professor jeffrey frankel exchange rate regimes: current issues in research & policy jeffrey...

Professor Jeffrey Frankel

Exchange Rate Regimes:Current Issues in Research & Policy

Jeffrey Frankel

Harpel Chair, Harvard University

IMF Institute

* May 28, 2010 *


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: 1. The RMB case2. Corners3. More on synthesis technique for regime estimation


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

I. Classification of exchange rate regimes:Continuum from flexible to rigid


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., contingenton terms of trade or reserve loss)


• 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).

De jure regime de factoas is by now well-known


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):


Correlations Among Regime Classification Schemes

Sample: 47 countries. From Frankel, ADB, 2004. Table 3, prepared by M. Halac & S.Schmukler.

IMF GGW LY-S R-R

IMF 1.00 (100.0)

GGW 0.60 (55.1)

1.00 (100.0)

LY-S 0.28 (41.0)

0.13 (35.3)

1.00 (100.0)

R-R 0.33 (55.1)

0.34 (35.2)

0.41 (45.3)

1.00 (100.0)

(Frequency of outright coincidence, in %, given in parenthesis.)

GGW =Ghosh, Gulde & Wolf. LY-S = Levy-Yeyati & Sturzenegger. R-R = Reinhart & Rogoff


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.

Percentage agreement of methodologies to code who pegs

De

Jure Jay S. LY-S R-R

De Jure

100%

Jay S.

86% 100%

LY-S

74% 80% 100%

R-R

81% 82% 73% 100%


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)


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).

=> Something must be wrong.


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).


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:


• 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.


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.


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?



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.


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.



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.


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)

Estimation of implicit weights in basket peg: Frankel (1993), Frankel & Wei (1993, 94, 95); Ohno (1999), F, Schmukler & Servén (2000), Bénassy-Quéré (1999, 2006)…

Estimation of degree of flexibility in managed float: Calvo & Reinhart (2002); Levi-Yeyati & Sturzenegger (2003)…

Allow for parameter variation: “Estimation of De Facto Flexibility Parameter and Basket Weights in Evolving Exchange Rate Regimes” F & Xie (AER, 2010)

Application to RMB: Frankel (2009) Econometric estimation of structural break points: Bai & Perron (1998, 2003)

Application to RMB:Eichengreen (06), Ogawa (06), F & Wei (07)


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

Δ logH(t) =c + ∑ w(j) [Δ logX(j)] (1)


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.


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.


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.


ttitji

k

jjiit uEMPXwcH

,,1

, loglog

1,...,1 ; ;0 ;,...,1 101 miTTTTTt mii

(6)

Now we introduce Bai-Perron technique for endogenous estimation

of m possible structural break points

For further details, see NBER WP, Dec. 2009.


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)

http://images.google.com/imgres?imgurl=http://www.thai-eyes.com/wp-content/uploads/2008/03/thai-baht.jpg&imgrefurl=http://www.thai-eyes.com/thai-bath-exchange-rate-thailand/&usg=__b3VEGoJEQQutmtCR46eSyGNE4gA=&h=272&w=470&sz=47&hl=en&start=4&um=1&tbnid=hY5jIBfBdEGELM:&tbnh=75&tbnw=129&prev=/images%3Fq%3Dthai%2Bbaht%26hl%3Den%26rlz%3D1T4GGLL_enUS309US342%26sa%3DN%26um%3D1


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.


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.


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

(1) (2) (3) (4) (5) (6)

VARIABLES 1/21/1999-9/2/2001

9/9/2001-3/18/2003

3/25/2003-7/29/2006

8/5/2006-1/28/2008

2/4/2008- 12/15/2008

12/22/2008-7/29/2009

US dollar 0.92*** 0.88*** 0.62*** 1.11*** 0.96*** 0.20(0.09) (0.12) (0.07) (0.10) (0.19) (0.22)

euro 0.14 -0.09 0.30*** 0.20* 0.51*** 0.51***(0.08) (0.14) (0.09) (0.11) (0.16) (0.18)

Jpn yen -0.05 0.22*** 0.08 -0.34*** -0.33** 0.18(0.06) (0.07) (0.06) (0.06) (0.12) (0.13)

△EMP 0.14*** 0.32*** 0.17*** 0.02 0.07 0.28***(0.03) (0.03) (0.03) (0.02) (0.07) (0.04)

Constant 0.00 -0.00*** -0.00* -0.00 -0.00 0.00

(0.00) (0.00) (0.00) (0.00) (0.00) (0.00)

Observations 131 78 168 76 46 29

R-squared 0.62 0.86 0.69 0.67 0.54 0.78

Br. Pound -0.01 -0.01 -0.01 0.02 -0.14 0.11


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.

http://images.google.com/imgres?imgurl=http://www.thai-eyes.com/wp-content/uploads/2008/03/thai-baht.jpg&imgrefurl=http://www.thai-eyes.com/thai-bath-exchange-rate-thailand/&usg=__b3VEGoJEQQutmtCR46eSyGNE4gA=&h=272&w=470&sz=47&hl=en&start=4&um=1&tbnid=hY5jIBfBdEGELM:&tbnh=75&tbnw=129&prev=/images%3Fq%3Dthai%2Bbaht%26hl%3Den%26rlz%3D1T4GGLL_enUS309US342%26sa%3DN%26um%3D1


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.


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.


II. Advantages of fixed rates

1) 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).


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.

1. Gravity estimates of effect of € on intra-EMU trade in the first decade show the coefficient steady ≈ 15% .

2. << estimates of other Monetary Unions’ effects (x2 or x3)

3. No evidence that the gap is explained by a MU effect that1. diminishes with country size, or

2. is subject to long lags.

http://www.hks.harvard.edu/fs/jfrankel/EuroTradeNBER08Milan.doc

http://www.hks.harvard.edu/fs/jfrankel/EuroTradeNBER08Milan.doc

http://www.nber.org/books/ales08-1/


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


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.


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%.


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.


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.)


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)


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


III. Advantages of floating rates

1. Monetary independence

2. Automatic adjustment to trade shocks

3. Retain seignorage

4. Retain Lender of Last Resort ability

5. Avoiding crashes that hit pegged rates. (This is an advantage especially if origin of speculative attacks is multiple equilibria, not fundamentals.)


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.


Which category experienced the most rapid growth?

Levy-Yeyati & Sturzenegger: floating

Reinhart & Rogoff:limited flexibility

Ghosh, Gulde & Wolf: currency boards


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.


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


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.


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)


1990’s criteria for the firm-fix cornersuiting 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.


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


(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?


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.


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 .


““Are Bilateral Remittances Countercyclical?Are Bilateral Remittances Countercyclical?

Implications for…Currency UnionsImplications for…Currency Unions”” -- Frankel -- Frankel (Oct. 2009)(Oct. 2009)

I combine the three substantial data sets on I combine the three substantial data sets on bilateral remittances that I know of:bilateral remittances that I know of: I find strong evidence of countercyclicality 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.I find strong evidence of countercyclicality.


Table 3: Cross-Section 2003-04 --Composite data set (merging three sources)

Dependent Variable:

Ln Remittances 2003-04 between Countries

(1) (2) (3) (4)

Ln (Stock migrants 2000 ) 0.762*** 0.741*** 1.061*** 1.233***

(0.040) (0.041) (0.088) (0.152)

Cyclical Difference (Ln (Real GDP/ Trend GDP)) 16.199*** 16.099*** 14.723*** 13.983***

Sender relative to recipient (2.905) (2.765) (3.390) (3.927)

GDP per capita Sender 0.039*** 0.028* 0.022

(0.015) (0.016) (0.019)

Currency Union 1.345*** 0.087 -0.590

(0.222) (0.389) (0.632)

Estimation Method OLS OLS 2SLS 2SLS

Instrumental variables

border/language/islands/colonial

border/language

Observations 331 328 328 328

R2 0.526 0.546 0.463 0.351

Statistical significance: * 10% level, ** 5% level, *** 1% level

Three sources of remittance data for 2003-04: Central America data, FOMIN and the Central Banks; EU data: Jiménez-Martín, S., Jorgensen, N. and Labeaga, J. M. (2007); IMF data: Lueth, E. and Ruiz-Arranz, M. (2006).


(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%.


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


(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


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.


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


Source: IMF Survey. October 23, 2000. Andrea Schaechter, Mark Stone, Mark Zelmer in the IMF, MEA Dept. Online at: http://www.imf.org/external/pubs/ft/survey/2000/102300.pdfThe background papers for the high-level seminar “Implementing Inflation Targets,” 2000,available on the IMF Website: http://www.imf.org/external/pubs/ft/seminar/2000/targets/index.htm

Inflation Targeting:“It’s not just for rich countries anymore”


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.


• 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.


Proposal to Peg the Export Price (PEP)

Intended for countries with volatile terms of trade, particularly those specialized in the production of mineral or agricultural commodity exports.

Proposal in its pure form: The authorities peg the currency to a basket or price index that includes the price of their leading commodity export (oil, gold, copper, coffee…), rather than to the $ or € or CPI.

My claim is that the regime combines the best of both worlds:

(i) The advantage of automatic accommodation to terms of trade shocks, together with

(ii) the advantages of a nominal anchor and integration.


6 proposed nominal targets and the Achilles heel of each:

Targeted variable

Vulnerability Example

Monetarist rule

M1 Velocity shocks US 1982

Inflation targeting CPI

Import price

shocks Oil shocks of

1973-80, 2000-08

Nominal income targeting

Nominal GDP

Measurement problems

Less developed countries

Gold standard Price

of gold Vagaries of world

gold market 1849 boom; 1873-96 bust

Commodity standard

Price of agric. & mineral

basket

Shocks in imported

commodity

Oil shocks of 1973-80, 2000-08

Fixed exchange rate

$ (or €)

Appreciation of $ (or € ) 1995-2001


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.

PEP


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.


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).

0.000

20.000

40.000

60.000

80.000

100.000

120.000

140.000

160.000

180.000

200.000

RERICPIactual RERICPIFitted RERICPIProjected

Actual vs Fitted vs. Actual vs Fitted vs. Fundamentals-Fundamentals-

Projected Projected ValuesValues


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.)

PEP


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.

PEP


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.

PEP


Readings:

Fischer, Stanley, 2001, “Exchange Rate Regimes: Is the Bipolar View Correct?” Journal of Economic Perspectives 15 (2).

Frankel, Jeffrey, 2003, “Experience of and Lessons from Exchange Rate Regimes in Emerging Economies,” in Monetary and Financial Cooperation in East Asia, ADB ( Macmillan).

Frankel, 2009, “A Comparison of Monetary Anchor Options for Commodity-Exporters in Latin America and the Caribbean,” Myths and Realities of Commodity Dependence: Policy Challenges and Opportunities for Latin America and the Caribbean, World Bank, Sept.

Frankel, and Daniel Xie, 2010, “Estimation of De Facto Flexibility Parameter and Basket Weights in Evolving Exchange Rate Regimes,” American Economic Review Papers & Proceedings 100, May.

Ghosh, Atish, Anne-Marie Gulde, and Holger C. Wolf, 2000, “Currency Boards: More Than a Quick Fix?” Economic Policy 31.

Rogoff, Kenneth, and Maurice Obstfeld, 1995, “The Mirage of Fixed Exchange Rates,” J. of Econ. Perspectives 9, No. 4 (Fall).

Rose, Andrew, 2000, “One Money, One Market: Estimating the Effect of Common Currencies on Trade,” Economic Policy.

Taylor, Alan, 2002, “A Century of Purchasing Power Parity,” Rev. Ec. & Statistics, 84.

http://www.hks.harvard.edu/fs/jfrankel/LACA-PEP-09.doc

http://www.hks.harvard.edu/fs/jfrankel/LACA-PEP-09.doc


Additional Readings:

Arteta, Carlos, 2005, “Exchange Rate Regimes and Financial Dollarization: Does Flexibility Reduce Currency Mismatches,” Topics in Macroeconomics 5, no. 1, Article 10.

Calvo, Guillermo, and Carmen Reinhart, 2002, “Fear of Floating,” Quarterly J. Economics, 117, no. 2.

Calvo, Guillermo, and Carlos Vegh, 1994, “Inflation Stabilization and Nominal Anchors,” Contemporary Economic Policy, 12 (April).

Eichengreen, Barry, Paul Masson, Miguel Savastano, and Sunil Sharma, 1999, “Transition Strategies and Nominal Anchors on the Road to Greater Exchange Rate Flexibility,” Essays in International Finance, No. 213 (Princeton: Princeton University Press).

Frankel, Jeffrey, 2003, “A Proposed Monetary Regime for Small Commodity-Exporters: Peg the Export Price (‘PEP’),” International Finance, Spring.

___, “A Proposal to Tie Iraq’s Currency to Oil,” Financial Times, June 13, 2003.

Frankel, and Andrew Rose, 1998, “The Endogeneity of the Optimum Currency Area Criterion,” The Economic Journal.

___, and ___, 2002, “An Estimate of the Effect of Common Currencies on Trade and Income,” Quarterly Journal of Economics.

Frankel, and Shang-Jin Wei, 2008, “Estimation of De Facto Exchange Rate Regimes: Synthesis of the Techniques for Inferring Flexibility and Basket Weights,” IMF Staff Papers.

http://ksghome.harvard.edu/~jfrankel/F&W-EstDeFactoExRR-IMFSP08.pdf

http://ksghome.harvard.edu/~jfrankel/F&W-EstDeFactoExRR-IMFSP08.pdf


Friedman, Milton, 1953, “The Case for Flexible Exchange Rates,” in Essays in Positive Economics.

Husain, Asim, Ashoka Mody & Kenneth Rogoff, 2005, “Exchange Rate Regime Durability and Performance in Developing Vs. Advanced Economies” JME 52 , Jan.35-64.

Ishii, Shogo, et al, Exchange Arrangements and Foreign Exchange Markets (IMF) 2003.

Levy-Yeyati, Eduardo, and Federico Sturzenegger, 2003, “To Float or to Trail: Evidence on the Impact of Exchange Rate Regimes,” American Economic Review, 93, No. 4, Sept. .

McKinnon, Ronald, 1963, “Optimum Currency Areas,” American Economic Review, Sept., pp. 717-24

Mundell, Robert, 1961, “A Theory of Optimum Currency Areas,” AER, Nov., pp. 509-17.

Parsley, David, and Shang-Jin Wei, 2001, "Explaining the Border Effect: The Role of Exchange Rate Variability, Shipping Costs, and Geography,” Journal of International Economics, 55, no. 1, 87-106.

Reinhart, Carmen, and Kenneth Rogoff. 2004. “The Modern History of Exchange Rate Arrangements: A Reinterpretation.” Quarterly Journal of Economics 119(1):1-48, February.

Tavlas, George, Harris Dellas & Alan Stockman, “The Classification and Performance of Alternate Exchange-Rate Systems,” 2006.

Williamson, John, “The Case for a Basket, Band and Crawl (BBC) Regime for East Asia,” in D.Gruen & J.Simon, eds., Future Directions for Monetary Policies in East Asia, Reserve Bank of Australia, 2001.

Additional Readings:

professor jeffrey frankel exchange rate regimes: current issues in research & policy jeffrey...

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