Transcript Exchange Rate Regimes Appendices Jeffrey Frankel Harpel Chair, Harvard University IMF Institute * May 28, 2010 * Professor Jeffrey Frankel.

Exchange Rate Regimes
Appendices
Jeffrey Frankel
Harpel Chair, Harvard University
IMF Institute
* May 28, 2010 *
Professor Jeffrey Frankel
Appendices
I)
On the RMB
II)
Charts showing evolution
of choices of regimes, from IMF
III) Tables comparing economic
performance of different regimes
IV) Corners Hypothesis
V)
Do exchange rate regimes have real effects?
VI) More on the synthesis technique
for estimating de facto exchange rate regimes.
Professor Jeffrey Frankel
Appendix I
On the RMB:
More on China’s currency policy
Professor Jeffrey Frankel
Five reasons China should let RMB
appreciate, in its own interest
1. Overheating of economy
2. Excessive reserves.
3. Attaining internal and external balance.
4. Avoiding future crashes.
5. RMB undervalued, judged by
Balassa-Samuelson relationship.
Professor Jeffrey Frankel
1. Overheating of economy:
• Bottlenecks.
Pace of economic growth (10%) outrunning
– Raw material supplies
– Physical infrastructure.
• Shanghai stock market bubble (2006-07).
• Inflation 6-7%
=> price controls (Sept. 2007), …
=> shortages and social unrest.
• After the 2008-09 interruption,
China in 2010 is again in danger of overheating
– inflation
– real estate bubble.
Professor Jeffrey Frankel
China’s CPI accelerates in 2007-08
Inflation 2002 to 2008 Q1
Source: HKMA, Half-Yearly Monetary and Financial Stability Report, June 2008
Professor Jeffrey Frankel
2. Foreign Exchange Reserves
•
Excessive:
–
–
–
•
Though a useful shield against currency crises,
China has enough reserves: $2 ½ trillion by mid-2010;
& US treasury securities do not pay high returns.
Harder to sterilize
the inflow over time.
Professor Jeffrey Frankel
The Balance of Payments
≡ rate of change of foreign exchange reserves
rose rapidly over last decade
Source: HKMA, Half-Yearly Monetary and Financial Stability Report, June 2008
Professor Jeffrey Frankel
The Balance of Payments
rose rapidly in China over past decade,
due to all 3 components:
trade balance, Foreign Direct Investment, and portfolio inflows
Source: Prasad & Sorkin
Professor Jeffrey Frankel
Not only has the level of fx reserves risen,
but the rate of change (BoP surplus) shows acceleration
Source: Prasad & Sorkin
Professor Jeffrey Frankel
Attempts
sterilize reserve
inflow:
Successfultosterilization
in China:
2005-06
High reserve growth
=> steady money
offset by cuts in
domestic credit
While reserves (NFA) rose rapidly, the growth of the monetary base
was keptwere
to the remarkably
growth of the real
economy – even
reduced in 2005-06.
successful
in 2005-06.
Professor Jeffrey Frankel
In 2007 China began to have more trouble
sterilizing the reserve inflow (as predicted)
• PBoC began to have to pay
higher domestic interest rates
– and to receive lower interest rate on US T bills
– => quasi-fiscal deficit.
• Inflation became a serious problem in 2007-08.
– True, global increases in food & energy prices
were much of the explanation.
– But
• Appreciation is a good way to put immediate downward
pressure on local prices of agricultural & mineral commodities.
• Price controls are inefficient and ultimately ineffective.
Professor Jeffrey Frankel
In 2008, domestic Chinese interest rates
went above US T bill rates
=> quasi fiscal deficit
Source: Prasad & Sorkin
Professor Jeffrey Frankel
Sterilization faltered in 2007 & 2008
Growth of China’s monetary base, & its components
Source: HKMA, Half-Yearly Monetary and Financial Stability Report, June 2008
Professor Jeffrey Frankel
3. Need a flexible exchange rate to
attain internal & external balance
• Between 2002 and 2007, China crossed from the deflationary side
of internal balance (ES: excess supply, recession, unemployment),
to the inflationary side (ED: excess demand side, overheating).
– =>Moved upward in the “Swan Diagram”
– => appreciation called for.
– Together with expansion of domestic demand
• gradually replacing foreign demand, and
• developing neglected sectors:
–
health, education, environment, housing, finance, services
• In late 2008 it probably fell back to the deflation side, temporarily.
Professor Jeffrey Frankel
China is now in the overheating +
surplus quadrant of the Swan Diagram
ED & TB>0
Excgange rate E
BB:
External balance
CA=0
China
2007
or 2010
ES & TB>0
ED & TD
China
2002
ES & TD
YY:
Internal balance
Y = Potential
Spending A
Professor Jeffrey Frankel
The general principle: to attain
2 policy targets (internal & external balance),
• a country needs 2 policy instruments.
• In a large country like China, the expenditureswitching policy should be the exchange rate.
Professor Jeffrey Frankel
4. Avoiding future crashes
Experience of other emerging markets
suggests it is better to exit from a peg in
good times, when the BoP is strong, than
to wait until the currency is under attack.
Introduce some flexibility now,
even though not ready for free
floating.
Professor Jeffrey Frankel
5. Longer-run perspective:
Balassa-Samuelson relationship
• Prices of goods & services in China are low
– compared at the nominal exchange rate.
– Of course they are a fraction of those in the U.S.: < ¼ .
– This is to be expected,
explained by the Balassa-Samuelson effect
• which says that low-income countries have lower price levels.
• As countries’ real income grows, their currencies experience real
appreciation: approx. .3% for every 1 % in income per capita.
– But China is one of those countries that is cheap or undervalued
even taking into account Balassa-Samuelson.
Professor Jeffrey Frankel
1
.5
-1
-.5
0
The Balassa-Samuelson Relationship
2005
-3
-2
-1
0
1
Log of Real Per capita GDP (PPP)
2
coef = .23367193, (robust) se = .01978263, t = 11.81
Source: Arvind Subramanian, April 2010,
“New PPP-Based Estimates of Renminbi Undervaluation
and Policy Implications,” PB10-08, Peterson Institute for International Economics
Undervaluation of RMB in the regression estimated above = 26%.
Estimated undervaluation averaging across four such estimates = 31%.
Compare to Frankel (2005) estimate for 2000 = 36%.
Professor Jeffrey Frankel
The Balassa-Samuelson
relationship has predictive power
 Typically across countries, gaps are corrected halfway, on
average, over subsequent decade.
 => 3-4 % real appreciation on average per year for China,
including effect of further growth differential
.
 Correction could take the form of either inflation or
nominal appreciation, but appreciation is preferable.
Professor Jeffrey Frankel
The conclusion – that it would be in China’s
interest to allow RMB to appreciate -• has long been shared by top economic
officials in China, it is believed.
• But the decision is a political one:
• It is a matter of Hu and Wen !
Professor Jeffrey Frankel
$2
Professor Jeffrey Frankel
A new irony
The Chinese decision to re-establish the dollar
link in 2008, has not depreciated the RMB.
• If the alternative were the loose basket peg of
2008, with heavy weight on the €, the RMB
would have depreciated against the $
over the three years (because the € has) !
Professor Jeffrey Frankel
Appendix II
Charts showing evolution of
choices of regimes, from the IMF
Professor Jeffrey Frankel
IMF classification
Last de jure (end-1999). Of 185 Fund members,
“De facto” (end-2004)
• Have given up own currencies: 45
–
–
–
–
EMU:
CFA Franc Zone:
E.Caribbean CA
“dollarized”
11
14
6
8
• Currency boards:
• Intermediate regimes:
–
–
–
–
–
–
12 (+ Sloven.07;
14
6
9
Cyp.&Malta08, Slova.09)
(plus Montenegro in 06)
8
89
7
104
33 (incl. China)
8
6
5 (minus Slovenia in 06)
1
51
pegs to a single currency 30
pegs to a composite
13
crawling pegs
5
horizontal bands
7
crawling bands
7
managed floats
26
• “independent floaters”:
41
51
35
Professor Jeffrey Frankel
Professor Jeffrey Frankel
Professor Jeffrey Frankel
Appendix III
Tables comparing economic
performance of different
regimes:
– Ghosh, Gulde & Wolf
– Sturzenegger & Levy-Yeyati
– Reinhart & Rogoff
Professor Jeffrey Frankel
Professor Jeffrey Frankel
Professor Jeffrey Frankel
Professor Jeffrey Frankel
Source: Levy-Yeyati
and Sturzenegger
(2001).
Sample: yearly
observations 19741999.
Professor Jeffrey Frankel
Source: Levy-Yeyati
and Sturzenegger
(2001).
Sample: yearly
observations 19741999.
Professor Jeffrey Frankel
Appendix IV: The corners hypothesis
Aliases:
•
•
•
•
Hollowing out
Bipolarity (Stan Fischer)
The Missing Middle (The Economist)
Hypothesis of the vanishing intermediate exchange rate regime
Origins:
• 1992-93 ERM crises -- Eichengreen (1994)
• Late-90’s crises in emerging markets
•1994 Mexico
•1997 Thailand, Korea
•1998 Russia; Brazil
•2001 Turkey
Other supporters included: Summers Treasury, CFR, Meltzer Commission, IMF…
Professor Jeffrey Frankel
Are countries moving to the corners?
• Fischer (2001): Intermediate pegs, at 34%, are
down from 62% in 1991. Trend is toward a smaller
number of blocs, each on its own currency.
• But, in fact:
–
–
–
–
There are as many currencies now as in 1991.
Many de jure floaters never have been genuine.
The intermediate regimes are alive and well.
The dominant long-term trend is, rather, to flexibility.
Professor Jeffrey Frankel
The trend is in fact not
away from intermediate
regimes, but rather away
from fixed exchange rates.
Professor Jeffrey Frankel
The Corners Hypothesis has ebbed
• The hypothesis that countries could rigidly peg or freely
float, but should abandon intermediate regimes like
target zones, became fashionable in the late 1990s.
• The pendulum has swung back:
– Especially after failure of Argentina’s currency board & 2001
economic collapse
– Surely an intermediate regime (BBC)
is the right answer for China now.
•
Bottom line on corners hypothesis:
• Don’t cling to overvalued pegs.
• But don’t blame exchange rate regime for symptoms of other problems.
Professor Jeffrey Frankel
Appendix V:
Do exchange rate regimes matter “real”-ly?
• I.e., do nominal regimes affect real variation?
• Some theoretical models say they don’t,
that they only determine whether real shocks show up
in the form of nominal exchange rates or prices.
• History says they do.
-- e.g., Mussa (1986):
• The final nail in the coffin is Alan Taylor’s (2002)
century-of-PPP study.
Professor Jeffrey Frankel
VOLATILITY OF Q DEPENDS ON REGIME
Is it coincidence? No, it can’t be. Every time a move to
increased flexibility raises variability of nominal exchange
rates, it also raises variability of real exchange rates.
• Pre- and post-1973
•Inter-war period (Eichengreen 1988):
1922-26 float vs. 1927-31 fix
• Post-war regimes (Mussa 1986):
- Canadian float in the 1950s
- Ireland: 1957-70 $ peg; 1973-78 union with £; 1979-99 Eur. ERM
•A Century of PPP (Alan Taylor 2002):
1870-1914 Gold standard
1914-45 Interwar
1946-71 Bretton Woods
1971-96 Float
Taylor spliced together 100 years
of data for 20 currencies.
Professor Jeffrey Frankel
Exchange rate variability across a century of regimes
Each observation is a country-regime. Adapted from A.Taylor (2002).
Variability
of real
exchange
rate
Variability of nominal exchange rate
Professor Jeffrey Frankel
Appendix VI:
Synthesis Technique for Estimating
De Facto Exchange Rate Regimes
Frankel & Wei (IMF Staff Papers, 2008)
Professor Jeffrey Frankel
Synthesis of the techniques for inferring flexibility
parameter and for inferring basket weights
(Frankel & Wei, IMF Staff Papers, 2008)
Δ log Ht = c + ∑ w(j) Δ logX(j)t + ß {Δ empt } + ut
= c + w(1) Δ log $ t + w(2) Δ log € t + w(3) Δ log ¥ t
+ w(4) Δ log £t + … + ß {Δ empt } + u t
where H ≡ value of home currency, X(j) ≡ value of foreign currency,
defined in terms of suitable numeraire, like SDR
w(j) ≡ currency weights in basket, to be estimated;
Δ empt ≡ change in Exchange Market Pressure
≡ Δ log Ht + (ΔRest )/Monetary Baset
ß ≡ flexibility parameter, to be estimated:
ß=1 => the currency floats purely (no changes in reserves);
ß=0 => the exchange rate is purely fixed.
Professor Jeffrey Frankel
Findings
First we test out the synthesis technique
on some known $ peggers
• RMB
(Table 2.5):
– a perfect peg to the dollar during 2001-04
($ coefficient =.99, flexibility coefficient
insignificantly different from 0, & R2=.99).
– In 2005-07 the EMP coefficient suggested that only
90% of increased demand for the currency shows up
in reserves, rather than 100%;
but the $ weight & R2 were as high as ever.
• Hong Kong $ (Table 2.8):
– close to full weight on US$,
0 flexibility, & perfect fit.
Professor Jeffrey Frankel
A commodity-producing pegger
• Kuwaiti dinar shows a firm peg
throughout most of the period:
a near-zero flexibility parameter, & R2 > .9
(IV estimates in Table 3.5; IV= price of oil).
• A small weight was assigned to other currencies in the
1980s basket,
• but in the 2nd half of the sample, the anchor was
usually a simple $ peg.
Professor Jeffrey Frankel
A first official basket pegger
which is on a path to the €
• The Latvian lat
(Table 2.10)
– Flexibility is low during the 1990s, and has disappeared
altogether since 2000. R2 > .9 during 1996-2003.
– The combination of low flexibility coefficient and a high R2
during 2000-03 suggests a particularly tight basket peg
during these years.
– Initially the estimated weights include
$-weight .4
¥-weight .3; though both decline over time.
DM-weight .3 until 1999,
– then transferred to €: .2 in 2000-03 and .5 in 2004-07.
Professor Jeffrey Frankel
A 2nd official basket pegger
also on a path to the €
• The Maltese lira
(Table 2.12)
– a tight peg during 1984-1991 and 2004-07
(low flexibility coefficient & high R2).
– During 1980-2003, weight on the $ is .2 -.4.
– During 1980-1995, the European currencies
garner .3-.4, the £ .2-.3 & the ¥ .1.
– At the end of the sample period, the weight on the €
rises almost to .9.
Professor Jeffrey Frankel
3rd official basket pegger
• Norwegian kroner (Table 2.14)
– The estimates show heavy intervention.
– Weights are initially .3 on the $ and .4 on European
currencies (+ perhaps a little weight on ¥ & £ ).
– But the weight on the European currencies rises at the
expense of the $, until the latter part of the sample period
shows full weight on the € and none on the $.
Professor Jeffrey Frankel
th
4
official basket pegger
• Seychelles rupee (Table 2.17)
– confirms its official classification,
particularly in 1984-1995: not only
is the flexibility coefficient essentially 0, but R2 > .97.
– Estimated weights: .4 on the $,
.3 on the European currencies,
.2 on the ¥ and
.1 on the £.
– After 2004, the $ weight suddenly shoots up to .9 .
Professor Jeffrey Frankel
2 Pacific basket peggers
• Vanuatu (Table 2.19)
– low exchange rate flexibility and a fairly close fit.
– roughly comparable weights on the $ , ¥, €, and £ .
• Western Samoa (Table 2.20)
–
–
–
–
heavy intervention during the first 3 sub-periods,
around a basket that weights the $ most , and the ¥ 2nd.
More flexibility after 1992.
Weights in the reference basket during 2000-2003 are similar,
except the € now receives a large significant weight (.4).
Professor Jeffrey Frankel
A BBC country,
rare in that it announced explicitly the parameters:
basket weights, band width and rate of crawl.
• Chile in the 1980s & 1990s (Table 2.4)
– R2 > .9.
– The $ weight is always high, but others enter too.
– Significant downward crawl 1980-99.
• Estimates qualitatively capture Chile’s
– shift from $ anchor alone in the 1980s,
to a basket starting in 1992.
– move to full floating in 1999.
Professor Jeffrey Frankel
Chile,
continued
• But the estimates do not correspond perfectly to the
policy shifts of 1992 & 99
• Possible explanations for gap between official regime and
estimates include:
– De facto  de jure
– Parameter changes more frequent than the 4-year sub-periods.
• The Chilean authorities announced 18 changes in regime
parameters (weights, width, and rate of crawl) during the 18year period 1982 -1999.
• The difficulty is that we have only monthly data on reserves,
for most countries => it is not possible to estimate
meaningful parameter values if they change every year or so.
Professor Jeffrey Frankel
Floaters
• Australian $ (Table 2.1)
– The coefficient on EMP shows
less flexibility than one would have
expected, given that the currency is
thought to have floated throughout this period.
– Perhaps the problem is endogeneity of EMP.
• World commodity prices are a natural IV. (Table 3.1)
• For each sub-period, the estimated flexibility coefficient is indeed higher than
it was under OLS, but still far below 1.
Professor Jeffrey Frankel
Current applications
using higher-frequency data
• (I) RMB
– “New Estimation of China’s Exchange Rate Regime,”
forthcoming, Pacific Ec.Rev., 2009.
– Updated through early 2009, on my weblog
http://content.ksg.harvard.edu/blog/jeff_frankels_weblog/2009/03/11/the-rmb-has-now-moved-back-to-the-dollar/ .
• (II) Estimation to allow for frequent parameter shifts
– Results for 13 countries offering weekly reserve data,
• Therefore allowing estimation intervals shorter than 1 year.
– Econometric techniques to estimate parameter shifts
endogenously from Bai & Perron.
Professor Jeffrey Frankel
(I) Estimation of RMB with updated
technique and data (through early 2008)
• This approach reveals that the RMB basket had
loosened link to the $ by late 2006, and switched
substantial weight onto the € by mid 2007.
• An implication is that the appreciation of the RMB
against the $ observed during this period was due
to the appreciation of the € against the $, not to any
upward trend in the RMB relative to its basket.
Professor Jeffrey Frankel
Table 2: Rolling 12-month regressions of value of RMB
Δ (EMP) defined as [res(t)-res(t-1)]/mb(t-1) + [exr(t)-exr(t-1)]/exr(t-1)
12-month windows, ending on the month shown
COEFFICIENT
usd
jpy
eur
Δ emp
Constant
06M11
07M2
07M3
08M3
08M5
0.909***
0.756***
0.756***
0.613***
0.597***
(0.147)
(0.105)
(0.067)
(0.171)
(0.130)
-0.015
-0.095
-0.140
0.059
0.030
(0.098)
(0.085)
(0.089)
(0.081)
(0.083)
0.029
0.116
0.169**
0.357**
0.397***
(0.117)
(0.096)
(0.068)
(0.143)
(0.105)
0.137
0.179***
0.187***
0.290***
0.249**
(0.100)
(0.047)
(0.029)
(0.076)
(0.097)
-0.001
-0.003*
-0.004***
-0.006
-0.004
(0.001)
(0.003)
(0.003)
12
12
12
0.975
0.967
0.215
-0.030
(0.003)
Observations
12
R-squared
0.984
krw
0.077
(0.002)
12
0.967
0.966
Professor Jeffrey Frankel
-0.024
In 2008, however, RMB policy changed again.
• The appreciation of the previous year had put
unwelcome pressure on exporters.
• Chinese leaders changed policy
– Naughton (2008).
– Observing that putting half-weight on the € during a
downward $ trend had led to appreciation,
– in mid-2008, they decided to switch back to a $ peg.
– During the most recent period, mid-2008 to 2010,
all the weight has once again fallen on the $.
Professor Jeffrey Frankel
RMB was roughly flat against
basket of ½-$ + ½-€ in 2007;
$ in 2008 (like 2005) .
0.16
Appreciation vs. $ was due to weight
on € during period of $ weakening
0.15
0.14
RMB valued in terms of $
RMB valued in terms of ½$+½€
0.12
basket
0.11
0.1
0.09
RMB valued in terms of €
EUR/RMB
USD/RMB
½$+½€ basket
4/1/2009
2/1/2009
12/1/2008
10/1/2008
8/1/2008
6/1/2008
4/1/2008
2/1/2008
12/1/2007
10/1/2007
8/1/2007
6/1/2007
4/1/2007
2/1/2007
12/1/2006
10/1/2006
8/1/2006
6/1/2006
4/1/2006
2/1/2006
12/1/2005
10/1/2005
8/1/2005
0.08
6/1/2005
/RMB
0.13
Professor Jeffrey Frankel
Ironically…
• The $ has appreciated vs. € since mid-2008.
– So the $-pegged RMB is stronger
than if the basket had been retained.
– The dangers of switching horses in mid-stream:
• the Chinese authorities jumped back
onto the $ horse at almost exactly
the same time that the $ horse and
€ horse reversed directions !
Professor Jeffrey Frankel
(II) Results for 13 countries that offer
weekly data on reserves (1991-2008):
• Argentina, Brazil, Canada, Chile, Colombia,
India, Indonesia, Mexico, Peru, Russia, Thailand,
Turkey & Venezuela.
• E.g.,
– Colombia: during 2008, $ weight fell & flexibility
increased.
– Turkey during 2008 moved from high € weight with
low flexibility to low € weight with high flexibility.
Professor Jeffrey Frankel
Colombia: Evolution of Basket Weights,
Monthly Regressions with Daily data, 2008
(2)
(4)
(5)
(8)
(9)
(10)
VARIABLES
2/2008
4/2008
5/2008
8/2008
9/2008
10/2008
JPY
-0.028
0.023
0.227
0.028
-0.139
0.319**
(0.093)
(0.063)
(0.198)
(0.134)
(0.164)
(0.121)
0.480**
0.334***
0.019
-0.073
0.218
-0.294
(0.165)
(0.060)
(0.340)
(0.173)
(0.233)
(0.230)
0.602**
0.522***
0.226
0.774***
0.738**
0.886**
(0.274)
(0.091)
(0.277)
(0.180)
(0.343)
(0.347)
USD
EUR
Δ(emp)
Observations
GBP
0.160
0.447*** 0.688*** 0.931***
0.858*** 0.650***
(0.110)
(0.049)
(0.091)
(0.062)
(0.076)
(0.203)
21
22
14
15
20
21
-0.054
0.121
0.528
0.270
0.183
0.089
Jeffrey Frankel
Robust standard errors in parentheses *** p<0.01, ** p<0.05,Professor
* p<0.1
Turkey: Evolution of Basket Weights,
Quarterly Regressions with Weekly data
(1)
VARIABLES
JPY
USD
EUR
Δ(emp)
Observations
GBP
(3)
(5)
(7)
7/2007
1/2008
7/2008
-0.660
-0.250
-0.758**
0.899
(0.329)
(0.166)
(0.255)
(0.803)
0.397
-0.036
0.912
-0.961
(0.930)
(0.302)
(0.500)
(0.920)
0.906
1.931***
0.566
-0.088
(0.863)
(0.260)
(0.371)
(0.738)
0.149
0.231***
0.798***
0.825**
(0.083)
(0.056)
(0.204)
(0.279)
10
14
13
10
0.357
-0.644
0.281
1/2007
Professor Jeffrey Frankel
1.151
For countries that do not have weekly data
on reserves, we can interpolate between
months to take advantage of highfrequency exchange rate data
• giving enough observations per year to allow
the use of more sophisticated econometric techniques
that estimate endogenously the dates at which parameters
shift.
• Application to China
– (next slide; thanks to Dan Xie)
– reinforces conclusion:
RMB shifted back to $ peg 9/15/08 (through March 09)
Professor Jeffrey Frankel
Identifying
Break Points
in China’s
Exchange
Rate Regime
With weekly
exchange rate
data and
monthly reserve
data
(interpolations are
made to get
weekly reserve
data)
Frankel & Xie (2009)
(1)
(2)
(3)
(4)
(5)
(6)
VARIABLES
1/6/20057/15/2005
7/29/20054/27/2007
5/4/200711/16/2007
11/23/20079/8/2008
9/15/200812/8/2008
12/15/20083/11/2009
US dollar
1.000***
0.893***
0.596***
0.685***
0.965***
0.929***
(0.000)
(0.030)
(0.066)
(0.091)
(0.058)
0.000
0.046*
0.241***
0.128
0.037
(0.000)
(0.025)
(0.050)
(0.082)
(0.049)
-0.000
0.014
0.059**
-0.065**
0.010
(0.000)
(0.013)
(0.022)
(0.025)
(0.021)
0.000
0.034
0.185***
0.165
0.042
(0.000)
(0.024)
(0.052)
(0.125)
(0.063)
-0.000
0.000
0.000
-0.000
0.000
(0.000)
(0.000)
(0.000)
(0.001)
(0.000)
Observations
28
92
29
42
13
13
Korean won
-0.000
0.047
0.254
0.015
-0.027
0.023
R-squared
1.000
0.979
0.929
0.990
0.999
0.999
euro
Jpn yen
Δemp
Constant
(0.101)
0.087
(0.077)
0.063
(0.038)
0.129**
(0.060)
0.000
(0.001)
Professor Jeffrey Frankel
Note: *** p<0.01, ** p<0.05, * p<0.1 Robust standard errors in parentheses
Appendix VI.1: Monte Carlo study
on fabricated currency regimes
• Two kinds of flexibility
– Leaning ½ -way against the wind of EMP fluctuations
(Table 8.1)
– Or else constrained to remain in a 5% band
(Table 8.2)
• Two anchors
– $ peg
– Basket: 1/3 $, 1/3 €, 1/3 ¥
• Synthesis technique generally gives the right answer.
Professor Jeffrey Frankel
Monte Carlo exchange rate under
simulated basket+band regime
-.45
-.4
-.35
-.3
-.25
-.2
(with parameters from Papual New Guinea)
240
260
280
300
320
340
T
mcsa
upperb
mcsa_non
lowerb
Professor Jeffrey Frankel
Appendix VI.2 -- One concern: endogeneity
of the exchange market pressure variable
• One would prefer to observe changes in the
international demand for the home currency known to
originate in exogenous shocks.
• In the case of countries that specialize in the
production of mineral or agricultural commodities,
there is a ready-made IV: changes in the price of the
commodity on world markets.
• Accordingly, Tables 3 repeat the synthesis estimation
technique, but for the commodity producers it uses
changes in the world price of the commodity in
question as an IV for changes in EMP.
Professor Jeffrey Frankel
To address endogeneity of EMP, we
use commodity prices as IV
• Malaysian ringgit
(Table 2.11 )
OLS.
– Only in 1996-99 is there evidence of
exchange rate flexibility (Asia crisis ).
– During 2000-03 there is a perfect peg to the $
(coefficient $ R2 both =1).
– In 2004-07 the peg is still fairly strong, but here the weight of
the US$ falls to .6, partially replaced by the Singapore
$ (weight = .4) .
• IV = prices of tin & semiconductors (Table 3.6)
– Again, a perfect $ peg during 2000-03,
– followed by shift to a basket consisting of an average of the US
$ + the Singapore $.
Professor Jeffrey Frankel
Recurrent finding: IV estimate on EMP is
higher than OLS estimate
(but lower in significance)
• Floaters: IV estimates for Canadian $, as with A$,
show flexibility parameters in each sub-period
higher than they were under OLS, but surprisingly
insignificant statistically.
• IV also raises flexibility coefficient for Intermediate
regimes:
– Thailand (Table 3.11) IV = price of rice
– W.Samoa (Table 3.12) IV = price of coconuts.
Professor Jeffrey Frankel
Exchange Rate Regimes
Professor Jeffrey Frankel