Description
Exchange rate regime decisively impacts key policy objectives such as financial stability,
inflation control, etc. The purpose of this paper is to overview the evolution of exchange rate regimes
spanning 12 nations in the Latin American region over the last two decades and estimate the degrees
of influence of other major currencies on each nation.
Journal of Financial Economic Policy
Exchange rate flexibility in Latin America
Amit Ghosh
Article information:
To cite this document:
Amit Ghosh, (2013),"Exchange rate flexibility in Latin America", J ournal of Financial Economic Policy, Vol. 5
Iss 2 pp. 238 - 250
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http://dx.doi.org/10.1108/17576381311329689
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Exchange rate ?exibility
in Latin America
Amit Ghosh
Department of Economics, Illinois Wesleyan University, Bloomington,
Illinois, USA
Abstract
Purpose – Exchange rate regime decisively impacts key policy objectives such as ?nancial stability,
in?ation control, etc. The purpose of this paper is to overview the evolution of exchange rate regimes
spanning 12 nations in the Latin American region over the last two decades and estimate the degrees
of in?uence of other major currencies on each nation.
Design/methodology/approach – Using the methodology developed by Frankel and Wei, the de
facto extent of exchange rate ?exibility is discerned for these nations and put into perspective with
that of the IMF exchange rate regime classi?cations.
Findings – An increase in ?exibility is found from the 1990s to the 2000s, especially for in?ation
targeting nations. However, the results reveal these nations adopt a policy of “guarded caution” and
follow more of a de facto managed ?oating regime that is far from pure ?oats. The smaller economies of
the region still pursue more ?xed regimes. While the results correlate, to an extent, with the IMF’s
classi?cations, several areas of discrepancy are noted. The ?ndings are robust to several sensitivity
analyses.
Originality/value – A discrepancy between the IMF regime categorization and the true regime a
country actually follows may cause IMF ?nancial assistance programs to be less effective. Do
countries follow regimes they are classi?ed into? The present study gleans deeper into the issue and
discerns this. The comparative analysis includes the relatively larger economies of the region as well
as the seldom researched smaller ones.
Keywords Latin America, Exchange rate mechanisms, Foreign exchange, Exchange rate regime,
Foreign exchange reserves, Exchange rate ?exibility, Exchange market pressure, Frankel-Wei estimation,
Recursive least squares
Paper type General review
1. Introduction
A de?ning feature of Latin American countries is intra-regional diversity in terms of
economic development, rates of growth and key economic structures. A similar degree
of heterogeneity exists in the IMF exchange rate regimes of these nations. A critical
question is how do de facto regimes compare with the IMF classi?cations? The
objective of this paper is to draw inferences about de facto regime classi?cations and
put them into perspective with that of the IMF’s for 12 Latin American nations over the
past two decades. Do countries follow regimes they are classi?ed into? The present
study discerns this and estimates the degrees of in?uences of other currencies on a
nation’s currency. The comparative analysis includes the relatively larger economies of
the region as well as the seldom researched smaller ones.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
This research was supported by an Illinois Wesleyan University Artistic and Scholarly
Development grant awarded to Amit Ghosh. The author would like to thank conference
participants at the Midwest Economics Association, annual meeting held in St Louis, March 2011,
for their valuable comments.
Journal of Financial Economic Policy
Vol. 5 No. 2, 2013
pp. 238-250
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576381311329689
JFEP
5,2
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IMF’s advice on monetary and exchange rate issues to its members and ?nancial
assistance programs are based on either its own or the of?cial exchange rate regime
categorization of countries. However, if there is disconnect between the IMF classi?cation
and the true regime a country actually follows, these programs may be less effective.
Recently, IMF has been under some pressure both on its regimes classi?cations and the
advice it proffers (Truman, 2006). So, it is important to discern the true regime a country
follows. Moreover, exchange rate regimes decisively affect key economic policyobjectives
like ?nancial stability, economic growth, in?ation, and trade balance. A discrepancy
betweenthe de jure regime andthat actuallyfollowedrenders fewer ef?cacies inachieving
their intended outcomes.
Exchange rate regimes in Latin America have spanned a wide spectrum. Post
Bretton Woods with the movement away from ?xed rates, the 1980s to mid-1990s saw
the use of basket pegs with a band-basket-crawl (BBC) type of arrangements on
grounds of price stabilization. The mid-1990s witnessed a spate of currency crises in
various parts of the globe including Latin America. A common feature of the crises
hit nations were the use of intermediate regimes. This contributed to the emergence of
the bi-polar or corners hypothesis. Nations should abandon intermediate regimes and
adopt either an institutionally ?xed exchange rate regime or a freely ?oating regime[1].
Countries like Brazil, Chile, Colombia, Mexico, Peru of?cially moved to a more
?oating exchange rate with in?ation targeting (referred to as FIT, hereafter), while
Argentina used a currency board till 2001. Ecuador dollarized from 2000 onwards.
However, corner solutions are not insulated from market pressures and are subject to
misalignments that undermine their sustainability (Corden, 2003; Williamson, 2000).
The consensus then shifted back again from the corners hypothesis to intermediate
exchange rate regimes. Table I documents the IMF regime classi?cations for these
nations from 1990 to 2008.
The paper proceeds as follows. Section 2 constructs exchange rate ?exibility indices
for each nation. Section 3 presents the econometric model, results and their
interpretations. Section 4 examines the currency linkages of a cluster of countries
within the same IMF exchange rate regime classi?cation with the major industrialized
countries. Finally Section 5 concludes.
2. Exchange rate ?exibility in Latin America
To assess how exchange rate regimes have evolved in Latin America I ?rst create a
?exibility index for each nation. This is motivated by the fact that the degree of
?exibility in a country’s exchange rate regime cannot be judged solely by variations in
the price of its currency. Gyrations in exchange rates may be due to shocks confronted
by the foreign sector of a nation and not necessarily due to a more ?oating regime per se.
To judge the factual stance of the exchange rate regime one needs to look into exchange
rate variability along with the variability of other policy intervention instruments like
interest rates and foreign exchange reserves.
Following Calvo and Reinhert (2002), I use the changes in exchange rate per unit of
US dollar divided by sum of the changes in foreign exchange reserves and interest
rates. A higher value denotes a more ?exible regime[2]:
ðFLEX
1
Þ ¼
D
E
D
FER
þD
r
ð1Þ
Exchange rate
?exibility
239
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where D
E
¼ changes in exchange rates, D
FER
¼ changes in foreign exchange
reserves, D
r
¼ changes in interest rates, where all changes are in absolute values.
Table II presents the average exchange rate ?exibility across the two decades for each
nation.
In the 1990s, Venezuela (1.42) has the highest degree of ?exibility followed by Brazil
(0.90) and Colombia (0.884) while Argentina (0.029) exhibits the least ?exibility
Country 1990s 2000s
Argentina Independently ?oating (1990), currency board
(1991-1999)
Currency board (2000-2001), managed
?oating (2002-2005), other conventional
?xed peg (2007-2008)
Bolivia Backward looking crawling peg (1990-1998),
forward looking crawling peg (1999)
Forward looking crawling peg (2000-
2001), crawling peg (2002-2008)
Brazil Managed ?oating (1990), backward-looking
crawling peg (1991-1993), tightly managed
?oating (1994), backward-looking crawling
peg (1995-1997), forward-looking crawling
peg (1998), independently ?oating (1999)
Independently ?oating (2000-2008)
Chile Backward-looking crawling band (1990-1997),
forward-looking crawling band (1998),
independently ?oating (1999)
Independently ?oating (2000-2008)
Colombia Backward-looking crawling peg (1990),
forward-looking crawling band (1991-1998),
independently ?oating (1999)
Independently ?oating (2000-2004),
managed ?oating (2005-2008)
Ecuador Forward looking crawling peg (1990-1991),
pegged with a horizontal band (1991),
backward-looking crawling band (1992),
forward-looking crawling band (1994-1998),
independently ?oating (1999)
Another currency as legal tender (2000
onwards)
Mexico Forward-looking crawling peg (1990),
forward-looking crawling band (1991-1993),
independently ?oating (1994-1999)
Independently ?oating (2000-2008)
Nicaragua Backward-looking crawling peg (1990),
conventional ?xed peg to single currency
(1991-1992), forward looking crawling peg
(1993-1999)
Forward looking crawling peg (2000),
crawling peg (2001-2008)
Paraguay Tightly managed ?oating (1991-1999) Managed ?oating (2000-2008)
Peru Independently ?oating (1991-1992), other
managed ?oating (1993-1998), independently
?oating (1999)
Independently ?oating (2000-2001),
managed ?oating (2003-2008)
Uruguay Tightly managed ?oating (1990-1991),
forward-looking crawling band (1992-1999)
Forward-looking crawling band (2000-
2001), independently ?oating (2002-2005),
managed ?oating (2006-2008)
Venezuela Other managed ?oating (1991-1993),
backward-looking crawling peg (1993),
conventional ?xed peg to single currency
(1994-1995), forward-looking crawling band
(1996-1999)
Forward-looking crawling band (2000-
2001), conventional ?xed peg to single
currency (2002-2008)
Source: Compiled by author from Bubula and Otker-Robe (2002), and from IMF’s Classi?cation of
Exchange Rate Arrangements and Monetary Frameworks
Table I.
IMF exchange rate
regime classi?cations
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capturing its currency board arrangement. For the next decade, an increase in ?exibility
is found for nine nations, and is most attenuated for Chile (9.54), followed by Colombia
(2.47) and Peru (2.46).
Changes in interest rates may capture general market conditions and not
necessarily be used by central banks to manipulate movements in currencies.
So I further create a second index by excluding interest rates, similar to Bayoumi and
Eichengreen (1998) and Baig (2001):
ðFLEX
2
Þ ¼
D
E
D
E
þD
FER
ð2Þ
where 0 , FLEX
2
, 1 and a higher number again denotes a greater degree of
?exibility. I also provide a broader de facto regime classi?cation based on FLEX
2
.
In the 1990s, Colombia is most ?exible (0.514) and Brazil is second (0.501) while
Argentina is again the least ?exible (0.076). For the next decade Colombia retains its
highest ?exibility (0.54) followed by Chile (0.537) and Brazil (0.498). Unlike the ?rst
measure, using FLEX
2
, I ?nd a lower degree of ?exibility for Peru and Uruguay across
decades. Using both measures Bolivia and Venezuela also exhibit declining ?exibility
over time. A general trend towards increased ?exibility is evident in the 2000s from the
1990s for the rest. This is particularly so for Mexico, Chile and Colombia – nations that
have adopted FIT regimes, post crises. Section 3, next investigates the evolution of
exchange rate regimes in further details.
3. Frankel-Wei estimation of currency weights
I use the estimation framework developed by Frankel and Wei (2008), popularly called
the synthesis equation to infer the de facto exchange rate regime across the spectrum of
?exibility and across the array of possible anchors:
DlogðE
t
Þ ¼ b
0
þ
X
n
i¼1
b
i
DlogðH
t
Þ
i
þaðEMP
t
Þ þ1
t
ð3Þ
1990s 2000s 1990s 2000s
FLEX
1
FLEX
1
FLEX
2
Classi?cation FLEX
2
Classi?cation
Argentina 0.029 0.141 0.076 Fixed 0.280 Intermediate
Bolivia 0.151 0.113 0.151 Fixed 0.111 Fixed
Brazil 0.904 1.545 0.501 Floating 0.498 Managed ?oating
Ecuador 0.401 n.a. 0.336 Intermediate n.a. n.a.
Chile 0.321 9.543 0.369 Intermediate 0.537 Floating
Colombia 0.884 2.474 0.514 Flexible 0.540 Floating
Mexico 0.196 0.638 0.260 Intermediate 0.456 Managed ?oating
Nicaragua 0.136 0.195 0.138 Fixed 0.301 Intermediate
Paraguay 0.252 0.313 0.248 Intermediate 0.355 Intermediate
Peru 0.532 2.457 0.387 Intermediate 0.329 Intermediate
Uruguay 0.355 2.416 0.387 Intermediate 0.304 Intermediate
Venezuela 1.442 0.260 0.295 Intermediate 0.109 Fixed
Table II.
Exchange rate
?exibility index
Exchange rate
?exibility
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where:
EMP
t
¼ DlogðE
t
Þ þDlogðFER
t
Þ ð4Þ
E
t
is the local currency per unit of SDR[3] and FER
t
denotes foreign exchange reserves.
Theoretically, if a country follows a truly ?xed exchange rate regime Dlog(E
t
) ¼ 0
and the EMP
t
coef?cient, a is also zero. On the other extreme, if a country follows a
truly ?oating exchange rate regime then Dlog(FER
t
) ¼ 0 and the EMP
t
coef?cient is
unity. H
t
is a vector of currencies included in each nation’s basket (Germany, Japan,
Italy, Spain, Portugal, and the USA). I simply run the regression of the changes in the
logarithmic values of local currencies against the changes in the logs of the major
currencies that are potential candidates for the anchor currency or basket of currencies.
Following previous research I also impose the constraints that the sums of the weights
of the currencies add up to unity by simply subtracting one currency (the British
pound, here) from both the left and right hand side currencies[4].
The b
i
coef?cients are often interpreted as implicit currency weights. While it is
tempting to do so, it is more prudent to interpret them as “degree of in?uence” as it is
dif?cult to ascertain whether a high and signi?cant coef?cient implies a basket currency
or merely market driven correlations. The results are explained by summarizing the
interaction between the currency weights (b
i
) and the EMP coef?cients. A statistically
insigni?cant or a low value of a denotes a de facto ?xed regime with the extent of ?xity
to the major currencies captured by the bcoef?cients, while a higher value of aindicates
a more ?exible regime. The results are used again to construct a de facto regime
classi?cation.
3.1 Estimates for 1990s
In the 1990s the international ?nancial environment was characterized by low interest
rates and external debt restructuring package for the heavily indebted Latin American
nations. Mexico started the decade by replacing the crawling peg with an asymmetric
band where the ceiling of the band was replaced regularly but the ?oor remained
unchanged. IMF classi?es the nation as a crawling pegger. Argentina’s exchange
rate regime was characterized by the establishment of a currency board to stabilize
prices from hyperin?ation. Brazil launched the new currency the “real” and is classi?ed
by the IMF as following managed ?oating–crawling peg regimes. Both Chile and
Colombia had less in?ationary problems and pursued crawling band regimes
aimed at sustaining a competitive real exchange rate but allowed some degree of
nominal exchange rate volatility (Ocampo and Tovar, 2003). This is also re?ected in
their IMF classi?cations. The Peruvian economy confronting high in?ation and
stagnant growth moved from a ?xed exchange rate with an asymmetric band towards
a managed ?oating regime characterized by foreign exchange market intervention
(Dancourt, 2009). Bolivia and Nicaragua are categorized by IMF as crawling peggers
while Venezuela is classi?ed to follow a variety of regimes. Table III presents the
results.
The results for 1990s showa very high weight around unity attached to the USD. The
EMP coef?cient is signi?cant and is of the highest magnitude for Peru (0.77), followed
by Brazil (0.64). Peru’s results are broadly consistent with its IMF categorization as
independent-managed regime while Brazil also exhibits suf?cient de facto ?exibility.
For Argentina we ?nd the EMP variable to be signi?cant (0.58) and USD coef?cient
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Table III.
Frankel-Wei estimation
results for 1990s
Exchange rate
?exibility
243
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
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T
Y
A
t
2
1
:
4
6
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
insigni?cant. This de facto “induced” ?exibility re?ects its usage of dollar as the legal
tender in the 1990s. The EMP coef?cient is positive and signi?cant at similar levels both
for Chile (0.166) and Colombia (0.193) re?ecting their crawling band regime. Bolivia,
Mexico, Paraguay, Uruguay have insigni?cant EMP coef?cients, and USD coef?cients
around unity, indicative of a de facto peg to the USD. For Bolivia the high R
2
is
indicative of a tight dollar-peg. Venezuela’s signi?cant EMP coef?cient (0.519) is
consistent with its high ?exibility index shown earlier.
3.2 Estimates for 2000s
The ?rst decade of the new millennium started with Mexico, Brazil, Chile, Colombia
and Peru using FIT regimes in the aftermath of the currency crises. Argentina, a
non-in?ation targeter moved of?cially towards a managed ?oating regime to allow
some degree of nominal exchange rate volatility. This was aimed to attain a long-term
competitive real exchange rate.
The results in Table IV reveal the US dollar coef?cients are of a lower magnitude
compared to the previous decade for seven nations. The EMP coef?cient is of a greater
magnitude compared to the 1990s for Chile, Colombia, Mexico and Paraguay. These two
facts imply a move towards a more ?exible regime compared to the previous decade.
EMP coef?cient is highest for Colombia (0.721) and is consistent with its exchange rate
?exibility index.
Noticeably, for the in?ation targeters the EMP coef?cient is typically around 0.4
which resembles more of a de facto managed ?oating regime contrary to their IMF
classi?cation. Pointedly, from the middle to late stages of the decade the in?ation
targeters have accumulated substantial amounts of foreign exchange reserves due to
“fear of ?oating” concerns. The ?nding can be related to recent literature that views this
most likely to prevent excessive real exchange rate appreciation (see inter alia Frenkel
and Rapatti, 2010 and the references cited therein)[5].
Turning to the smaller economies, Bolivia and Nicaragua’s dollar coef?cient around
unity along with very high R
2
, re?ects a tight dollar-peg and do not validate their IMF
categorization as crawling peggers. Argentina’s (0.418) signi?cant EMP coef?cients
re?ects its managed ?oating regime consistent with the IMF classi?cation. Paraguay
(0.153) and Venezuela’s (0.261) signi?cant EMP coef?cients, high dollar-weights and
relatively low R
2
s are indicative of a loose dollar-peg, and are at odds with their IMF
categorization of managed ?oating and conventional ?x peg regimes, respectively.
Venezuela’s decrease in exchange rate ?exibility from the previous decade is consistent
with its ?exibility index shown earlier. Finally, Uruguay’s results do not provide
evidence of its IMF categorization of a ?oating regime.
3.3 Sensitivity analyses
Exchange rates in a region often interact or may be affected by common shocks.
To ascertain possible in?uences’ of regional currencies on a given nation I used a
seemingly unrelated regressions method on the basic Frankel-Wei estimation model. The
results using this systems equation framework remained largely unchanged. For further
sensitivity analysis I also used a basic GARCH model. This enables to capture the impact
of the variations in other currencies on the conditional variance of the concerned nation’s
currency. Both US dollar weights and EMP coef?cients were found to be of similar
magnitude compared to the OLS results. These results are available on request.
JFEP
5,2
244
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Table IV.
Frankel-Wei estimation
results for 2000s
Exchange rate
?exibility
245
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3.4 Dynamic evolution of regimes
Central banks in most nations in reality do not maintain the same stance on their
exchange rate for more than a few years. The currency of any nation is most likely to
change its weights attached to other currencies or switch parameters or even the
exchange rate regime frequently. Table I makes it clear that different exchange rate
regimes are in operation for speci?c years and even months only[6].
To ascertain the dynamic evolution of the degree of ?exibility I use the recursive
least squares for the US dollar coef?cients, similar to Cavoli and Rajan (2010). This
entails running the regressions iteratively and recording the corresponding US dollar
coef?cient until we reach the full-sample. To render insuf?cient degrees of freedom
I omit the ?rst 30 observations. Figure 1 compares the recursive coef?cients for the US
dollar in 1990s with that in 2000s.
An ocular view shows the time plot of the US dollar coef?cients to be lower in 2000s
than that in 1990s for Brazil, Chile, Colombia and Mexico, and is also declining over the
last decade. For Peru and Uruguay I see a declining trend in the dollar weights in 2000s
albeit around unity, while for Venezuela the plot of the dollar coef?cients in 2000s is
above that in 1990s indicative of less ?exibility which is broadly consistent with the
earlier ?ndings. Nicaragua’s US dollar coef?cient hovers around unity over 2000s and
is not indicative of any increase in ?exibility.
4. Estimation across exchange rate regime type
An interesting point of analysis is how do a cluster of nations under a given IMF
exchange rate classi?cation behave in their currency linkages with the major currencies
compared to a group of nations falling under another regime classi?cation
(e.g. independent ?oaters vs crawling peggers)? The latest IMF classi?cation is used
here for clustering the countries where each panel represents a regime type[7]. A priori
the EMP coef?cient should be greater for in?ation targeting regimes compared to
non-in?ation targeting ones, if the former truly follows a ?oating regime. Likewise EMP
coef?cient is expected to be highest for independent ?oaters, followed by managed
?oaters and then crawling and conventional pegs, respectively, while dollar weights are
expected to be lowest for independent ?oaters and highest for conventional pegs.
Table V presents the panel results with cross sectional ?xed effects.
The EMP coef?cient is of similar magnitude for in?ation targeting regimes (0.206)
vis-a` -vis non-in?ation targeters (0.208). This reinforces the issue of foreign exchange
market intervention, which makes the FIT regimes to resemble no differently than
non-FIT regimes. This coef?cient is highest (0.427) and dollar weight lowest (0.781)
for independent ?oating regimes, followed by managed ?oating regimes consistent
with theoretical priors. It is insigni?cant for crawling pegs but is signi?cant at a very
low value for conventional pegs. Noteworthy, the EMP coef?cient of only 0.427 for
independent ?oaters is again suggestive of suf?cient propensity to intervene in foreign
exchange markets. I also ?nd the euro to complement the dollar in the currency weights
and is signi?cant and highest for the independent ?oaters (0.262) followed by the
in?ation targeters (0.24) and then managed ?oaters (0.178).
5. Conclusion
This paper reviews the de facto evolution of exchange rate regimes in Latin America
spanning across nations and over time. I ?nd Latin American currencies to have high
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Figure 1.
Recursive estimates of US
dollar coef?cients
Argentina
0.5
0.7
0.9
1.1
1.3
3
0
4
2
5
4
6
6
7
8
9
0
1
0
2
1
1
4
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Bolivia
0.94
0.96
0.98
1
1.02
1.04
3
1
5
5
7
9
1
0
3
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Brazil
0.4
0.6
0.8
1
1.2
3
1
5
2
7
3
9
4
1
1
5
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Chile
0.5
0.6
0.7
0.8
0.9
1
1.1
3
1
5
5
7
9
1
0
3
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Colombia
0.5
0.7
0.9
1.1
3
1
5
1
7
1
9
1
1
1
1
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Ecuador
0.9
1
1.1
1.2
1.3
3
1
4
8
6
5
8
2
9
9
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
Mexico
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
3
1
5
3
7
5
9
7
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Nicaragua
0.92
0.94
0.96
0.98
1
1.02
1.04
3
1
5
3
7
5
9
7
Observations
U
S
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g
h
t
s
1990 s
2000 s
Paraguay
0.7
0.9
1.1
1.3
1.5
3
1
5
3
7
5
9
7
Observations
U
S
D
w
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g
h
t
s
1990 s
2000 s
Peru
0
0.2
0.4
0.6
0.8
1
1.2
3
1
5
1
7
1
9
1
1
1
1
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Uruguay
0.9
1.1
1.3
1.5
1.7
1.9
3
1
4
8
6
5
8
2
9
9
1
1
6
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Venezuela
0
0.5
1
1.5
2
3
1
4
9
6
7
8
5
1
0
3
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Exchange rate
?exibility
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weightage with the dollar, regardless of their IMF regime classi?cation. A noticeable
increase in ?exibility is evident from the 1990s to the 2000s especially for Colombia,
Chile and Mexico. However, the results document FIT nations to adopt a policy of
“guarded caution” and follow more of a de facto managed ?oating regime and are far
from pure ?oats, which is the normative stance for in?ation targeters. The former
allows an extra degree of freedom to central banks by intervening in foreign exchange
markets to smoothen out periods of excessive volatilities in their currencies. Hysteresis
on real exchange rate appreciation and precautionary motive of hoarding foreign
exchange reserves to prevent potential runs on their currency explain this. This ?nding
is further reinforced when I cluster the countries according to IT and non-IT nations.
While the results correlate to an extent with the IMF classi?cation of exchange rate
regimes I note areas of discrepancy. Smaller economies of Bolivia, Uruguay and
Venezuela exhibit low degrees of ?exibility, inconsistent with their respective IMF
classi?cations. The results presented here are suggestive of a “crowding to the middle”
across the spectrum of regime options.
Notes
1. The IMF also lent support to this view of ?eeing the middle and moving to the corners in
proffering advice to its members about the selection of exchange rate regimes. See IMF’s
Independent Evaluation Of?ce 2007 Report.
2. A country leaning towards a more ?xed (?exible) regime a priori will have less (more)
variability of its exchange rate series relative to the variability of its foreign exchange
reserves. Countries can of course intervene in foreign exchange markets to limit the extent of
de facto ?exibility due to “fear of ?oating” concerns.
3. SDR is used here as the numeraire currency. A weighted index of currencies such as the SDR
is most appropriate here. If the central bank of a nation intervenes in the foreign exchange
market to allow only a partial deviation of their currency from a standard level, then they
would think more in terms of a weighted average of the major currencies of that nation and
In?ation
targeting
Non-in?ation
targeting
Independent
?oating
Managed
?oating
Crawling peg Conventional
peg
C 20.001 0.003
* * *
20.003
* * *
0.001 0.003 0.004
* * *
(20.845) (2.182) (22.126) (0.612) (6.422) (2.763)
DLEURO 0.240
* * *
0.091 0.262
* * *
0.178
* * *
0.047
* * *
0.100
(4.382) (1.326) (3.804) (2.506) (2.351) (1.580)
DLJAP 20.151
* * *
20.071 20.179
* * *
20.104
*
20.021 20.089
(23.276) (21.225) (23.068) (21.732) (21.253) (21.677)
DLUS 0.873
* * *
1.004
* * *
0.781
* * *
0.924
* * *
0.997
* * *
1.073
* * *
(14.172) (13.041) (10.046) (11.662) (44.302) (15.085)
EMP
t
0.206
* * *
0.208
* * *
0.427
* * *
0.193
* * *
20.001 0.070
* * *
(10.460) (10.519) (15.853) (8.063) (20.214) (4.037)
Adj. R
2
0.353 0.397 0.522 0.320 0.933 0.384
D-W 1.663 1.557 2.047 1.857 2.391 1.782
Cross-
sections/N
6/738 5/615 3/369 4/492 2/246 2/246
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
1 percent levels; terms in brackets denote t-stat.; a lagged
dependent variable was used to deal with issues of serial correlation
Table V.
Panel results by
exchange rate regime
type – 2000M1: 2010M6
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not in terms of one speci?c currency. Also from an econometric perspective SDR reduces
potential correlation issues of the error term with the numeraire.
4. The pound weight can be retrieved by simply subtracting the sum of the weights of the
currencies’ from unity.
5. Apprehensions to ?oat a nation’s currency can also occur due to “balance sheet
mismanagement” where a country is exposed to substantial foreign currency denominated
obligations often constrains a nation from ?oating its currency, a highly dollarized economy
like Peru’s recent intervention in the foreign exchange market to maintain ?nancial stability
is evidence of the latter (Dancourt, 2009). As such its EMP coef?cient (0.135) is low and less
than other in?ation targeters.
6. An option is to re-run the regression for each sub-sample. But that would require very high
frequency data like weekly or bi-weekly and is not available for most of these nations.
7. IMF classi?es Bolivia, Nicaragua as crawling peggers; Brazil, Chile, Mexico as independent
?oaters; Colombia, Peru, Uruguay, Paraguay as managed ?oaters; Argentina and Venezuela
as conventional ?xed peggers.
References
Baig, T. (2001), “Characterizing exchange rate regimes post-crisis East Asia”, Working Paper
No. 01/152, International Monetary Fund, Washington, DC.
Bayoumi, T. and Eichengreen, B. (1998), “Exchange rate volatility intervention: implications of
the theory of optimum currency areas”, Journal of International Economics, Vol. 45 No. 2,
pp. 191-209.
Calvo, G. and Reinhert, C. (2002), “Fear of ?oating”, Quarterly Journal of Economics, Vol. 117
No. 2, pp. 379-408.
Cavoli, T. and Rajan, R.S. (2010), “Exchange rate regimes in Asia: are they what they claim to
be?”, Economics Bulletin, Vol. 30 No. 4, pp. 2864-2876.
Corden, W.M. (2003), Too Sensational on the Choice of Exchange Rate Regimes, MIT Press,
Cambridge, MA.
Dancourt, O. (2009), “Peru´: la recesio´n del 2008-09 en perspective”, available at: www.itf.org.ar/
pdf/documentos/67-2010.pdf
Frankel, J. and Wei, S.J. (2008), “Estimation of de facto exchange rate regimes: synthesis of the
techniques for inferring ?exibility and basket weights”, Staff Paper No. 55, International
Monetary Fund, Washington, DC, pp. 384-416.
Ocampo, J.A. and Tovar, C. (2003), “Colombia’s experience with reserve requirements on capital
in?ows”, Cepal Review, Vol. 81, pp. 7-31.
Truman, E.M. (2006), “A strategy for IMF reform”, Policy Analyses in International Economics,
Vol. 77, Peterson Institute for International Economics, Washington, DC.
Williamson, J. (2000), “Exchange rate regimes for emerging market economies: reviving the
intermediate options”, Policy Analysis in International Economics, Vol. 60, Peterson
Institute for International Economics, Washington, DC.
Further reading
Bubula, A. and O
¨
tker-Robe, I. (2002), “The evolution of exchange rate regimes since 1990:
evidence from de facto policies”, Working Paper No. 02/155, International Monetary Fund,
Washington, DC.
Exchange rate
?exibility
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Frenkel, R. and Rapetti, M. (2010), AConcise History of Exchange Rate Regimes in Latin America,
Centre for Economic and Policy Research, Report, Washington, DC.
Independent Evaluation Of?ce of the International Monetary Fund (2007), An IEO Evaluation of
IMF Exchange Rate Policy Advice, 1999-2005: Evaluation Report, Independent Evaluation
Of?ce of the International Monetary Fund, Washington, DC.
About the author
Dr Amit Ghosh is currently Assistant Professor of Economics at Illinois Wesleyan University,
Department of Economics, Illinois, USA. Previously he worked in the capacity of Visiting
Assistant Professor at Colorado College, Department of Business and Economics, Colorado, USA
from 2006-2008. He has also served as a research assistant at the Lowe Institute of Political
Economy, Claremont McKenna College, California, USA. He works mainly in the areas of
international trade and ?nance. He has published several articles on the topics of “cross-border
production sharing” and “exchange rate pass-through,” with particular reference to Asia and
Latin America. His current ongoing research includes analyzing different aspects and implications
of exchange rate regimes, open-economy policy trilemma, and examining the relationship between
terms-of-trade and trade balance. Amit Ghosh can be contacted at: [email protected]
JFEP
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doc_703104079.pdf
Exchange rate regime decisively impacts key policy objectives such as financial stability,
inflation control, etc. The purpose of this paper is to overview the evolution of exchange rate regimes
spanning 12 nations in the Latin American region over the last two decades and estimate the degrees
of influence of other major currencies on each nation.
Journal of Financial Economic Policy
Exchange rate flexibility in Latin America
Amit Ghosh
Article information:
To cite this document:
Amit Ghosh, (2013),"Exchange rate flexibility in Latin America", J ournal of Financial Economic Policy, Vol. 5
Iss 2 pp. 238 - 250
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Exchange rate ?exibility
in Latin America
Amit Ghosh
Department of Economics, Illinois Wesleyan University, Bloomington,
Illinois, USA
Abstract
Purpose – Exchange rate regime decisively impacts key policy objectives such as ?nancial stability,
in?ation control, etc. The purpose of this paper is to overview the evolution of exchange rate regimes
spanning 12 nations in the Latin American region over the last two decades and estimate the degrees
of in?uence of other major currencies on each nation.
Design/methodology/approach – Using the methodology developed by Frankel and Wei, the de
facto extent of exchange rate ?exibility is discerned for these nations and put into perspective with
that of the IMF exchange rate regime classi?cations.
Findings – An increase in ?exibility is found from the 1990s to the 2000s, especially for in?ation
targeting nations. However, the results reveal these nations adopt a policy of “guarded caution” and
follow more of a de facto managed ?oating regime that is far from pure ?oats. The smaller economies of
the region still pursue more ?xed regimes. While the results correlate, to an extent, with the IMF’s
classi?cations, several areas of discrepancy are noted. The ?ndings are robust to several sensitivity
analyses.
Originality/value – A discrepancy between the IMF regime categorization and the true regime a
country actually follows may cause IMF ?nancial assistance programs to be less effective. Do
countries follow regimes they are classi?ed into? The present study gleans deeper into the issue and
discerns this. The comparative analysis includes the relatively larger economies of the region as well
as the seldom researched smaller ones.
Keywords Latin America, Exchange rate mechanisms, Foreign exchange, Exchange rate regime,
Foreign exchange reserves, Exchange rate ?exibility, Exchange market pressure, Frankel-Wei estimation,
Recursive least squares
Paper type General review
1. Introduction
A de?ning feature of Latin American countries is intra-regional diversity in terms of
economic development, rates of growth and key economic structures. A similar degree
of heterogeneity exists in the IMF exchange rate regimes of these nations. A critical
question is how do de facto regimes compare with the IMF classi?cations? The
objective of this paper is to draw inferences about de facto regime classi?cations and
put them into perspective with that of the IMF’s for 12 Latin American nations over the
past two decades. Do countries follow regimes they are classi?ed into? The present
study discerns this and estimates the degrees of in?uences of other currencies on a
nation’s currency. The comparative analysis includes the relatively larger economies of
the region as well as the seldom researched smaller ones.
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
This research was supported by an Illinois Wesleyan University Artistic and Scholarly
Development grant awarded to Amit Ghosh. The author would like to thank conference
participants at the Midwest Economics Association, annual meeting held in St Louis, March 2011,
for their valuable comments.
Journal of Financial Economic Policy
Vol. 5 No. 2, 2013
pp. 238-250
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/17576381311329689
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IMF’s advice on monetary and exchange rate issues to its members and ?nancial
assistance programs are based on either its own or the of?cial exchange rate regime
categorization of countries. However, if there is disconnect between the IMF classi?cation
and the true regime a country actually follows, these programs may be less effective.
Recently, IMF has been under some pressure both on its regimes classi?cations and the
advice it proffers (Truman, 2006). So, it is important to discern the true regime a country
follows. Moreover, exchange rate regimes decisively affect key economic policyobjectives
like ?nancial stability, economic growth, in?ation, and trade balance. A discrepancy
betweenthe de jure regime andthat actuallyfollowedrenders fewer ef?cacies inachieving
their intended outcomes.
Exchange rate regimes in Latin America have spanned a wide spectrum. Post
Bretton Woods with the movement away from ?xed rates, the 1980s to mid-1990s saw
the use of basket pegs with a band-basket-crawl (BBC) type of arrangements on
grounds of price stabilization. The mid-1990s witnessed a spate of currency crises in
various parts of the globe including Latin America. A common feature of the crises
hit nations were the use of intermediate regimes. This contributed to the emergence of
the bi-polar or corners hypothesis. Nations should abandon intermediate regimes and
adopt either an institutionally ?xed exchange rate regime or a freely ?oating regime[1].
Countries like Brazil, Chile, Colombia, Mexico, Peru of?cially moved to a more
?oating exchange rate with in?ation targeting (referred to as FIT, hereafter), while
Argentina used a currency board till 2001. Ecuador dollarized from 2000 onwards.
However, corner solutions are not insulated from market pressures and are subject to
misalignments that undermine their sustainability (Corden, 2003; Williamson, 2000).
The consensus then shifted back again from the corners hypothesis to intermediate
exchange rate regimes. Table I documents the IMF regime classi?cations for these
nations from 1990 to 2008.
The paper proceeds as follows. Section 2 constructs exchange rate ?exibility indices
for each nation. Section 3 presents the econometric model, results and their
interpretations. Section 4 examines the currency linkages of a cluster of countries
within the same IMF exchange rate regime classi?cation with the major industrialized
countries. Finally Section 5 concludes.
2. Exchange rate ?exibility in Latin America
To assess how exchange rate regimes have evolved in Latin America I ?rst create a
?exibility index for each nation. This is motivated by the fact that the degree of
?exibility in a country’s exchange rate regime cannot be judged solely by variations in
the price of its currency. Gyrations in exchange rates may be due to shocks confronted
by the foreign sector of a nation and not necessarily due to a more ?oating regime per se.
To judge the factual stance of the exchange rate regime one needs to look into exchange
rate variability along with the variability of other policy intervention instruments like
interest rates and foreign exchange reserves.
Following Calvo and Reinhert (2002), I use the changes in exchange rate per unit of
US dollar divided by sum of the changes in foreign exchange reserves and interest
rates. A higher value denotes a more ?exible regime[2]:
ðFLEX
1
Þ ¼
D
E
D
FER
þD
r
ð1Þ
Exchange rate
?exibility
239
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where D
E
¼ changes in exchange rates, D
FER
¼ changes in foreign exchange
reserves, D
r
¼ changes in interest rates, where all changes are in absolute values.
Table II presents the average exchange rate ?exibility across the two decades for each
nation.
In the 1990s, Venezuela (1.42) has the highest degree of ?exibility followed by Brazil
(0.90) and Colombia (0.884) while Argentina (0.029) exhibits the least ?exibility
Country 1990s 2000s
Argentina Independently ?oating (1990), currency board
(1991-1999)
Currency board (2000-2001), managed
?oating (2002-2005), other conventional
?xed peg (2007-2008)
Bolivia Backward looking crawling peg (1990-1998),
forward looking crawling peg (1999)
Forward looking crawling peg (2000-
2001), crawling peg (2002-2008)
Brazil Managed ?oating (1990), backward-looking
crawling peg (1991-1993), tightly managed
?oating (1994), backward-looking crawling
peg (1995-1997), forward-looking crawling
peg (1998), independently ?oating (1999)
Independently ?oating (2000-2008)
Chile Backward-looking crawling band (1990-1997),
forward-looking crawling band (1998),
independently ?oating (1999)
Independently ?oating (2000-2008)
Colombia Backward-looking crawling peg (1990),
forward-looking crawling band (1991-1998),
independently ?oating (1999)
Independently ?oating (2000-2004),
managed ?oating (2005-2008)
Ecuador Forward looking crawling peg (1990-1991),
pegged with a horizontal band (1991),
backward-looking crawling band (1992),
forward-looking crawling band (1994-1998),
independently ?oating (1999)
Another currency as legal tender (2000
onwards)
Mexico Forward-looking crawling peg (1990),
forward-looking crawling band (1991-1993),
independently ?oating (1994-1999)
Independently ?oating (2000-2008)
Nicaragua Backward-looking crawling peg (1990),
conventional ?xed peg to single currency
(1991-1992), forward looking crawling peg
(1993-1999)
Forward looking crawling peg (2000),
crawling peg (2001-2008)
Paraguay Tightly managed ?oating (1991-1999) Managed ?oating (2000-2008)
Peru Independently ?oating (1991-1992), other
managed ?oating (1993-1998), independently
?oating (1999)
Independently ?oating (2000-2001),
managed ?oating (2003-2008)
Uruguay Tightly managed ?oating (1990-1991),
forward-looking crawling band (1992-1999)
Forward-looking crawling band (2000-
2001), independently ?oating (2002-2005),
managed ?oating (2006-2008)
Venezuela Other managed ?oating (1991-1993),
backward-looking crawling peg (1993),
conventional ?xed peg to single currency
(1994-1995), forward-looking crawling band
(1996-1999)
Forward-looking crawling band (2000-
2001), conventional ?xed peg to single
currency (2002-2008)
Source: Compiled by author from Bubula and Otker-Robe (2002), and from IMF’s Classi?cation of
Exchange Rate Arrangements and Monetary Frameworks
Table I.
IMF exchange rate
regime classi?cations
JFEP
5,2
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capturing its currency board arrangement. For the next decade, an increase in ?exibility
is found for nine nations, and is most attenuated for Chile (9.54), followed by Colombia
(2.47) and Peru (2.46).
Changes in interest rates may capture general market conditions and not
necessarily be used by central banks to manipulate movements in currencies.
So I further create a second index by excluding interest rates, similar to Bayoumi and
Eichengreen (1998) and Baig (2001):
ðFLEX
2
Þ ¼
D
E
D
E
þD
FER
ð2Þ
where 0 , FLEX
2
, 1 and a higher number again denotes a greater degree of
?exibility. I also provide a broader de facto regime classi?cation based on FLEX
2
.
In the 1990s, Colombia is most ?exible (0.514) and Brazil is second (0.501) while
Argentina is again the least ?exible (0.076). For the next decade Colombia retains its
highest ?exibility (0.54) followed by Chile (0.537) and Brazil (0.498). Unlike the ?rst
measure, using FLEX
2
, I ?nd a lower degree of ?exibility for Peru and Uruguay across
decades. Using both measures Bolivia and Venezuela also exhibit declining ?exibility
over time. A general trend towards increased ?exibility is evident in the 2000s from the
1990s for the rest. This is particularly so for Mexico, Chile and Colombia – nations that
have adopted FIT regimes, post crises. Section 3, next investigates the evolution of
exchange rate regimes in further details.
3. Frankel-Wei estimation of currency weights
I use the estimation framework developed by Frankel and Wei (2008), popularly called
the synthesis equation to infer the de facto exchange rate regime across the spectrum of
?exibility and across the array of possible anchors:
DlogðE
t
Þ ¼ b
0
þ
X
n
i¼1
b
i
DlogðH
t
Þ
i
þaðEMP
t
Þ þ1
t
ð3Þ
1990s 2000s 1990s 2000s
FLEX
1
FLEX
1
FLEX
2
Classi?cation FLEX
2
Classi?cation
Argentina 0.029 0.141 0.076 Fixed 0.280 Intermediate
Bolivia 0.151 0.113 0.151 Fixed 0.111 Fixed
Brazil 0.904 1.545 0.501 Floating 0.498 Managed ?oating
Ecuador 0.401 n.a. 0.336 Intermediate n.a. n.a.
Chile 0.321 9.543 0.369 Intermediate 0.537 Floating
Colombia 0.884 2.474 0.514 Flexible 0.540 Floating
Mexico 0.196 0.638 0.260 Intermediate 0.456 Managed ?oating
Nicaragua 0.136 0.195 0.138 Fixed 0.301 Intermediate
Paraguay 0.252 0.313 0.248 Intermediate 0.355 Intermediate
Peru 0.532 2.457 0.387 Intermediate 0.329 Intermediate
Uruguay 0.355 2.416 0.387 Intermediate 0.304 Intermediate
Venezuela 1.442 0.260 0.295 Intermediate 0.109 Fixed
Table II.
Exchange rate
?exibility index
Exchange rate
?exibility
241
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where:
EMP
t
¼ DlogðE
t
Þ þDlogðFER
t
Þ ð4Þ
E
t
is the local currency per unit of SDR[3] and FER
t
denotes foreign exchange reserves.
Theoretically, if a country follows a truly ?xed exchange rate regime Dlog(E
t
) ¼ 0
and the EMP
t
coef?cient, a is also zero. On the other extreme, if a country follows a
truly ?oating exchange rate regime then Dlog(FER
t
) ¼ 0 and the EMP
t
coef?cient is
unity. H
t
is a vector of currencies included in each nation’s basket (Germany, Japan,
Italy, Spain, Portugal, and the USA). I simply run the regression of the changes in the
logarithmic values of local currencies against the changes in the logs of the major
currencies that are potential candidates for the anchor currency or basket of currencies.
Following previous research I also impose the constraints that the sums of the weights
of the currencies add up to unity by simply subtracting one currency (the British
pound, here) from both the left and right hand side currencies[4].
The b
i
coef?cients are often interpreted as implicit currency weights. While it is
tempting to do so, it is more prudent to interpret them as “degree of in?uence” as it is
dif?cult to ascertain whether a high and signi?cant coef?cient implies a basket currency
or merely market driven correlations. The results are explained by summarizing the
interaction between the currency weights (b
i
) and the EMP coef?cients. A statistically
insigni?cant or a low value of a denotes a de facto ?xed regime with the extent of ?xity
to the major currencies captured by the bcoef?cients, while a higher value of aindicates
a more ?exible regime. The results are used again to construct a de facto regime
classi?cation.
3.1 Estimates for 1990s
In the 1990s the international ?nancial environment was characterized by low interest
rates and external debt restructuring package for the heavily indebted Latin American
nations. Mexico started the decade by replacing the crawling peg with an asymmetric
band where the ceiling of the band was replaced regularly but the ?oor remained
unchanged. IMF classi?es the nation as a crawling pegger. Argentina’s exchange
rate regime was characterized by the establishment of a currency board to stabilize
prices from hyperin?ation. Brazil launched the new currency the “real” and is classi?ed
by the IMF as following managed ?oating–crawling peg regimes. Both Chile and
Colombia had less in?ationary problems and pursued crawling band regimes
aimed at sustaining a competitive real exchange rate but allowed some degree of
nominal exchange rate volatility (Ocampo and Tovar, 2003). This is also re?ected in
their IMF classi?cations. The Peruvian economy confronting high in?ation and
stagnant growth moved from a ?xed exchange rate with an asymmetric band towards
a managed ?oating regime characterized by foreign exchange market intervention
(Dancourt, 2009). Bolivia and Nicaragua are categorized by IMF as crawling peggers
while Venezuela is classi?ed to follow a variety of regimes. Table III presents the
results.
The results for 1990s showa very high weight around unity attached to the USD. The
EMP coef?cient is signi?cant and is of the highest magnitude for Peru (0.77), followed
by Brazil (0.64). Peru’s results are broadly consistent with its IMF categorization as
independent-managed regime while Brazil also exhibits suf?cient de facto ?exibility.
For Argentina we ?nd the EMP variable to be signi?cant (0.58) and USD coef?cient
JFEP
5,2
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(
1
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Table III.
Frankel-Wei estimation
results for 1990s
Exchange rate
?exibility
243
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
4
6
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
insigni?cant. This de facto “induced” ?exibility re?ects its usage of dollar as the legal
tender in the 1990s. The EMP coef?cient is positive and signi?cant at similar levels both
for Chile (0.166) and Colombia (0.193) re?ecting their crawling band regime. Bolivia,
Mexico, Paraguay, Uruguay have insigni?cant EMP coef?cients, and USD coef?cients
around unity, indicative of a de facto peg to the USD. For Bolivia the high R
2
is
indicative of a tight dollar-peg. Venezuela’s signi?cant EMP coef?cient (0.519) is
consistent with its high ?exibility index shown earlier.
3.2 Estimates for 2000s
The ?rst decade of the new millennium started with Mexico, Brazil, Chile, Colombia
and Peru using FIT regimes in the aftermath of the currency crises. Argentina, a
non-in?ation targeter moved of?cially towards a managed ?oating regime to allow
some degree of nominal exchange rate volatility. This was aimed to attain a long-term
competitive real exchange rate.
The results in Table IV reveal the US dollar coef?cients are of a lower magnitude
compared to the previous decade for seven nations. The EMP coef?cient is of a greater
magnitude compared to the 1990s for Chile, Colombia, Mexico and Paraguay. These two
facts imply a move towards a more ?exible regime compared to the previous decade.
EMP coef?cient is highest for Colombia (0.721) and is consistent with its exchange rate
?exibility index.
Noticeably, for the in?ation targeters the EMP coef?cient is typically around 0.4
which resembles more of a de facto managed ?oating regime contrary to their IMF
classi?cation. Pointedly, from the middle to late stages of the decade the in?ation
targeters have accumulated substantial amounts of foreign exchange reserves due to
“fear of ?oating” concerns. The ?nding can be related to recent literature that views this
most likely to prevent excessive real exchange rate appreciation (see inter alia Frenkel
and Rapatti, 2010 and the references cited therein)[5].
Turning to the smaller economies, Bolivia and Nicaragua’s dollar coef?cient around
unity along with very high R
2
, re?ects a tight dollar-peg and do not validate their IMF
categorization as crawling peggers. Argentina’s (0.418) signi?cant EMP coef?cients
re?ects its managed ?oating regime consistent with the IMF classi?cation. Paraguay
(0.153) and Venezuela’s (0.261) signi?cant EMP coef?cients, high dollar-weights and
relatively low R
2
s are indicative of a loose dollar-peg, and are at odds with their IMF
categorization of managed ?oating and conventional ?x peg regimes, respectively.
Venezuela’s decrease in exchange rate ?exibility from the previous decade is consistent
with its ?exibility index shown earlier. Finally, Uruguay’s results do not provide
evidence of its IMF categorization of a ?oating regime.
3.3 Sensitivity analyses
Exchange rates in a region often interact or may be affected by common shocks.
To ascertain possible in?uences’ of regional currencies on a given nation I used a
seemingly unrelated regressions method on the basic Frankel-Wei estimation model. The
results using this systems equation framework remained largely unchanged. For further
sensitivity analysis I also used a basic GARCH model. This enables to capture the impact
of the variations in other currencies on the conditional variance of the concerned nation’s
currency. Both US dollar weights and EMP coef?cients were found to be of similar
magnitude compared to the OLS results. These results are available on request.
JFEP
5,2
244
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6
;
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:
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–
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,
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–
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a
p
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;
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–
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–
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c
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t
p
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s
s
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r
e
Table IV.
Frankel-Wei estimation
results for 2000s
Exchange rate
?exibility
245
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
4
6
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
3.4 Dynamic evolution of regimes
Central banks in most nations in reality do not maintain the same stance on their
exchange rate for more than a few years. The currency of any nation is most likely to
change its weights attached to other currencies or switch parameters or even the
exchange rate regime frequently. Table I makes it clear that different exchange rate
regimes are in operation for speci?c years and even months only[6].
To ascertain the dynamic evolution of the degree of ?exibility I use the recursive
least squares for the US dollar coef?cients, similar to Cavoli and Rajan (2010). This
entails running the regressions iteratively and recording the corresponding US dollar
coef?cient until we reach the full-sample. To render insuf?cient degrees of freedom
I omit the ?rst 30 observations. Figure 1 compares the recursive coef?cients for the US
dollar in 1990s with that in 2000s.
An ocular view shows the time plot of the US dollar coef?cients to be lower in 2000s
than that in 1990s for Brazil, Chile, Colombia and Mexico, and is also declining over the
last decade. For Peru and Uruguay I see a declining trend in the dollar weights in 2000s
albeit around unity, while for Venezuela the plot of the dollar coef?cients in 2000s is
above that in 1990s indicative of less ?exibility which is broadly consistent with the
earlier ?ndings. Nicaragua’s US dollar coef?cient hovers around unity over 2000s and
is not indicative of any increase in ?exibility.
4. Estimation across exchange rate regime type
An interesting point of analysis is how do a cluster of nations under a given IMF
exchange rate classi?cation behave in their currency linkages with the major currencies
compared to a group of nations falling under another regime classi?cation
(e.g. independent ?oaters vs crawling peggers)? The latest IMF classi?cation is used
here for clustering the countries where each panel represents a regime type[7]. A priori
the EMP coef?cient should be greater for in?ation targeting regimes compared to
non-in?ation targeting ones, if the former truly follows a ?oating regime. Likewise EMP
coef?cient is expected to be highest for independent ?oaters, followed by managed
?oaters and then crawling and conventional pegs, respectively, while dollar weights are
expected to be lowest for independent ?oaters and highest for conventional pegs.
Table V presents the panel results with cross sectional ?xed effects.
The EMP coef?cient is of similar magnitude for in?ation targeting regimes (0.206)
vis-a` -vis non-in?ation targeters (0.208). This reinforces the issue of foreign exchange
market intervention, which makes the FIT regimes to resemble no differently than
non-FIT regimes. This coef?cient is highest (0.427) and dollar weight lowest (0.781)
for independent ?oating regimes, followed by managed ?oating regimes consistent
with theoretical priors. It is insigni?cant for crawling pegs but is signi?cant at a very
low value for conventional pegs. Noteworthy, the EMP coef?cient of only 0.427 for
independent ?oaters is again suggestive of suf?cient propensity to intervene in foreign
exchange markets. I also ?nd the euro to complement the dollar in the currency weights
and is signi?cant and highest for the independent ?oaters (0.262) followed by the
in?ation targeters (0.24) and then managed ?oaters (0.178).
5. Conclusion
This paper reviews the de facto evolution of exchange rate regimes in Latin America
spanning across nations and over time. I ?nd Latin American currencies to have high
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Figure 1.
Recursive estimates of US
dollar coef?cients
Argentina
0.5
0.7
0.9
1.1
1.3
3
0
4
2
5
4
6
6
7
8
9
0
1
0
2
1
1
4
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Bolivia
0.94
0.96
0.98
1
1.02
1.04
3
1
5
5
7
9
1
0
3
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Brazil
0.4
0.6
0.8
1
1.2
3
1
5
2
7
3
9
4
1
1
5
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Chile
0.5
0.6
0.7
0.8
0.9
1
1.1
3
1
5
5
7
9
1
0
3
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Colombia
0.5
0.7
0.9
1.1
3
1
5
1
7
1
9
1
1
1
1
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Ecuador
0.9
1
1.1
1.2
1.3
3
1
4
8
6
5
8
2
9
9
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
Mexico
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
3
1
5
3
7
5
9
7
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Nicaragua
0.92
0.94
0.96
0.98
1
1.02
1.04
3
1
5
3
7
5
9
7
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Paraguay
0.7
0.9
1.1
1.3
1.5
3
1
5
3
7
5
9
7
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Peru
0
0.2
0.4
0.6
0.8
1
1.2
3
1
5
1
7
1
9
1
1
1
1
Observations
U
S
D
w
e
i
g
h
t
s
1990 s
2000 s
Uruguay
0.9
1.1
1.3
1.5
1.7
1.9
3
1
4
8
6
5
8
2
9
9
1
1
6
Observations
U
S
D
w
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i
g
h
t
s
1990 s
2000 s
Venezuela
0
0.5
1
1.5
2
3
1
4
9
6
7
8
5
1
0
3
Observations
U
S
D
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i
g
h
t
s
1990 s
2000 s
Exchange rate
?exibility
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weightage with the dollar, regardless of their IMF regime classi?cation. A noticeable
increase in ?exibility is evident from the 1990s to the 2000s especially for Colombia,
Chile and Mexico. However, the results document FIT nations to adopt a policy of
“guarded caution” and follow more of a de facto managed ?oating regime and are far
from pure ?oats, which is the normative stance for in?ation targeters. The former
allows an extra degree of freedom to central banks by intervening in foreign exchange
markets to smoothen out periods of excessive volatilities in their currencies. Hysteresis
on real exchange rate appreciation and precautionary motive of hoarding foreign
exchange reserves to prevent potential runs on their currency explain this. This ?nding
is further reinforced when I cluster the countries according to IT and non-IT nations.
While the results correlate to an extent with the IMF classi?cation of exchange rate
regimes I note areas of discrepancy. Smaller economies of Bolivia, Uruguay and
Venezuela exhibit low degrees of ?exibility, inconsistent with their respective IMF
classi?cations. The results presented here are suggestive of a “crowding to the middle”
across the spectrum of regime options.
Notes
1. The IMF also lent support to this view of ?eeing the middle and moving to the corners in
proffering advice to its members about the selection of exchange rate regimes. See IMF’s
Independent Evaluation Of?ce 2007 Report.
2. A country leaning towards a more ?xed (?exible) regime a priori will have less (more)
variability of its exchange rate series relative to the variability of its foreign exchange
reserves. Countries can of course intervene in foreign exchange markets to limit the extent of
de facto ?exibility due to “fear of ?oating” concerns.
3. SDR is used here as the numeraire currency. A weighted index of currencies such as the SDR
is most appropriate here. If the central bank of a nation intervenes in the foreign exchange
market to allow only a partial deviation of their currency from a standard level, then they
would think more in terms of a weighted average of the major currencies of that nation and
In?ation
targeting
Non-in?ation
targeting
Independent
?oating
Managed
?oating
Crawling peg Conventional
peg
C 20.001 0.003
* * *
20.003
* * *
0.001 0.003 0.004
* * *
(20.845) (2.182) (22.126) (0.612) (6.422) (2.763)
DLEURO 0.240
* * *
0.091 0.262
* * *
0.178
* * *
0.047
* * *
0.100
(4.382) (1.326) (3.804) (2.506) (2.351) (1.580)
DLJAP 20.151
* * *
20.071 20.179
* * *
20.104
*
20.021 20.089
(23.276) (21.225) (23.068) (21.732) (21.253) (21.677)
DLUS 0.873
* * *
1.004
* * *
0.781
* * *
0.924
* * *
0.997
* * *
1.073
* * *
(14.172) (13.041) (10.046) (11.662) (44.302) (15.085)
EMP
t
0.206
* * *
0.208
* * *
0.427
* * *
0.193
* * *
20.001 0.070
* * *
(10.460) (10.519) (15.853) (8.063) (20.214) (4.037)
Adj. R
2
0.353 0.397 0.522 0.320 0.933 0.384
D-W 1.663 1.557 2.047 1.857 2.391 1.782
Cross-
sections/N
6/738 5/615 3/369 4/492 2/246 2/246
Notes: Signi?cant at:
*
10,
* *
5 and
* * *
1 percent levels; terms in brackets denote t-stat.; a lagged
dependent variable was used to deal with issues of serial correlation
Table V.
Panel results by
exchange rate regime
type – 2000M1: 2010M6
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not in terms of one speci?c currency. Also from an econometric perspective SDR reduces
potential correlation issues of the error term with the numeraire.
4. The pound weight can be retrieved by simply subtracting the sum of the weights of the
currencies’ from unity.
5. Apprehensions to ?oat a nation’s currency can also occur due to “balance sheet
mismanagement” where a country is exposed to substantial foreign currency denominated
obligations often constrains a nation from ?oating its currency, a highly dollarized economy
like Peru’s recent intervention in the foreign exchange market to maintain ?nancial stability
is evidence of the latter (Dancourt, 2009). As such its EMP coef?cient (0.135) is low and less
than other in?ation targeters.
6. An option is to re-run the regression for each sub-sample. But that would require very high
frequency data like weekly or bi-weekly and is not available for most of these nations.
7. IMF classi?es Bolivia, Nicaragua as crawling peggers; Brazil, Chile, Mexico as independent
?oaters; Colombia, Peru, Uruguay, Paraguay as managed ?oaters; Argentina and Venezuela
as conventional ?xed peggers.
References
Baig, T. (2001), “Characterizing exchange rate regimes post-crisis East Asia”, Working Paper
No. 01/152, International Monetary Fund, Washington, DC.
Bayoumi, T. and Eichengreen, B. (1998), “Exchange rate volatility intervention: implications of
the theory of optimum currency areas”, Journal of International Economics, Vol. 45 No. 2,
pp. 191-209.
Calvo, G. and Reinhert, C. (2002), “Fear of ?oating”, Quarterly Journal of Economics, Vol. 117
No. 2, pp. 379-408.
Cavoli, T. and Rajan, R.S. (2010), “Exchange rate regimes in Asia: are they what they claim to
be?”, Economics Bulletin, Vol. 30 No. 4, pp. 2864-2876.
Corden, W.M. (2003), Too Sensational on the Choice of Exchange Rate Regimes, MIT Press,
Cambridge, MA.
Dancourt, O. (2009), “Peru´: la recesio´n del 2008-09 en perspective”, available at: www.itf.org.ar/
pdf/documentos/67-2010.pdf
Frankel, J. and Wei, S.J. (2008), “Estimation of de facto exchange rate regimes: synthesis of the
techniques for inferring ?exibility and basket weights”, Staff Paper No. 55, International
Monetary Fund, Washington, DC, pp. 384-416.
Ocampo, J.A. and Tovar, C. (2003), “Colombia’s experience with reserve requirements on capital
in?ows”, Cepal Review, Vol. 81, pp. 7-31.
Truman, E.M. (2006), “A strategy for IMF reform”, Policy Analyses in International Economics,
Vol. 77, Peterson Institute for International Economics, Washington, DC.
Williamson, J. (2000), “Exchange rate regimes for emerging market economies: reviving the
intermediate options”, Policy Analysis in International Economics, Vol. 60, Peterson
Institute for International Economics, Washington, DC.
Further reading
Bubula, A. and O
¨
tker-Robe, I. (2002), “The evolution of exchange rate regimes since 1990:
evidence from de facto policies”, Working Paper No. 02/155, International Monetary Fund,
Washington, DC.
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Frenkel, R. and Rapetti, M. (2010), AConcise History of Exchange Rate Regimes in Latin America,
Centre for Economic and Policy Research, Report, Washington, DC.
Independent Evaluation Of?ce of the International Monetary Fund (2007), An IEO Evaluation of
IMF Exchange Rate Policy Advice, 1999-2005: Evaluation Report, Independent Evaluation
Of?ce of the International Monetary Fund, Washington, DC.
About the author
Dr Amit Ghosh is currently Assistant Professor of Economics at Illinois Wesleyan University,
Department of Economics, Illinois, USA. Previously he worked in the capacity of Visiting
Assistant Professor at Colorado College, Department of Business and Economics, Colorado, USA
from 2006-2008. He has also served as a research assistant at the Lowe Institute of Political
Economy, Claremont McKenna College, California, USA. He works mainly in the areas of
international trade and ?nance. He has published several articles on the topics of “cross-border
production sharing” and “exchange rate pass-through,” with particular reference to Asia and
Latin America. His current ongoing research includes analyzing different aspects and implications
of exchange rate regimes, open-economy policy trilemma, and examining the relationship between
terms-of-trade and trade balance. Amit Ghosh can be contacted at: [email protected]
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