Exchange Rate Regimes Some New Themes Jeffrey Frankel Harpel Chair Harvard University IMF Institute * May 22, 2009 * Professor Jeffrey Frankel – Kennedy School of Government.

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Transcript Exchange Rate Regimes Some New Themes Jeffrey Frankel Harpel Chair Harvard University IMF Institute * May 22, 2009 * Professor Jeffrey Frankel – Kennedy School of Government.

Exchange Rate Regimes

Some New Themes Jeffrey Frankel

Harpel Chair Harvard University IMF Institute

* May 22, 2009 *

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Topics to be covered

1. Classifying countries by exchange rate regime 1.

The categories De facto vs. de jure My preferred technique to infer de facto regimes: the case of the RMB 2. Advantages of fixed rates : the case of EMU 3. Advantages of floating rates 4. Which regime dominates?

Tests of economic performance 2.

Conceptual frameworks for evaluation: • OCA: 4 traditional criteria; endogeneity • 1990s emerging markets criteria 5. Additional factors for developing countries 1. Emigrants’ remittances 2. Financial development 3. Terms-of-trade shocks return; PEP 6. Appendices: Corners … Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Topics to be covered 1. Country classification

, de jure vs. de facto

2. Advantages of fixed rates 3. Advantages of floating rates 4. Which regime dominates?

1. Tests of economic performance 2. Conceptual frameworks for evaluation: •

Traditional OCA criteria

•

1990s emerging markets criteria

5. Intermediate regimes and

the corners hypothesis 6. Financial development 7. Terms-of-trade shocks return.

•

Proposal

eg the

xport

rice (PEP) 8. The case of

the RMB

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

1. Classification of exchange rate regimes :

Continuum from flexible to rigid 1) Free float

FLEXIBLE CORNER

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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

IMF classification

Last de jure (end-1999).

Of 185 Fund members,

“De facto” (end-2004)

• Have given up own currencies:

– EMU: 11 – CFA Franc Zone: 14 – E.Caribbean CA 6 – “dollarized”

• Currency boards:

• Intermediate regimes:

– 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”:

51 41

12 (+ Sloven.07; Cyp.&Malta08, Slova.09) 14 6

(plus Montenegro in 06)

104 7

33 (incl. China) 8 6 5 (minus Slovenia in 06) 1 51

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

De jure regime



de facto

1. Most “fixers” don’t:

“

Mirage of Fixed Rates”:

Countries declaring a peg, often abandon it.

Few major pegs > 5 yrs.

-- Obstfeld & Rogoff (1995).

Average duration of pegs in Western. Hem.: 10 months - Klein & Marion (1997).

2. Most “floaters” don’t: “Fear of Floating”

- Calvo & Reinhart (2002).

Variability of

(vs.

Reserves

) not greater among floaters than fixers!

3. Most “basket peggers” don’t

: weights are kept secret & are manipulated. - Frankel, Schmukler & Serven (2000) 4. The IMF’s

IFS

abandoned its de jure classification tables after 1999.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Schemes for de facto classification

• have been surveyed by Tavlas, Dellas & Stockman ( 2006) • and divided into two classifications, viewed as: – “mixed de jure-de facto classifications, because the self-declared regimes are adjusted by the devisers for anomalies.” – Vs. “pure de facto classifications because…assignment of regimes is based solely on statistical algorithms and/or econometric estimation.” Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Adjusted de jure classification schemes

1. Ghosh, Gulde, Ostry & Wolf (1995) identify “peggers” who in fact devalue often.

2. B

ubula &

tker-

obe (2002): New tables of IMF MEA Dept. adjust by consulting IMF economists, and movements in reserves & exchange rates.

3. R

einhart &

ogoff (2003, 04): add category of “free falling”, use parallel rates in place of official, and look at longer-term frequencies of classification.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

The de facto schemes do not agree

• That de facto schemes to classify exchange rate regimes differ from the IMF’s previous de jure classification is by now well-known.

• It is less well-known that the de facto schemes also do not agree with each other !

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Correlations Among Regime Classification Schemes

IMF

IMF

1.00 (100.0)

GGW LY-S R-R

GGW 0.60 (55.1) 1.00 (100.0) LY-S 0.28 (41.0) 0.13 (35.3) 1.00 (100.0) R-R 0.33 (55.1

) 0.34 (35.2) 0.41 (45.3) 1.00 (100.0) (Frequency of outright coincidence, in %, given in parenthesis.) Sample: 47 countries.

From Frankel, “ Experience of and Lessons from Exchange Rate Regimes in Emerging Economies, ” ADB, 2004. Table 3, prepared by Marina Halac & Sergio Schmukler.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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 R-R De Jure

100% 86% 100%

Jay S. LY-S R-R

74% 81% 80% 82% 100% 73% 100% Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

The IMF now has its own “de facto classification” -- still close to official IMF one.

Bénassy-Quéré

et al

(2004) : correlation (BOR, IMF) = .76

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

De facto classification schemes

Shambaugh (2004): variability of exchange rate.

& evy Δ

eyati &

turzenegger ex.rates, and of Δ (2005): cluster analysis based on variability of exchange rates reserves • • Implicit basket weights method: regress Δ value of local currency against Δ values of major currencies. Frankel & Wei (1993, 94, 2007), Bénassy-Quéré (1999), B-Q

et al

(2004).

• • Close fit => a peg. Coefficient of 1 on $ => $ peg. Or other currencies => basket peg.

• • • Example of China, post 7/05: Still de facto pegged to $ into 2006.

Equal weight on the € in 2007 Back to the $ in 2008.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Synthesis of the techniques for inferring flexibility parameter and for inferring basket weights

(Frankel & Wei,

IMF Staff Papers

, 2008)

Δ log H

= c + ∑ w(j) Δ logX(j)

+ ß {Δ emp

t } + u t

= c + w(1) Δ log $

+ w(4) Δ log £

+ w(2) Δ log €

+ w(3) Δ log ¥

+ … + ß {Δ emp

t } + 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 emp

≡ change in Exchange Market Pressure ≡

Δ log H

+ (ΔRes

t )/Monetary Base t 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 – Kennedy School of Government – Harvard University

Findings

First we test out the synthesis technique

• RMB

on some known $ peggers (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 – Kennedy School of Government – Harvard University

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 2 nd half of the sample, the anchor was usually a simple $ peg. Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

3 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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

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 ¥ 2 nd .

– 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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

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 18 year 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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

Current applications using higher-frequency data

• (I) RMB – “New Estimation of China’s Exchange Rate Regime,” forthcoming,

Pacific E c .R

ev .,

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 not yet written up) – Results for 13 countries offering weekly reserve data, • Therefore allowing estimation intervals shorter than 1 year. – Econometric techniques to estimate parameter shifts endogenously.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

(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 dollar 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 – Kennedy School of Government – Harvard University

Table 1: Evolution of RMB Basket Weights from 10-22-2006 , 3-month windows of daily data, ending on the month shown

COEFFICIENT 12/2006 3/2007 2/2008 9/2008 11/2008 usd 1.005*** (0.038) 0.814*** (0.035) 0.878*** (0.041) 0.992*** (0.027) 0.971*** (0.039) eur 0.006

(0.038) 0.068** (0.027) 0.019

(0.026) 0.049** (0.020) 0.070** (0.028) jpy -0.023

(0.035) 0.020* (0.011) 0.044*** (0.017) -0.030

(0.019) -0.022

(0.027) Constant 0.000** (0.000) 0.000

(0.000) 0.001*** (0.000) 0.000

(0.000) 0.000

(0.000) Observations R-squared krw 61 0.95

0.011

64 0.94

0.098

61 0.96

0.059

60 1.00

-0.011

18 1.00

-0.019

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

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 06M11 0.909*** (0.147) 07M2 0.756*** (0.105) 07M3 0.756*** (0.067) 08M3 0.613*** (0.171) 08M5 0.597*** (0.130) jpy -0.015

(0.098) -0.095

(0.085) -0.140

(0.089) 0.059

(0.081) 0.030

(0.083) eur Δ emp Constant Observations

R-squared krw

0.029

(0.117) 0.116

(0.096) 0.169** (0.068) 0.357** (0.143) 0.397*** (0.105) 0.137

(0.100) 0.179*** (0.047) 0.187*** (0.029) 0.290*** (0.076) 0.249** (0.097) -0.001

(0.003) 12

0.984

0.077

-0.003* (0.002) -0.004*** (0.001) -0.006

(0.003) -0.004

(0.003) 12 12 12 12

0.967

0.975

0.967

0.966

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University 0.215

-0.030

-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 virtually to a $ peg.

– During the most recent period, September 2008-February 2009, estimates show that all the weight has once again fallen on the $. Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

The weights in the RMB basket

shifted toward € in 2007, back to $ in 2008.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

0.16

0.15

0.14

0.13

0.12

0.11

0.1

0.09

0.08

RMB was roughly flat against basket of ½-$ + ½-€ in 2007; $ in 2008 (like 2005) .

Appreciation vs. $ was due to weight on € during period of $ weakening RMB valued in terms of $ RMB valued in terms of ½$+½€ basket RMB valued in terms of € EUR/RMB USD/RMB ½$+½€ basket

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 – Kennedy School of Government – Harvard University

(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 & 2008 moved from high euro weight with low flexibility to low euro weight with high flexibility.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Colombia: Evolution of Basket Weights, Monthly Regressions with Daily data, 2008

(2) (4) (5) (8) (9) VARIABLES JPY 2/2008 -0.028

(0.093) 4/2008 0.023

(0.063) 5/2008 0.227

(0.198) 8/2008 0.028

(0.134) (10) 9/2008 -0.139

(0.164) 10/2008 0.319** (0.121) USD EUR 0.480** (0.165) 0.334*** (0.060) 0.019

(0.340) -0.073

(0.173) 0.218

(0.233) -0.294

(0.230) 0.602** (0.274) 0.522*** (0.091) 0.226

(0.277) 0.774*** (0.180) 0.738** (0.343) 0.886** (0.347) Δ(emp) Observations GBP 0.160

(0.110) 0.447

*** (0.049) 0.688

*** (0.091) 0.931

*** (0.062) 0.858

*** (0.076) 0.650

*** (0.203) 21 -0.054

22 0.121

14 0.528

15 0.270

20 0.183

21 0.089

VARIABLES

Turkey: Evolution of Basket Weights, Quarterly Regressions with Weekly data

(1) (3) (5) (7) 1/2007 7/2007 1/2008 7/2008 JPY USD EUR Δ(emp) Observations GBP -0.660

(0.329) 0.397

(0.930) 0.906

(0.863) 0.149

(0.083) 10 0.357

-0.250

(0.166) -0.036

(0.302) 1.931

*** (0.260) 0.231

*** (0.056) 14 -0.758** (0.255) 0.912

(0.500) 0.566

(0.371) 0.798*** (0.204) 13 0.899

(0.803) -0.961

(0.920) -0.088

(0.738) 0.825** (0.279) 10

For countries that do not have weekly data on reserves, we can interpolate between months to take advantage of high frequency 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 – Kennedy School of Government – Harvard University

(1) (2) (3) (4) (5) (6)

Identifying Break Points in China ’ s Exchange Rate Regime

VARIABLES

US dollar euro

1/6/2005 7/15/2005

1.000***

(0.000) 7/29/2005 4/27/2007

0.893***

(0.030) 5/4/2007 11/16/2007

0.596***

(0.101) 11/23/2007 9/8/2008

0.685***

(0.066) 9/15/2008 12/8/2008

0.965***

(0.091)

0.000

(0.000)

0.046*

(0.025)

0.087

(0.077)

0.241***

(0.050)

0.128

(0.082) With weekly exchange rate data and monthly reserve data (interpolations are made to get weekly reserve data) Frankel & Xie (2009)

Jpn yen Δemp

Constant Observations

Korean won

R-squared

-0.000

(0.000)

0.000

(0.000) -0.000

(0.000)

0.014

(0.013)

0.034

(0.024) 0.000

(0.000)

0.063

(0.038)

0.129**

(0.060) 0.000

(0.001)

0.059**

(0.022)

0.185***

(0.052) 0.000

(0.000)

-0.065**

(0.025)

0.165

(0.125) -0.000

(0.001) 28 -0.000

1.000

92 0.047

0.979

29 0.254

0.929

42 0.015

0.990

13 -0.027

0.999

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University Note: *** p<0.01, ** p<0.05, * p<0.1 Robust standard errors in parentheses 12/15/2008 3/11/2009

0.929***

(0.058)

0.037

(0.049)

0.010

(0.021)

0.042

(0.063) 0.000

(0.000) 13 0.023

0.999

Bottom line(s)

• The new synthesis technique is necessary to discern exchange rate regimes where both the anchor weights and the flexibility parameter are unknown.

• Weekly data are necessary to capture the frequency with which many countries’ exchange rate regimes evolve.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

Most important finding of last 10 years

• Empirical finding of Rose magnitude.

(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 – Estimated magnitudes are often smaller, but the basic finding has withstood perturbations and replications remarkably well. ii/ – Some developing countries seeking enhanced regional integration may now try to follow 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 – Kennedy School of Government – Harvard University

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-Krumgan hypothesis) Frankel & Rose,

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

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 or measures of performance? No.

– The de facto schemes do not correspond to each other.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Which category experienced the most rapid growth? Ghosh, Gulde & Wolf: currency boards Levy Yeyati & Sturzenegg er: floating Reinhart & Rogoff: limited flexibility Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Survey of classification schemes

by Tavlas, et al (2006)

finds

• “wide disparity of results” re performance.

• Some consensus that,

for developing countries only,

pegs associated with higher growth – GGW, L-Y&S, Rogoff

et al

, DeG&S, & DLM.

• Strong monetary framework, whether exchange rate target

or other

, is good for growth – Baillu, Lafrance & Perrault (2003).

• “Country-specific factors matter.” Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

Optimum Currency Area Theory (OCA)

Broad definition: An optimum currency area is a region that should have its own currency and own monetary policy.

This definition can be given more content, by first observing that smaller units tend to be more open and integrated.

Then an OCA can be defined as:

a region that is neither so small 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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

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

P

eg the

E

xport

P

rice

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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

Cyclically-stabilizing emigrants’ remittances.

• If country

has sent many immigrants to country

, and their remittances are correlated with the differential in growth or employment in

versus

, this strengthens the case for

pegging to

• Why? It helps stabilize

’s current account even when

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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

“Are Bilateral Remittances Countercyclical?

Implications for…Currency Unions ” -- Frankel (May 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 – Kennedy School of Government – Harvard University

Table 3: Cross-Section 2003-04 - Composite data set Ln (Stock migrants 2000 ) Cyclical Difference

(merging three sources)

(Ln (Real GDP/ Trend GDP))

Sender relative to recipient

GDP per capita Sender (1) 0.762*** Dependent Variable: Ln Remittances 2003-04 between Countries (2) 0.741*** (3) 1.061*** (4) 1.233***

(0.040)

16.199***

(2.905) (0.041)

16.099***

(2.765) (0.088)

14.723***

(3.390) (0.152)

13.983***

(3.927)

0.039***

(0.015)

1.345*** 0.028*

(0.016)

0.087

0.022

(0.019)

-0.590

Currency Union Estimation Method

OLS (0.222) OLS (0.389) 2SLS (0.632) 2SLS

Instrumental variables Observations

R2 331 0.526

328 0.546

border/language/ islands/colonial 328 0.463

border/language 328 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: Jim é nez-Mart í n, S., Jorgensen, N. and Labeaga, J. M. (2007); IMF data: Lueth, E. and Ruiz-Arranz, M. (2006).

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

(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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

(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 – Kennedy School of Government – Harvard University

Terms-of-trade variability returns

• Prices of crude oil and other agricultural & mineral commodities have 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).

• 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 – Kennedy School of Government – Harvard University

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 • At the IMF • Among central bankers Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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, Monetary and Exchange Affairs Dept. Online at: http://www.imf.org/external/pubs/ft/survey/2000/102300.pdf

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University The background papers for the high-level seminar “Implementing Inflation Targets,” held in Washington in March 2000, are available on the IMF Website: http://www.imf.org/external/pubs/ft/seminar/2000/targets/index.htm

Inflation targeting is the reigning orthodoxy

• Economists, central bankers, IMF… • “Have a LR target for inflation, and be transparent.” ?

Who could disagree?

• But many countries who say they are doing it aren’t. Fear of floating again. Why?

• Big disadvantage of floating + IT (with CPI) combination: – Gives wrong answer in case of supply shocks: • E.g., in response to a rise in oil import prices, it says to tighten monetary policy and appreciate.

• In response to a rise in world prices of export commodities, it does not allow monetary tightening and appreciation.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Proposal to

eg the

xport

rice (PEP) Intended for countries with volatile terms of trade, particularly those specialized in the production of mineral or agricultural commodity exports.

Proposal: 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 – Kennedy School of Government – Harvard University

6 proposed nominal targets and the Achilles heel of each:

Monetarist rule Inflation targeting Targeted variable

M1 CPI

Vulnerability Example

Velocity shocks US 1982 Import price shocks Oil shocks of 1973-80, 2000-08

Nominal income targeting Gold standard Commodity standard Fixed exchange rate

Nominal GDP Measurement problems Less developed countries Price of gold Price of agr. & mineral basket $ (or euro) Vagaries of world gold market Shocks in imported commodity Appreciation of $ (or other) 1849 boom; 1873-96 bust Oil shocks of 1973-80, 2000-08 1995-2001 Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

How would it work operationally, say, for a Gulf oil-exporter?

• • Each day, after noon spot price of oil in London

($/barrel), the central bank announces the day’s exchange rate, according to the formula:

(dirham/$) = fixed target price

(dirham/barrel) / S($/barrel). It intervenes in $ to hold this exchange rate for the day • The result is that

(dirham/barrel) is indeed fixed from day to day.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Does floating give the same answer?

• True, commodity currencies tend to appreciate when commodity markets are strong, & vice versa – Australian, Canadian & NZ $ – South African rand ( e.g., Chen & Rogoff ) ( e.g., Frankel, 2007 ) – Chilean peso and others • But – Some volatility under floating appears gratuitous.

– Floaters still need a nominal anchor.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

200.000

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).

180.000

160.000

140.000

120.000

100.000

80.000

60.000

40.000

20.000

Actual vs Fitted vs. Fundamentals Projected Values

0.000

Q 2 1 98 4 Q 1 1 98 5 Q 4 1 98 5 Q 3 1 98 6 Q 2 1 98 7 Q 1 1 98 8 Q 4 1 98 8 Q 3 1 98 9 Q 2 1 99 0 Q 1 1 99 1 Q 4 1 99 1 Q 3 1 99 2 Q 2 1 99 3 Q 1 1 99 4 Q 4 1 99 4 Q 3 1 99 5 Q 2 1 99 6 Q 1 1 99 7 Q 4 1 99 7 Q 3 1 99 8 Q 2 1 99 9 Q 1 2 00 0 Q 4 2 00 0 Q 3 2 00 1 Q 2 2 00 2 Q 1 2 00 3 Q 4 2 00 3 Q 3 2 00 4 Q 2 2 00 5 Q 1 2 00 6 RERICPIactual RERICPIFitted RERICPIProjected Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Why is PEP better than CPI-targeting

for countries with volatile terms of trade

?

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. (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. (E.g., Gulf currencies in 2007-08.) Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

Moderate versions of PEP

• Target a broader

xport

rice

ndex (

PEPI

• 1 st step for any central bank dipping its toe in these waters:

compute monthly export price index

. • 2 nd 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 production price index

(e.g., PPI).

•

Key point:

• Flaw of CPI target: exclude import prices from the index, & include export prices. it does it the other way around .

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Readings: Fischer, Stanley. 2001, “Exchange Rate Regimes: Is the Bipolar View Correct?”

Journal of Economic Perspectives

15(2): 3-24.

Frankel, Jeffrey, “Experience of and Lessons from Exchange Rate Regimes in Emerging Economies,” in

Monetary and Financial Cooperation in East Asia

, Asian Development Bank, Macmillan, 2003

___, “A Proposal to Tie Iraq’s Currency to Oil,”

Financial Times

, June 13, 2003.

Frankel, Jeffrey, and Shang-Jin Wei, “ Estimation of De Facto Exchange Rate Regimes: Synthesis of The Techniques for Inferring Flexibility and Basket Weights ,”

IMF Staff Papers

, Sept. 2008.

Ghosh, Atish, Anne-Marie Gulde, and Holger C. Wolf, 2000, “Currency Boards: More Than a Quick Fix?”

Economic Policy

31, Oct., pp. 270-335.

Rogoff, Kenneth, and Maurice Obstfeld, 1995, “The Mirage of Fixed Exchange Rates,”

J. of Econ. Perspectives

, Vol. 9, No. 4 (Fall), pp. 73-96.

Rose, Andrew, “One Money, One Market: Estimating the Effect of Common Currencies on Trade,”

Economic Policy

, 2000.

Taylor, Alan, “A Century of Purchasing Power Parity,”

Rev. Ec. & Statistics

, Feb. 2002, 84, 139-150.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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 Journal of Economics

, 117, no. 2, May, 379-408.

Calvo, Guillermo, and Carlos Vegh, 1994, “Inflation Stabilization and Nominal Anchors,”

Contemporary Economic Policy

, 12 (April), 35-45.

Clark, Peter, Natalia Tamirisa, and Shang-Jin Wei, with Azim Sadikov and Li Zeng, “Exchange Rate Volatility and Trade Flows—Some New Evidence,” IMF, May 2004.

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, “A Proposed Monetary Regime for Small Commodity-Exporters: Peg the Export Price (‘PEP’),” International Finance Spring 2003, 6, no. 1 (Blackwill Publishers).

Frankel, Jeffrey, and Andrew Rose, 1998, “The Endogeneity of the Optimum Currency Area Criterion,”

The Economic Journal

, Vol. 108, No. 449 (July), pp. 1009-25.

Frankel, Jeffrey, and Andrew Rose, 2002, “An Estimate of the Effect of Common Currencies on Trade and Income,”

Quarterly Journal of Economics.

Friedman, Milton, 1953, “The Case for Flexible Exchange Rates,” in

Essays in Positive Economics

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Additional Readings: Husain, Asim, Ashoka Mody & Kenneth Rogoff, “Exchange Rate Regime Durability and Performance in Developing Vs. Advanced Economies”

JME

52 , Jan. 2005 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. .

Masson, Paul, 2001, “Exchange Rate Regime Transitions

,” J. Development Econ.

, vol. 64, 571-586.

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,” March 2006.

Williamson, John, “The Case for a Basket, Band and Crawl (BBC) Regime for East Asia,” in D. Gruen and J. Simon, eds., Future Directions for Monetary Policies in East Asia, Reserve Bank of Australia, 2001, 97-109.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

I) On the RMB

Appendices

II) III) Charts showing evolution of choices of regimes, from IMF 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 – Kennedy School of Government – Harvard University

Appendix I On the RMB:

More on China’s currency policy

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Five reasons China should let RMB appreciate, in its own interest

- Overheating of economy, 2005-08 No longer relevant, in 2009.

– – Reserves excessive. It gets harder to sterilize the inflow over time.

China’s reserves seemed >> needed to forestall crises. Not so clear now. 3.

– – Attaining internal and external balance.

To attain both, need 2 policy instruments. In a large country like China, the expenditure-switching policy should be the exchange rate.

Avoiding future crashes.

RMB undervalued, judged by Balassa-Samuelson relationship.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

1. Overheating of economy:

• Bottlenecks.

Pace of economic growth (11%) was outrunning – Raw material supplies – Physical infrastructure – Environmental capacity – Level of sophistication of financial system.

• Shanghai stock market bubble (2006-07).

• Inflation 6-7% => price controls (Sept. 2007), … => shortages and social unrest.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Attempts at sterilization where emerging markets have faced large inflows

• Sterilization is defined as offsetting of international reserve inflows so as to prevent them from showing up domestically as excessive money growth & inflation.

• In this decade, has PBoC has successfully sterilized for some years … until 2007-08 .

– The usual limitations are finally showing up: • Prolongation of capital inflows • Quasi- fiscal deficit • Failure to sterilize • Rising inflation Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

2. Foreign Exchange Reserves

• Excessive: – Though a useful shield against currency crises, – China has enough reserves: $1.95 trillion by end 2008 ; – & US treasury securities do not pay high returns.

• Harder to sterilize the inflow over time.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Components of China’s rising balance of payments and the evolution of foreign exchange reserves

Source: HKMA, Half-Yearly Monetary and Financial Stability Report, June 2008 Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Sterilization in China While reserves (NFA) rose rapidly, the growth of the monetary base was kept to the growth of the real economy – even reduced in 2005-06 .

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

But to sterilize, the PBoC had to raise the reserve ratios required of banks

and to raise lending rates while continuing to underpay depositors

Source: HKMA,

Half-Yearly Monetary & Financial Stability Report

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

In 2007-08 China had 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 • China’s overly rapid growth itself contributes.

• 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 – Kennedy School of Government – Harvard University

China’s attempts to sterilize its large inflows, to prevent real appreciation – 2002-2007

• In early 1990s, Colombia, Korea, Indonesia and others tried for a year or two and then gave it up.

• In this decade, China successfully sterilized for some years … until 2007-08 .

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Sterilization falters 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 – Kennedy School of Government – Harvard University

China’s CPI accelerates in 2007-08

Inflation 2002 to 2008 Q1

3. Need a flexible exchange rate to attain internal and 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 under current conditions.

– Together with expansion of domestic demand • gradually replacing foreign demand, • developing neglected sectors: health, education, environment, housing, finance, services • Of course in late 2008 it probably fell back to the deflation side.

• But the general principle remains: to attain 2 policy targets (internal & external balance), a country needs to use 2 policy instruments (real exchange rate & spending).

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

China is now in the overheating

+

surplus quadrant of the Swan Diagram

ED & TB>0 China 2007 BB: External balance

=0 ED & TD China 2002 ES & TB>0 ES & TD YY: Internal balance

= Potential Spending

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

4. Avoiding future crashes

Experience of other emerging markets (1994 2002) 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.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

5. Longer-run perspective: Balassa-Samuelson relationship

• Prices of goods & services in China are low – not just low relative to the United States (.23) – but also low by standards of Balassa-Samuelson relationship estimated across countries ( which predicts .36

– before Dec. 2007 statistical revisions by IPC project • In this specific sense, the yuan was undervalued by an estimated 35% in 2000 – and is by at least as much today.

– But wouldn’t imply need for sudden change of this size.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Estimation of B-S relationship for 2000 (118 countries, PWT) • For every 1% increase in real income/capita (relative to US), prices increase .38% (relative).

• China’s estimated residual was .45 in logs (Frankel, 2006) • Subramanian, 2008, estimates only .15, on revised ICP stats.

Fitted values CHN logRER00 .370385

-2.15096

6.17768

CHN loginc00 10.6917

Does the Balassa-Samuelson relationship have predictive power?

 Typically across countries, gaps are corrected halfway, on average, over subsequent decade.

 => 3-4 % real appreciation on average per year, including effect of further growth differential  Correction could take the form of either inflation or nominal appreciation, but appreciation is preferable.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

US politicians focus on the bilateral trade deficit, despite its lack of economic importance.

Moreover, they have not yet learned how dependent on Chinese financing we have become.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

In 2008, however, the financial crisis caused a flight to quality which apparently still means a flight

US$.

• US Treasury bills are more in demand than ever, as reflected in very low interest rates.

• The $

appreciated

in 2008, rather than depreciating as the “hard landing” scenario had predicted.

• => The day of reckoning had not yet arrived.

• Chinese warnings in early 2009 may be a turning point: – Luo Ping “Except for US Treasuries, what can you hold?...We hate you guys.” – Premier Wen worries US Treasury bills will lose value.

– PBoC Gov. Zhou proposes replacing $ as international currency.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

$2 Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

“Be careful what you wish for”

If China gave US politicians what they say they want...

• We’d probably regret it.

– especially if it included reserve shift to match switch in basket weights.

• US TB & employment would hardly rise – Fall in US bilateral trade deficit with China would be offset by rise in US bilateral deficit with other cheap-labor countries, • but US interest rates probably

would

– possible hard landing for the $.

rise.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Now a

new

irony

If the Chinese authorities abandoned the dollar link that they re-established in 2008, it is no longer even clear, as of early 2009, that this would appreciated 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 last year (because the € did) !

• In early 2009, the PBoC has no longer been adding to reserves rapidly. Indeed in Jan.& Feb., reserves fell => if RMB floated, it might depreciated even against a basket. Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Appendix II Charts showing evolution of choices of regimes, from the IMF

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Appendix III Tables comparing economic performance of different regimes:

– Ghosh, Gulde & Wolf – Sturzenegger & Levy-Yeyati – Reinhart & Rogoff

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Source: Levy-Yeyati and Sturzenegger (2001).

Sample: yearly observations 1974 1999.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Source: Levy-Yeyati and Sturzenegger (2001).

Sample: yearly observations 1974 1999.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

The trend is in fact not away from intermediate regimes, but rather away from fixed exchange rates.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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 started to swing 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 – Kennedy School of Government – Harvard University

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

. -- e.g., Mussa (1986): • The final nail in the coffin is Alan Taylor’s (2002) century-of-PPP study.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

VOLATILITY OF

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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

Appendix VI: Synthesis Technique for Estimating De Facto Exchange Rate Regimes

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

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 ¥ • The synthesis technique generally gives the right answer.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University

Monte Carlo exchange rate under simulated basket+band regime

(with parameters from Papual New Guinea) 240 260 280 mcsa T 300 mcsa_non 320 340

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 – Kennedy School of Government – Harvard University

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 – Kennedy School of Government – Harvard University

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) – W.Samoa (Table 3.12) IV = price of rice IV = price of coconuts.

Professor Jeffrey Frankel – Kennedy School of Government – Harvard University