Appendices to:Exchange Rate Regimes

Jeffrey Frankel

Harpel Chair, Harvard University

IMF Institute

 * April 27, 2011 *

Appendices

I) Tables comparing economic performance of different regimes

II) Do exchange rate regimes have real effects?

III) The case of the euro’s effect on trade

IV) Emigrants’ remittances

V) More on the synthesis technique for estimating de facto exchange rate regimes.

VI) Proposal to Peg the Export Price

Appendix I

Tables comparing economic performance of different regimes:

– Ghosh, Gulde & Wolf

– Sturzenegger & Levy-Yeyati

– Reinhart & Rogoff

Which category experienced the most rapid growth?

Levy-Yeyati & Sturzenegger: floating

Reinhart & Rogoff:limited flexibility

Ghosh, Gulde & Wolf: currency boards

Source: Levy-Yeyati and Sturzenegger (2001).

Sample: yearly observations 1974-1999.

Source: Levy-Yeyati and Sturzenegger (2001).

Sample: yearly observations 1974-1999.

Appendix II:Do exchange rate regimes make a “real” difference?

• 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 was Alan Taylor’s (2002) century-of-PPP study.

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 Woods1971-96 Float

Taylor spliced together 100 years of data for 20 currencies.

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

Appendix III: 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 that1. diminishes with country size, or

2. is subject to long lags.

Why is the estimated effect in euro-land so much smaller than monetary unions among small developing countries?

16

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.

17

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%.

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.

Appendix IV. Emigrants’ remittances: 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 & 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, 08) have largest bilateral data set to date.

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 .

Are Bilateral Remittances Countercyclical?Are Bilateral Remittances Countercyclical? Frankel (2011a)Frankel (2011a)

• I combine the three substantial data sets I combine the three substantial data sets on bilateral remittances:on bilateral remittances:

• 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)

• Result: evidence of countercyclicality.Result: evidence of countercyclicality.• Highly significant positive coefficient on cyclical

difference between home & sending countries.

Table 3: Cross-Section 2003-04 --Composite data set (merging three sources) 

Dependent Variable:

Ln Remittances 2003-04 between Countries

  (1) (2) (3) (4)

Ln (Stock migrants 2000 ) 0.762*** 0.741*** 1.061*** 1.233***

(0.040) (0.041) (0.088) (0.152)

Cyclical Difference (Ln (Real GDP/ Trend GDP)) 16.199*** 16.099*** 14.723*** 13.983***

Sender relative to recipient (2.905) (2.765) (3.390) (3.927)

GDP per capita Sender 0.039*** 0.028* 0.022

(0.015) (0.016) (0.019)

Currency Union 1.345*** 0.087 -0.590

(0.222) (0.389) (0.632)

Estimation Method OLS OLS 2SLS 2SLS

Instrumental variables

border/language/islands/colonial

border/language

Observations 331 328 328 328

R2 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).

Frankel (2011a)

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

Frankel & Xie (AER, 2010),which adds endogenous break points to Frankel & Wei (IMF Staff Papers, 2008)

Shambaugh (2007) again finds: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%

Jay S.

86% 100%

LY-S

74% 80% 100%

R-R

81% 82% 73% 100%

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

Bénassy-Quéré et al (2004): correlation (BOR, IMF) = .76

Δ log Ht =

c + w(1) Δlog$ t + w(2) Δlog¥t + w(3) Δlog€t

+ w(4) Δlog£t + ß {Δ EMPt} + ut

where Δ EMPt ≡ ΔlogH t + (ΔRest /MBt.). • We impose ∑ w(j) = 1, implemented by treating £ as the last currency.

• If the exchange rate is governed by a strict peg,• we should recover the true weights, w(j), precisely; • and the equation should have a perfect fit.

• Flexibility in the exchange rate around the central parity should be captured by ß > 0 .

Synthesis technique to estimate de facto exchange rate regime

ttitji

k

jjiit uEMPXwcH

,,1

, loglog

1,...,1 ; ;0 ;,...,1 101 miTTTTTt mii

(6)

Finally, we introduce the Bai-Perron technique for endogenous estimation

of m possible structural break points

For further details, see NBER WP, Dec. 2009.

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)

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.

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 full global liquidity crisis hit and $ appreciated.

Table 1A. Identifying Break Points in Mexican Exchange Rate Regime M1:1999-M7:2009

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

VARIABLES 1/21/1999-9/2/2001

9/9/2001-3/18/2003

3/25/2003-7/29/2006

8/5/2006-1/28/2008

2/4/2008- 12/15/2008

12/22/2008-7/29/2009

US dollar 0.92*** 0.88*** 0.62*** 1.11*** 0.96*** 0.20(0.09) (0.12) (0.07) (0.10) (0.19) (0.22)

euro 0.14 -0.09 0.30*** 0.20* 0.51*** 0.51***(0.08) (0.14) (0.09) (0.11) (0.16) (0.18)

Jpn yen -0.05 0.22*** 0.08 -0.34*** -0.33** 0.18(0.06) (0.07) (0.06) (0.06) (0.12) (0.13)

△EMP 0.14*** 0.32*** 0.17*** 0.02 0.07 0.28***(0.03) (0.03) (0.03) (0.02) (0.07) (0.04)

Constant 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 0.78

Br. Pound -0.01 -0.01 -0.01 0.02 -0.14 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.

Future research• Results for the other currencies,

– often requiring weekly interpolation between monthly reserve figures

– are reported in Frankel & Wei (2008)

– or, with endogenous break points, will be forthcoming.

• Next econometric extension: Threshold Autoregression for target zones.

Appendix VI:Original 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.

The regime is intended to combine 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.

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.

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.

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).

0.000

20.000

40.000

60.000

80.000

100.000

120.000

140.000

160.000

180.000

200.000

RERICPIactual RERICPIFitted RERICPIProjected

Actual vs Fitted vs. Actual vs Fitted vs. Fundamentals-Fundamentals-

Projected Projected ValuesValues

Why are PEP & PPT better than CPI-targetingfor 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.)

• If the $ price of the export commodity goes up, PEP (or PPT) says to tighten monetary policy enough to appreciate currency. Right. (E.g., Gulf currencies.)

PEP, in its strict form, has some disadvantages

• Passes every fluctuation in world commodity prices straight through to domestic-currency prices of other Traded Goods, 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.

Moderate versions of the proposal

• 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.

• The still more moderate version is PPT:target a monthly index of product prices.

• Key point: exclude import prices from the index, & include export prices.

• Flaw of CPI target: it does it the other way around.