Exchange Rate Regimes: Current Issues in Research & Policy Jeffrey Frankel

1. Exchange Rate Regimes: Current Issues in Research & Policy Jeffrey Frankel Harpel Chair, Harvard University IMF Institute  * May 28, 2010 * Professor Jeffrey Frankel

2. Topics to be covered • I. Classifying countries by exchange rate regime • De facto vs. de jure • The approaches used to infer de facto regimes • II. Advantages of fixed rates • The trade-promoting effect of currency unions: the € case • III. Advantages of floating rates • IV. Which regime dominates? • V. Additional factors for developing countries • Emigrants’ remittances • Financial development • Terms-of-trade shocks; the PEP proposal • Appendices: • The RMB case • Corners • More on synthesis technique for regime estimation Professor Jeffrey Frankel

3. I. Classification of exchange rate regimes:Continuum from flexible to rigid FLEXIBLE CORNER 1) Free float 2) Managed float INTERMEDIATE REGIMES 3) Target zone/band 4) Basket peg 5) Crawling peg 6) Adjustable peg FIXED CORNER 7) Currency board 8) Dollarization 9) Monetary union Professor Jeffrey Frankel

4. Intermediate regimes • target zone (band) • Krugman-ERM type (with nominal anchor) • Bergsten-Williamson type (FEER adjusted automatically) • basket peg • weights can be either transparent • or secret • crawling peg • pre-announced (e.g., tablita) • indexed (to fix real exchange rate) • adjustable peg • (escape clause, e.g., contingent • on terms of trade or reserve loss) Professor Jeffrey Frankel

5. De jure regime  de facto as is by now well-known • Many countries that say they float, in fact intervene heavily in the foreign exchange market. [1] • Many countries that say they fix, in fact devalue when trouble arises. [2] • Many countries that say they target a basket of currencies, in fact fiddle with the weights. [3] [1] “Fear of floating” -- Calvo & Reinhart (2001, 2002); Reinhart (2000). [2] “The mirage of fixed exchange rates” -- Obstfeld & Rogoff(1995);Klein & Marion(1997). [3] Parameters kept secret -- Frankel, Schmukler & Servén(2000). Professor Jeffrey Frankel

6. Economists have offered de facto classifications, placing countries into the “true” categories • Important examples include Ghosh, Gulde & Wolf(2000),Reinhart & Rogoff(2004),Shambaugh(2004a), & more to be cited. • Tavlas, Dellas & Stockman(2008)survey the literature. • Unfortunately, these classification schemes disagree with each other as much as they disagree with the de jure classification! [1] • => Something must be wrong. [1] See Bénassy-Quéré, et al(Table 5, 2004); Frankel(Table 1, 2004); and Shambaugh(2004b): Professor Jeffrey Frankel

7. Correlations Among Regime Classification Schemes Sample: 47 countries. From Frankel, ADB, 2004.Table 3, prepared by M. Halac & S.Schmukler. GGW =Ghosh, Gulde & Wolf. LY-S = Levy-Yeyati & Sturzenegger. R-R = Reinhart & Rogoff Professor Jeffrey Frankel

8. Shambaugh (2007) finds the same thing:the de facto classification schemes tend to agree with each other even less than they agree with the de jure scheme. Professor Jeffrey Frankel

9. The IMF now has its own “de facto classification” -- but still close to official IMF one: correlation (BOR, IMF) = .76 Bénassy-Quéré et al(2004) Professor Jeffrey Frankel

10. => Something must be wrong. Several things are wrong. Difficulty #1:Attempts to infer statistically a currency’s flexibility from the variability of its exchange rate alone ignore that some countries experience greater shocks than others. That problem can be addressed by comparing exchange rate variability to foreign exchange reserve variability: • Calvo & Reinhart (2002); • Levy-Yeyati & Sturzenegger (2003, 2005). Professor Jeffrey Frankel

11. Phrase this 1st approach in terms of Exchange Market Pressure: • Define EMP = Δ value of currency + Δ reserves. • EMP represents shocks in currency demand. • Flexibility can be estimated as the propensity of the central bank to let shocks show up in the price of the currency (floating) ,vs. the quantity of the currency (fixed), or in between (intermediate exchange rate regime). Professor Jeffrey Frankel

12. Several things are wrong, continued. Difficulty #2:Those papers sometimes impose the choice of the major currency around which the country in question defines its value (often the $). • It would be better to estimate endogenously whether the anchor currency is the $, the €, some other currency, or some basket of currencies. • That problem has been addressed by a 2nd approach: Professor Jeffrey Frankel

13. Some currencies have basket anchors, often with some flexibility that can be captured either by a band (BBC) or by leaning-against-the-wind intervention. • Most basket peggers keep the weights secret. They want to preserve a degree of freedom from prying eyes,whether to pursue • a less de facto flexibility, as China, • or more, as with most others. Professor Jeffrey Frankel

14. The 2nd approach in the de facto regime literature estimates implicit basket weights: Regress Δvalue of local currency against Δ values of major currencies. • First examples: Frankel(1993) and Frankel & Wei(1994, 95). • More:Bénassy-Quéré(1999), Ohno(1999),Frankel, Schmukler, Servén & Fajnzylber(2001),Bénassy-Quéré, Coeuré, & Mignon(2004)…. • Example of China, post 7/05: • Eichengreen (2006), Shah, Zeileis & Patnaik (2005), Yamazaki (2006), Ogawa (2006), Frankel-Wei (2006, 07), Frankel (2009) • Findings: • RMB still pegged in 2005-06, with 95% weight on $. • Moved away from $ (weight on €) in 2007-08 • Returned to $ peg in mid 2008. Professor Jeffrey Frankel

15. Implicit basket weights method -- regress Δvalue of local currency against Δ values of major currencies -- continued. • Null Hypotheses: Close fit => a peg. • Coefficient of 1 on $ => $ peg. • Or significant weights on other currencies => basket peg. • But if the test rejects tight basket peg, what is the Alternative Hypothesis? Professor Jeffrey Frankel

16. Several things are wrong, continued. Difficulty #3: The 2nd approach (inferring the anchor currency or basket) does not allow for flexibility around that anchor. • Inferring de facto weights and inferring de facto flexibility are equally important, • whereas most authors have hitherto done only one or the other. Professor Jeffrey Frankel

17. The synthesis technique • A synthesis of the two approaches for statistically estimating de facto exchange rate regimes:(1) the technique that we have used in the past to estimate implicit de facto weights when the hypothesis is a basket peg with little flexibility. + (2) the technique used by others to estimate de facto exchange rate flexibility when the hypothesis is an anchor to the $, but with variation around that anchor. • => We need a synthesis that can cover both dimensions: inferring weights and inferring flexibility. Professor Jeffrey Frankel

18. Several things are wrong, continued. Difficulty #4:All these approaches, even the synthesis technique, are plagued by the problem that many countries frequently change regimes or (for those with intermediate regimes) change parameters. • E.g., Chile changed parameters 18 times in 18 years (1980s-90s) • Year-by-year estimation won’t work, because parameter changes come at irregular intervals. • Chow test won’t work, because one does not usually know the candidate dates. • Solution: Apply Bai-Perron (1998, 2003) technique for endogenous estimation of structural break point dates. Professor Jeffrey Frankel

19. Estimation of implicit weightsin basket peg: Frankel(1993),Frankel & Wei(1993, 94, 95); Ohno (1999), F, Schmukler & Servén(2000),Bénassy-Quéré (1999, 2006)… Statistical estimation of de facto exchange rate regimes Estimation of degree of flexibilityin managed float: Calvo & Reinhart (2002); Levi-Yeyati & Sturzenegger (2003)… Synthesis: “Estimation of De Facto Exchange Rate Regimes: Synthesis of the Techniques for Inferring Flexibility and Basket Weights”Frankel & Wei (IMF SP2008) Application to RMB:Eichengreen (06), Ogawa (06), F & Wei (07) Application to RMB: Frankel(2009) Econometric estimation of structural break points: Bai & Perron(1998, 2003) Allow for parameter variation: “Estimation of De Facto Flexibility Parameter and Basket Weights in Evolving Exchange Rate Regimes”F & Xie (AER, 2010) Professor Jeffrey Frankel

20. The technique that estimates basket weights • Assuming the value of the home currency is determined by a currency basket, how does one uncover the currency composition & weights? Regress changes in log H, the value of the home currency, against changes in log values of candidate currencies. • Algebraically, if the value of the home currency H is pegged to the values of currencies X1, X2, … & Xn, with weights equal to w1, w2, … & wn, then ΔlogH(t) =c + ∑ w(j) [ΔlogX(j)] (1) Professor Jeffrey Frankel

21. Δ log Ht = c + ∑ w(j) [Δ logX(j)t ] = c + w(1) Δ log $t+ w(2) Δ log ¥t + w(3) Δ log €t + α Δ log £t • If the exchange rate is governed by a strict basket peg, • we should recover the true weights, w(j), precisely; • and the equation should have a perfect fit. Professor Jeffrey Frankel

22. Distillation of technique to infer flexibility • When a shock raises international demand for the currency, do the authorities allow it to show up as an appreciation, or as a rise in reserves? • Frame the issue in terms of Exchange Market Pressure (EMP), defined as: % increase in the value of the currency plus increase in reserves (as share of monetary base). • EMP variable appears on the RHS of the equation. The % rise in the value of the currency appears on the left. • A coefficient of 0 on EMP signifies a fixed E(no changes in the value of the currency), • a coefficient of 1 signifies a freely floating rate (no changes in reserves) and • a coefficient somewhere in between indicates a correspondingly flexible/stable intermediate regime. Professor Jeffrey Frankel

23. Synthesis equation Δ logH(t) = c + ∑ w(j) Δ[logX(j, t)] + ß {Δ EMP(t)} + u(t) (2) where Δ EMP(t) ≡ Δ[logH(t)] + [ΔRes(t) / MB(t)]. We impose ∑ w(j) = 1, implemented by treating £ as the last currency. Professor Jeffrey Frankel

24. Now we introduce Bai-Perron technique for endogenous estimation of m possible structural break points (6) For further details, see NBER WP, Dec. 2009. Professor Jeffrey Frankel

25. Illustration using 5 currencies • These are 5 emerging market currencies of interest all of which now make available their data on reserves on a weekly basis (which is necessary to get good estimates, if structural changes happen as often as yearly) • Mexico (monetary base is also available weekly) • Chile, Russia, Thailand, India (although reserves available weekly, denominator must be interpolated from monthly monetary base data) Professor Jeffrey Frankel

26. Overview of findings • For all five, the estimates suggest managed floats during most of the period 1999-2009. • This was a new development for emerging markets. • Most of the countries had had some variety of a peg before the currency crises of the 1990s. • But the Bai-Perron test shows statistically significant structural breaks for every currency, • even when the threshold is set high, at the 1% level of statistical significance. Professor Jeffrey Frankel

27. Table 1A reports estimation for the Mexican peso • 5 structural breaks • The peso is known as a floater. • To the extent Mexico intervenes to reduce exchange rate variation, $ is the primary anchor, but some weight on € also appears, starting in 2003. • Aug.2006 - Dec.2008, coefficient on EMP is essentially 0, surprisingly, suggesting intervention around a $ target. • But in the period starting Dec.2008, the peso once again moved away from the currency to the north, as the worst phase of the global liquidity crisis hit and $ appreciated. Professor Jeffrey Frankel

28. Table 1A. Identifying Break Points in Mexican Exchange Rate Regime M1:1999-M7:2009 Professor Jeffrey Frankel

29. Tables 1B-1E • Chile (with 3 estimated structural breaks) appears a managed floater throughout. • The anchor is exclusively the $ in some periods, but puts significant weight on the € in other periods. • Russia (3 structural breaks) is similar, except that the $ weight is always significantly less than 1. • For Thailand (3 structural breaks), the $ share in the anchor basket is slightly > .6, but usually significantly < 1. • The € & ¥ show weights of about .2 each Jan.1999-Sept. 2006. • India (5 structural breaks) apparently fixed its exchange rate during two of the sub-periods, but pursued a managed float in the other four sub-periods. • $ was always the most important of the anchor currencies, but the € was also significant in four out of six sub-periods, and the ¥ in two. Professor Jeffrey Frankel

30. Future research • Results for other currencies will be published in other papers • Often requiring weekly interpolation between monthly reserve figures. • Including our China updates • And true basket/band/crawl currencies • Econometric extension: use Threshold Autoregression for target zones. Professor Jeffrey Frankel

31. Bottom line on classifying exchange rate regimes • It is genuinely difficult to classify most countries’ de facto regimes: intermediate regimes that change over time. • Need techniques • that allow for intermediate regimes (managed floating and basket anchors) • and that allow the parameters to change over time. Professor Jeffrey Frankel

32. II. Advantages of fixed rates • Encourage trade <= lower exchange risk. • In theory, can hedge risk. But costs of hedging: • missing markets, transactions costs, and risk premia. • Empirical: Exchange rate volatility ↑ => trade ↓ ? • Time-series evidence showed little effect. But more in: • - Cross-section evidence, • especially small & less developed countries.- Borders, e.g., Canada-US: McCallum-Helliwell (1995-98); Engel-Rogers (1996). • - Currency unions: Rose (2000). Professor Jeffrey Frankel

33. The case of the euro’s effect on tradeFrankel,“The Estimated Effects of the Euro on Trade:  Why are They Below Historical Evidence on Effects of Monetary Unions Among Smaller Countries?” in Europe and the Euro, edited byA.Alesina & F.Giavazzi, 2010. • Gravity estimates of effect of € on intra-EMU trade in the first decade show the coefficient steady ≈ 15% . • << estimates of other Monetary Unions’ effects (x2 or x3) • No evidence that the gap is explained by a MU effect that • diminishes with country size, or • is subject to long lags. Professor Jeffrey Frankel

34. Why is the estimated effect in euro-land so much smaller than monetary unions among small developing countries? Professor Jeffrey Frankel

35. A natural experiment:The effects of the French franc’s conversion to € on bilateral trade of African CFA members. The long-time link of CFA currencies to the French franc has clearly always had a political motivation. So CFA-France trade could not reliably be attributed to currency link, perhaps even after controlling for common language, former colonial status, etc. But in Jan. 1999, 14 CFA countries suddenly found themselves with the same currency link to Germany, Austria, Finland, etc. No economic/political motivation. A natural experiment. If CFA trade with these other countries has risen, that suggests a € effect that we can declare causal. 35 Professor Jeffrey Frankel

36. Results of CFA experiment The dummy variable representing when one partner is a CFA country and the other a € country has a highly significant coefficient of .57. Taking the exponent, the point estimate is that the euro boosts bilateral trade between the relevant African and € countries by 76%. 36 Professor Jeffrey Frankel

37. Bottom line on discrepancy in € effect • The large effect of monetary unions on developing countries is real. • Tentative conclusion: • Although monetary unions don’t have larger effects on small countries per se, • They do have larger effects on poor countries per se. Professor Jeffrey Frankel

38. Advantages of fixed rates, cont. 2) Encourage investment <= cut currency premium out of interest rates 3) Provide nominal anchor for monetary policy • Barro-Gordon model of time-consistent inflation-fighting • But which anchor? • Exchange rate target vs. • Alternatives such as Inflation Targeting 4) Avoid competitive depreciation 5) Avoid speculative bubbles that afflict floating. (If variability were all fundamental real exchange rate risk, and no bubbles, then fixing the nominal rate would mean it would just pop up in prices instead.) Professor Jeffrey Frankel

39. Most important finding of last decade • Empirical finding of Rose (2000) that the boost to bilateral trade from currency unions is significant, ≈ FTAs, & larger (3-fold) than had been thought. • Many others have advanced critiques of Rose research. • Re: Endogeneity, small countries, missing variables & sheer magnitude. • Estimated magnitudes are often smaller, but the basic finding has withstood perturbations and replications remarkably well. ii/ • Some developing countries seeking regional integration talk of following Europe’s lead, tho plans merit skepticism. • Parsley-Wei: currency effect explains border effects. • Klein-Shambaugh: de facto pegs have major effect too. [ii] E.g., Rose & van Wincoop (2001); Tenreyro & Barro (2003). Survey: Baldwin (2006) Professor Jeffrey Frankel

40. Evidence on currency unions • Currency unions • promote trade/GDP (no evidence of trade-diversion), & • thereby promote LR growth. -- Frankel & Rose, QJE, 2002. • Endogeneity of OCA criteria: • Trade responds positively to currency regime • A pair’s cyclical correlation rises too(rather than falling, as under Eichengreen-Krugman hypothesis)-- Frankel & Rose, EJ, 1996 Professor Jeffrey Frankel

41. III. Advantages of floating rates • Monetary independence • Automatic adjustment to trade shocks • Retain seignorage • Retain Lender of Last Resort ability • Avoiding crashes that hit pegged rates. (This is an advantage especially if origin of speculative attacks is multiple equilibria, not fundamentals.) Professor Jeffrey Frankel

42. IV. Which dominate: advantages of fixing or advantages of floating?Performance by category is inconclusive. • To over-simplify findings of 3 important studies: • Ghosh, Gulde & Wolf: hard pegs work best • Sturzenegger & Levy-Yeyati: floats perform best • Reinhart-Rogoff: limited flexibility is best • Why the different answers? • Conditioning factors. • The de facto schemes do not correspond to each other. Professor Jeffrey Frankel

43. Which category experienced the most rapid growth? • Ghosh, Gulde & Wolf: currency boards • Levy-Yeyati &Sturzenegger: floating • Reinhart & Rogoff:limited flexibility Professor Jeffrey Frankel

44. Which dominate: advantages of fixing or advantages of floating? Answer depends on circumstances, of course: No one exchange rate regime is rightfor all countries or all times. • Traditional criteria for choosing - Optimum Currency Area.Focus is on trade and stabilization of business cycle. • 1990s criteria for choosing –Focus is on financial markets and stabilization of speculation. Professor Jeffrey Frankel

45. Optimum Currency Area Theory (OCA) Broad definition: An optimum currency area is a region that should have its own currency and own monetary policy. This definition can be given more content:. An OCA can be defined as: a region that is neither so small and open that it would be better off pegging its currency to a neighbor, nor so large that it would be better off splitting into sub-regions with different currencies Professor Jeffrey Frankel

46. Optimum Currency Area criteria for fixing exchange rate: • Small size and openness • because then advantages of fixing are large. • Symmetry of shocks • because then giving up monetary independence is a small loss. • Labor mobility • because then it is possible to adjust to shocks even without ability to expand money, cut interest rates or devalue. • Fiscal transfers in a federal system • because then consumption is cushioned in a downturn. Professor Jeffrey Frankel

47. New popularity in 1990s ofinstitutionally-fixed corner • currency boards (e.g., Hong Kong, 1983- ; Lithuania, 1994- ; Argentina, 1991-2001; Bulgaria, 1997- ; Estonia 1992- ; Bosnia, 1998- ; …) • dollarization (e.g, Panama, El Salvador, Ecuador) • monetary union (e.g., EMU, 1999) Professor Jeffrey Frankel

48. 1990’s criteria for the firm-fix corner suiting candidates for currency boards or union (e.g. Calvo) Regarding credibility: • a desperate need to import monetary stability, due to: • - history of hyperinflation, • - absence of credible public institutions, • - location in a dangerous neighborhood, or • - large exposure to nervous international investors • a desire for close integration with a particular neighbor or trading partner • Regarding other “initial conditions”: • an already-high level of private dollarization • high pass-through to import prices • access to an adequate level of reserves • the rule of law. Professor Jeffrey Frankel

49. V. Three additional considerations, particularly relevant to developing countries • (i) Emigrants’ remittances • (ii) Level of financial development • (iii) External terms of trade shocks and the proposal to Pegthe Export Price Professor Jeffrey Frankel

50. (i) I would like to add another criterionto the traditional OCA list:Cyclically-stabilizing emigrants’ remittances. • If country S has sent many immigrants to country H, and their remittances are correlated with the differential in growth or employment in S versus H, this strengthens the case for s pegging to H. • Why? It helps stabilize S’s current account even when S has given up ability to devalue. • But are remittances stabilizing,in the way that private capital flows promise to be in theory, but fail in practice? Professor Jeffrey Frankel