Exchange Rate Regimes

Jeffrey Frankel

Harpel Chair, Harvard University

IMF Institute  * April 27, 2011 *

Topics to be covered

I. Classifying countries by exchange rate regime• Statistical inference of 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

• Alternative nominal anchors• Proposal for Product Price Targeting

Appendices

PPT

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 major 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)..[3] Parameters kept secret: Frankel, Schmukler & Servén (2000).

De jure regime de factoas is by now well-known

II. Economists offer 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] Bénassy-Quéré, et al (Table 5, 2004); Frankel (Table 1, 2004); and Shambaugh (2007).

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

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, 05).

=> Something must be wrong.

Korea & Singapore in 2010 took inflows mostly in the form of reserves,

while India & Malaysia took them mostly in the form of currency appreciation.

GS Global ECS Research

less-managed floating (“more appreciation-friendly”)

more-managed floating

In Latin America, renewed inflows

less-managed floating (“more appreciation-friendly”)

more-managed floating

Source: GS Global ECS Research

but as appreciation in Chile & Colombia. are reflected mostly as reserve accumulation in Peru,

This 1st approach can be phrased in terms of Exchange Market Pressure:

– Define Δ EMP = Δ value of currency + x Δ reserves.

– Δ 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).

x ≡ 1/MBase or sometimes the inverse relative variance.

In Asia since 2008, India, followed by Indonesia, have had the greatest tendency to float, given EMP;

Hong Kong & Singapore the least, followed by Malaysia & China.

Goldman Sachs Global Economics Weekly 11/07 Feb. 16, 2011

Distillation of technique to infer flexibility• When a shock raises international demand for the currency,

does it show up as an appreciation, or as a rise in reserves?

• 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.

Several things are wrong, continued.

Difficulty #2: We shouldn’t 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 – less de facto flexibility, as China, – or more, as with most others.

• To uncover the currency composition & weights,

regress changes in log H, the home currency value, against changes in log values of candidate currencies.

• Algebraically, if the value of the home currency 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)

The 2nd approach in the de facto regime literature estimates implicit basket weights:

• First examples: Frankel (1993) and Frankel & Wei (1994, 95). • More: Bénassy-Quéré (1999), Ohno (1999),

Bénassy-Quéré, Coeuré & Mignon (2004)….

• Application to the RMB, post 7/05: – Shah, Zeileis & Patnaik (2005), Eichengreen (2006), Ogawa (2006),

Yamazaki (2006), Frankel-Wei (2006, 07), Frankel (2009).

The technique to estimate basket weights

Professor Jeffrey Frankel

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

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 do only one or the other.

The synthesis technique

• => We need a technique that can cover both dimensions: inferring weights and inferring flexibility.

• 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.

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)].

Professor Jeffrey Frankel

Several things are wrong, continued.

Difficulty #4: All these approaches are plagued by the problem that many countries frequently change regimes or change parameters.

• E.g., Chile’s BBC 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

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)

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. • Theoretically, can hedge risk. But costs of hedging: missing markets, transactions costs, and risk premia.

• Empirically: Exchange rate volatility ↑ => trade ↓ ? - Shows up in cross-section evidence,

especially with small & less developed countries.- Borders, e.g., Canada-US:

McCallum-Helliwell (1995-98); Engel-Rogers (1996).

- Currency unions: Rose (2000).

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 depreciation5) 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.)

• Influential finding of Rose (2000): the boost to bilateral trade from currency unions is– significant,– ≈ boost from FTAs, & – larger (3-fold) than had been thought.

• Many others have advanced critiques of Rose research, re:• endogeneity of currency decision, • small countries ≠ large, • missing variables & • implausibility of sheer magnitude.

– Estimated magnitudes are often smaller, but the basic finding has withstood perturbations and replications well. ii/

• Parsley-Wei: currency effect explains border effects.[ii] E.g., Rose & van Wincoop (2001); Tenreyro & Barro (2003). Survey: Baldwin (2006)

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

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 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, by first observing that smaller units tend to be more open and integrated.

Then an OCA can be defined as: a region that is neither so small &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 & 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.

Popularity in the 1990s of the institutionally-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, alternative nominal anchors, and the proposal for Product Price Targeting.

(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? – as private capital flows promise to be in theory, but fail in practice?

(i) I would like to add another criterionto the traditional OCA list:

Cyclically-stabilizing emigrants’ remittances.

• If country S has sent immigrants to country H, are their remittances correlated with the differential in growth or employment in S versus H?

• Apparently yes. (Frankel, “Are Bilateral Remittances Countercyclical?” 2011)

• 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.

(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 (2005)

• 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– E.g., Ramcharan (2007).

.

• Most common case of real shocks: trade– Edwards & Levy-Yeyati (2003):

Empirically, among peggers terms-of-trade shocks are amplified and long-run growth falls, as compared to flexible-rate countries.

Terms-of-trade variability returns

• Prices of crude oil and other agricultural & mineral commodities hit record highs during the decade 2001-2011.

• => Favorable terms of trade shocks for some (oil producers; South America, Africa, etc.);

• => Unfavorable terms of trade shock for others (oil importers, such as Asia)..

Nominal anchors for monetary policyNominal anchors for monetary policy

• If the exchange rate is not to be nominal anchor,If the exchange rate is not to be nominal anchor,– something else must be…something else must be…– especially where institutions lack credibilityespecially where institutions lack credibility

– 2 alternatives for nominal anchor 2 alternatives for nominal anchor have had ardent supporters in the past, have had ardent supporters in the past, but are no longer in the running:but are no longer in the running:

• the price of gold, as 19th century gold standard; andthe price of gold, as 19th century gold standard; and• the money supply, the choice of monetarists.the money supply, the choice of monetarists.

– Inflation targetingInflation targeting• Orthodox implementation: the CPIOrthodox implementation: the CPI• Unorthodox versions for countries Unorthodox versions for countries

with volatile terms of tradewith volatile terms of tradePPT

Fashions in international currency policy

• 1980-82: Monetarism (target the money supply)

• 1984-1997: Fixed exchange rates (including currency boards)

• 1993-2001: The corners hypothesis• 1998-2009: Inflation targeting (+ currency float)

became the new conventional wisdom• Among academic economists• Among central bankers• At the IMF

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• and at the IMF

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

After the 1990s’ EM Crises, Inflation Targetingspread from rich countries to emerging markets

Professor Jeffrey Frankel

• The shocks of 2008-2011 showed The shocks of 2008-2011 showed disadvantages to Inflation Targetingdisadvantages to Inflation Targeting ,,– analogously to how the EM crises of the 1994-2001analogously to how the EM crises of the 1994-2001

showed disadvantages of exchange rate targeting.showed disadvantages of exchange rate targeting.

• One disadvantage of IT: One disadvantage of IT: no response to asset price bubbles.no response to asset price bubbles.

• Another disadvantageAnother disadvantage::

– It gives the wrong answer in case of trade shocks:It gives the wrong answer in case of trade shocks:• E.g., it says to tighten money & appreciate

in response to a rise in oil import prices; • It does not allow monetary tightening

& appreciation in response to a rise in world prices of export commodities.

• That is backwards.

Professor Jeffrey Frankel

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

6 proposed nominal targets and the Achilles heel of each:

Professor Jeffrey Frankel

Proposal for Product Price Targeting

Intended for countries with volatile terms of trade, e.g., those specialized in commodities.

The authorities stabilize the currency in terms of a basket that gives heavy weight to prices of its commodity exports, rather than to the $ or € or CPI.

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.

PPT

In practice, most IT proponents agree central banks should not tighten to offset oil price shocks

• They want focus on core CPI, excluding food & energy.

• But – food & energy consumption do not cover all supply shocks.

– Use of core CPI sacrifices some credibility:• If core CPI is the explicit goal ex ante, the public feels confused.• If it is an excuse for missing targets ex post, the public feels tricked.

– The threat to credibility is especially strong where there are historical grounds for believing that government officials fiddle with the CPI for political purposes.

– Perhaps for that reason, IT central banks apparently do respond to oil shocks by tightening/appreciating….

Table 1: LACA Countries’ Current Regimes and Monthly Correlations of Exchange Rate Changes ($/local currency) with Dollar Import Price Changes

Import price changes are changes in the dollar price of oil.

Exchange Rate Regime Monetary Policy 1970-1999 2000-2008 1970-2008

ARG Managed floating Monetary aggregate target -0.0212 -0.0591 -0.0266

BOL Other conventional fixed peg Against a single currency -0.0139 0.0156 -0.0057

BRA Independently floating Inflation targeting framework (1999) 0.0366 0.0961 0.0551

CHL Independently floating Inflation targeting framework (1990)* -0.0695 0.0524 -0.0484

CRI Crawling pegs Exchange rate anchor 0.0123 -0.0327 0.0076

GTM Managed floating Inflation targeting framework -0.0029 0.2428 0.0149

GUY Other conventional fixed peg Monetary aggregate target -0.0335 0.0119 -0.0274

HND Other conventional fixed peg Against a single currency -0.0203 -0.0734 -0.0176

JAM Managed floating Monetary aggregate target 0.0257 0.2672 0.0417

NIC Crawling pegs Exchange rate anchor -0.0644 0.0324 -0.0412

PER Managed floating Inflation targeting framework (2002) -0.3138 0.1895 -0.2015

PRY Managed floating IMF-supported or other monetary program -0.023 0.3424 0.0543

SLV Dollar Exchange rate anchor 0.1040 0.0530 0.0862

URY Managed floating Monetary aggregate target 0.0438 0.1168 0.0564

Oil Exporters

COL Managed floating Inflation targeting framework (1999) -0.0297 0.0489 0.0046

MEX Independently floating Inflation targeting framework (1995) 0.1070 0.1619 0.1086

TTO Other conventional fixed peg Against a single currency 0.0698 0.2025 0.0698

VEN Other conventional fixed peg Against a single currency -0.0521 0.0064 -0.0382* Chile declared an inflation target as early as 1990; but it also had an exchange rate target, under an explicit band-basket-crawl regime, until 1999.

LAC Countries’ Current Regimes and Monthly Correlations of Exchange Rate Changes ($/local currency) with $ Import Price Changes

Table 1

ITcoun-triesshowcorrel-ations> 0.

The 4 inflation-targeters in Latin Americashow correlation (currency value in $, import prices in $)

• > 0 ;

• > correlation before they adopted IT;

• > correlation shown by non-IT Latin American countries.

Why is the correlation between the $ import price and the $ currency value revealing?

• The currency of an oil importer should not respond to an increase in the world price of oil by appreciating, to the extent that these central banks target core CPI .

• If anything, floating currencies should depreciate in response to such an adverse terms of trade shock.

• When these IT currencies respond by appreciating instead, it suggests that the central bank is tightening monetary policy to reduce upward pressure on the CPI, – the opposite of accommodating the terms of trade shock.

Professor Jeffrey Frankel

Recap of Product Price Targeting:

Target an index of domestic production prices. [1]

The important point:

include export commodities in the index and exclude import commodities, whereas the CPI does it the other way around.

[1] Frankel (2011).

PPT

Readings:

Calvo, Guillermo, and Carmen Reinhart, 2002, “Fear of Floating,” Quarterly J. of Economics, May.

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, 2011b, “A Comparison of Monetary Anchor Options, Including Product Price Targeting, for Commodity-Exporters in Latin America,” for Economia. NBER WP 16362.

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.

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

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

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

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

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

Frankel, Jeffrey, 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,” Q.J.Ec..

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

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, 2001, “The Case for a Basket, Band and Crawl (BBC) Regime for East Asia,” in D.Gruen and J.Simon, eds., Future Directions for Monetary Policies in East Asia, Res.Bk.Australia.

Additional Readings: