Money and Banking

Lecture XI: Exchange Rate Regime Choice and Exchange Rate Forecast

Guoxiong ZHANG, Ph.D.

Shanghai Jiao Tong University, Antai

November 28th, 2017

Source: http://www.dailymirror.lk

Road Map

Exchange rate regime choicehistorical experienceChina’s perspective

Exchange rate forecastexchange rate forecast modelsexchange rate forecast performance

Gold Standard

Before World War I, the world economy operated under the goldstandard: currency of most countries was convertible directly into goldat fixed rates.

Disadvantage of this gold standard: can not have active monetarypolicy.

The world economy grows faster than the speed of gold production,caused deflation;Huge amount of gold discovered in South America caused inflation.

Bretton Woods System

After World War II, US became the world leader and USD became theonly reserve currency, and therefore Bretton Woods System wascreated in 1944:

All the other countries’ currency has a fixed exchange rate with USD;One USD has a fixed value of 1

35ounce of gold.

In 1971, US unilaterally devaluated dollar to one dollar equals 142

ounce of gold;

In 1973, US terminated convertibility of the US dollar to gold and letother countries to choose their own exchange rate with dollar.

Classification of Exchange Rate Regime

Textbook classification:fixed (Hong Kong, etc.)managed float (China, etc.)float (most other countries)

IMF classification:floatingsoft peg (managed float)hard peg (currency board)others?dollarization?

Map of Exchange Rate Regimes

Optimal Exchange Rate Regime

How to choose exchange rate regime that suits the country the besthas been an evolving theme:

before 1990s, most countries, especially developing and transitioneconomies prefer fixed exchange rate regime;in 1990s, several countries with fixed exchange rate regime suffer fromserious capital crisis and therefore shifted to more float exchange rateregimes;around 2000, bipolar exchange rate regime (either free float or hard peg)became popular until Argentina’s currency crisis in 2002;after every financial crisis (2001 IT bubble, 2007-2009 financial crisis),more countries tend to abandon float exchange rate regime (fear to float)

Benefits from a Fixed Exchange Rate Regime

A series of studies by IMF (1999 - 2009) do find empirical evidencethat a fixed exchange rate regime may benefits developing countries:

Pegged exchange rate regimes are associated with the best in ationperformanceGrowth performance is best under intermediate exchange rateregimes?those that maintain relatively rigid exchange rates but do notformally peg to a single anchor currency.Countries in a monetary union have deeper trade links.

Downsides of a Fixed Exchange Rate Regime

These studies also find downsides of a fixed or intermediate exchangerate regime may hurt a developing economy:

a fixed or intermediate exchange rate regime severely constrains the useof other macroeconomic policies (both monetary policy and fiscalpolicy);a fixed or intermediate exchange rate regime has greater susceptibility tocurrency and financial crises, such as debt crises, a sudden stop incapital inflows, or banking crisesa fixed or intermediate exchange rate regime impedes timely externaladjustment

Exchange Rate of RMB

Exchange Rate Regime of RMB

Before 1994, RMB is officially pegged to dollar (between 1985 and1993, dual exchange rates);

In 1994, RMB started managed-float with USD as the only referencecurrency: market exchange rate can fluctuate within a narrow bandaround the official benchmark rate;

Started in 2005, RMB use a basket of currencies as reference;

Band width: 0.3% in 2005, 0.5% in 2007, 1% in 2012 and 2% in 2014.

In August 2015, two major reforms were initiated:use last trading-day’s close rate as reference for the official benchmarkrate;reduce USD’s weight in the basket of reference currency.

Future Perspective of the Exchange Rate Regime of RMB

The direction of renminbi exchange rate reform is irreversible.China will continue to enhance exchange rate flexibility, and in thenear future, China is going to increase the floating band of therenminbi even further, letting market supply and demand play thefundamental role in exchange rate formation. China will alsoreduce central bank intervention, enhance the self-rebalancingcapability of foreign exchange market, and improve the self-pricingand risk management capabilities of the financial institutions.

-Yi, Gang (2013)

Exchange Rate Forecast Models

It is well known that exchange rates are very difficult to predict usingeconomic models

Meese and Rogoff puzzle: a simple random walk model without anyeconomic meaning can generate better exchange rate forecasts thaneconomic models.

Nevertheless it is important to understand the forecast models used byeconomists.

Older models (before 1990s): uncovered interest rate parity model,purchasing power parity model.Newer models (after 1990s): sticky price model, productivity differentialmodel, composite model

Random Walk Model

St = St−1 + εt,

where E(εt) = 0, var(εt) <∞ and corr(εi, εj) = 0 for ∀i 6= j.

USD-Euro Exchange Rate, Level

Source: https://fred.stlouisfed.org/series/DEXUSEU

USD-Euro Exchange Rate, Change

Source: https://fred.stlouisfed.org/series/DEXUSEU

USD-Euro Exchange Rate, Autocorrelation

Source: https://fred.stlouisfed.org/series/DEXUSEU

Purchasing Power Parity Model

st = α+ pt + ut,

where st = log(St), pt is the log of CPI,pt = pt,i − pt,j , and ut is an errorterm.

Uncovered Interest Rate Parity Model

st+k = st + it,k + ut,

where it,k is the interest rate of maturity k at time t.

Sticky Price Model

st = α+ β1mt + β2yt + β3 it + β4πt + ut,

where mt is log money supply, yt is log real GDP, it is nominal interestrate, πt is inflation rate, and again · denotes country differential.

Productivity Differential Model

st = α+ β1mt + β2yt + β3 it + β4zt + ut,

where zt is country productivity (TFP).

Composition Model

st = α+ pt + β1ωt + β2rt + β3 ˆg dt + β4 ˆTOT t + β4 ˆNFAt + ut,

where ωt is the price of non-tradables, rt is the real interest rate, g dt is theGDP over government debt ratio, TOT t is terms-of-trade (real exchangerate), and NFAt is net foreign asset holding.

Forecast Performance

We assess the forecast performance of these models by comparing itsforecast MSE with the one of the random walk model:

MSE =T∑

t=1

(st − st)2.

Forecast Performance

Table 1

The MSE ratios from the dollar-based exchange rates

Specification Horizon Sample 1: 1987q2e2000q4 Sample 2: 1983q1e2000q4

PPP S-P IRP PROD COMP PPP S-P IRP PROD COMP

Panel A: BP/$

ECM 1 4.165 1.047 1.008 0.995 1.085 5.678 1.050 1.046 1.042 1.049

0.003 0.409 0.883 0.897 0.208 0.031 0.310 0.318 0.303 0.448

4 1.750 1.127 1.092 1.017 1.099 1.612 1.142 1.123 1.085 1.127

0.199 0.503 0.620 0.802 0.253 0.224 0.171 0.310 0.237 0.225

20 0.782 1.809 1.342 1.095 1.340 0.632 1.457 0.841 1.545 2.179

0.536 0.014 0.240 0.411 0.168 0.156 0.071 0.518 0.092 0.057

FD 1 1.041 1.006 1.191 1.086 1.079 1.023

0.434 0.940 0.217 0.135 0.337 0.901

4 1.120 1.124 1.881 1.250 1.455 1.448

0.315 0.524 0.001 0.149 0.176 0.351

20 1.891 2.531 6.953 3.223 5.557 6.015

0.177 0.021 0.000 0.195 0.019 0.001

Panel B: CAN$/$

ECM 1 32.205 1.054 1.090 1.148 1.278 31.982 1.056 1.092 1.041 1.337

0.008 0.127 0.048 0.062 0.016 0.001 0.279 0.022 0.552 0.004

4 6.504 1.102 1.172 1.182 1.603 6.947 1.116 1.170 1.017 1.754

0.016 0.181 0.452 0.157 0.118 0.004 0.334 0.359 0.929 0.018

20 1.569 0.939 0.865 1.090 1.760 1.171 1.062 0.813 1.097 1.623

0.000 0.574 0.760 0.308 0.002 0.093 0.727 0.607 0.318 0.000

FD 1 1.100 1.115 0.614 1.101 1.171 0.666

0.179 0.138 0.109 0.257 0.047 0.151

4 1.137 1.160 0.899 1.196 1.269 1.143

0.461 0.341 0.798 0.347 0.192 0.704

20 0.515 0.504 1.924 1.892 2.004 2.289

0.193 0.182 0.006 0.182 0.143 0.204

Panel C: DM/$

ECM 1 6.357 1.059 1.030 1.041 0.995 11.173 1.105 1.029 0.997 0.911

0.006 0.464 0.295 0.574 0.955 0.005 0.416 0.364 0.961 0.206

4 2.301 1.080 1.136 1.080 1.116 2.675 1.104 1.063 0.949 0.898

0.016 0.444 0.069 0.282 0.642 0.007 0.599 0.485 0.626 0.558

20 0.649 1.047 0.596 1.131 2.137 0.411 1.771 0.895 1.260 0.633

0.363 0.637 0.167 0.141 0.216 0.248 0.212 0.656 0.039 0.202

FD 1 1.268 1.324 0.555 1.123 1.196 0.694

0.052 0.106 0.001 0.017 0.084 0.020

4 1.402 1.607 0.844 1.077 1.281 1.151

0.024 0.030 0.571 0.452 0.009 0.612

20 1.814 1.927 2.522 1.723 1.964 3.975

0.175 0.114 0.140 0.246 0.121 0.003

Panel D: SF/$

ECM 1 7.595 1.074 1.051 1.024 . 8.694 0.995 1.050 1.052 .

0.001 0.187 0.138 0.515 . 0.000 0.906 0.141 0.581 .

4 2.537 1.269 1.183 1.184 . 2.106 1.002 1.122 1.136 .

0.014 0.015 0.059 0.367 . 0.003 0.982 0.248 0.149 .

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1159Y.-W. Cheung et al. / Journal of International Money and Finance 24 (2005) 1150e1175