Professor Jeffrey Frankel

1. Professor Jeffrey Frankel

2. Professor Jeffrey Frankel

3. Professor Jeffrey Frankel 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

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5. Professor Jeffrey Frankel 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).

6. Professor Jeffrey Frankel 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):

7. Professor Jeffrey Frankel Correlations Among Regime Classification Schemes Sample: 47 countries. From Frankel, ADB, 2004. Table 3, prepared by M. Halac & S.Schmukler.

8. Professor Jeffrey Frankel 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.

9. Professor Jeffrey Frankel The IMF now has its own “de facto classification”

10. Professor Jeffrey Frankel 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).

11. Professor Jeffrey Frankel Phrase this 1st approach in terms of Exchange Market Pressure: Define EMP = ? value of currency + ? 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).

12. Professor Jeffrey Frankel 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:

13. Professor Jeffrey Frankel 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.

14. Professor Jeffrey Frankel The 2nd approach in the de facto regime literature estimates implicit basket weights: Regress ?value of local currency against ? 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.

15. Professor Jeffrey Frankel Implicit basket weights method -- regress ?value of local currency against ? 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?

16. Professor Jeffrey Frankel 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.

17. Professor Jeffrey Frankel 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.

18. Professor Jeffrey Frankel 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.

19. Professor Jeffrey Frankel Statistical estimation of de facto exchange rate regimes Synthesis: “Estimation of De Facto Exchange Rate Regimes: Synthesis of the Techniques for Inferring Flexibility and Basket Weights” Frankel & Wei (IMF SP 2008)

20. Professor Jeffrey Frankel 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 ? logH(t) =c + ? w(j) [? logX(j)] (1)

21. Professor Jeffrey Frankel ? log Ht  = c + ? w(j) [? logX(j)t ] = c + w(1) ? log $ t + w(2) ? log ¥t  + w(3) ? log €t + a ? log £t

22. Professor Jeffrey Frankel 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.

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

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25. Professor Jeffrey Frankel 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)

26. Professor Jeffrey Frankel 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.

27. Professor Jeffrey Frankel 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.

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29. Professor Jeffrey Frankel 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.

30. Professor Jeffrey Frankel 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.

31. Professor Jeffrey Frankel 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.

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33. Professor Jeffrey Frankel 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 by A.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.

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35. Professor Jeffrey Frankel 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.

36. Professor Jeffrey Frankel 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%.

37. Professor Jeffrey Frankel 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.

38. Professor Jeffrey Frankel 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.)

39. Professor Jeffrey Frankel 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)

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42. Professor Jeffrey Frankel 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.

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46. Professor Jeffrey Frankel 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.

47. Professor Jeffrey Frankel 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)

48. Professor Jeffrey Frankel

49. Professor Jeffrey Frankel 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 Peg the Export Price

50. Professor Jeffrey Frankel (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?

51. Professor Jeffrey Frankel Brief literature summary Theory Chami et al (2008): remittances are macroeconomically stabilizing. Martin (1990): steady flow of remittances can undermine the incentive for governments to create a sound institutional framework – a sort of natural resource curse for remittances.  Bilateral Data Ratha and Shaw (2005), in the absence of hard bilateral data, allocate the totals across partners. Schiopu & Siegfried (2006) created bilateral data set between some EU countries & neighbors. Jiménez-Martin, Jorgensen, & Labeaga (2007) estimate bilateral workers’ remittance flows from all 27 members of the EU. Lueth & Ruiz-Arranz (2006, 2008) have largest bilateral data set to date.

52. Professor Jeffrey Frankel Literature review: cyclicality of remittances Evidence on cyclicality World Bank: p.c. remittances respond significantly to home country p.c.income. Clarke & Wallstein (2004) & Yang (2007): receipts rise in response to natural disaster. Kapur (2003): they go up in response to an economic downturn. Lake (2006): remittances into Jamaica respond to the US-local income difference Yang and Choi (2007): they respond to rainfall-induced economic fluctuations. IMF finds less countercyclicality. Sayan (2006): 12-developing-country study finds no countercyclicaty. Lueth & Ruiz-Arranz (2006, 2008): similarly. Evidence on the Dutch Disease. On the one hand, Rajan & Subramanian (2005): although the Dutch Disease analogy does extend to foreign aid (leading to real appreciation & slow growth), it does not extend to remittances. On the other hand, Amuendo-Dorantes & Pozo (2004): an increase in remittances to LACA countries leads to real appreciation, a major symptom of Dutch Disease. OCA Singer (2008): counter-cyclical remittances are a determinant of the currency decision.

53. Professor Jeffrey Frankel “Are Bilateral Remittances Countercyclical?Implications for…Currency Unions” -- Frankel (Oct. 2009) I combine the three substantial data sets on bilateral remittances that I know of: I find strong evidence of countercyclicality Lueth & Ruiz-Arranz (2006, 2008), for an eclectic set of countries (mostly in Europe & Asia), thanks to their generosity in supplying the data. Jiménez-Martin, Jorgensen, & Labeaga (2007) for EU sending countries. For Central American receiving countries (incl. DR, El Salvador & Panama) I find strong evidence of countercyclicality.

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55. Professor Jeffrey Frankel (ii) Level of financial development  Aghion, Bacchetta, Ranciere & Rogoff (2005) Fixed rates are better for countries at low levels of financial development: because markets are thin => benefits of accommodating real shocks are outweighed by costs of financial shocks. When financial markets develop, exchange flexibility becomes more attractive. Estimated threshold: Private Credit/GDP > 40%.

56. Professor Jeffrey Frankel Level of financial development, cont.  Husain, Mody & Rogoff, JME 52 , Jan. 2005 35-64 For poor countries with low capital mobility, pegs work in the sense of being more durable & delivering low inflation For richer & more financially developed countries, flexible rates work better in the sense of being more durable & delivering higher growth without inflation

57. Professor Jeffrey Frankel (iii) External Shocks An old wisdom regarding the source of shocks: Fixed rates work best if shocks are mostly internal demand shocks (especially monetary); floating rates work best if shocks tend to be real shocks (especially external terms of trade). One case of supply shocks: natural disasters R.Ramcharan, 2007, finds support. “Does the Exchange Rate Regime Matter for Real Shocks? Evidence from Windstorms and Earthquakes,” JIE. Most common case of real shocks: trade

58. Professor Jeffrey Frankel Terms-of-trade variability returns Prices of crude oil and other agricultural & mineral commodities hit record highs in 2008. => Favorable terms of trade shocks for some (oil producers, Chile, Africa, etc.); => Unfavorable terms of trade shock for others (oil importers like Japan, Korea). Textbook theory says a country where trade shocks dominate should accommodate by floating. Edwards & L.Yeyati (2003): Among peggers, terms-of-trade shocks are amplified and long-run growth is reduced, as compared to flexible-rate countries.

59. Professor Jeffrey Frankel Fashions in international currency policy 1980-82: Monetarism (target the money supply) 1984-1997: Fixed exchange rates  (incl. currency boards) 1993-2001: The corners hypothesis 1998-2008: Inflation targeting (+ currency float) became the new conventional wisdom Among academic economists Among central bankers At the IMF

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61. Professor Jeffrey Frankel Inflation targeting is the reigning orthodoxy. Economists, central bankers, IMF… Flexible inflation targeting =“Have a LR target for inflation, and be transparent.” ? Who could disagree? But define IT as setting yearly CPI targets, to the exclusion of asset prices exchange rates export commodity prices.

62. Professor Jeffrey Frankel The shocks of 2007-2010 have shown some disadvantages to Inflation Targeting, analogously to how the emerging market crises of 1994-2001 showed disadvantages to exchange rate targeting. One disadvantage of IT: no response to asset price bubbles. Another disadvantage: It gives the wrong answer in case of supply shocks: E.g., in response to a rise in oil import prices, it says to tighten monetary policy & appreciate, to keep CPI steady. In response to a rise in world prices of export commodities, it does not allow monetary tightening and appreciation.

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65. Professor Jeffrey Frankel How would it work operationally, say, for a Gulf oil-exporter? Each day, after noon spot price of oil in London S($/barrel), the central bank announces the day’s exchange rate, according to the formula: E (dirham/$) = fixed target price P(dirham/barrel) / S($/barrel). It intervenes in $ to hold this exchange rate for the day. The result is that P (dirham/barrel) is indeed fixed from day to day.

66. Professor Jeffrey Frankel Does floating give the same answer? True, commodity currencies tend to appreciate when commodity markets are strong, & vice versa Australian, Canadian & NZ $ (e.g., Chen & Rogoff, 2003) South African rand (e.g., Frankel, 2007) Chilean peso and others But Some volatility under floating appears gratuitous. Floaters still need a nominal anchor.

67. Professor Jeffrey Frankel The Rand, 1984-2006:Fundamentals (real commodity prices,real interest differential, country risk premium, & l.e.v.) can explain the real appreciation of 2003-06 – Frankel (SAJE, 2007).

68. Professor Jeffrey Frankel Why is PEP better than CPI-targetingfor countries with volatile terms of trade? Better response to adverse terms of trade shocks: If the $ price of imported commodity goes up, CPI target says to tighten monetary policy enough to appreciate currency. Wrong response. (E.g., oil-importers in 2007-08.) If the $ price of the export commodity goes up, PEP says to tighten monetary policy enough to appreciate currency. Right response. (E.g., Gulf currencies in 2007-08.)

69. Professor Jeffrey Frankel PEP, in its strict form, has some disadvantages Passes every fluctuation in world commodity prices straight through to domestic-currency prices of other TGs, creating high volatility Even for countries where non-commodity TGs are a small share of the economy, some would like to nurture this sector, so as to encourage diversification in the long run. Exposing it to full volatility could shrink non-commodity TG sector. The volatility is undesirable, in particular, for those short-term fluctuations that are likely to be reversed. Better to dampen real exchange rate fluctuations a bit, until terms of trade shift appears permanent.

70. Professor Jeffrey Frankel Moderate versions of PEP Target a broader Export Price Index (PEPI). 1st step for any central bank dipping its toe in these waters: compute monthly export price index. 2nd step: announce that it is monitoring the index. Target a basket of major currencies ($, €, ¥) and minerals. A still more moderate, still less exotic-sounding, version of PEPI proposal: target a monthly index of producer prices. Key point: exclude import prices from the index, & include export prices. Flaw of CPI target: it does it the other way around.

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