Transcript Day 3: Monetary Regimes For Commodity-Producing Developing Countries Jeffrey Frankel Harvard University & NBER Monetary Policy & Commodity Prices Study Center Gerzensee 23-25 June, 2014

Day 3: Monetary Regimes
For Commodity-Producing
Developing Countries
Jeffrey Frankel
Harvard University & NBER
Monetary Policy & Commodity Prices
Study Center Gerzensee
23-25 June, 2014
The Choice of Monetary Regimes
for Emerging Markets / Developing Countries
I.
How are DCs structurally different
from Advanced Economies?
II.
Choice of exchange rate regime
III. Alternative anchors for monetary policy
-- Proposal for Nominal GDP Targeting
I. How are EMs & Developing Countries
different from Advanced Economies?
1. Need for monetary credibility.
2. Supply shocks.
3. Terms of trade shocks.
How are EMs different from Advanced Economies? continued
1. Monetary policy-makers have
more need for credibility
a) due to high-inflation histories,
b) absence of credible institutions,
c) or political pressure to monetize big budget deficits.
A. Fraga, I. Goldfajn & A. Minella (2003),
“Inflation Targeting in Emerging Market Economies,”
NBER Macro Annual 2003, K.Rogoff & M.Gertler, eds. (MIT Press).
How are EMs different from Advanced Economies? continued
1.
2. The economy is more exposed to supply shocks
a) such as natural disasters
(hurricanes, cyclones, earthquakes, tsunamis…)
b) other weather events (droughts…),
c) social unrest (strikes…),
d) productivity shocks (“Are we the next Tiger economy?”).
3. And more exposed to terms of trade shocks.
a) Volatility in price of export commodity on world markets
b) Volatility in price of imports on world markets.
Trade & Supply Shocks are More Common
in Emerging Markets & Low-Income Countries
IMF SPRD & World Bank PREM, 2011, “Managing Volatility in Low-Income Countries:
The Role and Potential for Contingent Financial Instruments,” approved by R.Moghadam & O.Canuto
II. What is the desirable exchange rate regime?
• Advantages of fixing.
• Advantages of floating.
• Which dominate?
– Optimum Currency Area criteria
– Other criteria
• Intermediate exchange rate regimes
– E.g., systematic managed float.
Advantages of fixed rates
1) Encourage trade <= lower exchange risk
& lower transaction costs.
E.g., Rose (2000): currency unions triple trade among members.
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.
4) Avoid competitive depreciation (“currency wars”)
5) Avoid speculative bubbles that afflict floating.
(vs. if variability is fundamental real exchange rate risk,
it will just pop up in prices instead of nominal exchange rates).
Advantages of floating rates
1. Monetary independence
2. Automatic adjustment to trade shocks
3. Retain seigniorage
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
Which dominate: advantages
of fixing or advantages of floating?
The answer depends on circumstances.
No one exchange rate regime is right
for all countries or all times.
• Traditional criteria for choosing - Optimum Currency Area.
Focus is on stabilization of trade balance & business cycle.
• 1990s criteria for choosing –
Focus is on stabilization of financial markets.
• Additional criteria relevant for developing countries -- Financial development
-- Terms of trade volatility.
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:
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
Optimum Currency Area criteria
for fixing exchange rate:
• Small size and openness
– because then the 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
(i) Level of financial development
– Fixed rates are better for countries with low financial
development because markets are thin:
• => costs of financial shocks outweigh benefits of accommodating realshocks.
– As financial markets develop, exchange flexibility becomes more attractive.
• Estimated threshold: Private Credit/GDP > 40%.
• Aghion, Bacchetta, Ranciere & Rogoff (2005).
• For richer & more financially developed countries,
flexible rates work better:
•
more durable & deliver higher growth without inflation
•
Husain, Mody & Rogoff (2005).
Professor Jeffrey Frankel
(ii) 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.
• Most common case of real shocks: trade
Professor Jeffrey Frankel
Terms-of-trade volatility
• Prices of crude oil and other agricultural & mineral commodities
spiked in 2008 & 2011.
• => Favorable terms of trade shocks for some
(oil producers, Africa, Latin America, etc.);
• => Unfavorable terms of trade shock for others
(oil importers like Japan, Korea).
• 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).
Professor Jeffrey Frankel
Céspedes & Velasco (Nov.2012)
NBER WP 18569
“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 less is exchange rate flexibility. 16
Conclusion: Desirable exchange rate regime
 Very small, very open, economies usually
find that the advantages of fixing dominate.
 Very large countries like US & euroland usually
find that the advantages of floating dominate.
 Most countries are in between,
 particularly middle-sized middle-income countries.
• Most of these countries should have
intermediate exchange rate regimes,
– neither firm fixing nor free floating.
– Intermediate regimes include band & basket arrangements.
Distribution of EM exchange rate regimes
The big rise is in the “managed float” category
Distribution of
Exchange Rate
Regimes in Emerging
Markets, 1980-2011
}
(percent of total)
Atish Ghosh, Jonathan
Ostry & Mahvash
Qureshi, 2013, “Exchange
Rate Management and Crisis
Susceptibility: A Reassessment,”
IMF ARC , Nov..
So I reject the Corners Hypothesis.
 But Stan Fischer has a good point:
giving speculators a target to shoot at
is often a losing proposition,
• such as the boundary of a declared band.
• A particular intermediate regime could be
useful, a systematic managed float.
A systematic managed float
• Proposed rule: for every 1% of Exchange
Market Pressure, the central bank takes
x % as appreciation of the currency
& (1-x) % as an increase in reserves
(relative to the monetary base).
– This arrangement, though rather obvious,
has seldom been formalized.
– The parameter x calibrates exchange rate flexibility,
• and can range from 0 (fixing) to close to 1 (full flexibility).
– Thus one can have ½ monetary independence
+ ½ exchange rate stability.
Systematic managed floating
• refutes the corners hypothesis,
– but without capital controls,
– without violating the Impossible Trinity,
– and even without giving speculators
a line to shoot at.
 ≈ what some central banks do anyway.
 Attempts at econometric estimation
 G.Adler & C.Tovar, 2011, “Foreign Exchange Intervention:
A Shield Against Appreciation Winds?” IMF WP 11/165.
 J.Frankel & D, Xie, 2010, “Estimation of De Facto Flexibility Parameter
and Basket Weights in Evolving Exchange Rate Regimes,” AER.
Systematic 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
Example: Renewed capital inflows to Asia in 2010
Korea & Singapore took them mostly in the form of reserves,
while India & Malaysia took them mostly
in the form of currency appreciation.
more-managed floating
Slope
= 1/x
less-managed floating
GS Global ECS Research
Renewed inflows in 2010 in Latin America
were reflected mostly as reserve accumulation in Peru,
but as appreciation in Chile & Colombia.
more-managed floating
Slope
= 1/x
less-managed floating
Source: GS Global ECS Research
III: If the exchange rate is not to be
the anchor for monetary policy, what is?
• The need for an alternative anchor led
many EMs to Inflation Targeting (IT),
– after the currency crises of the late 1990s
pushed them off exchange rate targets.
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.
• IT was in many ways successful.
Professor Jeffrey Frankel
Drawbacks to IT have been revealed
• since 2008,
–analogously to how the currency
crashes of the 1990s revealed the
drawbacks of exchange rate targets.
• Two problems with IT:
– Neglect of asset bubbles
– Neglect of supply & trade shocks.
If the exchange rate is not to be the monetary anchor, what is? Cont.
• IT’s neglect of supply & trade shocks.
• Remember the textbook maxim: the exchange rate
should accommodate terms of trade shocks.
• If IT sets the CPI, it doesn’t allow the exchange rate
to rise & fall with the terms of trade.
• When the world price of copper exports falls, a CPI
target does not allow the currency to depreciate.
• When the world price of imported oil rises,
a literal CPI target says to tighten monetary policy
enough to appreciate the currency,
= the opposite of accommodating the adverse trade shock.
Nominal GDP Targeting
• NGDPT is more robust with respect to
supply shocks & terms of trade shocks,
– compared to the alternatives of IT
or exchange rate targets.
– And more robust with respect to velocity shocks,
• compared to M targets.
• The logic holds whether the immediate aim is
– disinflation (as in 1980s, and again today
among many EMs & developing countries);
– monetary stimulus (as among big Advanced Cs recently);
– or just staying the course.
Figure 2: When a Nominal GDP Target
Delivers a Better Outcome than IT
Supply shock is split between output & inflation objectives
rather than falling exclusively on output as under IT (at B).
Figure 3: When IT Delivers a Better Outcome
than a Nominal GDP Target
…if the Aggregate Supply curve is steep
(b is low, relative to a, the weight on the price stability objective)
NGDPT for Developing Countries
• The proponents of Nominal GDP Targets
have focused on the biggest countries.
• But middle-size, middle-income countries
are better candidates.
• Why? They suffer bigger supply shocks & trade shocks.
• Evidence suggests that the AS curve is indeed sufficiently
steep so that NGDPT minimizes quadratic loss function,
– for the cases of Kazakhstan and India:
– “Nominal GDP Targeting for Middle-Income Countries,”
June 2014 for Central Bank Review, of CB R Turkey.
• Recommendation: EM/DCs should consider NGDPT
as a serious alternative to IT & exchange rate targeting.
.
Mathematical analysis:
Which regime best achieves objectives
of price stability and output stability?
• The goal is to minimize a quadratic loss function:
2
2
Λ = a p + (y - )
where p ≡ the inflation rate,
y ≡ the log of real output,
≡ the preferred level of output;
a ≡ the weight assigned to the price stability objective.
.
Which regime best achieves objectives of price & output stability? continued
• Any nominal rule, provided it is credible, can set
expected inflation at the desired level (say, 0),
• e.g., eliminating the inflation bias that comes with discretion
• pe = Ep = (
) b/a. in Barro-Gordon (1982) model
of dynamic inconsistency,
• where the Aggregate Supply relationship is
y = 𝒚 + b(p – pe) + u,
• and 𝒚 ≡ potential output.
Which regime best achieves objectives of price & output stability? continued
• But different rules => different outcomes, when shocks hit
•
Rogoff (1985) & Fischer (1990).
• IT & NGDPT both neutralize AD shocks so far as possible.
• That leaves AS shocks, u.
• NGDP rule dominates IT, if…
a < (2 + b)b;
• Example 1: holds if b>a (AS flat, vs. loss function lines).
• Example 2: holds if a = 1 (as in Taylor rule)
and AS slope 1/b < 2.414.
• Under these conditions, the economy looks
more like Figure 2 than like Figure 3:
– If inflation were not allowed to rise in response to an AS shock,
the resulting loss in GDP could be severe => NGDPT dominates IT.
Which regime best achieves objectives of price and output stability? continued
• For Kazakhstan, an oil exporter, over the period 1993-2012:
the estimated AS slope is 1.66 and statistically < 2.41.
• For India, an oil importer, over the period 1996-2013:
– AS slope at the 1-year horizon ranges from .38 to .67.
– Each estimate of the slope coefficient is not only > 0 statistically,
but significantly < 2.41.
– Here the annual monsoon rain is one important supply shock.
• Thus under the assumptions we have made, it is estimated
that Nominal GDP Targeting dominates Inflation Targeting
– in terms of achieving the objectives of output & price stability,
– at least for these two countries.
•
•
Frankel, 2013, “Exchange Rate and Monetary Policy for Kazakhstan
in Light of Resource Exports,” CID, Harvard.
Bhandari & Frankel, 2014, “The Best of Rules and Discretion:
A Case for Nominal GDP Targeting in India,” HKS, June.
Estimation of AS curve for Kazakhstan
& other oil exporters
Regression of inflation against GDP growth, to estimate Aggregate Supply
for oil-exporting countries – Table 4, Frankel (2013), thanks to Gulzar Natarajan
Regression with AD shocks
Country
1
Iran
2 Saudi Arabia
3
Nigeria
4 Kazakhstan
(partner GDP & military spending)
as IVs for GDP
Coefficient
SE
t-stat
-3.29
3.33
5.86
1.66
5.14
1.98
6.82
0.75
-0.64
1.68
0.86
2.21
Period
1988-2009
1988-2012
1988-2012
1993-2012
Note: For some countries, estimated slope did not come out significantly > 0 .
Estimation of AS curve for India
Bhandari & Frankel (2014), Table 1:
Estimation of Supply Curve Slope
1st stage dependent
variable: output gap
2nd stage dependent
Variable: inflation surprises
winarm/ginarm/ginrw)
Note: First stage non-IV variables not shown.
Memo: List of variables with brief description
WINGAP & GINGAP: Annual inflation rate
minus expected inflation rate derived from an
ARMA model for WPI inflation & GDP deflator
respectively
GINRW: Annual inflation rate - expected
inflation rate derived from random walk
assumption
OGAP: Output gap. Potential calculated by
passing through HP filter
(
Aggregate demand instruments:
WG: World annual GDP growth
NREG: Dummy variable = 0 when the program
had not started and the value of ratio of
districts covered when it was operating
Aggregate supply shocks:
OIL (-2): Terms of trade variable calculated as
US$ price of a barrel of oil x USDINR exchange
rate, to get the Rupee value of oil; then
deflated by WPI inflation index to convert to
real terms. Quarterly change in the real value
of oil. 2 quarter lag worked best.
RAINS: Percentage deviation of monsoon rains
from normal.
Std. errors in parentheses
*** p<0.01,
** p<0.05,
* p<0.10
Estimates
Suggest:
Figure 2:
When a Nominal GDP Target
Delivers a Better Outcome than IT
Supply shock is split between output & inflation objectives
rather than falling exclusively on output as under IT (at B).
Appendix 1:
Rules vs. discretion
Appendix 2:
Are Emerging Markets vulnerable
to a global financial shock?
Appendix 1:
Why constrain monetary policy
by a rule?
In the dynamic consistency model (Barro-Gordon, 1982)
discretion leads to a positive bias in inflation.
A credible rule can eliminate that inflation bias.
Dynamic inconsistency: The Intuition
• Assume governments, if operating under discretion,
choose monetary policy and hence AD
so as to maximize a social function of Y & π.
– => Economy is at tangency of AS curve &
one of the social function’s indifference curves.
– Assume also that the social function centers on Yˆ > Y ,
even though this point is unattainable, at least in the long run.
• Assume W & P setters have rational expectations
– => πe (& AS) shifts up if rationally-expected E π shifts up
– => πe = E π
=
π on average.
•
•
economy is at point B on average.
Inflationary bias: πe=E π > 0.
• Lesson: The authorities can’t raise Y anyway,
so they might as well concentrate on price stability at point C.
Professor Jeffrey Frankel, Kennedy School of
Government, Harvard University
3. But πe adjusts
upward in response
to observed π>0.
The LR or Rational
Expectations
equilibrium must
feature πe = π.
π
πe
●
Result: inflationary
bias π>0, despite
failure to raise Y
above Y .
●
4. The country
would be better off
“tying the hands”
of the central bank.
Result: Y = Y
●
(no worse on average
than under discretion),
and yet π=0.
2. If πe would stay
at 0,
then to get the
higher Y
it would be
worth paying the price
of π>0.
Yˆ
1. Barro-Gordon
innovation:
It can be useful to
think of society’s
1st choice as Y= Yˆ
(& π=0), even if it
is unattainable.
API-120 - Macroeconomic Policy Analysis I Professor Jeffrey Frankel, Harvard University
TIME-INCONSISTENCY
OF NON-INFLATIONARY MONETARY POLICY
(Romer 11.53)
y  y   (   )
e
+ Policy-maker minimizes quadratic loss function:
(11.54)
1
1
2
2
  ( y  yˆ )  a ( )
2
2
where the target
yˆ  y.
1
1
e
2
2
ˆ
=>   ( y   (   )  y )  a( )
2
2
Professor Jeffrey Frankel, Kennedy School of
Government, Harvard University
Given discretion, the CB chooses the rate of money growth
and inflation (assuming it can hit it) where
d
e
 ( y   (   )  yˆ )  a( )  0
d
Take the mathematical expectation:
( y  E(   )  yˆ )  aE( )  0.
e
+ Rational expectations:
(11.58)
(10.15)
E 

a
  E
e
( yˆ  y)  0 ,
=>
the inflationary bias.
Professor Jeffrey Frankel, Kennedy School of
Government, Harvard University
.
ADDRESSING THE TIMEINCONSISTENCY PROBLEM

How can the CB credibly commit
to a low-inflation monetary policy?

Announcing a policy target π = 0 is time-inconsistent,
because a CB with discretion will inflate ex post,
and everyone knows this ex ante.

CB can eliminate inflationary bias
only by establishing non-inflationary credibility,

which requires abandoning the option of discretion.

so public will see the CB can’t inflate even if it wants to.

CB “ties its hands,” as Odysseus did in the Greek myth.
Professor Jeffrey Frankel, Kennedy School of
Government, Harvard University
Addressing the Time-Inconsistency Problem (continued)
 Reputation
 Delegation. Rogoff (1985): Appoint a CB with high weight
on low inflation a′ >> a , and grant it independence.
It will expand at only    ( yˆ  y )
a
<< inflationary bias of discretion.
 Binding rules. Commit to rule for a nominal anchor:
1. Price of gold
3. Exchange rate
5. CPI
2. Money growth
4. Nominal GDP
6. GDP deflator
Professor Jeffrey Frankel, Kennedy School of
Government, Harvard University
4.
Appendix 2:
Are Emerging Markets vulnerable
to a global financial shock?
• Boom-bust cycle in EM capital flows
• External shocks
– “Risk off”
– US interest rates
• Which countries withstand shocks
– In 2008-09 and previous crises?
– In 2013 US “taper tantrum”?
3 waves of capital flows to Emerging Markets:
• late 1970s, ended in the intl. debt crisis of 1982-89;
• 1990-97, ended in East Asia crisis of 1997-98;
• and 2003-2008, ended … when?
IIF
http://www.iif.com/press/press+406.php
The Joseph cycle
Joseph prophesied 7 years of plenty,
with abundant harvests from a full Nile
-- followed by 7 lean years of drought & famine.
The Pharaoh empowered his technocratic official (Joseph)
to save grain in the 7 years of plenty,
building up sufficient stockpiles to save the Egyptian people
from starvation during the bad years.
-- a valuable lesson for today’s government officials in
industrialized & developing countries alike.
51
For emerging markets,
the first phase of 7 years
of plentiful capital flows occurred in 1975-1981,
recycling petrodollars as loans to developing countries.
The international debt crisis that began in Mexico
in 1982 was the catalyst for the 7 lean years,
known in Latin America as the “lost decade.”
The turnaround year, 1989, saw the 1st Brady bond issue.
52
Biblical cycle, cont
.
The second cycle of 7 fat years was
the period of record capital flows
to emerging markets in 1990-96.
The 1997 “sudden stop” in East Asia
was then followed by 7 years of capital drought.
The third cycle of inflows, often identified with
“carry trade” & “BRICs” came in 2004-2018
and persisted even through the Global Financial Crisis.
If history repeats, it may be time for a 3rd
sudden stop of capital flows to emerging markets!
53
When implicit volatility is high (↓ in graph),
capital flows to EMs fall: “Risk off” (e.g., 2009 GFC)
Kristin Forbes, 2014 http://www.voxeu.org/article/understanding-emerging-market-turmoil
Notes: Data on private capital flows from IMF's IFS database, Dec. 2013. Capital flows are private financial flows to emerging markets
and developing economies. Volatility index measured by the Chicago Board's VIX or VXO at end of period. 2013 data are estimates.
See K.Forbes & F.Warnock (2012), “Capital Flow Waves: Surges, Stops, Flight and Retrenchment”, J. Int.Ec.
The role of US monetary policy
• Low US real interest rates contributed to EM flows
in late 1970s, early 1990s, and early 2000s.
• The Volcker tightening of 1980-82 precipitated
the international debt crisis of 1982.
• The Fed tightening of 1994 helped precipitate
the Mexican peso crisis of that year.
• But the correlation is not always there.
The relationship between the Fed’s interest rate
and EM capital flows does not always hold.
Kristin Forbes, 2014 http://www.voxeu.org/article/understanding-emerging-market-turmoil
Notes: Data on private capital flows and policy rates from IMF's IFS database, Dec. 2013 version. Capital flows are private financial
flows to emerging markets and developing economies. Policy rates measured at end of period. Data for 2013 are estimates.
After Fed “taper talk” in May 2013, capital
flows to Emerging Markets reversed again.
Powell, Jerome. 2013. “Advanced Economy Monetary Policy and Emerging Market Economies.”
Speech at the Federal Reserve Bank of San Francisco Asia Economic Policy Conference, November .
http://www.frbsf.org/economic-research/publications/economic-letter/2014/march/federal-reserve-tapering-emerging-markets/
When Ben Bernanke
warned of tapering QE
in May/June 2013,
US interest rates rose,
and EMs fell.
Financial Times
58
Global investors required higher interest
rates from EMs after May 2013
Global Economics Weekly: 14/07 - The downside risks to EM growth and their market implications, 2/19/2014
Which EM countries are hit the hardest?
• For past studies of past crises, such as 1997-98,
• Early Warning Indicators that worked well include:
– Foreign exchange reserves
• especially relative to short-term debt;
– Currency overvaluation;
– Current account deficits.
•
E.g.,
– J. Frankel & A. Rose (1996) "Currency Crashes in Emerging Markets," JIE.
– G. Kaminsky, S. Lizondo, & C.Reinhart (1998) “Leading Indicators of Currency Crises," IMF Staff Papers.
– G. Kaminsky, & C.Reinhart (1999)
– J. Frankel & G. Saravelos (2012) “Are Leading Indicators Useful for Assessing Country
Vulnerability? Evidence from the 2008-09 Global Financial Crisis.” JIE.
The variables that show up as the strongest predictors
of country crises in the past are:
(i) reserves and (ii) currency overvaluation
0%
10%
20%
30%
40%
50%
60%
Reserves
Real Exchange Rate
GDP
Credit
Current Account
Money Supply
Budget Balance
Exports or Imports
Inflation
Equity Returns
Real Interest Rate
Debt Profile
Terms of Trade
Political/Legal
Contagion
Capital Account
% of studies where leading indicator was found to be
statistically signficant
(total studies = 83, covering 1950s-2009)
External Debt
Source: Frankel & Saravelos (2012)
70%
Many EM countries learned lessons from
the crises of the 1990s, which better-prepared them
to withstand the Global Financial Crisis of 2008-09.
• More-flexible exchange rates
• Higher reserve holdings
• Less dollar-denominated debt
• More local-currency debt
• More equity & FDI
• Macro-prudential regulation
• Fewer Current Account deficits
• Stronger government budgets
Foreign exchange reserves are useful
• One purpose is dampening appreciation,
– thus limiting current account deficits.
• Another is the precautionary motive.
• The best predictor of who got hit in the 2008
Global Financial Crisis was reserves
– Frankel & Saravelos (2012).
– Dominguez & Ito.
– This was the same Warning Indicator that also
had worked in the most studies of earlier crises.
Best and Worst Performing Countries
in Global Financial Crisis of 2008-09-- F&S (2010),
Appendix 4
GDP Change, Q2 2008 to Q2 2009
Lithuania
Latvia
Ukraine
Estonia
Macao, China
Russian Federation
Bo tto m 10
Georgia
Mexico
Finland
Turkey
Australia
Poland
Argentina
Sri Lanka
Jordan
Indonesia
To p 10
Egypt, Arab Rep.
Morocco
64 countries in sample
India
China
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
Which EM countries were hit the hardest
by the “taper tantrum” of May-June 2013?
• Those with big current account deficits,
• or with exchange rate overvaluation.
• Reserves did not seem to help this time.
•
E.g.,
– B. Eichengreen & P. Gupta (2013) Tapering Talk: The Impact of Expectations of Reduced Federal
“
Reserve Security Purchases on Emerging Markets,” Working Paper.
– Jon Hill (2014) “Exploring Early Warning Indicators for Financial Crises in 2013 & 2014,” HKS, April.
,
Which EM countries were hit the hardest
by the “taper tantrum” of May-June 2013?
Or January 2014?
• Those with big current account deficits,
• or with exchange rate overvaluation.
• Reserves did not seem to help this time.
• E.g.,
– B. Eichengreen and P. Gupta (2013)
“Tapering Talk: The Impact
of Expectations of Reduced Federal Reserve Security Purchases on Emerging Markets,” UCB WP.
– Jon Hill (2014)
“Exploring Early Warning Indicators for Financial Crises in 2013 & 2014,” MPA/ID SYPA, HKS, April.
Current account deficits opened up
among the “Fragile Five” after 2005
Global Economics Weekly: 14/07 - The downside risks to EM growth and their market implications, 2/19/2014
Countries with current account deficits
were hit in June 2013.
Kristin Forbes, 2014
http://www.voxeu.org/article/understanding-emerging-market-turmoil
The
“Fragile
Five”
Countries with high inflation rates were also hit
in the year since May 2013.
A.Klemm, A.Mei
er & S.Sosa, IMF,
May 22, 2014
Taper Tantrum or
Tedium: How U.S.
Interest Rates Affect
Financial Markets in
Emerging Economies
Are EMs vulnerable to a new global shock?
Conclusion
• Many EMs learned lessons from the 1980s & 1990s,
and by 2008 were in a stronger position to withstand shocks:
–
–
–
–
More flexible exchange rates
More fx reserves
Less fx-denominated public debt
Stronger budget positions & Stronger current account positions.
• Some backsliding, 2010-2014:
– Weaker budgets
– Current account deficits
– The return of fx-denominated private debt.
• A promising direction: macro-prudential regulations
– E.g., counter-cyclical loan-to-value ratios for mortgages.