Abstract
Summary
Summary
New Member States (NMS)2 have considerable leeway over the timing of euro adoption. Even though the NMS have committed to eventually joining the euro area in their accession treaties, key steps to initiate adoption—such as harmonizing the legal framework with euro area standards, or applying for ERM2 entry—remain under sovereign control. Conversely, the euro area institutions have substantial discretion in admitting countries to ERM2—a pre-condition to euro adoption.
The NMS-6 maintain different monetary regimes. Bulgaria and Croatia have tied their currencies to the euro, while the Czech Republic, Hungary, Poland, and Romania target inflation and allow exchange rates to float.
The euro area crisis has reduced some attractions associated with joining the euro. While countries adopting the euro in the 2000s benefited from a sizeable premium as regards investors’ perception of credit risk, this premium has mostly vanished with the euro crisis. This said, euro adoption continues to hold advantages for highly euroized economies.
For NMS that have maintained monetary autonomy, this has been helpful in containing macro-economic imbalances, suggesting that, for them, ceding autonomy could be costly. Monetary tightening and exchange rate appreciation helped contain credit booms in the mid-2000s. After the outbreak of the 2008-09 financial crisis, monetary easing supported domestic demand. More recently, it has helped offset imported disinflationary pressures.
The trade-offs associated with euro adoption present themselves differently for the NMS-6, depending on their monetary regimes. For floaters, key issues are the extent to which monetary autonomy can be replaced by instruments such as macro-prudential tools and fiscal policy, and the scope for internal adjustment in the euro area. For peggers, the question is to what extent they can continue to use macro-prudential and other regulatory tools after adopting the euro.
For many NMS-6, uncertainty about the euro area’s evolving institutional framework provides a rationale to wait for final outcomes before taking an irreversible adoption decision.
A. European Integration and Euro Adoption
1. Euro adoption forms the endpoint of monetary integration in the EU.
In their EU accession treaties, the NMS-6 committed to adopting the euro “once the necessary conditions are fulfilled.3 Parallel biannual reports by the European Commission (EC) and the European Central Bank (ECB) assess the readiness of non-euro area EU member states to join. In the latest reports from June 2014, no NMS-6 fulfills all adoption criteria, hence, none is assessed as ready to join the euro at this stage.4
The NMS-6 have considerable leeway over the timing of euro adoption. Especially two adoption criteria—harmonization of the legal framework with euro area standards and joining the European Exchange Rate Mechanism (ERM2)—require a sovereign decision. At the same time, the euro area institutions have also substantial discretion in the euro adoption process, especially as regards admitting countries to ERM2.
2. Since 2004—when the first Central and Eastern European countries joined the EU—five NMS have adopted the euro: Slovenia, the Slovak Republic, and the Baltic countries. While in the Baltics, euro adoption followed many years of unilateral hard pegs to the euro, Slovenia and the Slovak Republic maintained monetary autonomy until shortly before euro adoption. At the same time, new countries have joined the EU in the past decade—Bulgaria, Romania, Croatia—and now face the issue of euro adoption.
3. The NMS-6 that have not yet adopted the euro maintain fairly different monetary regimes and strategies.
Bulgaria and Croatia have tied their currencies to the euro: the Bulgarian lev by means of a currency board, the Croatian kuna in the form of a tightly managed quasi-peg. In both countries, the exchange rate anchor was introduced in the mid-1990s to combat hyper-inflation (in Croatia in the context of the dissolution of former Yugoslavia). Thus, Bulgaria’s and Croatia’s currency regimes mimic many features of euro adoption already.
By contrast, central banks in the Czech Republic, Hungary, Poland, and Romania target inflation and, correspondingly, have in general allowed exchange rates to float—a policy framework that spread in the region with the Czech Republic’s adoption of inflation targeting in 1997. In Hungary and Romania, central banks have at times carried out significant interventions in foreign exchange markets, arguably to prevent the revaluation of foreign currency denominated loans in case of excessive exchange rate volatility. As a result, IMF (2014) classifies the Hungarian forint and the Romanian leu as “floating”, while the Polish zloty is classified as “free floating.” The Czech koruna is classified as “other managed arrangement”, reflecting recent currency interventions in the context of unconventional monetary policy at the zero interest bound. Until 2013, however—i.e., in the period covered by the empirical analysis of this paper—the Czech koruna was classified as “free floating”.
New Member States - Currency Arrangements
New Member States - Currency Arrangements
| EU Accession | Currency | Exchange rate regime classification (IMF, 2014) | Earlier regimes | |
|---|---|---|---|---|
| Bulgaria | 2007 | Lev | Hard peg - currency board | Float until 1997. Currency board adopted in response to hyperinflation. |
| Croatia | 2013 | Kuna | Soft peg - crawl-like arrangement | Dinar until 1994, hyperinflation. Soft peg to deutsche mark until euro introduction. |
| Czech Republic | 2004 | Koruna | Other managed arrangement | Peg to dollar/currency basked until 1997. Inflation targeting; free float until 2013. |
| Hungary | 2004 | Forint | Floating - inflation targeting | Various pegs and crawling pegs until 2008 with increasingly wide bands (15% 2001–08). |
| Poland | 2004 | Złoty | Free floating - inflation targeting | Various pegs and crawling pegs until 2000. |
| Romania | 2007 | Leu | Floating - inflation targeting | Monetary based targeting with managed float until 2005. Abandoned amid high inflation. |
| Estonia | 2004 | Euro (since 2011) | … | Pegged to deutsche mark/euro (currency board). |
| Latvia | 2004 | Euro (since 2014) | … | Pegged to SDR 1994–2004, pegged to euro 2004–2014. |
| Lithuania | 2004 | Euro (since 2015) | … | Pegged to dollar 1994–2002, pegged to euro 2002–2014 (currency board). |
| Slovak Republic | 2004 | Euro (since 2009) | … | Float until 2004. Float with a 15% band during ERM II (2005–08), repeated parity adjustments. |
| Slovenia | 2004 | Euro (since 2007) | … | Float until 2004. Pegged to euro during ERM II 2004–06. |
New Member States - Currency Arrangements
| EU Accession | Currency | Exchange rate regime classification (IMF, 2014) | Earlier regimes | |
|---|---|---|---|---|
| Bulgaria | 2007 | Lev | Hard peg - currency board | Float until 1997. Currency board adopted in response to hyperinflation. |
| Croatia | 2013 | Kuna | Soft peg - crawl-like arrangement | Dinar until 1994, hyperinflation. Soft peg to deutsche mark until euro introduction. |
| Czech Republic | 2004 | Koruna | Other managed arrangement | Peg to dollar/currency basked until 1997. Inflation targeting; free float until 2013. |
| Hungary | 2004 | Forint | Floating - inflation targeting | Various pegs and crawling pegs until 2008 with increasingly wide bands (15% 2001–08). |
| Poland | 2004 | Złoty | Free floating - inflation targeting | Various pegs and crawling pegs until 2000. |
| Romania | 2007 | Leu | Floating - inflation targeting | Monetary based targeting with managed float until 2005. Abandoned amid high inflation. |
| Estonia | 2004 | Euro (since 2011) | … | Pegged to deutsche mark/euro (currency board). |
| Latvia | 2004 | Euro (since 2014) | … | Pegged to SDR 1994–2004, pegged to euro 2004–2014. |
| Lithuania | 2004 | Euro (since 2015) | … | Pegged to dollar 1994–2002, pegged to euro 2002–2014 (currency board). |
| Slovak Republic | 2004 | Euro (since 2009) | … | Float until 2004. Float with a 15% band during ERM II (2005–08), repeated parity adjustments. |
| Slovenia | 2004 | Euro (since 2007) | … | Float until 2004. Pegged to euro during ERM II 2004–06. |
4. This paper’s objective is to illustrate economic benefits and costs from euro adoption by reviewing the main arguments and empirical evidence. The last time Fund staff analyzed this issue systematically was in 2004 (published as Schadler et al, 2005; see Box 1 for a summary of the main findings), in a study informed by the literature on optimal currency areas (Box 2). This paper follows and builds on the conceptual framework of 2004, by both reviewing new results from the literature and contributing analysis in areas less covered by existing research. We also discuss issues that were less on the radar screen in 2004 but have since come to the forefront, especially in the wake of the global financial crisis.
5. Broadly speaking, the trade-off presents itself as follows:
On the positive side—i.e., in favor of euro adoption—the 2004 study identified: (i) trade generation that could translate into higher growth; and (ii) improved country risk perception from deeper integration with the euro area that could, inter alia, lead to lower funding cost.
On (i) there is a solid body of evidence now that trade generation has remained far below original expectations—see Box 1—and we do not delve into this issue further. As for (ii) we reassess the impact of euro adoption on investor perception of country risk in the light of the evidence of the past 10 years.
We also analyze a benefit of euro adoption not covered in the 2004 paper: the elimination of currency mismatches resulting from the prevalence of foreign currency, mainly euro denominated loans in many NMS’s economies. As the global financial crisis illustrated, currency mismatches can translate into large vulnerabilities in times of financial strain.
As the main factor on the negative side—i.e., cautioning against rapid euro adoption—the 2004 study identified the loss of monetary autonomy; i.e., ceding the ability to adapt monetary conditions to the economy’s needs and use the exchange rate as shock absorber. We re-assess the value of monetary autonomy in light of the experience of the past ten years that were characterized by far higher macro-economic volatility than expected (Box 1).
Finally, we discuss how euro adoption changes countries’ macroeconomic policy frameworks beyond monetary policy, and how recent euro area wide reforms in these areas—fiscal compact, banking union—may affect a country’s calculus to join.
6. Importantly, weighing the pros and cons of euro adoption is ultimately an issue of preference that can differ between countries. Further, the decision on adoption clearly goes beyond purely economic aspects and includes political economy and broader political considerations. These are beyond the scope of this paper. As a result, we refrain from recommendations on whether a country should adopt the euro or not, but instead focus on key macro-economic tradeoffs.
7. The remainder of this paper is organized as follows. Section B reviews key economic advantages of euro adoption as sketched above, Section C the advantages from maintaining monetary policy autonomy. Section D discusses the impact of euro adoption on policy frameworks. Section E concludes.
B. Advantages from Adopting the Euro
8. As outlines above, this section analyzes two possible advantages of euro adoption:
Improved country risk perception from integrating deeper in the euro area’s institutional framework that may translate, inter alia, into lower funding costs, and
the elimination of currency mismatches between euros and domestic currencies.
Euro Area Membership and Country Risk Perception
9. Adopting the euro can reduce perceived risks through the elimination of exchange rate risk and access to lender-of-last resort facilities in a global reserve currency. For countries with weak institutions, euro adoption can also strengthen the credibility of the monetary anchor.5 Conversely, euro adoption may undermine a country risk perception, especially when it reduces the ability to handle country-specific shocks (as discussed in Section III).
10. To analyze the effect of euro adoption on country risk perception, we estimate an econometric model (Figure 1).
Country risk perception indices. We use two different indices: the Institutional Investor’s country credit ranking (IIR), and a linearized version of Standard & Poor’s sovereign credit ratings (S&P). The IIR index is based on anonymous inputs from economists and risk analysts at banks, money market funds, and securities firms. Participants’ responses are weighed according to their institutions’ exposure. The IIR thus directly measures investor attitudes toward country risk. The S&P rating is based on a formal assessment methodology, complemented by judgment. It is used both for regulatory purposes and to inform asset allocations of institutional investors, but has at times been criticized for (alleged) biases (see e.g. Vernazza et al, 2014). The two indices display similar patterns, and their relationship is broadly linear, with 4–5 points on the IIR scale corresponding to one rating notch with S&P (Figure 1).
Analysis. We estimate the relationship between perceived credibility and country characteristics for 34 countries during 2001–13. One characteristic is euro area membership. A positive coefficient suggests that investors put a “euro premium” on membership.6 The premium is estimated for each year separately (see Appendix I).
Results. The reputational value of euro area membership has declined. Through most of the 2000s, membership provided a substantial country risk premium of 10–15 rating points on the IIR scale, and of about two rating notches with S&P. This premium has mostly vanished—entirely for the S&P index, and to a somewhat lesser degree for the IIR. The timing of the decline—starting in 2010—suggests that the euro area crisis triggered a reassessment among investors of the relative benefits and drawbacks of euro membership for country risk.
Euro Premium, 2001-13
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: EBRD; International Investor Ratings; Standard and Poors; and IMF Staff calculations.Euro Premium, 2001-13
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: EBRD; International Investor Ratings; Standard and Poors; and IMF Staff calculations.Euro Premium, 2001-13
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: EBRD; International Investor Ratings; Standard and Poors; and IMF Staff calculations.11. As a result, the NMS-6 today face a different situation than the early euro adopters in the 2000s. While Slovenia or the Slovak Republic—that adopted the euro in 2007 and 2009, respectively—could expect to benefit from a sizeable reputational boost upon joining the euro, this benefit has vanished with the euro area crisis.
Eliminating Currency Mismatches
12. Beyond the impact of the euro on general risk perception, euro adoption can benefit a country if it reduces specific vulnerabilities—notably foreign currency mismatches. Such mismatches arise when households and corporations are indebted in foreign currency (FX), while their assets and income streams are in domestic currency. In this case, currency depreciation can trigger an upward revaluation of debt that can harm financial stability and economic activity. While countries can self-insure against depreciation risk—through accumulation of FX reserves and regulations forcing financial institutions to hold extra buffers—this is costly. FX indebtedness is widespread in Central and Eastern Europe, often—but not always—intermediated by subsidiaries of banks located in the euro area (see, e.g., Brown and de Haas 2012, or Rosenberg and Tirpak 2009). Among the NMS-6, balance sheet euroization—proxied here by the share of bank loans to the private sector denominated in FX (see figure)—is considerable in all economies except Poland and the Czech Republic.7
Investor Perception and Balance Sheet Euroization, 2006-14
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: EBRD; International Investor Ratings; Standard and Poors; and IMF Staff calculations.Investor Perception and Balance Sheet Euroization, 2006-14
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: EBRD; International Investor Ratings; Standard and Poors; and IMF Staff calculations.Investor Perception and Balance Sheet Euroization, 2006-14
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: EBRD; International Investor Ratings; Standard and Poors; and IMF Staff calculations.13. As most FX debt in the NMS is denominated in euro, euro adoption can eliminate sizeable currency mismatches,8 as it did in the Baltic states and in Slovenia upon joining the euro (see figure). Similarly, euro adoption grants access to euro lender-of-last-resort facilities for banks with a high share of euro denominated assets and, correspondingly, high euro funding needs.9 In contrast to the general euro premium discussed above, these FX-specific benefits are disproportionately to the advantage of economies with a high share of FX loans prior to euro adoption.
14. Our results suggest that for highly euroized economies, eliminating mismatches through euro adoption is indeed beneficial. This is shown by correlating the country-specific premium—captured by country dummies—with the share of FX bank loans. The results show that for nearly fully euroized economies, euro adoption can eliminate a ratings malus of more than 10 IIR points. Further statistical analysis points to a non-linear impact, i.e., the malus increases disproportionately with higher levels of euroization (see Appendix I).
15. In contrast to the general euro premium discussed above, FX-specific benefits from euro adoption have not vanished. This provides an economic rationale why the Baltic countries—all of them highly euroized—sought euro area membership in the early 2010s, even though at the time the general euro premium was already waning.
C. Advantages from Preserving Monetary Policy Autonomy and Exchange Rate Flexibility
16. We now turn to advantages from maintaining monetary autonomy, i.e., the ability to set monetary conditions in line with the economy’s needs, and to allow the exchange rate to operate as a shock absorber. If successful, monetary policy autonomy helps stabilize domestic demand—especially when economies are exposed to shocks—contain inflation volatility and credit developments. To assess the value of monetary autonomy for the NMS, we look at three distinct episodes in the past 10–12 years:
economic convergence, i.e. the period of about 2003–07, when the NMS outgrew the old EU member states (EU 15) by about three percentage points per year;
the financial crisis of 2008/09 and its aftermath that brought the convergence process in most NMS to a halt; and
the most recent period of 2012–14 when the NMS were affected by disinflationary pressures from global commodity markets and the euro area.
For each episode, we map a standard monetary conditions index10 against domestic demand volatility and related outcomes, such as real credit growth and inflation, in (i) NMS that have maintained monetary policy autonomy and (ii) NMS that have used external monetary anchors—either by adopting the euro, or by tying their currencies to the euro or other currencies/currency baskets. While there is considerable heterogeneity of outcomes within both groups—reflecting, among other things, countries’ policy stances in areas other than monetary policy—some broad patterns emerge.
GDP Per Capita in Purchasing Power Standard
(Percent of the euro area)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
GDP Per Capita in Purchasing Power Standard
(Percent of the euro area)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
GDP Per Capita in Purchasing Power Standard
(Percent of the euro area)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
17. Importantly, this section is not about whether fixed or flexible exchange rates are generally preferable. Many reasons that go beyond short-to medium-term demand management as discussed here may call for one regime or the other—e.g., in the case of a fixed exchange rate regime, the need for a credible monetary anchor. What choice is appropriate will typically depend on country-specific circumstances. A widespread finding in the literature is that long-term growth and inflation outcomes tend to be broadly similar under both regimes, while fluctuations tend to be larger with fixed exchange rates (see, e.g. IMF, 2005 and 2013b).
Managing Convergence
18. In 2003–07, the NMS grew at an average annual real rate of about 6 percent, 3 percentage points faster than the old members of the European Union (EU 15). As a result, the average income gap per capita (PPP) against the EU 15 fell by about 10 percent, until convergence stalled with the outbreak of the global financial crisis.
19. Higher growth rates for an extended period require a tighter monetary policy stance. Less wealthy countries have typically a smaller capital stock and therefore higher returns of capital. This attracts capital inflows, boosts economic growth, and gradually increases the capital share until economies converge. Unless the higher real return on capital is matched by tighter monetary conditions, however, there is a risk that capital inflows trigger credit and housing booms, inflation, and external imbalances (see Lipschitz et al., 2002).11 As countries with fixed exchange rate regimes tend to adopt the monetary policy stance of the economy to which their currency is tied, there is a risk that during convergence, monetary conditions are too loose. This risk increases with an economy’s real income gap with the euro area, and therefore with its potential for rapid growth.
20. The data show a pattern of tighter monetary conditions for economies that maintained monetary policy autonomy during convergence (Figure 3). This is especially evident for the Czech Republic and Poland, both of which let their currencies float during this period, and to a lesser degree for Hungary (that held the forint within a wide band against the euro). Importantly, the tightening in monetary conditions was achieved mostly by means of nominal exchange rate appreciation rather than higher central bank interest rates (Box 3).
New Member States: Monetary Policy, 2003-07
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: Haver Analytics; and IMF Staff calculations.New Member States: Monetary Policy, 2003-07
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: Haver Analytics; and IMF Staff calculations.New Member States: Monetary Policy, 2003-07
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: Haver Analytics; and IMF Staff calculations.
New Member States: Monetary Policy, 2008-14
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: Haver Analytics; and IMF Staff calculations.New Member States: Monetary Policy, 2008-14
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: Haver Analytics; and IMF Staff calculations.New Member States: Monetary Policy, 2008-14
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: Haver Analytics; and IMF Staff calculations.21. By contrast, monetary conditions in countries with fixed exchange rates tended to be, overall, fairly accommodative, often even more accommodative than in the euro area. Correspondingly, such countries tended to experience stronger overshooting in domestic demand, larger credit and asset booms, and higher and more volatile inflation (for a detailed discussion, see Bakker and Gulde, 2010).
Managing Downturns
22. In the global financial crisis of 2008/09 and its aftermath, the NMS were hit by a severe negative demand shock that stalled or even reversed convergence. Monetary autonomy allowed central banks to respond by cutting policy rates and—more importantly—allow nominal exchange rates to depreciate and act as shock absorbers (Figure 4). Nominal depreciations were especially large in Poland and Romania, where domestic demand held up better than elsewhere.12 By contrast, in countries with fixed exchange rates, monetary conditions tended to be tighter driven in part by the need to defend the exchange rate arrangement.13 As a consequence, the demand contraction in crisis tended to be larger, even though there are exceptions.14
Offsetting Disinflationary Spillovers
23. In recent years, the NMS have been affected by deflationary shocks from falling global commodity prices and euro area disinflation. The impact on NMS has been asymmetric: while in economies with flexible exchange rates, disinflation has mostly affected headline inflation, in exchange rate pegging economies deflationary pressures have tended to creep into core inflation.15
24. Econometric analysis suggests that the link between disinflation spillovers and the exchange rate regime is systematic. Iossifov and Podpiera (2014) decompose headline inflation in the NMS-6 into country-specific, global, and euro area factors using an open-economy New Keynesian Phillips curve within 2004–14 panel data framework (see Appendix III). The share of inflation variance explained by euro area developments is largest in Bulgaria and Croatia, both of which have tied their currencies to the euro (“ET”). By contrast, inflation targeting (“IT”) central banks have thus far been able to largely offset the deflationary impulse from the euro area with their monetary policy stance. 16
D. The Impact of Euro Adoption on Macroeconomic Policy Frameworks
25. Euro adoption would change the NMS-6’s policy frameworks. Ceding monetary autonomy is only one—although the most important—component. In addition, the stability and growth pact foresees stricter enforcement mechanisms for euro area members than for countries outside the euro area, and euro area members are obliged to join the Banking Union, which comes with the transfer of most authority for micro-prudential supervision and some aspects of macro-prudential policy to the ECB.
26. The challenge to adapt to the euro area policy framework presents itself differently for countries with flexible and with fixed exchange rates. 17
For NMS-6 that let exchange rates float and target inflation, monetary policy autonomy would have to be replaced with other instruments, such as counter-cyclical fiscal policy, macro-prudential tools, and internal adjustment through wages.
For the NMS-6 that have pegged their currencies to the euro, an important issue is to what extent they could use macro-prudential policies also within the euro area—as Bulgaria and Croatia have been among the heaviest users of macro-prudential instruments in Europe (see Lim et al., 2011, and Dumičić, 2014).18
27. At this juncture, key euro area reforms that will affect both fiscal and financial sector governance are ongoing or have only just been completed. The final shape and practical implementation of these reforms will determine countries’ policy space in the euro area, as well as the support they can expect from common euro area institutions in combating economic and financial shocks.
28. Given the large uncertainty surrounding these reforms—regarding both their final shape and how they will work in practice—there is a rationale to waiting for final outcomes before taking an irreversible euro adoption decision. In an uncertain environment, the option to wait until benefits and cost become clearer has value by itself. The standard economic application of the “option value of waiting” is for investment decisions (see McDonald and Siegel, 1986, or Dixit and Pindyck, 1994). However, the rationale also applies to irreversible policy choices, such as euro adoption.
E. Conclusions
29. The parameters of the euro adoption debate have shifted. While countries joining the euro area in the 2000s could expect to benefit from a significant country risk premium, this premium has mostly vanished with the euro crisis. When or whether it will return is uncertain and will depend in part on the success of ongoing reforms of the euro area’s institutional framework. At the same time, for countries with sizeable shares of foreign currency loans, there are still important financial stability benefits from adopting the euro.
30. The NMS that have maintained exchange rate flexibility and monetary policy autonomy have, in general, made good use of it. During convergence, nominal currency appreciation supported more balanced growth and restrained credit and asset price booms. In the crisis-induced downturn of 2008–09, depreciation and monetary loosening helped stabilizing demand and, more recently, prevented external deflationary pressure from spilling into domestic core inflation.
31. It is an open question whether the macroeconomic volatility of the past decade will recur. If divergent growth patterns and volatility were to repeat, euro adoption would constrain macro-policy options, especially for economies with large income gaps and asynchronized business cycles vis-à-vis the euro area. Thus, a large burden would be placed on other policy instruments to safeguard balanced growth, notably counter-cyclical fiscal policy—which, in turn, requires fiscal space—and macro-prudential policies. Structural reforms to boost growth potential and facilitate internal adjustment would also be key.
32. For countries that peg their currencies to the euro, the balance of the argument is somewhat different, as they have already traded monetary autonomy and exchange rate flexibility for benefitting from the euro as monetary anchor. Thus, for the most part, their policy frameworks would not change materially upon adopting the euro. An important remaining issue though is to what extent they could employ macro-prudential and other regulatory instruments also within the euro area.
33. The scope for using fiscal policy and macro-prudential instruments is currently being re-defined in the context of ongoing reforms of the European fiscal and financial architecture. Depending on the final shape of these reforms, this may or may not constrain policy space for euro area members. The uncertainty about the outcomes of these reform efforts—and the limited means of the NMS-6 to affect them—provides a rationale to wait for and analyze final outcomes before taking an irreversible adoption decision.
The 2004 IMF Study, and New Evidence on its Main Findings
The 2004 IMF study “Adopting the Euro in Central Europe—Challenges of the Next Step in European Integration” was cautiously optimistic about the net economic benefits of euro adoption.
As key factor in favor of euro adoption, the study singled out trade generation and, as a result, higher growth. Based on estimates from the literature (e.g., Frankel and Rose, 1998 and Rose, 2000), staff considered real GDP gains of 10 to 25 percent over 20 years plausible. Staff noted though that the mechanism generating such large effects was not entirely clear, as the reduction in transaction cost and the elimination of exchange rate uncertainty would explain only a minor portion. The study also anticipated that adoption would reduce perceived credit risk which could, inter alia, reduce funding costs for NMS in the euro.
As for possible risks from euro adoption, the study acknowledged that coping with asymmetric demand shocks would become more difficult without an independent monetary policy. However, the study noted that the NMS had experienced low growth volatility in the preceding years, suggesting that shocks may be manageable also without monetary autonomy—provided countries had fiscal space for countercyclical policies, and wages and prices were sufficiently flexible. Further, economic integration in the wake of euro adoption was expected to lead to more synchronized business cycles. As another potential risk from adopting the euro, the study identified large and volatile capital inflows and lending booms, as well as higher inflation due to the Balassa/Samuelson effect. Again, fiscal space and wage flexibility were seen as key to manage these phenomena, together with structural reforms to boost competitiveness, and strong financial supervision.1
Growth Volatility
(5-year rolling standard deviation of per-capital real GDP growth,)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Growth Volatility
(5-year rolling standard deviation of per-capital real GDP growth,)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Growth Volatility
(5-year rolling standard deviation of per-capital real GDP growth,)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Subsequent developments confirmed parts of the 2004 assessment, but in other parts yielded new insights.
Risk spread compression happened as anticipated in 2004, at least until the outbreak of the euro crisis. The study’s warnings of excessive asset and credit booms were well placed.
Recent estimates of trade and growth effects are much smaller than assumed at the time, however, and range from nil (Havranek, 2010) to 2–3 percent of GDP (Baldwin, 2006). Further, recent studies suggest that trade generation is more related to EU entry than to euro adoption.
Demand volatility has been significantly larger than anticipated in 2004, especially in the wake of the global financial crisis of 2008/09 and the ensuing euro crisis. Endogenous business cycle synchronization with euro adoption has not materialized—rather, there have been signs of divergence, such as growing external imbalances (Gayer 2007; Holinski et al. (2012), Enders et al. 2013, Lehwald, 2013; and Degiannakis et al., 2014).
New Member States, Euro Adoption, and the Theory of Optimal Currency Areas
The academic literature on currency unions often casts the issue in terms of whether member countries form an “optimum currency area, OCA” (Mundell, 1961; McKinnon, 1963; and Kenen, 1969).
In principle, countries can benefit from a currency union through capital market integration, lower terms-of-trade volatility and reduced exchange rate fluctuations. Countries with weaker institutions can import monetary policy credibility (McKinnon, 2004; Tavlas, 1993).
There are also costs, mostly associated with forgoing exchange rate flexibility and monetary policy autonomy for managing cyclical conditions. To minimize such costs, countries in currency unions would best have synchronized business cycles and growth patterns, which is typically enhanced by intra-industry trade (Frankel and Rose, 1998).
In currency unions with incomplete business cycle synchronization, flexible non-monetary adjustment mechanism are needed: notably price and wage flexibility and cross-border labor mobility. Risk sharing through integrated financial markets can also help, by diversifying income sources through cross-country asset holdings (McKinnon, 2004; Mongelli, 2008).
Business cycle synchronization of NMS with the euro area is in general lower than within the euro area, even though there are differences between countries (Fidrmuc and Korhonen, 2003; Artis et al., 2004; Darvas and Szapáry, 2005; Van Arle et al. 2008). For Hungary, Poland, and the Czech Republic, synchronization with the euro area is higher than for the other NMS; and also higher relative to Greece and Portugal (Fidrmuc and Korhonen, 2006; Rinaldi-Larribe, 2013).
Wage flexibility in the NMS tends to be high while cross-border labor mobility has been increased (Gruber, 2004; Dao et al. 2014), with substantial outward migration from some NMS in the wake of the global financial crisis (OECD, 2013):
Wage flexibility. According to Gruber (2004) and Boeri and Garibaldi (2006) NMS tend to have lower statutory minimum wages, union density rates and more decentralized wage bargaining structure than the euro area—all pointing to wage flexibility.
Labor mobility. Outward migration in the post-crisis period of 2009–2011mostly was younger and educated workers, typically finding employment abroad below their skill level (Anacka et al., 2011; Jauer et al., 2014).
Cross-country risk sharing through financial market integration is low. While prior to the 2008/09 financial crisis, there was some evidence of increasing integration in equity and debt markets—such as lower interest rate dispersion and increasing effects of the euro area shocks on NMS equity markets (Cappiello et al. 2006; Baltzer et al. 2008)—these reversed in the wake of the crisis, with higher interest rate spreads (Pungulescu, 2013) and funding market segmentation along national lines (van Rixtel and Gasperini, 2013). In addition, cross-border asset holdings tend to be one-directional: euro area banks hold sizeable assets in NMS, and also FDI and portfolio investment from euro area residents in NMS is much larger than vice versa. As a result, domestic investment in the NMS is more sensitive to domestic saving than in EU15, and national consumption is closely correlated with GDP (Pungulescu, 2013).
Overall, while there are significant structural differences and lack of integration with the euro area, for NMS like the Czech Republic, Hungary, and Poland, this do not seem larger than heterogeneity within the euro area itself.
Economic and Price Convergence in Emerging Europe
The political transformation in NMS in 1990s led to economic convergence through economic reforms, including trade and price liberalization, privatization, and the adoption of the legal framework of advanced Europe. Institutional change established the base for rapid growth, facilitated by external capital investment, a supportive external financing environment, and an often skilled labor force and reasonable infrastructure. As a result, productivity and income per capita increased by 20 percent relative to the Euro Area countries by between 1995 and 2013 (see IMF, 2014).
Improvements in productivity go typically hand in hand with real exchange rate appreciation. There are two, not mutually exclusive channels – the Balassa-Samuelson and the Podpiera effect:
The Balassa-Samuelson effect reflects faster productivity growth for tradable than for non-tradable goods during convergence. As the price for tradable goods is fixed in global goods markets, the price for non-tradables has to rise. However, contrary to initial expectations–formed during early stages of convergence–that such an effect could account for 1-2 percentage points of consumer price inflation per year (Cipriani, 2000, Kovacs et al., 2002, and Mihaljek and Klau, 2003), more recent studies find much smaller effects (Mihaljek and Klau, 2008).
The Podpiera effect is due to converging economies shifting production toward higher quality goods. As quality improvements come with price increases and are typically underreported in domestic CPI indices, these effects are reflected in real exchange rate appreciation. Cincibuch and Podpiera (2006) and Fabrizio et al. (2007) document the rapid increase in prices in tradable sectors in NMS. Bruha and Podpiera (2010 and 2011) devise and calibrate a model that explains the rapid (2-3 percent a year) CPI-based real exchange rate appreciation during convergence. Sonora and Tica (2014) test jointly the Balassa-Samuelson and Podpiera effects and find that the latter primarily explains the real exchange rate appreciation in Emerging Europe.
Real exchange rate appreciation happened partly through nominal exchange rate appreciation in countries with flexible exchange rate regimes. In exchange rate targeting countries, it happened solely through higher inflation differentials (box charts and see figure on Investor Perception and Balance Sheet Euroization).
Real and Nominal Convergence
(Indexes, 2005=1, 2003Q1–07Q4)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Source: Haver and IMF Staff calculations.Real and Nominal Convergence
(Indexes, 2005=1, 2003Q1–07Q4)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Source: Haver and IMF Staff calculations.Real and Nominal Convergence
(Indexes, 2005=1, 2003Q1–07Q4)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Source: Haver and IMF Staff calculations.
Nominal Exchange Rate Against Euro
(Percentage change 2003Q1–07Q4)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Nominal Exchange Rate Against Euro
(Percentage change 2003Q1–07Q4)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Nominal Exchange Rate Against Euro
(Percentage change 2003Q1–07Q4)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Appendix I. Estimating the Euro Premium
Euro Premium
The empirical analysis of the euro premium is based on panel data regression for 34 European countries with annual observations for the period 2001–2013. The time period is mostly determined by data availability. We estimate the following equation:
where
C is an expert assessment of country perception. We use two different measures, (i) the Institutional Investor’s country credit ranking (IIR) and, for comparison (ii) a linearized version of Standard & Poor’s sovereign credit ratings (S&P).1 A possible alternative measure would have been credit spreads as used, e.g., in Heinz and Sun (2014), Matei and Cheptea (2012), Maltritz (2012), or von Hagen et al. (2011). The high volatility of credit spreads, and the fact that spreads are affected by many other factors than perceived credibility—say, global liquidity conditions and/or cross-country spillovers—makes us select a metric that assesses investor perceptions directly.
X is a vector of country characteristics that may affect a country’s perception of credit worthiness. X includes macro-variables—such as fiscal and external balances, public debt, per-capita-GDP, real GDP growth, the unemployment rate, inflation, the exchange rate regime, national investment as share of GDP, and the country’s a international investment position (NIIP)—but also an indicator measuring institutional quality.
Most data are drawn from the IMF’s World Economic Outlook database. For institutional quality, we use a simple average of the Kaufmann et al. (2010) governance quality indices that is available, at this juncture, only for 2002–12. The exchange rate regime is captured with a dummy variable for floating currencies (freely or managed) drawn from Ilzetzki et al. (2011) until 2010 and extrapolated with IMF (2013a) for the period thereafter. Public debt data is available for only about 90 percent of the observations; we control for missing observations by including a corresponding dummy variable.
xit is typically the expected outcome of variable for year t at the time when the WEO fall forecast is produced. We experimented with leads and lags, but found that concurrent values have the greatest explanatory power.
δ and θ are a country/time-dummies capturing unobserved, time invariant country-specific factors/common unobserved time-specific factors, respectively. The time dummies control for common macroeconomic and financial developments.
Euro is a dummy variable that takes on value 1 if country i was member of the euro area in year t, and 0 otherwise (or technically speaking, we interact a general euro area dummy with a time dummy). The γt thus measure the impact of euro area membership on country perception, holding country characteristics—both observed and unobserved—constant. We allow γ to vary over time, to verify whether the value of euro membership has changed. Similarly, EU is a dummy variable capturing EU membership.
Table A1 displays the regression results.
Euro and EU premia. While estimates for the IIR index (column 1) and the S&P indices (column 2) are in general similar, the IIR tends to value euro area membership higher than S&P throughout. Further, the decline in the premium in the wake of the euro crisis is steeper for the S&P index than for the IIR.2 The premium for EU membership is generally insignificant (see chart), except for 2001/02, when EU membership displays modest positive significance with the IIR index.3
Among controls, unemployment, and government debt have the strongest impact on perceived credibility, followed by inflation, growth, and the NIIP. Note that the IIP puts most weight on stock variables, while for the S&P assessment flow variables also matter (budget deficit, current account balance). Governance quality shows up as a strong determinant of credibility (column 3).
At the same time, its inclusion (or omission) does not materially affect the pattern of the euro premium over time.
To check for robustness we estimated various other specifications, both by including additional control variables—such covariates capturing global macro/liquidity conditions, e.g. the VIX index—and by estimating dynamic panels—notably the Arellano-Bond (1991) GMM estimator. The basic pattern—a steep decline in the euro area premium from 2010—persists across all specifications.4
EU Membership Premium: IIR (red, lhs) and S&P (blue, rhs)
(Rating points)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
EU Membership Premium: IIR (red, lhs) and S&P (blue, rhs)
(Rating points)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
EU Membership Premium: IIR (red, lhs) and S&P (blue, rhs)
(Rating points)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
IIR Premium for Euro Area Membership: Arellano/Bond GMM Dynamic Panel Estimator
(Rating points)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
IIR Premium for Euro Area Membership: Arellano/Bond GMM Dynamic Panel Estimator
(Rating points)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
IIR Premium for Euro Area Membership: Arellano/Bond GMM Dynamic Panel Estimator
(Rating points)
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Euro Premium - Panel Regressions
Linearized and inverted
Euro Premium - Panel Regressions
| 2001–2013 | 2002–2012 | ||||||
|---|---|---|---|---|---|---|---|
| (1) IIR Rating | (2) S&P Rating1/ | (3) IIR Rating | |||||
| Coeff. | t-value | Coeff. | t-value | Coeff. | t-value | ||
| Controls Per-capita GDP | −1.8^(-5) | −0.51 | 0.1^(-5) | 0.58 | −1.7^(-5) | −0.39 | |
| Real growth | 0.40 | 3.63*** | 0.12 | 4.64*** | 0.37 | 3.41*** | |
| Investment/GDP | 0.13 | 1.36 | 0.04 | 1.74* | 0.11 | 1.09 | |
| Unemployment rate | −1.03 | −9.56*** | −0.31 | −12.16*** | −0.84 | −7.13*** | |
| CPI inflation | −0.26 | −3.92*** | −0.68 | −5.88*** | −0.20 | −2.46** | |
| Gen. gov. balance | −0.10 | −0.95 | −0.07 | −2.69*** | −0.00 | −0.01 | |
| Gen. gov. debt | −0.17 | −9.01*** | −0.03 | −6.62*** | −0.14 | −7.16*** | |
| External balance | 0.06 | 0.82 | 0.04 | 2.42** | 0.08 | 0.99 | |
| NIIP | 0.03 | 5.15*** | 0.01 | 4.10*** | 0.02 | 3.60*** | |
| Floating (dummy) | 0.16 | 0.14 | −0.50 | −1.82* | 0.72 | 0.56 | |
| Governance quality | … | … | … | … | 18.08 | 5.63*** | |
| Country fixed effects, time dummies, euro and EU membership dummies, dummy for missing gov. debt observations (not reported) | |||||||
| Observations | 442 | 442 | 374 | ||||
| Adjusted R 2 | 0.952 | 0.952 | 0.956 | ||||
| Significance of country FE | F(33,359)= 37.63 (0.000) | F(33,359)= 45.30 (0.000) | F(33,292)= 22.10 (0.000) | ||||
Linearized and inverted
Euro Premium - Panel Regressions
| 2001–2013 | 2002–2012 | ||||||
|---|---|---|---|---|---|---|---|
| (1) IIR Rating | (2) S&P Rating1/ | (3) IIR Rating | |||||
| Coeff. | t-value | Coeff. | t-value | Coeff. | t-value | ||
| Controls Per-capita GDP | −1.8^(-5) | −0.51 | 0.1^(-5) | 0.58 | −1.7^(-5) | −0.39 | |
| Real growth | 0.40 | 3.63*** | 0.12 | 4.64*** | 0.37 | 3.41*** | |
| Investment/GDP | 0.13 | 1.36 | 0.04 | 1.74* | 0.11 | 1.09 | |
| Unemployment rate | −1.03 | −9.56*** | −0.31 | −12.16*** | −0.84 | −7.13*** | |
| CPI inflation | −0.26 | −3.92*** | −0.68 | −5.88*** | −0.20 | −2.46** | |
| Gen. gov. balance | −0.10 | −0.95 | −0.07 | −2.69*** | −0.00 | −0.01 | |
| Gen. gov. debt | −0.17 | −9.01*** | −0.03 | −6.62*** | −0.14 | −7.16*** | |
| External balance | 0.06 | 0.82 | 0.04 | 2.42** | 0.08 | 0.99 | |
| NIIP | 0.03 | 5.15*** | 0.01 | 4.10*** | 0.02 | 3.60*** | |
| Floating (dummy) | 0.16 | 0.14 | −0.50 | −1.82* | 0.72 | 0.56 | |
| Governance quality | … | … | … | … | 18.08 | 5.63*** | |
| Country fixed effects, time dummies, euro and EU membership dummies, dummy for missing gov. debt observations (not reported) | |||||||
| Observations | 442 | 442 | 374 | ||||
| Adjusted R 2 | 0.952 | 0.952 | 0.956 | ||||
| Significance of country FE | F(33,359)= 37.63 (0.000) | F(33,359)= 45.30 (0.000) | F(33,292)= 22.10 (0.000) | ||||
Linearized and inverted
Euroization
The analysis of the impact of balance-sheet euroization on perceived credibility is constrained by limited data availability. We have information for only 11 new EU members states from 2006–2012 (in a few cases going back to 2004). This prevents including euroization as a covariate into the regression equation above. As an alternative strategy, we correlate both (i) the NMS’ country fixed effects
Figure A1 shows key results, using the
Ratings Premia and Euroization, Detailed Results
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Source: IMF Staff calculations.Ratings Premia and Euroization, Detailed Results
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Source: IMF Staff calculations.Ratings Premia and Euroization, Detailed Results
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Source: IMF Staff calculations.Appendix II. The Index of Monetary Conditions
Following Freedman (1994) and subsequent applications by several central banks and the IMF, the index of monetary conditions (MCI) has been calculated as the weighted average of the indexes of the real interest rate (RIR) and the real effective exchange rate (REER):
where α is the relative impact of RIR on domestic demand. The estimated weight α ranges from 0.6 in the Czech Republic, Poland, and Slovenia, through 0.8 in Bulgaria, Estonia, Latvia, Lithuania, and Slovakia, to 0.9 in Croatia and Hungary. For comparison, the European Commission1 uses α = 0.8 in its MCI calculations for the euro area. All indexes were set to 1 in 2003.
Appendix III. Model-Based Inflation Variance Decomposition
Iossifov and Podpiera (2014) analyze inflationary developments in ten non-euro area EU countries within the 2004–14 period, using a panel framework of an open-economy New Keynesian Phillips curve (Galí and Gertler, 1999). They assume inflation to be both forward-looking with some degree of inertia and driven by demand and supply-side shocks. The regression specification can be described, for a country i, as:
πi,t – Headline inflation is calculated using the Harmonized Indices of Consumer Prices (HICP) published by Eurostat
– Euro Area price pressures is the euro area HICP core inflation, which is stripped of direct, first-round effects of commodity price changes. – Expected inflation proxies expectations of future inflation by the mean forecasts of average annual inflation two-years ahead published by Consensus Economics.
zit - 1 × K vector of country-specific supply-side shocks:
Contribution of taxes and administered prices are captured by their combined contribution to headline inflation, calculated with HICP data published by Eurostat
Exchange rate appreciation/depreciation is calculated using the nominal effective exchange rates published by the IMF.
wt - 1 × p vector of common external supply-side shocks:
World commodity price inflation—world oil and food price indices in US dollars from the IMF’s World Economic Outlook (WEO) are used to capture commodity price changes. They are interacted with the weights of energy and food in consumer baskets to allow for differentiated impact across countries.
Exchange rate regime dummies—based on the classification of exchange rate regimes in the IMF’s Annual Report on Exchange Arrangements and Exchange Restrictions (IMF, 2013a).
Share of foreign value added in domestic demand—calculated using OECD-WTO’s Trade in Value Added dataset as an average of the 2005 and 2009 values. Data for Croatia is not available in the OECD-WTO database. We approximate the share of foreign value added in Croatian domestic demand by the average of its readings in Poland and Romania, as the ratio of imports to GDP of these three countries are very similar.
The estimation results suggest that food and energy prices account for a large share of the variance of headline inflation, but exchange rate regime and trade linkages to the Euro Area are also important. According to the inflation variance decomposition (Figure A2), world food and energy price changes together with changes in administered prices and taxes account for about half of the variability of headline inflation across non-euro area EU countries. However, disinflation spillovers from the euro area have been an important factor for NMS that peg their currency to the euro and inflation targeting countries with high foreign value added in domestic demand:
Countries with more rigid exchange rate arrangements tend to import more inflation from the euro area.
Inflation spillovers from the euro area are also larger, the higher the share of domestically consumed foreign value-added (e.g., in the Czech Republic and Hungary).
Model-based Inflation Variance Decomposition
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: IMF staff calculations.Note: 1 Inflation variances are normaliazed to the variance of NMS-ET countries.Model-based Inflation Variance Decomposition
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: IMF staff calculations.Note: 1 Inflation variances are normaliazed to the variance of NMS-ET countries.Model-based Inflation Variance Decomposition
Citation: IMF Staff Country Reports 2015, 098; 10.5089/9781484321393.002.A001
Sources: IMF staff calculations.Note: 1 Inflation variances are normaliazed to the variance of NMS-ET countries.Anacka, Marta, Agnieszka Fihel, Pawel Kaczmarczyk and Renata Stefanska, 2011, “Recent Trend in International Migration in Poland,” The 2011 SOPEMI Report.
Arellano, Manuel, and Stephen Bond, 1991, “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,” Review of Economic Studies, Vol. 58/2, pp. 277–297.
Artis, Michael J., Massimiliano Marcellino, and Tommaso Proietti, 2004, “Characterizing the Business Cycle for Accession Countries,” CEPR Discussion Paper 4457.
Bakker, Bas B., and Anne-Marie Gulde, 2010, “The Credit Boom in the EU New Member States: Bad Luck or Bad Policies?” IMF Working Paper No. 10/130. (Washington: International Monetary Fund).
Baldwin, Richard, 2006, “The Euro’s Trade Effects,” Working Paper 594, European Central Bank, March.
Baltzer, Markus, Lorenzo Cappiello, Roberto A. De Santis and Simone Manganelli, 2008, “Measuring Financial Integration in New EU Member States,” European Central Bank Occasional Paper Series 81.
Boeri, Tito and Pietro Garibaldi, 2006, “Are Labour Markets in the New Member States Sufficiently Flexible for EMU?” Journal of Banking & Finance, Vol. 30, pp. 1393–1407.
Brown, Martin and Robert de Haas, 2012, “Foreign Banks and Foreign Currency Lending in Emerging Europe,” Economic Policy, Vol. 27(69), pp. 57–98.
Bruha, Jan and Jiri Podpiera, 2010, “Real Exchange Rate in Emerging Economies: The Role of Different Investment Margins,” Economics of Transition, Vol. 18/3, pp. 599–628.
Bruha, Jan and Jiri Podpiera, 2011, “The Dynamics of Economic Convergence: The Role of Alternative Investment Decisions,” Journal of Economic Dynamics and Control, Vol. 35/7, pp. 1032–1044.
Cappiello, Lorenzo, Bruno Gerard, Arjan Kadareja and Simone Manganelli, 2006, “Financial Integration of New Member States,” European Central Bank Working Paper Series 683.
Cerutti, Eugenio, Stijn Claessens and Luc Laeven, 2015, “The Use and Effectiveness of Macroprudential Policies: New Evidence”, IMF, mimeo.
Cincibuch, Martin and Jiri Podpiera, 2006, “Beyond Balassa-Samuelson: Real Appreciation in Tradables in Transition Countries,” Economics of Transition, Vol. 14/3, pp. 547–573.
Cipriani, Marco, 2000, “The Balassa-Samuelson Effect in Transition Economies,” mimeo, Paper prepared by the CEC5 National Banks for the Basle meeting on March 2002.
Dao, Mai, Davide Furceri and Prakash Loungani, 2014, “Regional Labor Market Adjustments in the United States and Europe,” IMF Working Paper No. 14/26.
Darvas, Zsolt and György Szapáry, 2005, “Business cycle synchronization in the enlarged EU: Comovements in the new and old members,” CEPR Discussion Paper No. 5179.
Degiannakis, Stavros, David Duffy and George Fils, 2014, “Business Cycle Synchronization in EU: A Time-Varying Approach,” Scottish Journal of Political Economy, Vol 61(4), pp. 348–370.
Dixit, Avinash K. and Robert S. Pindyck, 1994, Investment under Uncertainty, Princeton University Press.
Dumičić, Mirna, 2014, “Macroprudential Policy in Central and Eastern European Countries - Is There Something We Should Learn?” Paper Presented at the 20th Dubrovnik Economic Conference.
Enders, Zeno, Philip Jung and Gernot J. Müller, 2013, “Has the Euro Changed the Business Cycle?” European Economic Review, Vol. 59, pp 189–211. European Commission, 2014, Convergence Report, ISSN 1725–3217.
Fabrizio, Stefania, Deniz Igan, and Ashoka Mody, 2007, “The Dynamics of Product Quality and International Competitiveness,” IMF Working Paper No. 07/97.
Fidrmuc, Jarko and Iikka Korhonen, 2003, “Similarity of supply and demand shocks between the euro area and the CEECs,” Economic Systems, Vol. 27(3), pp. 313–334.
Fidrmuc, Jarko and Iikka Korhonen, 2006, “Meta-analysis of the business cycle correlation between the euro area and the CEECs,” Journal of Comparative Economics, Vol. 34(3), pp. 518–537.
Frankel, Jeffrey A. and Andrew K. Rose, 1998, “The Endogeneity of the Optimum Currency Area Criteria,” Economic Journal, Vol. 108(449), pp. 1009–1025.
Freedman, C., 1994, “The Use of Indicators and of the Monetary Conditions Index in Canada”, In: Balino, T. J. T. and Cottarelli, C. (eds.), Frameworks for Monetary Stability: Policy Issues and Country Experiences, Chapter 18, pp. 458–476, International Monetary Fund, Washington, D.C.
Galí, Jordi and Mark Gertler, 1999, “Inflation dynamics: A structural econometric analysis,” Journal of Monetary Economics, 44(2), October, pp. 195–222.
Gayer, Christian, 2007, “A Fresh Look at Business Cycle Synchronization in the Euro Area,” European Economy, Economics Paper 287.
Government of the Republic of Slovenia and Bank of Slovenia, 2003, “The Euro is Coming,” OPOCE.
Gruber, Thomas, 2004, “Employment and Labor Market Flexibility in the New EU Member States,” in Focus 01/04, Osterreichische Nationalbank, pp. 96–121.
Havránek, TomáŠ, 2010, “Rose Effect and the Euro: Is the Magic Gone?” Review of World Economics, June 2010, Vol 146(2), pp. 241–261.
Heinz, Frigyes Ferdinand, and Yan Sun, 2014, “Sovereign CDS Spreads in Europe—the Role of Global Risk Aversion, Fundamentals, Liquidity, and Spillovers,” IMF Working Paper No. 14/17 (Washington: International Monetary Fund).
Holinski, Nils, Clemens Kool and Joan Muysken, 2012, “Persistent Macroeconomic Imbalances in the Euro Area: Cause and Consequences,” Federal Reserve Bank of St. Louis Review, January/February 2012, Vol 94(1), pp. 1–20.
Ilzetzki, Ethan, Carmen M. Reinhart and Kenneth S. Rogoff, 2011, “Exchange Rate Arrangements Entering the 21st Century: Which Anchor Will Hold?” London School of Economics, mimeo.
International Monetary Fund, 2005, “Does Inflation Targeting Work in Emerging Markets?” Chapter IV, World Economic Outlook, September, (Washington).
International Monetary Fund, 2013a, Annual Report on Exchange Arrangements and Exchange Restrictions, (Washington).
International Monetary Fund, 2013b, “The Yin and Yang of Capital Flow Management: Balancing Capital Inflows with Capital Outflows,” Chapter IV, World Economic Outlook, September (Washington).
International Monetary Fund, 2014, “25 Years of Transition: Post-Communist Europe and the IMF” Regional Economic Issues, October 2014, (Washington).
Iossifov, Plamen and Jiri Podpiera, 2014, “Are Non-Euro Area EU Countries Importing Low Inflation from the Euro Area?” IMF Working Paper No. 14/191.
Jauer, Julia, Tomas Leibig, John P. Martin and Patrick Puhani, 2014, “Migration as an Adjustment Mechanism in the Crisis? A comparison of Europe and the United States,” OECD Social, Employment and Migration Working Papers No. 155.
Kaufmann, Daniel, Aart Kraay, and Massimo Mastruzzi, 2010, “The Worldwide Governance Indicators: Methodology and Analytical Issues,” World Bank Policy Research Working Paper No. 5430.
Kenen, Peter B., 1969, “The Theory of Optimum Currency Areas: An Eclectic View,” In R. Mundell and A. Swoboda eds, Monetary Problems of the International Economy, The University of Chicago Press, pp. 41–60.
Kovacs, M. A. (ed.), 2002, “On the Estimated Size of the Balassa-Samuelson Effect in CEC5 Countries,” May. Paper prepared by the CEC5 National Banks for the Basle meeting on March 2002.
Lehwald Sybille, 2013, “Has the Euro Changed Business Cycle Synchronization? Evidence from the Core and the Periphery,” Empirica, Vol. 40 (4), pp. 655–684.
Lim, C., F. Columba, A. Costa, P. Kongsamut, A. Otani, M. Saiyid, T. Wetzel and X. Wu, 2011, “Macroprudential Policy: What Instruments and How to Use Them? Lessons From Country Experiences,” IMF Working Paper No. 11/238 (Washington: International Monetary Fund).
Lipschitz, Leslie, Timothy Lane, and Alex Mourmouras, 2002, “Capital Flows to Transition Economies: Master or Servant,” IMF Working Paper No. 02/11. (Washington: International Monetary Fund).
Maltritz, Dominik, 2012, “Determinants of Sovereign Yield Spreads in the Eurozone: A Bayesian Approach,” Journal of International Money and Finance, Vol. 31/3, pp. 657–672.
Matei, Iuliana and Angela Cheptea, 2012, “Sovereign Bond Spread Drivers in the EU Market in the Aftermath of the Global Financial Crisis,” in Essays in Honor of Jerry Hausman, pp. 327–352.
McDonald, Robert L. and Daniel Siegel, 1986, “The Value of Waiting to Invest,” Quarterly Journal of Economics, Vol. 101 (4), pp. 707–727.
McKinnon, Ronald I., 1963, “Optimum Currency Areas,” American Economic Review, Vol. 53, pp. 717–724.
McKinnon, Ronald I., 2004, “Optimum Currency Areas and Key Currencies: Mundell I versus Mundell II,” Journal of Common Market Studies, Vol. 42(4), pp. 689–715.
Mihaljek, Dubravko and Marc Klau, 2003, “The Balassa-Samuelson effect in Central Europe: A Disaggregated Analysis,” BIS Working Paper 143.
Mihaljek, Dubravko and Marc Klau, 2008, “Catching-up and inflation in transition economies: the Balassa-Samuelson effect revisited,” BIS Working Paper 270.
Mongelli, Francesco P., 2008, “European Economic and Monetary Integration, and the Optimum Currency Area Theory,” European Economy, Economic Paper 302, Directorate General Economic and Monetary Affairs (DG ECFIN), European Commission.
Mundell, Robert A., 1961, “A Theory of Optimum Currency Area,” American Economic Review, Vol. 51, pp. 657–665.
OECD, 2013, “Coping with emigration in Baltic and East European countries,” OECD Publishing.
Pungulescu, Crina, 2013, “Measuring financial market integration in the European Union: EU15 vs. New Member States,” Emerging Markets Review, Vol. 17, pp. 106–124
Ranciere, Romain, Aaron Tornell, and Athanasios Vamvakidis, 2010, “A New Index of Currency Mismatch and Systemic Risk,” IMF Working Paper No. 10/263 (Washington: International Monetary Fund).
Rinaldi-Larribe, Marie-José, 2013, “Is economic convergence in New Member States sufficient for an adoption of the euro?,” The European Journal of Comparative Economics, Vol. 5(2), pp. 133–154.
Rose, Andrew K., 2000, “One money, one market: the effect of common currencies on trade,” Economic Policy, Vol. 15(30), pp. 7–33.
Rosenberg, Christoph and Marcel Tirpak, 2009, “Determinants of Foreign Currency Borrowing in the New Member States of the EU,” Journal of Economics and Finance, vol. 59(3), pp. 216–228.
Schadler, Susan, Paulo Drummond, Louis Kuijs, Zuzana Murgasova, and Rachel van Elkan, 2005, “Adopting the Euro in Central Europe – Challenges of the Next Step in European Integration,” IMF Occasional Paper 234.
Slovakian National Bank, 2003, “Strategy of the Slovak Republic for Adoption of the Euro,” BIATEC, Volume XI, 10/2003.
Sonora, Robert J. and Josip Tica, 2014, “Harrod, Balassa and Samuelson (Re)Visit Eastern Europe,” Cogent Economics & Finance (2014–2).
Standard and Poor’s Rating Service, 2015, “Poland Could Reap Longer Term Benefits From Adopting The Euro”, McGraw Hill Financial.
Tavlas, George S., 1993, “The ‘New’ Theory of Optimum Currency Areas,” The World Economy, Vol. 16(6), pp. 663–685.
Traistaru, Iulia, 2004, “Transmission channels of business cycles synchronization in an enlarged EMU,” Working paper B18. Center for European Integration Studies, ZEI, Bonn.
Van Arle, Bas, Marcus Kappler, Andreas Sachs, Atilim Seymen, and Klaus Weyerstrass, 2008, “Study on Economic Integration and Business Cycle Synchronization,” Center for European Economic Research (ZEW) and Institute for Advanced Study (HIS).
Van Rixtel, Adrian and Gabriele Gasperini, 2013, “Financial Crises and Bank Funding: Recent Experience in the Euro Area,” BIS Working Papers 406.
Vernazza, Daniel, Erik F. Nielsen, and Vasileos Gkianakis, 2014, “The Damaging Bias of Sovereign Ratings,” UniCredit Global Themes No. 21.
Von Hagen, Jürgen, Ludger Schuknecht, and Guido Wolswijk, 2011, “Government Bond Risk Premiums in the EU Revisited: The Impact of the Financial Crisis,” European Journal of Political Economy, Vol. 27(1), pp. 36–43.
Wicksell, Knut, 1898/1936, Interest and Prices (Geldzins und Güterpreise), Sentry Press, New York.
Prepared by Jiri Podpiera, Johannes Wiegand and Jiae Yoo. Jessie Yang provided excellent research assistance. The authors are grateful to Csaba Balogh (Hungarian National Bank), Kalin Hrivstov (Bulgarian National Bank), Paul Kutos (European Commission), Andrzej Raczko (Polish National Bank), and Vedran Sosic (Croatian National Bank) who participated as discussants in the session on euro adoption at the New Member States (NMS) Policy Forum in Warsaw on December 12, 2014, and to the NMS-6, EC and ECB representatives who provided comments during bilateral discussions in November 2014. Ernesto Crivelli, Anna Ilyina, Plamen Iossifov, Murad Omoev, Andrea Schächter, Michelle Shannon, (other) members of NMS-6 country teams, and participants at an IMF seminar provided helpful discussions and comments.
NMS-6 includes Bulgaria, Croatia, Czech Republic, Hungary, Poland and Romania. NMS includes these countries and NMS-EA consisting of Estonia, Latvia, Lithuania, Slovakia and Slovenia.
This distinguishes the NMS-6 from the United Kingdom or Denmark, both of which negotiated an opt-out. Sweden did not negotiate an opt-out and is subject to the same assessment procedures as the NMS-6.
The criteria are fixed in the Treaty on European Union and defined as follows: 1/ Legal = includes the statutes of the national central bank; 2/ Fiscal = a government budgetary position without a deficit and debt level that are determined excessive; 3/ Price stability = a rate of inflation which is close to that of, at most, the three best performing Member States in terms of price stability; 4/ Exchange rate stability = the observance of the normal fluctuation margins provided for by the exchange-rate mechanism of the European Monetary System, for at least two years, without devaluing against the euro; 5/ Interest rate stability = observed over a period of one year before examination, a Member state has had an average nominal long-term interest rate that does not exceed by more than 2ppt that of, at most, the three best-performing Member States in terms of price stability.
These advantages were clearly on the mind of the early euro adopters. For example, in 2003 the Slovenian authorities listed as the first benefit of euro introduction “providing a more stable environment for the whole economy”, and in the same year the Slovakian central bank wrote “the adoption of the single currency will represent the completion of the integration process”.
Strictly speaking, the premium measures the impact of euro membership on the perceived distance to default.
This proxy correlates closely with more comprehensive metrics of balance sheet euroization, such as the currency mismatch index in Ranciere et al. (2010). Data requirements for these indices are larger than for FX bank loans, however, which would have restricted our sample significantly.
In some economies—notably Poland and Croatia—a significant part of FX loans is denominated in Swiss francs rather than euro (in Hungary, most CHF loans were converted into domestic currency, with a de-factor conversion date of November 2014). Thus, some currency mismatch would remain even after euro adoption.
The value of ECB access became apparent during the financial crisis of 2008/09, when cross-border currency markets became impaired. The problem was especially severe for banks with sizeable FX assets—and therefore high FX refinancing needs—but without a euro area based parent bank that could have accessed ECB facilities on their behalf.
The monetary conditions index is calculated as the weighted average of real interest rate and real exchange rate, with weights representing the impact of each component on domestic demand (see Appendix II).
This thought goes back as far as Wicksell (1898). It is also reflected in a simple Taylor rule that specifies the cyclical behavior of policy rates around a neutral rate. Policy rates that are systematically above/below the neutral rate will result in a monetary policy stance that is systematically too tight/too lose.
In Hungary, the scope for exchange rate depreciation was arguably constrained by the high share of FX loans, see Bakker and Gulde (2010).
In this regard, there is an important difference between countries with currencies tied to the euro and those already in the euro area (Slovak Republic and Slovenia), as the latter did not have to tighten monetary policy in order to defend a peg.
Bulgaria, for example, had a relatively muted demand contraction, arguably reflecting in part the use of fiscal buffers
This result holds even after controlling for the size of import exposure to the euro area.
The value of monetary autonomy is also being recognized by rating agencies, as the following quote from Standard and Poors’ (2015) illustrates: “Unlike in the Baltic countries, euro adoption would not immediately lead us to raise the ratings on Poland. This is because the Baltics, unlike Poland, already had currency pegs to the euro in place, which limited their monetary flexibility. Poland, on the other hand, has a flexible exchange rate, and the current ratings clearly take into account its monetary flexibility and effective monetary policymaking as a ratings strength. On the one hand, euro membership would give Poland access to a reserve currency and the ability to issue debt in it, which would be positive for the ratings. On the other hand, membership of a monetary union that has a monetary policy not necessarily geared toward the needs of individual countries could be ratings-negative, especially if we saw a strong asynchrony between European Central Bank (ECB) policies and a monetary policy stance needed for Poland’s purposes.”
It is worth noting that in case the NMS-6 were to adopt the euro, this would not only affect the NMS-6 but also the existing euro area members. The NMS-6 would account for about 8 percent of the euro area’s GDP (14 percent on a PPP basis), and a similar share of euro area consumption. In case convergence would resume at the same pace as in the early 2000s, staff estimates that NMS-6 adoption could increase average euro inflation by up to 0.3 percentage points, which would require a tighter monetary policy stance by the ECB to preserve its current inflation target. This, in turn, would further diminish space for nominal adjustment in case euro area members suffer asymmetric shocks.
The jury is still out on the effectiveness of these measures. A recent paper by Cerutti et al. (2015), for example, finds some effectiveness of macro-prudential policies in managing credit cycles, but also severe issues of avoidance through greater cross-border borrowing.
For the IIR, respondents grade each country on a scale of zero to 100, with 100 representing the least likelihood of default. Participants’ responses are weighed according to their institutions’ global exposure. As for the S&P index, the linearization assigns a value of 1 to an AAA rating, of 2 to AA+, and so on. We use the foreign currency sovereign credit rating, but for the vast majority of countries, the local and foreign currency ratings are identical.
This is consistent with claims that rating agencies downgraded euro area countries excessively in crisis—see, for example, Vernazza et al. (2014). The finding of a vanishing euro premium is consistent with the results in Heinz and Sun (2014) for credit spreads.
The pattern in the early 2000s reflects arguably more an improvement in investor perception of non-EU countries than a deterioration in the perception of EU member countries—see also Figure 1 in the main text.
With Arellano-Bond, the estimated size of the euro premium is on average smaller by about one-third.
Euroization correlates strongly with governance quality, thus inclusion of governance quality in X is necessary lest to overstate the link between euroization and perceived credibility.
The Baxter-King filter decomposes, in the frequency domain, the analyzed series into trend, cyclical, and irregular components, which are additive. For all countries, the Baxter-King filter is based on an 11-quarter centered moving average and a widely used definition of the business cycle—movements in economic series that occur with periodicity of between 6 quarters and eight years (32 quarters). In order to obtain estimates for the whole sample period, we augment the dataset with Fund staff forecasts through end-2016.
