Checking Out: Exits from Currency Unions Andrew K. Rose* Draft: December 15, 2006 Preliminary; Comments Welcome. Abstract This paper studies the characteristics of departures from monetary unions. During the post-war period, almost seventy distinct countries or territories have left a currency union, while over sixty have remained continuously in currency unions. I compare countries leaving currency unions to those remaining within them, and find that leavers tend to be larger, richer, and more democratic; they also tend to have higher inflation. However, there are typically no sharp macroeconomic movements before, during, or after exits. Keywords: empirical, data, panel, monetary, country, probit, statistic. JEL Classification Numbers: E42, E58 Contact: Andrew K. Rose, Haas School of Business, University of California, Berkeley, CA 94720-1900 Tel: (510) 642-6609 Fax: (510) 642-4700 E-mail: arose@haas.berkeley.edu URL: http://faculty.haas.berkeley.edu/arose * B.T. Rocca Jr. Professor of International Business, Economic Analysis and Policy Group, Haas School of Business at the University of California, Berkeley, Visiting Professor at the National University of Singapore, NBER Research Associate, and CEPR Research Fellow. I wrote this paper while I visited NUS and the Monetary Authority of Singapore, whom I thank for hospitality. The data set, key output, and a current version of the paper are available at my website. Introduction In this short paper, I examine the gross features of countries exiting currency unions. Since the end of the Second World War, 69 countries, territories, or other entities (hereafter “countries”) have left currency unions. I compare these countries to the 61 entities that remained continuously within currency unions during the same period of time. I find only a few macroeconomic differences between countries remaining in and leaving currency unions. Exiters tend to be larger, richer, and more democratic than stayers. But these differences tend to be persistent and sluggish; there are few dramatic macroeconomic events around currency union exits. The “Countries” of Interest I start my investigation by considering all 229 entities with IFS “country codes.” This includes: independent sovereign states (such as the United States, IFS code 111); colonies (such as the Cayman Islands, code 377), special administrative regions (e.g., Hong Kong, now a part of China, code 532), overseas department (e.g., Martinique, code 349), territories (e.g., Guam, code 829), and other entities (the West Bank and Gaza strip is not internationally recognized as a de jure part of any country, code 487). I refer below to all as “countries” for convenience. I then check each of these countries to see if they are or have been in a currency union since the end of WWII. For information on monetary unions, I follow Glick and Rose (2002). By “currency union” I mean essentially that a country’s money was interchangeable with that of another country at a 1:1 par for an extended period of time, so that there was no need to convert prices when trading between a pair of countries. Hard fixes of exchange rates, such as those of Hong Kong, Estonia, or Denmark, do not qualify as currency unions, even if they are currency 1 boards. The basic source for currency union data is the IMF’s Schedule of Par Values and issues of the IMF’s Annual Report on Exchange Rate Arrangements and Exchange Restrictions, supplemented with information from annual copies of The Statesman’s Yearbook. I ignore political dissolutions (e.g., of the Soviet Union and Yugoslavia) and unions (e.g., Germany and Yemen). I drop countries never in currency unions (including currency union “anchors” such as the United States). Since World War II, 61 countries have continuously been members of currency unions; their names are tabulated in Table A1.1 Another 69 countries left currency unions during this period of time; their names are tabulated in Table A2, along with the year of departure and the anchor country or multilateral monetary union they left.2 Potential Reasons for Currency Union Exit One might think that there is a typical scenario for a country leaving a currency union; it acquires its own money concurrently with its own flag, national anthem, and other trappings of political sovereignty. It is true that 24 currency union members are dependencies, such as Aruba, the Channel Islands, and Greenland. However, 37 independent countries have remained continuously in currency unions, including Cameroon, Luxembourg, and Panama. Most importantly, of the (over 60) countries that have left currency unions, the median delay was seven years after independence. Further, over a tenth left their currency unions before independence and over twenty waited at least a decade after independence before exiting. Succinctly, the tie between political and monetary independence is weak. 1 A few territories involved in currency unions are too small even to have IFS country codes, such as the Holy See, and Puerto Rico. 2 Parenthetically, I note that 19 countries have entered currency unions post-war. This is too small a number to study sensibly with statistical techniques, especially given that a dozen of them are associated with EMU and thus highly dependent. 2 Why might a country leave a currency union, if not as a demonstration of political sovereignty? That is, which macroeconomic characteristics should one examine around the time of currency union dissolutions? I look to standard theory to guide my choice. Mundell’s (1961) optimum currency area theory points to the difficulties of handling asymmetric cyclic shocks that affect one member of a currency union but not another. Since such business-cycle shocks can potentially be handled by fiscal policy, it is natural to examine the scope of government spending in the economy. More open economies benefit more from currency unions which lower the transactions costs associated with trade, so that it is also natural to look at the importance of trade in the economy. Richer countries and larger countries can more easily handle the expense associated with creating and operating a monetary institution; Alesina and Barro (2002). Thus the size and income of a country are of relevance. Since countries that leave currency unions have to establish a new monetary framework, I also examine their money growth and inflation rates. The Data Set The single biggest issue confronting the researcher interested in such issues is that of data availability. There are few broad political or economic data sets that cover the relevant period of time for members of currency unions. A number of unions dissolved either early in the postwar period; data is often not collected for the constituents of currency unions. Accordingly, while there have been a few studies of currency union dissolutions in the literature, these are essentially case studies (e.g., Bordo and Jonung, 1999). However, my interest is in creating a more comprehensive overview of economies around the time of currency union exit. In particular, I am interested in macroeconomic features of countries before, during, and after they leave 3 currency unions. I also wish to compare these characteristics to those for continuing members of currency unions, a natural comparison group. Thus, I need a data set that covers a long span of data over time, for a broad range of countries including many too small to be in standard data sets.3 I use the popular Penn World Tables (version 6.2) for series on: population, real GDP per capita, openness (exports plus imports), direct government spending and investment. The latter three are expressed as ratios to GDP, and the variables are available, with gaps, from 1950 through 2004. I also use the World Bank’s World Development Indicators for series on these variables, as well as government budget balance, inflation, money, and the trade balance; these series only go as far back as 1960. The International Monetary Fund’s International Financial Statistics provides series as far back as 1948 on CPI inflation, the budget balance, money growth, and the national accounts. Finally, I use the polity series from the University of Maryland’s Center for International Development and Conflict. I am left with a data set that covers 130 countries from 1946 through 2005, though there are many gaps. The data set is necessarily thin, simply because so many observations are missing for current or former currency union members.4 Descriptive statistics on the variables of interest are provided in Table 1. These are split into two tables: the one on the right covers the countries that left currency unions (labeled “Exits”) while that on the left covers the countries that were continuous members of currency unions (“Cont.”). I provide the sample means, standard deviations and number of observations 3 This unilateral approach makes much more sense than that of Nitsch (2004), who borrowed my bilateral data sets to investigate the same question. 4 I sometimes have series that represent the same concept from different sources. For instance, population data is available from PWT, WDI, and IFS. These are extremely highly correlated but have different samples. In such cases, I use PWT as the default series, filling in with WDI when the PWT is missing, and IFS when both other series are missing. 4 for twelve variables of interest. These are: 1) an “Out/In” dummy variable which is 1 for countries outside currency unions, and 0 for countries still inside; 2) an “Independent” dummy variable which is 1 for independent countries and 0 for dependencies; 3) the natural logarithm of population; 4) log real GDP per capita; 5) the percentage of GDP spent directly by the government; 6) investment as a percentage of GDP; 7) trade as a percentage of GDP; 8) the trade imbalance as a percentage of GDP; 9) the government budget imbalance as a percentage of GDP (positive for surplus); 10) the inflation rate; 11) the percentage growth of M1; and 12) Polity (which ranges from -10 for strongly autocratic states to +10 for strongly democratic states). Exiting countries are larger than those staying in currency unions, are more likely to be democratic and independent, and have higher inflation and money growth. An Event Study I begin by taking an event-study approach to the data. This provides a comprehensive look at the dynamic behavior of the variables of interest before, during, and after departures from currency unions. Figure 1 illustrates the behavior of the key variables around the time of currency union exits, comparing them with control group of (country-period) observations for countries remaining continuously in currency unions. Each of the nine small graphs portrays a different macroeconomic variable. The top-left panel, for example, shows the natural logarithm of real GDP per capita (measured in international dollars), beginning three years before currency union exit, continuing through the actual event (marked with a vertical line) and ending three years after the currency union dissolution. Along with the average values (marked with circles), a plus/minus two standard-deviation confidence interval is also provided to illustrate the extent of 5 cross-country variation around the mean. To aid comparison, I also show (with a horizontal line) the average log real income for currency union “stayers.” Thus, the top-left panel shows that real GDP per capita was both significantly lower for currency union exiters than for stayers, in both the economic and statistical senses. It is also striking that there are no important cyclic fluctuations of real income around the time of currency union exit, although these are the focus of both Mundell’s theory and much recent work (e.g., Alesina, Barro and Tenreyro, 2002). Countries leaving currency unions tend to have smaller government and international sectors than those staying inside currency unions. Since this implies that these countries have less fiscal capacity to respond to asymmetric shocks and fewer benefits from international trade, both features are consistent with standard optimum currency area theory. Exiters have similar investment shares and budget imbalances. Trade imbalances are smaller for exiters than stayers, and exiters tend to be less autocratic. Inflation is understandably volatile around the time of currency union dissolution, but not significantly different for stayers and exiters; the same is true of money growth. But perhaps the most striking feature of the data is the absence of volatility. In general, there are remarkably few signs of dramatic macroeconomic events either preceding or following currency union dissolutions. A Statistical Approach The event study of the preceding section provides an interesting picture of the (lack of) macroeconomic dynamics around currency union departures. However, this comes at a cost, since event-studies are intrinsically univariate in nature; one examines the variables one by one, in isolation from each other. Accordingly, I now proceed to a statistical approach, remaining non-structural in nature. 6 I begin by estimating a set of bivariate probit estimates, which examine the individual effect of the key variables on the probability of being inside or outside a currency union. The dependent variable is a binary indicator which is 0 for currency union members and 1 for countries that have left a currency union.5 Each row of Table 2 presents the coefficient of a probit regression of this regressand on a single variable of interest. As expected, countries are more likely to leave (or have left) currency unions if they are independent or large. Their government sectors are also larger, (manifestly the growth in government spending visible in Figure 1 continues long after exit), and trade is less important. Inflation and money growth are also higher for exiters than for stayers. These results are interesting but only suggestive since they are bivariate. Accordingly, I pursue a multivariate approach in Table 3a, by simply adding all the variables of interest to the probit regression simultaneously. This more complete look at the data comes at the cost of a reduced sample size. When one considers all the variables simultaneously, only five show through with sizable effects. The size and income of the country are both strongly positively associated with monetary independence, consistent with Alesina and Barro (2002). More democratic countries and those with larger government sectors are systematically more likely to have their own currencies. Finally, inflation is higher for with currency union exiters than stayers, though the causality here is ambiguous. High inflation countries may find it more difficult to remain with currency unions, as their competitiveness cannot be regained through a nominal devaluation; but countries with their own money may simply have systematically less disciplined monetary institutions and accordingly higher inflation. 5 Thus, countries that are continuous members of currency unions (like Panama) are 0 throughout the period, while exiters like Algeria are 0 before they exit and 1 during and after the year of exit from monetary union. 7 More democratic countries and those with larger government sectors may find it easier to asymmetric macroeconomic shocks, but are less likely to remain in currency unions. This is inconsistent with standard optimum currency area theory, as is the absence of any strong tie between the importance of trade and currency union membership. But these negative results should not be over-interpreted, since the model fits the data poorly, with a quasi-R2 of less than .2. The poor fit is verified by the frequency table displayed in Table 3b which compares actual currency union members (and non-members) to those predicted by the model to be members (and non-members); this shows large off-diagonal elements. That is, from the universe of countries that started off inside currency unions, it is difficult to determine which countries leave (and when). The remainder of Table 3a shows that the key results of the default model are reasonably insensitive to a number of perturbations of the default statistical model. I perform seven robustness checks. First, I drop the variables that are insignificant in the default specification. Then I add a comprehensive set of year-specific fixed effects. Then I drop observations from different regions: first, all African countries and then separately, all countries from Latin America and the Caribbean. Next, I drop observations from different periods of time: first, data after 1989, and then observations before 1970. Finally I use the one-year lead of the regressand, so that the equation is predictive. The five variables tend to remain statistically significant and consistently signed across the variations. Further, the goodness of fit remains poor (except for the small sample when the African countries are dropped). In Table A3, I use the same statistical model, but only on a purely cross-sectional basis. These equations fit the data poorly, given the small sample sizes. Essentially no variables are 8 statistically significant at conventional levels. I conclude that the model fails dismally to predict currency union membership on a cross-sectional basis. Conclusion In this short paper, I take a comprehensive look at postwar currency union exits, using as many such events as possible. My universe of countries is potentially large; I include 61 countries and territories that have remained in currency unions continuously since WWII and another 69 that left a currency union during the same period of time. The scope of this project is its advantage; the cost is that I am forced to restrict my attention to those countries with data that is consistent and comparable across time and countries, and there are many gaps in the data set. I find that countries leaving currency unions tend to be larger, richer, and more democratic; they also tend to experience somewhat higher inflation. Most strikingly, there is remarkably little macroeconomic volatility around the time of currency union dissolutions, and only a poor linkage between monetary and political independence. Indeed, aggregate macroeconomic features of the economy do a poor job in predicting currency union exits. I conclude that there is plenty of room for future research in this area. 9 References Alesina, Alberto and Robert J. Barro (2002) “Currency Unions” Quarterly Journal of Economics CXVII, 409-436. Alesina, Alberto, Robert J. Barro, and Silvana Tenreyro (2002) “Optimal Currency Areas” NBER Macroeconomics Annual (Gertler and Rogoff editors, MIT Press). Bordo, Michael D. and Lars Jonung (1999) “The Future of EMU: What Does the History of Monetary Unions Tell Us?” NBER Working Paper No. 7365. Glick, Reuven and Andrew K. Rose (2002) “Does A Currency Union Affect Trade? The TimeSeries Evidence” European Economic Review 46(6 June), 1125-1151. Mundell, Robert A. (1961) “A Theory of Optimum Currency Areas” American Economic Review 51, 657-665. Nitsch, Volker (2004) “Have a Break, Have a … National Currency: When do Monetary Unions Fall Apart?” CESIfo Working Paper No. 1113. 10 Table 1: Descriptive Statistics Obs. Mean Currency Union: Cont. Cont. 3660 n/a Out/In 3660 .39 Independent 2197 5.69 Log(Population) 1169 8.05 Log GDP p/c 1265 24.3 Gov’t Spending, %GDP 1241 13.1 Investment, %GDP 1276 99.8 Trade, %GDP 1080 -12.0 Trade Imbalance, %GDP -2.22 Budget Imbalance, %GDP 403 881 5.52 Inflation 951 11.7 M1 growth 695 -4.52 Polity Std. Dev Cont. n/a .49 2.06 1.19 13.8 9.06 48.0 23.8 4.59 7.01 18.1 4.99 Obs. Mean Std. Dev. Exits Exits Exits 4140 .60 .49 4140 .69 .46 3676 7.73 1.88 2540 7.89 1.08 2968 20.9 12.2 3021 14.2 9.57 3023 78.1 52.3 2599 -6.46 15.5 1425 -3.96 7.86 2227 32.7 527 2318 25.1 172 2307 -1.61 6.99 “Cont” denotes continuous membership in currency union; “Exits” denotes countries that departed from a currency union in the sample. 130 countries, 1946-2005. Table 2: Bivariate Probit Estimation Coeff. Obs. 1.72** 7800 Independent (.04) .29** 5873 Log (.01) Population .04* 3709 Log GDP (.02) Per capita .005** 4233 Gov’t Spending (.002) (% GDP) .004* 4262 Investment (.002) (% GDP) -.0022** 4299 Trade (.0003) (% GDP) .004** 3679 Trade Imbalance (.001) (% GDP) 1828 Budget Imbalance -.019** (.004) (% GDP) .033** 3108 Inflation (.002) .009** 3269 M1 (.001) growth .017** 3002 Polity (.004) Standard Errors in parentheses. Intercepts included but not recorded. Regressand is a 0 for (country*year) currency union observation and 1 for non-currency union observations. One (two) asterisk(s) indicates significance at .05 (.01). 11 Table 3a: Multivariate Panel Probit Estimation Default Independent Log Population Log GDP per capita Gov’t Spending (%GDP) Investment (%GDP) Trade (%GDP) Trade Imbalance (%GDP) Budget Balance (%GDP) Inflation M1 growth Polity Pseudo R2 Observations -.75 (.68) .33** (.04) .42** (.06) .016** (.005) .000 (.006) -.001 (.001) .009* (.004) .001 (.008) .034** (.005) .002 (.002) .027** (.006) .16 1195 Variant .29** (.03) .44** (.04) .015** (.003) .041** (.004) .030** (.005) .18 1954 Time Effects -.90 (.78) .27** (.05) .33** (.06) .011* (.005) .017* (.007) -.004** (.001) .014** (.004) -.002 (.008) .032** (.008) .001 (.002) .039** (.007) .20 1158 Drop Africa n/a .69** (.08) 1.34** (.14) .12** (.02) .004 (.010) .003 (.002) -.025* (.010) .034* (.016) .036** (.016) .006 (.006) .007 (.012) .46 549 Drop Latins -.43 (.67) .31** (.05) .45** (.06) .006 (.005) -.003 (.007) -.000 (.001) .009* (.004) .003 (.009) .027** (.005) .002 (.002) .027** (.007) .15 1041 Pre1990 -.82 (.62) .20** (.06) .14 (.08) .018** (.006) .022* (.009) -.002 (.002) .011* (.005) -.001 (.009) .037** (.007) .004 (.004) .012 (.008) .13 717 Post1969 n/a .29** (.05) .38** (.06) .014** (.005) .001 (.007) -.002 (.001) .011** (.004) .001 (.008) .026** (.005) .001 (.002) .050** (.007) .16 1047 Standard Errors in parentheses. Intercepts included but not recorded. Regressand is a 0 for (country*year) currency union observation and 1 for non-currency union observations. One (two) asterisk(s) indicates significance at .05 (.01). Table 3b: Frequency Distribution for Default Model Actual: In CU Actual: Outside CU Total 145 (12%) 104 (9%) 249 (21%) Predicted inside CU 232 (19%) 714 (60%) 946 (79%) Predicted outside CU 377 (32%) 818 (68%) 1195 Total 12 LeadLHS -.69 (.68) .33** (.04) .41** (.06) .015* (.005) .002 (.006) -.002 (.001) .009* (.004) .001 (.008) .034** (.005) .003 (.003) .029** (.006) .16 1195 Table A1: Continuous Currency Union Members American Samoa Andorra Antigua & Barbuda Aruba Benin Bermuda Brunei Darussalam Burkina Faso Central African Rep. Chad Cook Islands Cote d'Ivoire Faeroe Islands Falklands French Polynesia Gabon Greenland Grenada Guam Guernsey Kiribati Lesotho Liechtenstein Luxembourg Marshall Islands Martinique Monaco Montserrat Nauru New Caledonia Niue Palau San Marino Senegal St. Kitts St. Lucia Swaziland Togo Tuvalu Virgin Islands, British Wallis & Futuna 13 Anguilla Bahamas Bhutan Cameroon Congo Dominica French Guiana Gibraltar Guadeloupe Jersey Liberia Man, Isle of Micronesia Namibia Niger Panama St. Helena St. Vincent & Grens. Turks and Caicos Islands Wake Islands Table A2: Departures from Currency Unions Mauritania Country Year Anchor Algeria 1969 France Mauritius Angola 1976 Portugal Morocco Bahrain 1973 India Mozambique Bangladesh 1965 India Myanmar (Burma) Barbados 1975 ECCA New Zealand Botswana 1977 S Africa Nigeria Burundi 1964 Belgium Oman Cape Verde 1977 Portugal Pakistan Caymans 1972 Jamaica Qatar Comoros 1994 CFA Reunion Cuba 1950 USA Rwanda Cyprus 1972 UK Sao Tome and Principe Djibouti 1949 CFA Seychelles Dominican Rep 1985 USA Sierra Leone Equatorial Guinea 1969 Spain Singapore Gambia 1971 UK Solomon Islands Ghana 1965 UK Somalia Guatemala 1986 USA South Africa Guinea 1969 CFA South Yemen Guinea-Bissau 1976 Portugal Sri Lanka Guyana 1971 ECCA St. Pierre and Miquelon Iraq 1967 UK Sudan Ireland 1979 UK Suriname Israel 1954 UK Tanzania Jamaica 1954 UK Tonga Jordan 1967 UK Trinidad & Tobago Kenya 1978 EACB Tunisia Kuwait 1967 UK Uganda Libya 1967 UK Vanuatu Madagascar 1982 CFA Western Samoa Malawi 1971 CACB Yemen, North Maldives 1967 India Zaire Mali 1962 CFA Zambia Malta 1971 UK Zimbabwe 14 1973 1967 1959 1977 1967 1967 1967 1975 1949 1959 1976 1966 1977 1967 1965 1967 1979 1971 1961 1972 1966 1976 1956 1994 1978 1991 1976 1958 1978 1981 1967 1971 1961 1971 1971 CFA India France Portugal India UK UK UK UK India CFA Belgium Portugal India UK UK Australia EACB UK EACB India CFA Egypt Neth. Ant. EACB Australia ECCA France EACB CFP NZ EACB Belgium CACB CACB Table A3: Multivariate Cross-Section Probit Estimation 1970 1980 1990 2000 1.37 -.52 1.62 1.12 Log (1.24) (.52) (1.00) (.63) Population -.05 .07 .02 1.18 Log GDP (1.30) (.52) (.56) (.74) per capita .04 -.04 .06 -.01 Gov’t Spending (.10) (.04) (.08) (.04) (% GDP) -.05 .18 -.11 -.04 Investment (.08) (.11) (.09) (.07) (% GDP) .01 -.02 .02 -.01 Trade (.02) (.02) (.02) (.01) (% GDP) -.00 .03 .01 Trade Imbalance -.13 (.14) (.02) (.03) (.04) (% GDP) .09 -.00 -.17 .10 Budget Balance (.20) (.04) (.15) (.15) (% GDP) -.24 -.02 .34 .03 Inflation (.36) (.04) (.20) (.06) .02 .04 -.01 -.02 M1 (.10) (.04) (.01) (.04) growth .14 .06 .16 .02 Polity (.17) (.06) (.09) (.06) .29 .23 .53 .48 Pseudo R2 20 30 39 31 Observations Standard Errors in parentheses. Intercepts included but not recorded. Regressand is a 0 for (country*year) currency union observation and 1 for non-currency union observations. 15 8.2 25 18 7.8 20 14 15 7.4 -3 0 45 obs. Log Real GDP p/c 10 -3 3 0 54 obs. -3 3 Gov't Spending (% GDP) 5 0 80 -5 -4 -15 -3 0 55 obs. Trade (% GDP) -8 -3 3 0 47 obs. 0 24 obs. 3 Budget Imbalance/Y 2 30 20 20 -3 3 Trade Imbalance (% GDP) 40 3 Investment (% GDP) 100 60 0 55 obs. -2 10 0 0 -3 0 33 obs. Inflation 3 -6 -3 0 43 obs. 3 -3 M1 Growth Samples vary; Means for Continuous CU Members Marked Movements around Currency Union Exits Figure 1: Event Study for Departures from Monetary Unions 16 0 47 obs. Polity 3