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Stability or Upheaval? The Currency Composition of International Reserves in the Long Run

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Abstract

The paper analyzes how the role of different national currencies as international reserves was affected by the shift from fixed to flexible exchange rates. It extends data on the currency composition of foreign reserves backward and forward to investigate whether there was a shift in the determinants of the currency composition of international reserves around the breakdown of Bretton Woods. It finds that inertia and policy-credibility effects in international reserve currency choice have become stronger post-Bretton Woods, while network effects appear to have weakened. The paper shows that negative policy interventions designed to discourage international use of a currency have been more effective than positive interventions to encourage its use. These findings speak to the prospects of currencies like the euro and the renminbi seeking to acquire international reserve status and others like the U.S. dollar seeking to preserve it.

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Notes

  1. For early discussions of the euro’s future and a review of the debate by the time of the advent of the single currency, see for example Bergsten (1997), Feldstein (1997) and Portes and Rey (1998). Recent reviews of the prospects for the Chinese renminbi as an international currency include Chinn (2012), Subramanian and Kessler (2012), Eichengreen (2013), Prasad (2014) and Fratzscher and Mehl (2014).

  2. Truman and Wong (2006) describe the available data.

  3. These IMF data, also known as the Currency Composition of Official Foreign Exchange Reserves (COFER) data base, are confidential; the individual country data have been used only by two internal IMF staff studies (Dooley, Lizondo, and Mathieson, 1989, and Eichengreen and Mathieson, 2001).

  4. See for example Eichengreen (1998), Chinn and Frankel (2007 and 2008) and Li and Liu (2008).

  5. A partial exception is Schenk (2010), who assembles data on the share of the dollar, sterling and a residual “other currencies” category for the period 1950–82.

  6. For instance, Heller and Kahn (1978) examined whether there was a change in the demand for international reserves in 1973 due to the change from fixed to floating exchange rates, using data for the period 1964–76. Their results suggest that there was indeed a shift by industrial countries but not by non-oil developing countries. However, Heller and Kahn also stressed that they had a very short period available for formal statistical testing and that their conclusions should at best be regarded as preliminary (see also Crockett, 1978; Saidi, 1981; and Levy, 1983).

  7. Throughout, these are “allocated” foreign exchange reserves; there is also a residual unallocated component, attributable to central banks that decline to report the currency composition of their reserves (including certain major official reserve holders in Asia, which we do not analyze—more on this below).

  8. For part of the period there is in addition a small residual category of “claims in other currencies.” Before 2005 the IMF did not distinguish between reserves in “other currencies” (reserves whose currency of denomination was reported but which was other than one of the currencies distinguished in its reports) and reserves whose currency of denomination was not reported to the IMF. In 2005 the IMF revised its data back to 1994, distinguishing the two types of “others.” However, since we do not have information on the distinction prior to 1994, we do not analyze the “other currencies” category prior or subsequent to this.

  9. See Truman and Wong (2006) and Ouyang and Li (2013), for example. See also Dominguez, Hashimoto, and Ito (2012) for an attempt to estimate valuation effects as determinants of changes in reserve composition in emerging markets in early stages of the global financial crisis.

  10. Countries typically do not publish the composition of their reserve holdings. Short time series have been published by some countries, however (see ECB, 2013).

  11. This is the case of Eurodollar assets, which are included along with U.S.-issued reserve assets denominated in dollars.

  12. See Cairncross and Eichengreen (1981) and Burk and Cairncross (1992).

  13. The impact of the crisis on the euro’s international role is analyzed by ECB (2013).

  14. A number that rose with time, most notably in the 1970s, when the two lines in the figure converge.

  15. Details on these arrangements may be found in Schenk (1994 and 2010).

  16. The dilemma was analogous to that facing twenty-first century emerging markets holding mainly dollars as reserves in periods when questions are raised about the prospective stability of the dollar. Diversifying out of dollars may precipitate the dollar depreciation that portfolio managers fear if it goes too far, too quickly.

  17. See also Krugman (1980 and 1984), Matsuyama, Kiyotaki, and Matsui (1993) and Rey (2001).

  18. We calculate trend appreciation using data from the IMF’s International Financial Statistics.

  19. A different approach is that of Lyons and Moore (2009) who develop a model in which the pattern of currency trade is driven not by merchandise trade but by asset trade and the information it conveys. In their model, if the information available to market participants is insufficiently symmetric, currency pairs never trade directly and an international (vehicle) currency is used instead.

  20. We take data for these variables from the IMF’s International Financial Statistics, Global Financial Data and Fratzscher, Mehl, and Vansteenkiste (2011).

  21. An overview of the resulting data is in the online appendix.

  22. Including an entire vector of year effects would absorb all time series variation common to all currency units and introduce a large number of additional coefficients to be estimated. We therefore included instead a vector of nonoverlapping five-year effects.

  23. Earlier studies for shorter periods have similarly used random country effects (for example, Ouyang and Li, 2013). Estimates obtained with fixed effects yield economically implausible coefficients for the size variable, and are probably distorted by the time fixed effects (insofar as the estimates become close to those obtained with random effects, once we do not include time effects). The Hausman test rejects random effects relative to fixed effects at the 10 percent level of confidence only. We also correct for heteroskedasticity and clustering when computing panel-consistent standard errors. One might also wish to correct for left-censoring of the estimates that include values of zero with Tobit estimates (which also means dropping the correction for heteroskedasticity and clustered heterogeneity, implying inefficient standard errors). We report Tobit estimates in robustness checks, together with system GMM estimates to account for possible endogeneity arising, for example, from the dynamic specification of our model (see Section IV below).

  24. Just as reserves held in other currencies were even smaller throughout the period and are therefore not reported.

  25. This will be evident from the increase in the number of observations; see Table B1 in the online appendix.

  26. Arithmetically, the negative coefficient on the credibility-related exchange rate term for the period before 1973 reflects the fact that sterling depreciated on two occasions in this period, when the share of sterling reserves was relatively high, and that the deutschmark appreciated in the early 1970s, when the share of deutschmark reserves was low.

  27. Table B2 reports results with missing observations and Table B3 without. The main difference is that the interaction term for policy credibility and the post-1973 period dummy in column 4 is now insignificantly different from zero. That this result changes is not surprising, since allowing for exchange rate effects in the dependent variable creates the potential for spurious correlation with the exchange rate when the latter is included as an independent variable. We are therefore more inclined to trust the estimates of credibility effects in Table 1.

  28. Note that one needs to use unstandardized explanatory variables to compare the magnitude of our estimates with theirs. We also compute the exchange rate as SDRs per national currency unit, whereas Chinn and Frankel compute it as national currency units per SDR, which explains the difference in the reported sign of the effect.

  29. According to a Chow test.

  30. Our most extensive discussion of the “old” and “new” views is in Chiţu, Eichengreen, and Mehl (2014). In practice, the large coefficient on the lagged dependent variable (evidence of significant—but not insurmountable—persistence effects) may reflect the obstacles to the quick liquidation of sterling reserves discussed in Section II.

  31. Open standards, such as Linux, Apache or TeX, to take a few examples, are interoperable by design, with no specific cost or benefit for any user (aka foreign reserve holder) for selecting one product (aka unit) over another on the basis of standardized features. The vendors’ (aka reserve currency issuers) products (aka units) compete on an array of factors, such as performance, price, user-friendliness, and so on (aka reliability as a store of value, liquidity, and so on) while maintaining users’ data intact and transferable (aka foreign reserve holdings in a particular unit) even if the latter decide to switch to a competing product (aka to an another unit). Where the old view emphasized network effects, the new view emphasizes open systems, as just noted. Where the old view placed great weight on network effects, first-mover advantage and lock-in, the new view posits that interchangeability costs are not that high and first-mover advantage can be overcome relatively quickly.

  32. The Gold Pool is the subject of Eichengreen (2007, Chapter 3).

  33. One indication is that there is a sharp local peak in the number of books citing Bretton Woods, according to Google’s Ngram Viewer around 1966–68. The year 1968 was in turn a key year in negotiations to create Special Drawing Rights as a possible alternative to dollar reserves; an amendment to this effect to the IMF’s Articles of Agreement was drafted and ratified by a growing number of countries in the course of the year, although the amendment only came into effect in 1969 and actual SDRs were only issued (in small amounts) starting in 1970.

  34. Note also that dividing the sample in 1960 leaves too few observations for meaningful estimates for the preceding period.

  35. As aforementioned, see for example Frenkel (1978) and Heller and Kahn (1978).

  36. See Tables B4–B10 in the online appendix.

  37. Foreign exchange turnover was taken from the BIS Triennial Surveys of global foreign exchange market activity back to 1986 as well as from G30 and national central bank reports for the period 1973-86, as in Chinn and Frankel (2007 and 2008). Following the practice of these other authors they were linearly interpolated to annual data.

  38. Chen, Peng, and Shu (2009) and Huang, Daili, and Gang (2014) use stock market capitalization as a measure of liquidity and financial development and find that it is economically important and statistically significant in the recent period. A further alternative would be to use bond market capitalization as a metric, but data then would have an insufficiently long time span: BIS data usually go back to the mid-1990s and those from Beck, Demirgüç-Kunt, and Levine (2009) to the late 1980s.

  39. We used the Rajan and Zingales (2003) data for the period 1950–99 (linearly interpolated to annual data) and the data in Beck, Demirgüç-Kunt, and Levine (2009) for the period 1999–2013. The data on nominal GDP were taken from the IMF’s International Financial Statistics.

  40. Another alternative still is to substitute the log level of market capitalization for country size. In this case, stock market capitalization enters positively (but insignificantly) before 1973, while the interaction term for the post-1973 is negative (but also insignificant). This echoes the pattern found in the baseline model for economic size. Hence it is hard to know whether results obtained using this specification are in fact capturing the effects of market development and liquidity, or those of country size, with which market capitalization is correlated. This causes us to prefer the results shown in Table 1 and discussed in the text.

  41. The time-varying betas were estimated as five-year rolling beta estimates where the dependant variable are log currency i returns and the independent variable is the weighted average of the log returns in all other currencies of our sample (a proxy for world currency returns minus currency i itself to avoid spurious correlations), and where the weights are time-varying country shares in world exports in year t.

  42. One exception was that the effect for the credibility of policies measured by inflation rates was found to have weakened post-1973 (not increased). This is likely to reflect the correlation between relatively high British inflation and the falling share of sterling in international reserves over the earlier period. U.S. inflation in the later period, evidently, had a smaller and less significant effect, on the other hand.

  43. As noted before, one then has to forego robust standard errors adjusted for clustering.

  44. The reason is that we have no right/left-censored variables, in fact, so that Tobit estimation is actually not needed. When we obtain estimates without missing observations, the standard errors become quite large, however, which might be due to the fact that they are not robust to heteroskedasticity.

  45. In constructing the instrument matrix, we treated persistence, size, and credibility as endogenous and the year dummies as exogenous. The very high p-value of the Hansen statistic (which overwhelmingly suggests that the instruments are orthogonal) likely indicates that the number of instruments remains still very large relative to the number of currency units despite the Roodman (2009) correction. Moreover, there is evidence of significant dynamic effects at only the 25 percent level of confidence, as measured in the first-order serial correlation of the first-differenced disturbances of the estimated models (and evidence of second-order serial correlation in two specifications).

  46. Although the change was not statistically significant.

  47. Where the logistic transformation is defined as log[share/(1-share)].

  48. It could be argued that a logistic transformation of the dependent variable is not practical here because such a nonlinear transformation may lead to inconsistent estimates (especially when reserve currency shares are close or equal to zero). See Santos Silva and Tenreyro (2006) for further details.

  49. This may reflect the fact that we could not adjust the dependent variable for exchange rate valuation effects in the absence of information on the currency composition of non-U.S.-dollar reserve holdings. These results are available from the authors on request.

  50. We are not aware of similar measures adopted by other countries in our data set.

  51. The indices run from 0 (financial autarky) to 100 (complete financial openness) and are available for all the currencies in our sample.

  52. In general, the effect of unsupportive official positions and unsupportive exchange rate regime-related initiatives is economically smaller than that of other unsupportive measures.

  53. As aforementioned these estimates are obtained with currency shares already purged of exchange rate valuation effects.

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Supplementary information accompanies this article on the IMF Economic Review website (www.palgrave-journals.com/imfer)

*Barry Eichengreen is the George C. Pardee and Helen N. Pardee Professor of Economics and Professor of Political Science at the University of California, Berkeley, where he has taught since 1987. He is an NBER and CEPR Research Fellow and a fellow of the American Academy of Arts and Sciences. His research interests are broad-ranging, and include exchange rates and capital flows, the Great Depression, European and Asian integration and IMF policy. Livia Chiţu is an economist at the European Central Bank, where she works on issues related to the international role of currencies, the international financial architecture, the IMF and dollarization/euroization. She is a graduate from the University of Toulouse and the Academy of Economic Studies in Bucharest and a Ph.D. candidate at Paris School of Economics. Arnaud Mehl is principal economist at the European Central Bank, where he works on issues related to the international monetary system and global exchange rates. He is a graduate from Sciences Po Paris and ESCP Europe, a former visiting student at Oxford University and holds a Ph.D. in economics from University Paris Dauphine. His main area of specialization is international finance and economic history. The authors are grateful to the editor-in-chief (Pierre-Olivier Gourinchas), the associate editor (Pau Rabanal), two anonymous referees, Menzie Chinn, Jeffrey Frankel, and Morten Ravn for helpful comments and suggestions.

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Eichengreen, B., Chiţu, L. & Mehl, A. Stability or Upheaval? The Currency Composition of International Reserves in the Long Run. IMF Econ Rev 64, 354–380 (2016). https://doi.org/10.1057/imfer.2015.19

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