(VI) LECTURES 18-19:

EXCHANGE RATE REGIMES

Topics to be covered I. Classifying countries by exchange rate regime II. Advantages of fixed rates

III. Advantages of floating rates IV. Which regime dominates? ● Tests ● Optimum Currency Areas

V. Additional factors for developing countries • • •

Emigrants’ remittances Financial development Terms-of-trade shocks.

VI. Intermediate regimes & the corners hypothesis Appendices

Professor Jeffrey Frankel

I. Classification by exchange rate regime Continuum from flexible to rigid FLEXIBLE CORNER

1) Free float

2) Managed float INTERMEDIATE REGIMES

3) Target zone/band

4) Basket peg

5) Crawling peg

6) Adjustable peg FIXED CORNER

7) Currency board 9) Monetary union

8) Dollarization

Trends in distribution of EM exchange rate regimes • • • •

1973-1985 – Many abandoned fixed exchange rates 1986-94 – Exchange rate-based stabilization programs 1990s -- Corners Hypothesis: countries move to either hard peg or free float Since 2001 -- The rise of the “managed float” category. Distribution of Exchange Rate Regimes in Emerging Markets, 1980-2011

}

(percent of total)

Ghosh, Ostry & Qureshi, 2013, “Exchange Rate Management and Crisis Susceptibility: A Reassessment,” IMF ARC , Nov..

De jure regime  de facto • Many countries that say they float, in fact intervene heavily in the foreign exchange market. [1] • Many countries that say they fix, in fact devalue when trouble arises. [2] • Many countries that say they target a basket of major currencies in fact fiddle with the weights. [3] [1] “Fear of floating” -- Calvo & Reinhart (2001, 2002); Reinhart (2000). [2] “The mirage of fixed exchange rates” -- Obstfeld & Rogoff (1995). [3] Parameters kept secret -- Frankel, Schmukler & Servén (2000).

One statistical approach to ascertain de facto regimes: Var (exchange rate) vs. Var (reserves). •

Calvo & Reinhart (2002) note that many countries that de jure say they float in fact have a lower Var (Δe) relative to Var (ΔRes) than many that say they fix !

•

Levy-Yeyati & Sturzenegger (2005) classify all countries based on variability of Δe vs. variability of ΔRes.

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 !

Correlations Among Regime Classification Schemes IMF IMF GGW LY-S R-R

GGW

LY-S

R-R

1.00 (100.0)

0.60

1.00

(55.1)

(100.0)

0.28

0.13

1.00

(41.0)

(35.3)

(100.0)

0.33 (55.1)

0.34

0.41

1.00

(35.2)

(45.3)

(100.0)

(Frequency of outright coincidence, in %, given in parenthesis.) GGW =Ghosh, Gulde & Wolf. LY-S = Levy-Yeyati & Sturzenegger. R-R = Reinhart & Rogoff Sample: 47 countries.

From Frankel, ADB, 2004.

Table 3, prepared by M. Halac & S.Schmukler.

Professor Jeffrey Frankel

II. Advantages of fixed rates 1) Encourage trade trade ↓ ? Time-series evidence showed little effect. But more in: - Cross-section evidence, especially small & less developed countries.

- Currency unions: Rose (2000). Professor Jeffrey Frankel

The Rose finding • Rose (2000) -- the boost to bilateral trade from currency unions is: – significant, – ≈ FTAs, & – larger (2- or 3-fold) than had been previously thought. • Many others have advanced critiques of Rose research. – Re: sheer magnitude • endogeneity, • small countries, • missing variables.

– Estimated magnitudes are often smaller, but the basic finding has withstood perturbations and replications remarkably well. ii/

• Some developing countries seeking regional integration talk of following Europe’s lead, though plans merit skepticism. [ii] E.g., Rose & van Wincoop (2001); Tenreyro & Barro (2003). Survey: Baldwin (2006)

Advantages of fixed rates, cont. 2) Encourage investment 40%.

• Husain, Mody & Rogoff

(2005)

For richer & more financially developed countries, flexible rates work better – in the sense of being more durable – & delivering higher growth without inflation.

(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.

Terms-of-trade variability • Prices of crude oil and other agricultural & mineral commodities hit record highs in 2008 & 2011. • => Favorable terms of trade shocks for some (oil producers, such as Mideast, Africa, Latin America);

• => Unfavorable terms of trade shock for others (oil importers such as India, Korea, Turkey).

• Textbook theory says a country where trade shocks dominate should accommodate by floating. • Confirmed empirically: – Developing countries facing terms of trade shocks do better with flexible exchange rates than fixed exchange rates. – Broda (2004), Edwards & L.Yeyati (2005), Rafiq (2011), and Céspedes & Velasco (2012)

Céspedes & Velasco, 2012, IMF Economic Review “Macroeconomic Performance During Commodity Price Booms & Busts”

** Statistically significant at 5% level.

Constant term not reported.

(t-statistics in parentheses.)

Across 107 major commodity boom-bust cycles, output loss is bigger the bigger is the commodity price change & the smaller is exchange rate flexibility. 26

VI. Intermediate exchange rate regimes and the corners hypothesis

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)

• Managed float (leaning against the wind)

The Corners Hypothesis • The hypothesis: “Countries are, or should be, abandoning intermediate regimes like target zones and moving to either one corner or the other: rigid peg or free float. Origins: • 1992-93 ERM crises -- Eichengreen (1994) • Late-90’s crises in emerging markets – Fischer (2001).

But the pendulum swung back, • from 61% of IMF staff in 2002, to 0% in 2010. • Many developing countries follow intermediate exchange rate regimes. • The theoretical rationale for the corners hypothesis never was clear.

Managed float (“leaning against the wind”): Turkey’s central bank buys lira when it depreciates, and sells when it is appreciates.

Kaushik Basu & Aristomene Varoudakis, Policy RWP 6469, World Bank, 2013, “How to Move the Exchange Rate If You Must: The Diverse Practice of Foreign Exchange Intervention by Central Banks and a Proposal for Doing it Better” May, p. 14

In Latin America, renewed inflows in 2010 were reflected mostly as reserve accumulation in Peru, but as appreciation in Chile & Colombia. more-managed floating

less-managed floating (“more appreciation-friendly”)

Source: GS Global ECS Research

Korea & Singapore in 2010 took renewed inflows mostly in the form of reserves, while India & Malaysia took them mostly in the form of currency appreciation.

more-managed floating

less-managed floating (“more appreciation-friendly”)

Goldman Sachs Global ECS Research

The flexibility parameter can be estimated in terms of Exchange Market Pressure: – Define Δ EMP = Δ value of currency + Δ reserves/MB. – Δ EMP represents shocks in currency demand. – Flexibility can be estimated as the propensity of the central bank to let shocks show up in the price of the currency (floating) , vs. the quantity of the currency (fixed), or in between (intermediate exchange rate regime).

Distillation of technique to infer flexibility • When a shock raises international demand for the currency, does it show up as an appreciation, or as a rise in reserves? • EMP variable appears on the RHS of the equation. The % rise in the value of the currency appears on the left. – A coefficient of 0 on EMP signifies a fixed E (no changes in the value of the currency),

– a coefficient of 1 signifies a freely floating rate (no changes in reserves) and – a coefficient somewhere in between indicates a correspondingly flexible/stable intermediate regime.

APPENDICES ON EXCHANGE RATE REGIMES

• Appendix 1: Tables comparing economic performance of different regimes • Appendix 2: The econometrics of estimating de facto exchange rate regimes

.

•Appendix 3: IT versus alternative anchors, with volatility in commodity export prices

Appendix 1 Tables comparing economic performance of different regimes: – Ghosh, Gulde & Wolf – Sturzenegger & Levy-Yeyati – Reinhart & Rogoff

Which category experienced the most rapid growth? Ghosh, Gulde & Wolf: currency boards

Levy-Yeyati & Sturzenegger: floating

Reinhart & Rogoff: limited flexibility

Levy-Yeyati & Sturzenegger (2001): floats work best.

Effect of regime on growth rates, controlling for various determinants

Levy-Yeyati & Sturzenegger (2001). Sample: yearly observations 1974-1999.

Appendix 2: The econometrics of estimating de facto exchange rate regimes. • Why do the various schemes for classifying countries by de facto exchange rate regimes give such different answers?

• Synthesis of the technique for estimating the anchor and the technique for estimating the degree of exchange rate flexibility.

Schemes for de facto classification • have themselves been 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….” -- Tavlas, Dellas & Stockman (2006).

Jay Shambaugh (2007) again finds that the de facto classification schemes tend to agree with each other even less than they agree with the de jure scheme. Percentage agreement of methodologies to code who pegs

De Jure

Jay S.

LY-S

De Jure

100%

Jay S.

86%

100%

LY-S

74%

80%

100%

R-R

81%

82%

73%

R-R

100% Professor Jeffrey Frankel

As do Bénassy-Quéré et al (2004) The IMF now has its own “de facto classification” -- but still close to official IMF one: correlation (BOR, IMF) = .76

Pure de facto classification schemes 1. Method to estimate degree of flexibility: •

Levy-Yeyati & Sturzenegger (2005): compare variability of Δ exchange rates vs. variability of Δ reserves.

2. Method to estimate implicit basket weights: Regress Δ value of local currency against Δ values of major currencies. Frankel & Wei (1993, 95, 2007), Bénassy-Quéré (1999), B-Q et al (2004).

• • •

Close fit => a peg. Coefficient of 1 on $ => $ peg. Or on other currencies => basket peg. Example of China, post 7/2005.

3. Synthesis method: • •

F & Wei (2008), F & Xie (2010) . Regress Δ value of local currency against EMP, to estimate flexibility parameter and against Δ values of $ and other major currencies, to estimate weights in anchor basket.

Appendix 3 IT versus alternative anchor (PEP) to take into account commodity export prices

Fashions in international currency policy • 1980-82: Monetarism (target the money supply) • 1984-1997: Fixed exchange rates (incl. currency boards)

• 1993-2001: The corners hypothesis • 1998-2008: Inflation targeting (+ currency float) became the new conventional wisdom • Among academic economists • among central bankers • and at the IMF Professor Jeffrey Frankel

6 proposed nominal targets and the Achilles heel of each:

Monetarist rule Inflation targeting Nominal income targeting Gold standard Commodity standard Fixed exchange rate

Targeted variable

Vulnerability

Example

M1

Velocity shocks

US 1982

CPI

Import price shocks

Oil shocks of 1973-80, 2000-08

Measurement problems

Less developed countries

Vagaries of world gold market Shocks in imported commodity Appreciation of $

1849 boom; 1873-96 bust

Nominal GDP Price of gold Price of agric. & mineral basket $ (or €)

(or € )

Oil shocks of 1973-80, 2000-08

1995-2001

Professor Jeffrey Frankel

Inflation Targeting has been the reigning orthodoxy. • Flexible inflation targeting ≡ “Have a LR target for inflation, and be transparent.” Who could disagree? • But define IT as setting yearly CPI targets, to the exclusion of • asset prices • exchange rates • export commodity prices.

• Some reexamination is warranted, in light of 2008-2011. Professor Jeffrey Frankel

• The shocks of 2008-2015 showed disadvantages to Inflation Targeting, – analogously to how the EM crises of the 1994-2001 showed disadvantages of exchange rate targeting.

• It gives the wrong answer in case of trade shocks: • E.g., it says to tighten money & appreciate in response to a rise in oil import prices; • It does not allow monetary tightening & appreciation in response to a rise in world prices of export commodities. • That is backwards. Professor Jeffrey Frankel

Proposal to Peg the Export Price PEP Intended for countries with volatile terms of trade, e.g., those specialized in commodities. The authorities stabilize the currency in terms of a basket of currencies plus the price of the export commodity rather than to the CPI (which gives weight to imports) and rather than a simple fixed exchange rate. 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.

Why is PEP better than targeting the exchange rate or CPI for countries with volatile terms of trade?

PEP

Better response to adverse terms of trade shocks: • If the $ price of the export commodity goes up, PEP says to tighten monetary policy enough to appreciate currency. – Right response.

(E.g., Gulf currencies in 2007-08.)

• If the $ price of imported commodity goes up, CPI target says to tighten monetary policy enough to appreciate currency. – Wrong response. (E.g., ECB or other oil-importers in 2007-08.) – => CPI targeting gets it backwards.

Professor Jeffrey Frankel

Does floating give the same answer as PEP? • True, commodity currencies tend to appreciate when commodity markets are strong, & vice versa

– Australian, Canadian & NZ $ (e.g., Chen & Rogoff, 2003) – South African rand (e.g., Frankel, 2007) – Chilean peso and others • But – Some volatility under floating appears gratuitous. – Floaters still need a nominal anchor. Professor Jeffrey Frankel

The Rand, 1984-2006: Fundamentals (real commodity prices, real interest differential, country risk premium, & l.e.v.)

can explain the real appreciation of 2003-06 – Frankel (SAJE, 2007). 200.000

180.000

160.000

140.000

120.000

100.000

80.000

60.000

40.000

Actual

vs

Fitted

vs.

20.000

FundamentalsProjected Values

Q

Q

2

19 8 1 4 19 Q 85 4 19 Q 85 3 19 Q 86 2 19 Q 87 1 19 Q 88 4 19 Q 88 3 19 Q 89 2 19 Q 90 1 19 Q 91 4 19 Q 91 3 19 Q 92 2 19 Q 93 1 19 Q 94 4 19 Q 94 3 19 Q 95 2 19 Q 96 1 19 Q 97 4 19 Q 97 3 19 Q 98 2 19 Q 99 1 20 Q 00 4 20 Q 00 3 20 Q 01 2 20 Q 02 1 20 Q 03 4 20 Q 03 3 20 Q 04 2 20 Q 05 1 20 06

0.000

RERICPIactual

RERICPIFitted

RERICPIProjected

Professor Jeffrey Frankel

In practice, most IT proponents agree central banks should not tighten to offset oil price shocks • They want focus on core CPI, excluding food & energy. • But – food & energy ≠ all supply shocks.

– Use of core CPI sacrifices some credibility: • If core CPI is the explicit goal ex ante, the public feels confused. • If it is an excuse for missing targets ex post, the public feels tricked.

– The threat to credibility is especially strong where there are historical grounds for believing that government officials fiddle with the CPI for political purposes. – Perhaps for that reason, IT central banks apparently do respond to oil shocks by tightening/appreciating….