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
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
9) Monetary union
8) Dollarization
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)
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 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).
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
IMF
IMF
GGW
LY-S
R-R
GGW
LY-S
R-R
1.00
(100.0)
0.60
1.00
(55.1)
(100.0)
0.28
0.13
1.00
(41.0)
(35.3)
(100.0)
0.33
(55.1)
0.34
0.41
1.00
(35.2)
(45.3)
(100.0)
(Frequency of outright coincidence, in %, given in parenthesis.)
GGW =Ghosh, Gulde & Wolf. LY-S = Levy-Yeyati & Sturzenegger. R-R = Reinhart & Rogoff
Sample: 47 countries.
From Frankel, ADB, 2004.
Table 3, prepared by M. Halac & S.Schmukler.
=> 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, 05).
Korea & Singapore in 2010 took inflows
mostly in the form of reserves,
while India & Malaysia took them mostly
in the form of currency appreciation.
more-managed floating
less-managed floating
(“more appreciation-friendly”)
GS Global ECS Research
In Latin America, renewed inflows
are reflected mostly as reserve accumulation in Peru,
but as appreciation in Chile & Colombia.
more-managed floating
less-managed floating
(“more appreciation-friendly”)
Source: GS Global ECS Research
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.
The 2nd approach in the de facto regime
literature estimates implicit basket weights:
• 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 technique to estimate 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).
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.
Professor Jeffrey Frankel
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)].
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
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); LeviYeyati & Sturzenegger (2003)…
Application to RMB:
Eichengreen (06), Ogawa (06), F & Wei (07)
Synthesis: “Estimation of De Facto Exchange Rate
Regimes: Synthesis of the Techniques for Inferring
Flexibility and Basket Weights” Frankel & Wei (IMF SP 2008)
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
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 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.)
• 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:
– Sturzenegger & Levy-Yeyati:
– Reinhart-Rogoff:
hard pegs work best
floats perform best
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 right
for 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 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.
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 criterion
to 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 criterion
to 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 policy
•
If the exchange rate is not to be nominal anchor,
–
–
something else must be…
especially where institutions lack credibility
–
2 alternatives for nominal anchor
have had ardent supporters in the past,
but are no longer in the running:
•
•
–
the price of gold, as 19th century gold standard; and
the money supply, the choice of monetarists.
Inflation targeting
•
•
Orthodox implementation: the CPI
Unorthodox versions for countries
with volatile terms of trade
PPT
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
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
Professor Jeffrey Frankel
After the 1990s’ EM Crises, Inflation Targeting
spread from rich countries to emerging markets
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.pdf
The 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
• The shocks of 2008-2011 showed
disadvantages to Inflation Targeting,
– analogously to how the EM crises of the 1994-2001
showed disadvantages of exchange rate targeting.
• One disadvantage of IT:
no response to asset price bubbles.
• Another disadvantage:
– 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
6 proposed nominal targets and the Achilles heel of each:
Monetarist rule
Inflation targeting
Nominal income
targeting
Gold standard
Commodity
standard
Fixed
exchange rate
Targeted
variable
Vulnerability
Example
M1
Velocity shocks
US 1982
CPI
Import price
shocks
Oil shocks of
1973-80, 2000-08
Measurement
problems
Less developed
countries
Vagaries of world
gold market
Shocks in
imported
commodity
Appreciation of $
1849 boom;
1873-96 bust
Nominal
GDP
Price
of gold
Price of agric.
& mineral
basket
$
(or €)
(or € )
Oil shocks of
1973-80, 2000-08
1995-2001
Professor Jeffrey Frankel
Proposal for Product Price Targeting
PPT
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.
Professor Jeffrey Frankel
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
LAC Countries’ Current Regimes and Monthly Correlations
Exchange
($/local
currency)
withcurrency)
$ Import
Price
Changes
Table 1: of
LACA
Countries’ CurrentRate
Regimes Changes
and Monthly Correlations
of Exchange
Rate Changes ($/local
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
0.0524
-0.0484
CHL
Independently floating
Inflation targeting framework (1990)*
-0.0695
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.
IT
countries
show
correlations
> 0.
The 4 inflation-targeters in Latin America
show 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.
PPT
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).
Professor Jeffrey Frankel
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
Additional Readings:
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
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