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Lecture 4: Exchange Market Pressure and Warning Indicators
Causes of currency crisis: (See Lecture 5)
Weak fundamentals: monetization of government debt (Krugman, 1979)
Domestic credit expansion, or budget deficit.
Expansionary fiscal and credit policies lead to real appreciation, and current
account deficit. With sticky prices, nominal wages increase results in higher real
wages and lower competitiveness.
Self-fulfilling: economic policies are no predetermined but respond to changes in the
economy. Economic agents take this relationship into account in forming their
expectation (Obstfeld, 1986). Cost and benefit analysis of maintaining pegged.
Banking crisis: proceeds currency crisis, balance sheet effect (Krugman, 1998).
Twin crises (vs. twin deficits)
Contagion effects: if it is present, a crisis in a neighboring country may be an
indicator of a future domestic crisis through channels of trade or finance.
Exchange Market Pressure (EMP)
How a “crisis” is defined?
A crisis is defined as a situation in which an attack on the currency leads to a sharp
depreciation of the currency, a large decline in international reserves, or a combination
of the two.
Crisis are identified (ex post) by the behavior of an index of “exchange market
pressure.” The index is a weighted average of monthly percentage changes in the
exchange rate and monthly percentage changes in gross international reserves.
Periods in which the index is above its mean by more than three standard deviations
are defined as crisis.
EMP  P 
e  e r e
r



e r r
e
r
The weighted (  ) average of exchange rate depreciation and reserve outflows (scaled
by base money)
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The EMP can be used as a continuous variable (used for OLS regression) or
converted into a binary variable, c,
Crisis, c = 1, if
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P   p   p
otherwise
Girton, Lance and Don Roper (1977), “A Monetary Model of Exchange Market
Pressure Applied to the Postwar Canadian Experience,” American Economic Review,
Vol. 67, No. 4, 537-548.
Girton and Roper (1977): index of exchange market pressure
Since base money, H, is the sum of domestic credit, D, and international reserves, R,
we can define r=ER/H, and d=D/H. Let h denote a function of the percentage change
in the price level, p, the percentage change in real income, y, and the percentage
change in interest rates, i.
(r  r * )  (d  d * )  ( p  p * )  B( y  y * )  a(i  i * )
(1)
using purchasing power parity,
e  (r  r * )  (i  i * )  (d  d * )  B( y  y * )  (1  a)(i  i * )
(2)
the left-hand side of (2) is an index of speculative pressure, which says that pressure
increases as domestic reserves of foreign exchange decline, as interest rates rise, and
as the exchange rate depreciates. The theoretical underpinnings suggest that
speculative pressure should be a parametric function of fundamentals such as the rate
of growth of domestic credit, the level of income, and the interest rate differential.
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Three approaches of warning signals:
1. Signalling approach---monitoring the evolution of a number of economic
indicators that tend to systematically behave differently prior to a crisis.
Exceeding a certain threshold value within following 24 months signals a currency
crisis.
Kaminisky, Graciela L., Saul Lizondo, and Carmen M. Reinhart (1998), “Leading
Indicators of Currency Crises,” IMF Staff Papers, 45, 1-48.
The indicators:
1. the external sector
2. the financial sector
3. the real sector
4. the public finances
5. institutional and structural variables
6. political variables
Capital account: international reserves, capital flows, short-term capital flows,
foreign direct investment, and the differential between domesitc and foreign interest
rates
Debt profile: public foreign debt, total foreign debt, short-term debt, share of debt
classified by type of creditor and by interest structure, debt service, and foreign aid.
Current account: the real exchange rate, the current account balance, the trade
balance, exports, imports, the terms of trade, the price of exports, savings and
investment
International variables: foreign real GDP growth, interest rates, and price level.
Financial liberalization: credit growth, the change in the money multiplier, real
interest rates, and the spread between bank lending and deposit interest rates.
Other financial variables: central bank credit to the banking system, the gap
between money demand and supply, money growth, bond yields, domestic inflation,
the shadow exchange rate, the parallel market exchange rate premium, the central
exchange rate parity, the position of the exchange rate within the official band, and
M2/international reserves.
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Real sector: real GDP growth, the output gap, employment/unemployment, wages,
and changes in stock prices.
Fiscal variables: the fiscal deficit, government consumption, and credit to the public
sector.
Institutional/structural factors: openness, trade concentration, and dummies for
multiple exchange rates, exchange controls, duration of the fixed exchange rate
periods, financial liberalization, banking crises, past foreign exchange market crises,
and past foreign exchange market events.
Political variables: dummies for elections, incumbent electoral victory or loss,
change of government, legal executive transfer, illegal executive transfer, left-wing
government, and new finance minister; also degree of political instability.
Good signal: a signal that is followed by a crisis within 24 months
False signal (or noise): a signal not followed by a crisis within that interval of time.
General results:
a. an effective warning system should consider a broad variety of indicators
b. those individual variables that receive ample support as useful indicators of
currency crises include international reserves, the real exchange rate, credit growth,
credit to the public sector, and domestic inflation.
c. Only tentative conclusions can be drawn regarding the other indicators
d. The variables associated with the external debt profile did not fare well, the current
account balance did not receive much support as a useful indicator of crises.
Selected indicators
1. international reserves
2. imports
3. export
4. terms of trade (unit value of exports over unit value of imports) growth rate
5. deviations of the real exchange rate from trend
6. the differential between foreing and domestic real interest rates on deposits
7. “excess” real M1 balances
8. M2 multiplier
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9. domestic credit/GDP
10. real interest rate on deposits
11. the ratio of lending to deposit interest rates
12. the stock of commercial banks deposits
13. the ratio of broad money
14. an index of output
15. an index of equity prices
Signaling horizon: this is the period within which the indicators would be expected
to have an ability for anticipating crises. This period was defined a-priori as 24
months.
Good signal-a signal that is followed by a crisis within 24 months
False signal- a signal not followed by a crisis within that interval of time.
Signals and thresholds: an indicator is said to issue a signal whenever it departs from
its mean beyond a given threshold level., which was chosen so as to strike a balance
between the risks of having many false signals and the risk of missing many crises.
Thresholds were defined in relation to percentiles (say 10%) of the distribution of
observations of the indicator. Optimal set of thresholds was defined as the one that
minimized the noise-to-signal ratio.
Empirical results
76 currency crises, sample of 15 developing and 5 industrial countries during
1970-1995.
Forecasting ability: the lead time and persistence of the signals
Crisis(within 24 months) No crisis(within 24months)
Signal was issued
A(good signal)
B(false signal)
No signal was issued
C(missed signal)
D(good silence)
A,B,C, and D denote the number of months in which the indictor issued a signal.
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A/(A+C): issue good signals, real exchange rate issued the highest percentage of
possible good signals, while imports issued the lowest percentage of possible good
signals.
(C/(A+C), type I error)
B/(B+D): sending bad signals, real exchange rate shows the best performance, while
the ratio of lending to deposit interest rate shows the poorest performance. (B/(B+D),
type II error)
[B/(B+D)]/[A/(A+C)]: adjusted noise-to-signal ratio, the lower is the number the
better is the indicator.
Four indicators, with adjusted noise-to-signal ratio greater than 1, should be removed
from the list of those to be used within the signals approach, the ratio of lending
interest rates to deposit interest rates, bank deposits, imports, and the real interest rate
differential.
A/(A+B): a crisis conditional on a signal from the indicator
(A+C)/(A+B+C+D): unconditional probability of a crisis
How leading are the leading indicators?
Average months in advance of the crisis when the first signal occurs, on average, it
send the first signal anywhere between a year and a year and a half before the crisis
erupts. They are leading indicators!
Persistence of the signals
For top-tier indicators (by ranking), signals tend to be at least twice as persistent in
pre-crisis periods relative to tranquil times.
Conclusion
1. An effective warning system should consider a broad variety of indicators, since
currency crises seem to be usually preceded by multiple economic problems.
2. Indicators that have proven to be particularly useful in anticipating crises include
the behavior of international reserves, the real exchange rate, domestic credit,
credit to the public sector, and domestic inflation. Variables of trade balance,
export performance, money growth, M2/international reserves, real GDP growth,
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and the fiscal deficit are also supportive indicators.
3. Variables associated with external debt profile did not fare well. CA did not
receive much support as a useful indicator.(a reflection of real E, which was
included in the estimation and is significant)
References
Chui, Michael (2002), “Leading Indicators of Balance-of-Payments Crises: A Partial
Review, Bank of England Working Paper No. 171.
Kaminisky, Graciela L. and Carmen M. Reinhart (1999), “The Twin Crises: The
Causes of Banking and Balance-of-Payments Problems,” American Economic Review,
89, 473-500.
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2. Discrete-choice approach
Frankel, J. A. and A. K. Rose (1996), “Currency Crashes in Emerging Markets:
Empirical Indicators,” Journal of International Economics, 41, 351-367.
A panel annual data for over 100 developing countries from 1971 to 1992.
Define a currency crash:
4 problems need to be solved:
a. Should currency crashes be limited to episode that end in a large fall in the value of
the currency?
b. How big a change in the exchange rate is needed to qualify?
c. How should the exchange rate be measured?
d. How does one deal with high-inflation countries that routinely undergo large
changes in the exchange rate?
25% nominal depreciation, or at least 10% rate of depreciation
The variables of interest:
a. macroeconomic indicators: 3 variables( government budget, domestic credit, and
real per capital output)
b. external variables: 4 variables (ratio of international reserves, CA, external debt,
real exchange rate divergence)
c. debt composition:7 variables (commercial bank debt, concessional debt,
variable-rate debt, short-term debt, FDI, public sector debt, multilateral debt.
d. foreign variables: 2 variables (foreign interest rate, and northern growth rate)
Methods:
A. Event study methodology: Non-structural, univariate graphical techniques
117 different crashes (74 crashes are deleted because of the 3-year windowing)
no-crash observations constitute a sample of “tranquil” observations---control sample
Observing each variable 3 years prior to the crisis and 3 years after the crisis.
B. Regression analysis: multivariate statistical approach, Probit estimates
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Evaluate directly the conditional probability of a crisis given a set of indicators
P( y  1)  f (  ' x)
assume a logistic distribution function,
P( y  1) 
exp(  ' x)
,
1  exp(  ' x)
P( y  0) 
1
1  exp(  ' x)
can be estimated by Maximum likelihood and LOGIT regression.
Conclusion: Crashes tend to occur when FDI inflows dry up, when domestic credit
growth is high, when northern interest rates rise, and when the real exchange rate
shows over-valuation. Neither current account nor government budget deficits appear
to play an important role in a typical crash.
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3. Structural approach
Sachs, Tornell and Velasco (1996), “Financial Crises in Emerging Markets: The
Lessons from 1995,” Brookings Papers on Economic Activity: 1996:1, 147-215.
Data: cross-section of 20 emerging markets during the 1994 Mexican crisis.
EMP: between the end of November 1994 and the end of each of the first six months
of 1995.
The explanatory variables consist of a lending boom variable (LB) - proxy for the
strength of the banking system or fundamentals-the growth in loans in the private
sectors between 1990 to 1994,
An overvaluation measure (RER) - the average real effective exchange rate
depreciation of 1986-89 to that of 1990-94,
Dummies - for low reserves and weak fundamentals.
Low reserves, measured as the M2/reserves ratio (DLR=1) when they lie in the
lowest quartile in the sample.
Weak fundamentals (DWF=1) when the exchange rate depreciation is in the
lowest three quartiles and the lending boom variable in the highest three
quartiles.
EMP  1   2 ( RER )  3 ( LB)   4 ( DLR  RER )
 5 ( DLR  LB)   6 ( DLR  DWF  RER )
  7 ( DLR  DWF  LB)  
Hypothesis testing matrix
Fundamentals
High (DLR=0)
Strong (DWF=0)
 2  0, 3  0
Weak (DWF=1)
 2   4  0,
3  5  0
 2   4   6  0,
3  5  7  0
Reserves
Low (DLR=1)
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Finding:
Example: Nov.1994 - Apr.1995
EMP  37.039  6.393( RER )  1.770( LB)  6.165( DLR  RER )
 6.835( DLR  LB)  2.886( DLR  DWF  RER )  8.895( DLR  DWF  LB)
P-value for null hypothesis:
2  4  0
 2   4  6  0
3  5  0
3  5   7  0
0.72
0.07
0.12
0.04
Countries with strong fundamentals but low reserves are not likely to be attacked,
(  2   4 , 3  5 are not significantly different from zero)
Countries with weak fundamentals and low reserves: a more devalued real exchange
rate or a small lending boom will lead to a smaller crisis pressure index
(  2   4  6  0, 3  5  7  0 )
References
陳南光與張光亮(2002)，亞洲金融風暴的源起：基本面或傳染？經濟論文叢刊，
1-26。
Corsetti, G. Pesenti, P and Roubini, N (1999), “Paper Tigers? A Model of Asian
Crisis,” European Economic Review, 43, 1211-1236.
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