp Econ 30:597–617. https://doi.org/10.1007/s00181-005-0252-x

    Article  Google Scholar 

  • Tavlas G, Dellas H, Stockman AC (2008) The classification and performance of alternative exchange-rate systems. Eur Econ Rev 52(6):941–963

    Article  Google Scholar 

  • Taylor JB (2001) The role of the exchange rate in monetary-policy rules. Am Econ Rev 91(2):263–267

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. China Center for Special Economic Zone Research, Shenzhen University, Shenzhen, 518060, China

    Jia Hou

  2. Johannes Gutenberg University Mainz, Gutenberg School of Management and Economics, Jakob-Welder-Weg 4, Mariz, 55128, Germany

    Jakub Knaze

Authors
  1. Jia Hou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jakub Knaze
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jia Hou.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

We are indebted to audiences at the 2019 Goettingen workshop on International Economics, the 19th China Youth Economist Forum at Wuhan University, seminar participants at Johannes Gutenberg University Mainz and Technical University of Darmstadt for helpful comments. We are also grateful for helpful comments from the editor and two anonymous referees. All errors are on our own.

Appendix

Appendix

Fig. 5
figure 5

Distribution of untransformed and transformed coefficients of business cycle synchronization.

Full size image
Table 7 De-facto exchange rate regimes mapping.
Full size table
Fig. 6
figure 6

Variables used in the EBA to choose the EBA robust variables

Full size image
Table 8 Effect of exchange rate regimes on business cycle synchronization as an untransformed dependent variable without the Fisher’s-Z transformation
Full size table
Table 9 Excluding observations classified as freely falling or in crisis
Full size table
Table 10 Sample split by levels of financial openness and institutional quality
Full size table
Table 11 Effect of exchange rate regimes on business cycle synchronization: Limiting the sample of yearly data only for observations when the quarterly data are not missing
Full size table
Table 12 Controlling for the time-varying heterogeneity using country-time fixed effects
Full size table
Table 13 Exclusion of the selected country groups from the sample
Full size table
Table 14 Effect of exchange rate regimes on business cycle synchronization across time periods
Full size table
Table 15 Robustness to alternative indicators of different variables
Full size table
Table 16 Robustness to alternative indicators: Amplifying effect of other variables
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hou, J., Knaze, J. Exchange Rate Regimes and Business Cycle Synchronization. Open Econ Rev 33, 523–564 (2022). https://doi.org/10.1007/s11079-021-09648-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11079-021-09648-0

Keywords

JEL Codes

Search

Navigation