Transcript Exchange Rate Regimes: Current Issues in Research & Policy Jeffrey Frankel Harpel Chair, Harvard University IMF Institute * May 28, 2010 * Professor Jeffrey Frankel.

Exchange Rate Regimes:
Current Issues in Research & Policy
Jeffrey Frankel
Harpel Chair, Harvard University
IMF Institute
* May 28, 2010 *
Professor Jeffrey Frankel
Topics to be covered
I. Classifying countries by exchange rate regime
•
•
De facto vs. de jure
The approaches used to infer de facto regimes
II. Advantages of fixed rates
•
The trade-promoting effect of currency unions: the € case
III. Advantages of floating rates
IV. Which regime dominates?
V. Additional factors for developing countries
•
•
•
Emigrants’ remittances
Financial development
Terms-of-trade shocks; the PEP proposal
Appendices:
1.
2.
3.
The RMB case
Corners
More on synthesis technique for regime estimation
Professor Jeffrey Frankel
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
8) Dollarization
9) Monetary union
Professor Jeffrey Frankel
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)
Professor Jeffrey Frankel
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 currencies,
in fact fiddle with the weights. [3]
[1] “Fear of floating” -- Calvo & Reinhart (2001, 2002); Reinhart (2000).
[2] “The mirage of fixed exchange rates”
-- Obstfeld & Rogoff (1995); Klein & Marion (1997).
[3] Parameters kept secret -- Frankel, Schmukler & Servén (2000).
Professor Jeffrey Frankel
Economists have offered de facto
classifications, placing countries
into the “true” categories
• Important examples include Ghosh, Gulde & Wolf (2000),
Reinhart & Rogoff (2004), Shambaugh (2004a), & more to be cited.
• Tavlas, Dellas & Stockman (2008) survey the literature.
• Unfortunately, these classification schemes
disagree with each other as much as they
disagree with the de jure classification! [1]
• => Something must be wrong.
[1] See Bénassy-Quéré, et al (Table 5, 2004);
Frankel (Table 1, 2004); and Shambaugh (2004b):
Professor Jeffrey Frankel
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.
Professor Jeffrey Frankel
Shambaugh (2007) finds the same thing:
the de facto classification schemes tend to agree with each
other even less than they agree with the de jure scheme.
Percentage agreement of methodologies to code who pegs
De
Jure
Jay S.
LY-S
De
Jure
100%
Jay S.
86%
100%
LY-S
74%
80%
100%
R-R
81%
82%
73%
R-R
100%
Professor Jeffrey Frankel
The IMF now has its own “de facto classification”
-- but still close to official IMF one: correlation (BOR, IMF) = .76
Bénassy-Quéré et al (2004)
Professor Jeffrey Frankel
=> 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, 2005).
Professor Jeffrey Frankel
Phrase this 1st approach
in terms of Exchange Market Pressure:
• Define
EMP = Δ value of currency + Δ reserves.
– EMP represents shocks in currency demand.
– Flexibility can be estimated
as the propensity of the central bank to let shocks show
up in the price of the currency (floating) ,
vs. the quantity of the currency (fixed),
or in between (intermediate exchange rate regime).
Professor Jeffrey Frankel
Several things are wrong, continued.
Difficulty #2:
Those papers sometimes impose the choice
of the major currency around which the country
in question defines its value (often the $).
• It would be better to estimate endogenously whether the
anchor currency is the $, the €, some other currency, or
some basket of currencies.
• That problem has been addressed by a 2nd approach:
Professor Jeffrey Frankel
• Some currencies have basket anchors,
often with some flexibility that can
be captured either by a band (BBC) or
by leaning-against-the-wind intervention.
• Most basket peggers keep the weights secret.
They want to preserve a degree of freedom
from prying eyes, whether to pursue
– a less de facto flexibility, as China,
– or more, as with most others.
Professor Jeffrey Frankel
The 2nd approach in the de facto regime
literature estimates implicit basket weights:
Regress Δvalue of local currency
against Δ values of major currencies.
•
First examples: Frankel (1993) and Frankel & Wei (1994, 95).
•
More: Bénassy-Quéré (1999), Ohno (1999), Frankel, Schmukler, Servén
& Fajnzylber (2001), Bénassy-Quéré, Coeuré, & Mignon (2004)….
•
Example of China, post 7/05:
–
–
Eichengreen (2006), Shah, Zeileis & Patnaik (2005), Yamazaki (2006), Ogawa
(2006), Frankel-Wei (2006, 07), Frankel (2009)
Findings:
•
•
•
RMB still pegged in 2005-06, with 95% weight on $.
Moved away from $ (weight on €) in 2007-08
Returned to $ peg in mid 2008.
Professor Jeffrey Frankel
Implicit basket weights method
-- regress Δvalue of local currency against
Δ values of major currencies -- continued.
• Null Hypotheses: Close fit => a peg.
• Coefficient of 1 on $ => $ peg.
• Or significant weights on other currencies
=> basket peg.
•
But if the test rejects tight basket peg,
what is the Alternative Hypothesis?
Professor Jeffrey Frankel
Several things are wrong, continued.
Difficulty #3:
The 2nd approach
(inferring the anchor currency or basket)
does not allow for flexibility around that anchor.
• Inferring de facto weights and inferring de facto
flexibility are equally important,
• whereas most authors have hitherto done only one
or the other.
Professor Jeffrey Frankel
The synthesis technique
• A synthesis of the two approaches for statistically
estimating de facto exchange rate regimes:
(1) the technique that we have used in the past to
estimate implicit de facto weights
when the hypothesis is a basket peg with little flexibility. +
(2) the technique used by others to estimate de facto
exchange rate flexibility when the hypothesis is an anchor to
the $, but with variation around that anchor.
• => We need a synthesis that can cover both
dimensions: inferring weights and inferring flexibility.
Professor Jeffrey Frankel
Several things are wrong, continued.
Difficulty #4:
All these approaches, even the synthesis technique, are
plagued by the problem that many countries frequently
change regimes or (for those with intermediate regimes)
change parameters.
• E.g., Chile changed parameters 18 times in 18 years (1980s-90s)
• Year-by-year estimation won’t work,
because parameter changes come at irregular intervals.
• Chow test won’t work,
because one does not usually know the candidate dates.
• Solution: Apply Bai-Perron (1998, 2003) technique
for endogenous estimation of structural break point dates.
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
The technique that estimates basket weights
• Assuming the value of the home currency is
determined by a currency basket, how does
one uncover the currency composition & weights?
Regress changes in log H, the value of the home
currency, against changes in log values of candidate
currencies.
• Algebraically, if the value of the home currency H is
pegged to the values of currencies X1, X2, … & Xn,
with weights equal to w1, w2, … & wn, then
Δ logH(t) =c + ∑ w(j) [Δ logX(j)]
(1)
Professor Jeffrey Frankel
Δ log Ht
= c + ∑ w(j) [Δ logX(j)t ]
= c + w(1) Δ log $ t + w(2) Δ log ¥t
+ w(3) Δ log €t + α Δ log £t
• If the exchange rate is governed by a strict basket peg,
• we should recover the true weights, w(j), precisely;
• and the equation should have a perfect fit.
Professor Jeffrey Frankel
Distillation of technique to infer flexibility
• When a shock raises international demand for the currency,
do the authorities allow it to show up as an appreciation,
or as a rise in reserves?
• Frame the issue in terms of Exchange Market Pressure
(EMP), defined as: % increase in the value of the currency
plus increase in reserves (as share of monetary base).
• EMP variable appears on the RHS of the equation.
The % rise in the value of the currency appears on the left.
– A coefficient of 0 on EMP signifies a fixed E
(no changes in the value of the currency),
– a coefficient of 1 signifies a freely floating rate
(no changes in reserves) and
– a coefficient somewhere in between indicates
a correspondingly flexible/stable intermediate regime.
Professor Jeffrey Frankel
Synthesis equation
Δ logH(t) = c + ∑ w(j) Δ[logX(j, t)]
+ ß {Δ EMP(t)} + u(t)
(2)
where
Δ EMP(t) ≡ Δ[logH(t)] + [ΔRes(t) / MB(t)].
We impose ∑ w(j) = 1, implemented by treating £ as the last currency.
Professor Jeffrey Frankel
Now we introduce Bai-Perron technique
for endogenous estimation
of m possible structural break points
k
 log H t  ci   wi , j  log X i , j ,t  i  EMPt  ut
j 1
(6)
t  Ti1  1,...,Ti ; T0  0; Tm1  T ; i  1,...,m  1
For further details, see NBER WP, Dec. 2009.
Professor Jeffrey Frankel
Illustration using 5 currencies
• These are 5 emerging market currencies of interest
all of which now make available their data on
reserves on a weekly basis
(which is necessary to get good estimates, if structural changes
happen as often as yearly)
• Mexico (monetary base is also available weekly)
• Chile, Russia, Thailand, India
(although reserves available weekly, denominator must be
interpolated from monthly monetary base data)
Professor Jeffrey Frankel
Overview of findings
• For all five, the estimates suggest managed floats
during most of the period 1999-2009.
• This was a new development for emerging
markets.
• Most of the countries had had some variety of a
peg before the currency crises of the 1990s.
• But the Bai-Perron test shows statistically
significant structural breaks for every currency,
• even when the threshold is set high, at the 1%
level of statistical significance.
Professor Jeffrey Frankel
Table 1A reports estimation for the Mexican
peso
• 5 structural breaks
• The peso is known as a floater.
• To the extent Mexico intervenes to reduce exchange rate
variation, $ is the primary anchor, but some weight on €
also appears, starting in 2003.
• Aug.2006 - Dec.2008, coefficient on EMP is essentially 0,
surprisingly, suggesting intervention around a $ target.
• But in the period starting Dec.2008, the peso once again
moved away from the currency to the north,
as the worst phase of the global liquidity crisis hit and $
appreciated.
Professor Jeffrey Frankel
Table 1A. Identifying Break Points in Mexican Exchange Rate Regime
M1:1999-M7:2009
(1)
(2)
(3)
(4)
(5)
(6)
1/21/19999/2/2001
9/9/20013/18/2003
3/25/20037/29/2006
8/5/20061/28/2008
2/4/200812/15/2008
12/22/20087/29/2009
0.92***
0.88***
0.62***
1.11***
0.96***
0.20
(0.09)
(0.12)
(0.07)
(0.10)
(0.19)
(0.22)
0.14
-0.09
0.30***
0.20*
0.51***
0.51***
(0.08)
(0.14)
(0.09)
(0.11)
(0.16)
(0.18)
-0.05
0.22***
0.08
-0.34***
-0.33**
0.18
(0.06)
(0.07)
(0.06)
(0.06)
(0.12)
(0.13)
0.14***
0.32***
0.17***
0.02
0.07
0.28***
(0.03)
(0.03)
(0.03)
(0.02)
(0.07)
(0.04)
0.00
-0.00***
-0.00*
-0.00
-0.00
0.00
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
(0.00)
Observations
131
78
168
76
46
29
R-squared
0.62
0.86
0.69
0.67
0.54
Br. Pound
-0.01
-0.01
-0.01
0.02
-0.14
VARIABLES
US dollar
euro
Jpn yen
△EMP
Constant
0.78
Professor Jeffrey Frankel
0.11
Tables 1B-1E
• Chile (with 3 estimated structural breaks) appears a managed
floater throughout.
– The anchor is exclusively the $ in some periods,
but puts significant weight on the € in other periods.
• Russia (3 structural breaks) is similar,
except that the $ weight is always significantly less than 1.
• For Thailand (3 structural breaks), the $ share in the anchor
basket is slightly > .6, but usually significantly < 1.
– The € & ¥ show weights of about .2 each Jan.1999-Sept. 2006.
• India (5 structural breaks) apparently fixed its exchange rate
during two of the sub-periods, but pursued a managed float in
the other four sub-periods.
– $ was always the most important of the anchor currencies, but the € was also
significant in four out of six sub-periods, and the ¥ in two.
Professor Jeffrey Frankel
Future research
• Results for other currencies will be published
in other papers
– Often requiring weekly interpolation between
monthly reserve figures.
– Including our China updates
– And true basket/band/crawl currencies
• Econometric extension: use Threshold
Autoregression for target zones.
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.
Professor Jeffrey Frankel
II. Advantages of fixed rates
1) Encourage trade <= lower exchange risk.
• In theory, can hedge risk.
But costs of hedging:
missing markets, transactions costs, and risk premia.
•
Empirical:
Exchange rate volatility ↑ => trade ↓ ?
Time-series evidence showed little effect. But more in:
- Cross-section evidence,
especially small & less developed countries.
- Borders, e.g., Canada-US:
McCallum-Helliwell (1995-98); Engel-Rogers (1996).
- Currency unions: Rose (2000).
Professor Jeffrey Frankel
The case of the euro’s effect on trade
Frankel, “The Estimated Effects of the Euro on Trade: Why are They Below
Historical Evidence on Effects of Monetary Unions Among Smaller Countries?”
in Europe and the Euro, edited by A.Alesina & F.Giavazzi, 2010.
1. Gravity estimates of effect of € on intra-EMU trade
in the first decade show the coefficient steady ≈ 15% .
2. << estimates of other Monetary Unions’ effects (x2 or x3)
3. No evidence that the gap is explained by a MU effect that
1.
2.
diminishes with country size, or
is subject to long lags.
Professor Jeffrey Frankel
Why is the estimated effect in euro-land so much smaller
than monetary unions among small developing countries?
Professor Jeffrey Frankel
A natural experiment:
The effects of the French franc’s conversion to €
on bilateral trade of African CFA members.
•
The long-time link of CFA currencies to the French franc
has clearly always had a political motivation.
–
So CFA-France trade could not reliably be attributed to currency link,
•
•
perhaps even after controlling for common language, former colonial status, etc.
But in Jan. 1999, 14 CFA countries suddenly found themselves with
the same currency link to Germany, Austria, Finland, etc.
– No economic/political motivation. A natural experiment.
– If CFA trade with these other countries has risen,
that suggests a € effect that we can declare causal.
35
Professor Jeffrey Frankel
Results of CFA experiment
• The dummy variable
representing when one partner is
a CFA country and the other a € country
has a highly significant coefficient of .57.
• Taking the exponent, the point estimate
is that the euro boosts bilateral trade between
the relevant African and € countries by 76%.
36
Professor Jeffrey Frankel
Bottom line on discrepancy in € effect
• The large effect of monetary unions on
developing countries is real.
• Tentative conclusion:
– Although monetary unions don’t have larger effects
on small countries per se,
– They do have larger effects on poor countries per se.
Professor Jeffrey Frankel
Advantages of fixed rates, cont.
2) Encourage investment
<= cut currency premium out of interest rates
3) Provide nominal anchor for monetary policy
– Barro-Gordon model of time-consistent inflation-fighting
– But which anchor?
• Exchange rate target vs.
• Alternatives such as Inflation Targeting
4) Avoid competitive depreciation
5) Avoid speculative bubbles that afflict floating.
(If variability were all fundamental real exchange rate risk, and no bubbles,
then fixing the nominal rate would mean it would just pop up in prices instead.)
Professor Jeffrey Frankel
Most important finding of last decade
• Empirical finding of Rose (2000) that the boost to bilateral
trade from currency unions is significant, ≈ FTAs, &
larger (3-fold) than had been thought.
– Many others have advanced critiques of Rose research.
• Re: Endogeneity, small countries, missing variables & sheer magnitude.
– Estimated magnitudes are often smaller, but the basic finding
has withstood perturbations and replications remarkably well. ii/
– Some developing countries seeking regional integration
talk of following Europe’s lead, tho plans merit skepticism.
• Parsley-Wei: currency effect explains border effects.
• Klein-Shambaugh: de facto pegs have major effect too.
[ii] E.g., Rose & van Wincoop (2001); Tenreyro & Barro (2003).
Survey: Baldwin (2006)
Professor Jeffrey Frankel
Evidence on currency unions
Currency unions
• promote trade/GDP (no evidence of trade-diversion), &
• thereby promote LR growth.
-- Frankel & Rose, QJE, 2002.
Endogeneity of OCA criteria:
• Trade responds positively to currency regime
• A pair’s cyclical correlation rises too
(rather than falling, as under Eichengreen-Krugman hypothesis)
-- Frankel & Rose, EJ, 1996
Professor Jeffrey Frankel
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.)
Professor Jeffrey Frankel
IV. Which dominate: advantages of
fixing or advantages of floating?
Performance by category is inconclusive.
• To over-simplify findings of 3 important studies:
– Ghosh, Gulde & Wolf:
hard pegs work best
– Sturzenegger & Levy-Yeyati: floats perform best
– Reinhart-Rogoff:
limited flexibility is best
• Why the different answers?
– Conditioning factors.
– The de facto schemes do not correspond to each other.
Professor Jeffrey Frankel
Which category
experienced the
most rapid
growth?
Ghosh, Gulde
& Wolf:
currency boards
LevyYeyati &
Sturzenegg
er:
floating
Reinhart &
Rogoff:
limited
flexibility
Professor Jeffrey Frankel
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.
Professor Jeffrey Frankel
Optimum Currency Area Theory (OCA)
Broad definition: An optimum currency area is a region
that should have its own currency and own monetary policy.
This definition can be given more content:.
An OCA can be defined as:
a region that is neither so small and open that it would be
better off pegging its currency to a neighbor, nor so large
that it would be better off splitting into sub-regions with
different currencies
Professor Jeffrey Frankel
Optimum Currency Area criteria for
fixing exchange rate:
• Small size and openness
– because then advantages of fixing are large.
• Symmetry of shocks
– because then giving up monetary independence is a small loss.
• Labor mobility
– because then it is possible to adjust to shocks even without
ability to expand money, cut interest rates or devalue.
• Fiscal transfers in a federal system
– because then consumption is cushioned in a downturn.
Professor Jeffrey Frankel
New popularity in 1990s of
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)
Professor Jeffrey Frankel
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.
Professor Jeffrey Frankel
V. Three additional considerations,
particularly relevant
to developing countries
• (i) Emigrants’ remittances
• (ii) Level of financial development
• (iii) External terms of trade shocks
and the proposal to Peg the Export Price
Professor Jeffrey Frankel
(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, in the way that private
capital flows promise to be in theory, but fail in practice?
Professor Jeffrey Frankel
Brief literature summary
• Theory
– Chami et al (2008): remittances are macroeconomically
stabilizing.
– Martin (1990): steady flow of remittances can undermine the
incentive for governments to create a sound institutional
framework – a sort of natural resource curse for remittances.
• Bilateral Data
– Ratha and Shaw (2005), in the absence of hard bilateral data,
allocate the totals across partners.
– Schiopu & Siegfried (2006) created bilateral data set between
some EU countries & neighbors.
– Jiménez-Martin, Jorgensen, & Labeaga (2007) estimate bilateral
workers’ remittance flows from all 27 members of the EU.
– Lueth & Ruiz-Arranz (2006, 2008) have largest bilateral data set
to date.
Professor Jeffrey Frankel
Literature review: cyclicality of remittances
• Evidence on cyclicality
–
–
–
–
–
–
World Bank: p.c. remittances respond significantly to home country p.c.income.
Clarke & Wallstein (2004) & Yang (2007): receipts rise in response to natural disaster.
Kapur (2003): they go up in response to an economic downturn.
Lake (2006): remittances into Jamaica respond to the US-local income difference
Yang and Choi (2007): they respond to rainfall-induced economic fluctuations.
IMF finds less countercyclicality.
• Sayan (2006): 12-developing-country study finds no countercyclicaty.
• Lueth & Ruiz-Arranz (2006, 2008): similarly.
• Evidence on the Dutch Disease.
– On the one hand, Rajan & Subramanian (2005): although the Dutch Disease analogy
does extend to foreign aid (leading to real appreciation & slow growth), it does not
extend to remittances.
– On the other hand, Amuendo-Dorantes & Pozo (2004): an increase in remittances to
LACA countries leads to real appreciation, a major symptom of Dutch Disease.
• OCA
– Singer (2008): counter-cyclical remittances are a determinant of the currency decision.
Professor Jeffrey Frankel
“Are Bilateral Remittances Countercyclical?
Implications for…Currency Unions” -- Frankel (Oct. 2009)
I combine the three substantial data sets on
bilateral remittances that I know of:
I find strong evidence of countercyclicality
– Lueth & Ruiz-Arranz (2006, 2008), for an eclectic set of countries (mostly in
Europe & Asia), thanks to their generosity in supplying the data.
– Jiménez-Martin, Jorgensen, & Labeaga (2007) for EU sending countries.
• For Central American receiving countries (incl. DR, El Salvador & Panama)
I find strong evidence of countercyclicality.
Professor Jeffrey Frankel
Dependent Variable:
Table 3: Cross-Section 2003-04 -Composite data set (merging three sources)
Ln (Stock migrants 2000 )
Cyclical Difference (Ln (Real GDP/ Trend GDP))
Sender relative to recipient
Ln Remittances 2003-04 between Countries
(1)
(2)
(3)
(4)
0.762***
0.741***
1.061***
1.233***
(0.040)
(0.041)
(0.088)
(0.152)
16.199***
16.099***
14.723***
13.983***
(2.905)
(2.765)
(3.390)
(3.927)
0.039***
0.028*
0.022
(0.015)
(0.016)
(0.019)
1.345***
0.087
-0.590
(0.222)
(0.389)
(0.632)
OLS
2SLS
2SLS
border/language/
islands/colonial
border/language
GDP per capita Sender
Currency Union
Estimation Method
OLS
Instrumental variables
Observations
R2
331
328
328
328
0.526
0.546
0.463
0.351
Statistical significance: * 10% level, ** 5% level, *** 1% level
Three sources of remittance data for 2003-04: Central America data, FOMIN and the Central Banks; EU data: Jiménez-Martín, S., Jorgensen, N.
and Labeaga, J. M. (2007); IMF data: Lueth, E. and Ruiz-Arranz, M. (2006).
Professor Jeffrey Frankel
(ii) Level of financial development
Aghion, Bacchetta, Ranciere & Rogoff
(2005)
– Fixed rates are better for countries at
low levels of financial development:
because markets are thin =>
benefits of accommodating real shocks are outweighed by
costs of financial shocks.
– When financial markets develop, exchange flexibility
becomes more attractive.
– Estimated threshold: Private Credit/GDP > 40%.
Professor Jeffrey Frankel
Level of financial development, cont.
Husain, Mody & Rogoff, JME
52 , Jan.
2005 35-64
• For poor countries with low capital mobility, pegs work
– in the sense of being more durable
– & delivering low inflation
• For richer & more financially developed countries,
flexible rates work better
– in the sense of being more durable
– & delivering higher growth without inflation
Professor Jeffrey Frankel
(iii) External Shocks
• An old wisdom regarding the source of shocks:
– Fixed rates work best if shocks are mostly internal
demand shocks (especially monetary);
– floating rates work best if shocks tend to be real
shocks (especially external terms of trade).
• One case of supply shocks: natural disasters
– R.Ramcharan, 2007, finds support.
“Does the Exchange Rate Regime Matter for Real Shocks? Evidence from Windstorms and Earthquakes,” JIE.
• Most common case of real shocks: trade
Professor Jeffrey Frankel
Terms-of-trade variability returns
• Prices of crude oil and other agricultural & mineral
commodities hit record highs in 2008.
• => Favorable terms of trade shocks for some
(oil producers, Chile, Africa, etc.);
• => Unfavorable terms of trade shock for others
(oil importers like Japan, Korea).
• Textbook theory says a country where trade shocks
dominate should accommodate by floating.
• Edwards & L.Yeyati (2003): Among peggers, terms-of-trade
shocks are amplified and long-run growth is reduced,
as compared to flexible-rate countries.
Professor Jeffrey Frankel
Fashions in international currency policy
• 1980-82: Monetarism (target the money supply)
• 1984-1997: Fixed exchange rates
(incl. currency boards)
• 1993-2001: The corners hypothesis
• 1998-2008: Inflation targeting (+ currency float)
became the new conventional wisdom
• Among academic economists
• Among central bankers
• At the IMF
Professor Jeffrey Frankel
Inflation Targeting:
“It’s not just for rich countries anymore”
Source: IMF Survey. October 23, 2000. Andrea Schaechter, Mark Stone, Mark Zelmer in the IMF, MEA Dept.
Online at: http://www.imf.org/external/pubs/ft/survey/2000/102300.pdf
The background papers for the high-level seminar “Implementing Inflation Targets,” 2000,
available on the IMF Website: http://www.imf.org/external/pubs/ft/seminar/2000/targets/index.htm
Professor Jeffrey Frankel
Inflation targeting is the reigning orthodoxy.
• Economists, central bankers, IMF…
• Flexible inflation targeting ≡
“Have a LR target for inflation, and be transparent.” ?
Who could disagree?
• But define IT as setting yearly CPI targets, to the exclusion of
• asset prices
• exchange rates
• export commodity prices.
Professor Jeffrey Frankel
• The shocks of 2007-2010 have shown
some disadvantages to Inflation Targeting,
– analogously to how the emerging market crises of 19942001 showed disadvantages to exchange rate targeting.
• One disadvantage of IT:
no response to asset price bubbles.
• Another disadvantage:
– It gives the wrong answer in case of supply shocks:
• E.g., in response to a rise in oil import prices,
it says to tighten monetary policy & appreciate, to keep CPI steady.
• In response to a rise in world prices of export commodities,
it does not allow monetary tightening and appreciation.
Professor Jeffrey Frankel
Proposal to Peg the Export Price (PEP)
Intended for countries with volatile terms of trade,
particularly those specialized in the production of
mineral or agricultural commodity exports.
Proposal in its pure form:
The authorities peg the currency to a basket or
price index that includes the price of their leading
commodity export (oil, gold, copper, coffee…),
rather than to the $ or € or CPI.
My claim is that the regime combines the best of both worlds:
(i) The advantage of automatic accommodation to terms of
trade shocks, together with
(ii) the advantages of a nominal anchor and integration.
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
PEP
How would it work operationally,
say, for a Gulf oil-exporter?
• Each day, after noon spot price of oil in London S($/barrel),
the central bank announces the day’s exchange rate,
according to the formula:
• E (dirham/$) = fixed target price P(dirham/barrel) / S($/barrel).
It intervenes in $ to hold this exchange rate for the day.
• The result is that P (dirham/barrel)
is indeed fixed from day to day.
Professor Jeffrey Frankel
Does floating give the same answer?
• True, commodity currencies tend to appreciate
when commodity markets are strong, & vice versa
– Australian, Canadian & NZ $ (e.g., Chen & Rogoff, 2003)
– South African rand (e.g., Frankel, 2007)
– Chilean peso and others
• But
– Some volatility under floating appears gratuitous.
– Floaters still need a nominal anchor.
Professor Jeffrey Frankel
The Rand, 1984-2006:
Fundamentals (real commodity prices,
real interest differential, country risk premium, & l.e.v.)
can explain the real appreciation of 2003-06 – Frankel (SAJE, 2007).
200.000
180.000
160.000
140.000
120.000
100.000
80.000
60.000
40.000
Actual
vs
Fitted
vs.
20.000
FundamentalsProjected Values
Q
Q
2
19
8
1 4
19
Q 85
4
19
Q 85
3
19
Q 86
2
19
Q 87
1
19
Q 88
4
19
Q 88
3
19
Q 89
2
19
Q 90
1
19
Q 91
4
19
Q 91
3
19
Q 92
2
19
Q 93
1
19
Q 94
4
19
Q 94
3
19
Q 95
2
19
Q 96
1
19
Q 97
4
19
Q 97
3
19
Q 98
2
19
Q 99
1
20
Q 00
4
20
Q 00
3
20
Q 01
2
20
Q 02
1
20
Q 03
4
20
Q 03
3
20
Q 04
2
20
Q 05
1
20
06
0.000
RERICPIactual
RERICPIFitted
RERICPIProjected
Professor Jeffrey Frankel
Why is PEP better than CPI-targeting
for countries with volatile terms of trade?
PEP
Better response to adverse terms of trade shocks:
• If the $ price of imported commodity goes up, CPI
target says to tighten monetary policy enough to
appreciate currency.
– Wrong response.
(E.g., oil-importers in 2007-08.)
• If the $ price of the export commodity goes up, PEP
says to tighten monetary policy enough to
appreciate currency.
– Right response.
(E.g., Gulf currencies in 2007-08.)
Professor Jeffrey Frankel
PEP
PEP, in its strict form, has some disadvantages
• Passes every fluctuation in world commodity prices
straight through to domestic-currency prices of other
TGs, creating high volatility
– Even for countries where non-commodity TGs are a small
share of the economy, some would like to nurture this sector,
• so as to encourage diversification in the long run.
• Exposing it to full volatility could shrink non-commodity TG sector.
– The volatility is undesirable, in particular, for those
short-term fluctuations that are likely to be reversed.
– Better to dampen real exchange rate fluctuations a bit,
until terms of trade shift appears permanent.
Professor Jeffrey Frankel
Moderate versions of PEP
PEP
• Target a broader Export Price Index (PEPI).
• 1st step for any central bank dipping its toe in these waters:
compute monthly export price index.
• 2nd step: announce that it is monitoring the index.
• Target a basket of major currencies ($, €, ¥) and minerals.
• A still more moderate, still less exotic-sounding, version of PEPI
proposal: target a monthly index of producer prices.
• Key point:
exclude import prices from the index,
& include export prices.
• Flaw of CPI target:
it does it the other way around.
Professor Jeffrey Frankel
Professor Jeffrey Frankel
Readings:
Fischer, Stanley, 2001, “Exchange Rate Regimes: Is the Bipolar View Correct?” Journal of
Economic Perspectives 15 (2).
Frankel, Jeffrey, 2003, “Experience of and Lessons from Exchange Rate Regimes in Emerging
Economies,” in Monetary and Financial Cooperation in East Asia, ADB ( Macmillan).
Frankel, 2009, “A Comparison of Monetary Anchor Options for Commodity-Exporters in Latin
America and the Caribbean,” Myths and Realities of Commodity Dependence: Policy Challenges
and Opportunities for Latin America and the Caribbean, World Bank, Sept.
Frankel, and Daniel Xie, 2010, “Estimation of De Facto Flexibility Parameter and Basket Weights
in Evolving Exchange Rate Regimes,” American Economic Review Papers & Proceedings 100, May.
Ghosh, Atish, Anne-Marie Gulde, and Holger C. Wolf, 2000, “Currency Boards: More Than a
Quick Fix?” Economic Policy 31.
Rogoff, Kenneth, and Maurice Obstfeld, 1995, “The Mirage of Fixed Exchange Rates,” J. of Econ.
Perspectives 9, No. 4 (Fall).
Rose, Andrew, 2000, “One Money, One Market: Estimating the Effect of Common Currencies on
Trade,” Economic Policy.
Taylor, Alan, 2002, “A Century of Purchasing Power Parity,” Rev. Ec. & Statistics, 84.
Professor Jeffrey Frankel
Additional Readings:
Arteta, Carlos, 2005, “Exchange Rate Regimes and Financial Dollarization: Does Flexibility Reduce
Currency Mismatches,” Topics in Macroeconomics 5, no. 1, Article 10.
Calvo, Guillermo, and Carmen Reinhart, 2002, “Fear of Floating,” Quarterly J. Economics, 117, no. 2.
Calvo, Guillermo, and Carlos Vegh, 1994, “Inflation Stabilization and Nominal Anchors,” Contemporary
Economic Policy, 12 (April).
Eichengreen, Barry, Paul Masson, Miguel Savastano, and Sunil Sharma, 1999, “Transition Strategies and
Nominal Anchors on the Road to Greater Exchange Rate Flexibility,” Essays in International Finance,
No. 213 (Princeton: Princeton University Press).
Frankel, Jeffrey, 2003, “A Proposed Monetary Regime for Small Commodity-Exporters: Peg the Export
Price (‘PEP’),” International Finance, Spring.
___, “A Proposal to Tie Iraq’s Currency to Oil,” Financial Times, June 13, 2003.
Frankel, and Andrew Rose, 1998, “The Endogeneity of the Optimum Currency Area Criterion,” The
Economic Journal.
___, and ___, 2002, “An Estimate of the Effect of Common Currencies on Trade and Income,”
Quarterly Journal of Economics.
Frankel, and Shang-Jin Wei, 2008, “Estimation of De Facto Exchange Rate Regimes: Synthesis of the
Techniques for Inferring Flexibility and Basket Weights,” IMF Staff Papers.
Professor Jeffrey Frankel
Additional Readings:
Friedman, Milton, 1953, “The Case for Flexible Exchange Rates,” in Essays in Positive Economics.
Husain, Asim, Ashoka Mody & Kenneth Rogoff, 2005, “Exchange Rate Regime Durability and
Performance in Developing Vs. Advanced Economies” JME 52 , Jan.35-64.
Ishii, Shogo, et al, Exchange Arrangements and Foreign Exchange Markets (IMF) 2003.
Levy-Yeyati, Eduardo, and Federico Sturzenegger, 2003, “To Float or to Trail: Evidence on the Impact of
Exchange Rate Regimes,” American Economic Review, 93, No. 4, Sept. .
McKinnon, Ronald, 1963, “Optimum Currency Areas,” American Economic Review, Sept., pp. 717-24
Mundell, Robert, 1961, “A Theory of Optimum Currency Areas,” AER, Nov., pp. 509-17.
Parsley, David, and Shang-Jin Wei, 2001, "Explaining the Border Effect: The Role of Exchange Rate
Variability, Shipping Costs, and Geography,” Journal of International Economics, 55, no. 1, 87-106.
Reinhart, Carmen, and Kenneth Rogoff. 2004. “The Modern History of Exchange Rate Arrangements: A
Reinterpretation.” Quarterly Journal of Economics 119(1):1-48, February.
Tavlas, George, Harris Dellas & Alan Stockman, “The Classification and Performance of Alternate
Exchange-Rate Systems,” 2006.
Williamson, John, “The Case for a Basket, Band and Crawl (BBC) Regime for East Asia,” in D.Gruen &
J.Simon, eds., Future Directions for Monetary Policies in East Asia, Reserve Bank of Australia, 2001.
Professor Jeffrey Frankel