Download Discussion on “Monetary Policy “Contagion” in the Pacific: A Historical Inquiry

2015 Asia Economic Policy Conference (November 19-20, San Francisco)
Policy Challenges in a Diverging Global Economy
Discussion on Sebastian Edward (2015)
Discussion on
“Monetary Policy “Contagion” in the Pacific:
A Historical Inquiry
November 19, 2015
Woon Gyu Choi
Deputy Governor
Director General, Economic Research Institute
The Bank of Korea
Prepared by: Woon Gyu Choi, Geun-Young Kim, Byongju Lee, and Daeyup Lee
DISCLAIMER: The views expressed in this presentation represent those of the
presenter and do not necessarily represent those of the Bank of Korea or IMF.
Outline
I. Elements of the paper by Edwards
(2015) and Specific Comments
II. Recent Development in Cross-Border
Flows—Evolution of Debt Flows
III. Diverging Impacts of Global Liquidity
2
I. Elements of the Paper and Comments
 Main findings and Contributions
 Methodology and Related Channels
 Specific Comments
3
Elements of the Paper
Main Findings & Literature
• Finding 1: Six EMEs adjust their policy rates to the U.S.
policy rate
• Finding 2: The degree of cross-border pass-through of
U.S. interest rates differs by region and by capital
mobility (Asia only)
– (Conceptual) The slope and intercept of PP curve (Figure 3) could differ
across countries
– (Empirical) Regional difference: Latin America > Asia
• Contribute to the literature of cross-border interest rate
transmission
• Shed light on EME responses to global interest rate
normalization
4
Elements of the Paper
Methodology
• Single Equation Error Correction Model:
𝑝
𝑝
𝑝
∆𝑟𝑡 = 𝛼 + 𝛽 𝐹𝐹𝑡−1 + 𝛾∆𝑟𝑡−1 + 𝛿𝑟𝑡−1 + ∑𝜃𝑗𝑡 𝑥𝑗𝑡 + 𝜖𝑡
 Weekly data
 Long-term policy spillover: −𝛽/𝛿
 Least squares or IV method
• Panel Regression by Country Groups
5
Elements of the Paper
Possible Channels of Policy Rate Contagion
Global(US)
Demand
or Supply
Shocks
Agg. Demand
Channel :
Export, Output
Appreciation
U.S.
Policy
Rate
Capital
inflows
Liquidity Channel :
Domestic Liquidity
EMEs’
Policy
Rate
Agg. Supply
Channel :
Domestic Inflation
•
The degree of policy rate pass-through is affected
by various factors.
6
Elements of the Paper
Factors Affecting the Degree of Policy Contagion
• (Factor 1) Real and Financial Linkages
– Higher degree of linkages, higher contagion in policy
rate in response to common global shocks
• (Factor 2) Type of Causes
– Output-driven vs. Inflation-driven Policy Responses
• (Factor 3) Room for Other Policy Tools
– Foreign Reserves, Fiscal Policy Space
• (Factor 4) Constraints on Monetary Policy
– Foreign Debt (Exchange Rates)
– Household/Corporate Debt (Interest Rates)
7
Elements of the Paper
Recent Related Studies
using Factor-Augmented Panel VAR Models
• Choi et al. (2014): Identify the three momenta of global
liquidity and analyze their impacts on EMEs’ fundamentals
and financial markets
– U.S. policy tightening is equivalent to the withdrawal of policydriven GL
• Kim and Shin (2015): U.S. credit expansions boost output
and lower sovereign bond yields in the EMEs; and U.S.
credit expansions also stimulate the offshore bond
issuance after 2010
• Choi et al. (2015): Quantify the effect of U.S. policy
tightening, in comparison with EMEs’ own policy tightening,
on their macro-fundamentals and capital flows
– Explore how some EMEs are more vulnerable than others
8
Specific Comments
Degree of Pass-through
• The 1% hike of the U.S. Federal Funds rate
– Increased EMEs’ policy rates by 33 to 74 bps
– Choi et al. (2015) : 4 to 12 bps
• Differences
– Sample Period : Edwards <2000~2008> vs. Choi et al. <1995~2014>
 Fed tightening in the period 2000 to 2008 was largely attributable
to U.S. inflation, while policy actions after the GFC are more
associated with output slowdown and slow recovery
 The degree of interest rate transmission may differ depending on
the cause of policy actions
 Inflation-driven vs. output-driven policy responses
9
Specific Comments
Shifts in Macroeconomic Conditions
CPI Inflation(%)
Real GDP Growth(%)
10
10
9
8
8
6
7
6
4
5
1
-4
Chile
Mexico
Philippines
Colombia
Korea
Malaysia
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
0
-6
Chile
Mexico
Philippines
Colombia
Korea
Malaysia
• EMEs’ policy responses may differ, depending on their resilience
associated with fundamentals and relative weights of policy goals
10
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
-2
2003
2
2002
0
2001
3
2000
2
4
Specific Comments
Model Specifications and Tests
• Gauging long-term spillover in extended regressions
– Some control variables are not negligible in the long run: Expected
U.S. inflation, (domestic) inflation in Tables 4-7; U.S. 10-year yield
and (domestic) policy rates in addition to short-term deposit rates
in Tables 11-12
 Policy rates, short-term deposit rates, and U.S. funds rates could
be cointegrated (Table 12);
 Cross-border pass-through could be decoupled from domestic
pass-through along the yield-curve to avoid complexity
• Endogeneity control and tests for instrument validity
– Expected depreciation and EMBI could be affected by the dependent
variable (policy rates or short-term deposit rates)
– What are related instruments and specification test results?
11
II. Recent Development in
Cross-Border Flows
 Recent Evolution in the Financial Landscape
– Debt flows could be increasingly important in crossborder financial flows in the face of global interest rate
normalization
 Global Fund Flows: Bond and Equity
 Global Funding Network
Implications for interest rate normalization?—debt flows
are not balanced among countries
12
Recent Development in Cross-Border Flows
Changing Composition of
EM Corporate Debt : Bonds vs. Loans
The share of bonds edged up to 17%, whereas that of domestic
bank loans declined from 84% to 78% after the GFC
18
(% of Total Debt)
85
17
16
84
83
14
82
12
81
10
80
8
79
6
78
Bonds
4
2
0
2003
5
78
Foreign banks lending
77
Domestic banks lending (right scale)
76
2004
2005
2006
Source : IMF GFSR (2015)
2007
2008
2009
2010
75
2011
2012
2013
2014
13
Recent Development in Cross-Border Flows
Trend in Global Fund Flows
Bond inflows in EMEs… Headwinds of
U.S. interest rate hikes but reflows in
developed economies?
De-equitization in EMEs … but
not in developed economies?
500
(Bil. USD)
Developed
400
Bond Fund Flows
천
천
Equity Fund Flows
Emerging
200
150
(Bil. USD)
Developed
Emerging
300
200
100
100
50
0
-100
0
-200
-300
Source: EPFR (Emerging Portfolio Fund Research)
-50
14
Recent Development in Cross-Border Flows
Evolving Global Banking Networks
Decreases in bank loans from European countries may indicate the fragility of
European interbank network
Shifts from 2011:Q4 to 2014:Q4
December 2014
Policy
Data: BIS, Banking Statistics
Source: BOK staff calculation (Daeyup Lee, 2015)
•
•
22 reporting countries + China
Bank loans from JP to US is still the
thickest link, followed by that from
UK to US.
•
•
Real Sector
The network of European area becomes
relatively less active (more red(-) links).
CN experiences the largest increase (the largest
blue(+) vertex).
15
Recent Development in Cross-Border Flows
Pattern of Portfolio Investment
•
(June, 2014)
The pattern of bidirectional investment is more pronounced in equity
than in debt securities and bank loans… Hence, equity investment supports
the resilience of the domestic financial system… However, interest rate hikes
may accompany net capital outflows owing to the unwinding of debt
investment.
Equity and Investment Fund Shares
Total Debt Securities
Data: IMF, CPIS
(IMF, CPIS)
Source: BOK staff calculation (Daeyup Lee, 2015)
16
Recent Development in the Global Banking Network:
Bank Loan Flows
 From 2014.4Q to 2015.2Q, capital inflows (Blue Line) change to outflows
(Red Line). Euro funds decrease from U.S, EM Europe, Latin, and Asia (in
order of size)
2014Q1~2014.Q2
2014Q4~2015.Q2
Data: BOK Staff Calculation based on BIS Consolidated Banking Statistics
17
Recent Development in the Global Banking Network :
Bank Loan Flows in Asia
 During 2014.4Q~2015.2Q, mainly Euro and U.K funds showed outflows
from Asia, whereas U.S. funds increased inflows to China
 Euro funds retreat from Singapore, China (CN), but less severely than from
Brazil
2014Q1~2014.Q2
Data: BOK Staff Calculation based on BIS Consolidated Banking Statistics
2014Q4~2015.Q2
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III. Diverging Impacts of Global Liquidity (GL)
• How do interest rate hikes in the U.S. and EMEs
affect capital flows in EMEs?
• Is there any differentiation between EME subgroups depending on fundamentals?
• What explains country-differential impacts on
output loss from a GL shock?
– Economic structure and dynamics
– Or exposure to the shock and policy responses
19
Global Liquidity Transmissions:
Diverging Impacts of Interest Rate Hikes (Choi et al. 2015)
1.
Global interest rate hikes
outstrip domestic interest
rate hikes in their
impacts on the financial
front.
2.
Bond flows are more
sensitive to interest-rate
differential than equity
flows.
3.
Fragile EMEs are more
susceptible to U.S.
interest rate hikes.
Interest Rate
Normalization
Global
Domestic
Interest Rate
Interest Rate
Resilient
Fragile
Resilient
Fragile
EMEs
EMEs
EMEs
EMEs
Bond Flows
Equity Flows
Bond Flows
Equity Flows
4.
Resilient EMEs would have room for independent monetary policy.
5.
Resilience hinges on strong fundamentals—including current-account
and fiscal sustainability, and debt management.
20
Factor-augmented Panel VAR
𝑋𝑡 = 𝐴1 𝑋𝑡−1 + 𝐴2 𝑋𝑡−2 + 𝐵1 𝐹𝑡 + 𝐵2 𝐹𝑡−1 + 𝑒𝑡
• Xt: the quarterly panel of 19 EMEs comprising 9 variables
– Argentina, Brazil, Bulgaria, Chile, Czech Republic, Hungary, India, Indonesia, Israel,
Korea, Malaysia, Mexico, Philippines, Poland, Romania, Russia, South Africa,
Thailand, Turkey
– 1995Q1~2014Q3
• Ft : derived from G-5’s monetary and financial data (8 variables)
– Monetary and financial data are controlled by growth and PPI
– Identified by sign restrictions
• Policy-driven global liquidity factor, market-driven GL factor, and risk-averseness
GL factor
21
U.S. Policy Rate Hikes Slow Down EMEs
Factor-Augmented Panel VAR (19 EMEs, 1995Q1-2014Q3): Choi et al. (2015)
• GL cuts weaken EMEs’ currencies and stock markets as well as output
– A 1%p U.S. interest rate rise is embedded as a decrease in the policy-driven GL factor
Data: All variables except stock prices and exchange rates (REER) are seasonally adjusted by X-13 ARIMA-SEATS program of US
census. Variables are measured as quarter-over-quarter growth (Real GDP, CPI, stock prices, and REER) or percent of nominal GDP
of previous five years (capital inflows, foreign reserves, current account). All numbers are in percent.
22
U.S. Policy Tightening Outweighs EME’s Own Policy
Tightening on the Financial Front
• Impacts on capital flows and stock prices from U.S. policy tightening
are much stronger than those from their own policy tightening
23
Bond Markets Would Bear the Brunt of U.S.
Policy Tightening?
• Most outflows would take place in EMEs’ bond markets
24
Two EME Groups: High inflation vs. Low Inflation
• High inflation EMEs: 14% per annum
–
Argentina, India, Hungary, Mexico, Indonesia, Russia, Romania, Bulgaria, Turkey
• Low inflation EMEs: 4% per annum
–
Malaysia, Thailand, Korea, Israel, Czech Republic, Chile, Philippines, Poland, South Africa
One country, Brazil, at the midpoint in the inflation levels among the panel countries, is excluded.
High inflation vs. Low Inflation (2)
• The loss of real GDP from U.S. policy tightening is 0.3% point
greater for high-inflation EMEs than for low-inflation EMEs…
– Despite larger deployments in foreign reserves and higher policy rate in highinflation EMEs
All
Global Liquidity
High Inflation (H) Low Inflation (L)
Difference (H-L)
Real GDP
CPI
Current Account
Exchange Rates
Overnight Call Rates
Foreign Reserves
-0.33
-0.04
0.68
-0.22
0.04
-1.30
-0.46
0.23
0.95
-0.28
0.12
-3.16
-0.17
-0.03
0.69
-0.26
0.04
-0.52
-0.29
0.26
0.26
-0.02
0.08
-2.64
Domestic Liquidity Real GDP
CPI
Current Account
Exchange Rates
Overnight Call Rates
Foreign Reserves
-0.16
-0.19
0.97
0.15
0.17
0.99
-0.17
-0.09
0.70
0.10
0.18
-0.42
-0.20
-0.53
2.23
0.33
0.13
4.49
0.03
0.45
-1.53
-0.23
0.05
-4.90
Overnight call rates for domestic liquidity reports the level of policy rate after a 1% increase.
Counterfactual Analysis:
high- vs. low-inflation EMEs
• How would U.S. interest rate hikes affect if highinflation EME had the domestic economic structure of
low-inflation EMEs?
• Method: Stock and Watson (2002)
– Calculate the impulse response of the following model:
𝑋𝑡 =
𝐴1𝐿𝑜𝑤 𝑋𝑡−1 + 𝐴𝐿𝑜𝑤
2 𝑋𝑡−2
𝐻𝑖𝑔ℎ
+ 𝐵2 𝐹𝑡−1
+
𝐻𝑖𝑔ℎ
𝐵1
𝐹𝑡
𝐹𝑡 = Ψ1 𝐹𝑡−1 + 𝑢𝑡
Stock, James H., and Mark W. Watson, 2003, "Has the Business Cycle Changed and
Why?" NBER Macroeconomics Annual 2002, Vol. 17. pp. 159-230, MIT press.
Counterfactual of EMEs (2)
• High-inflation EMEs of would have little improvement by mimicking
the domestic economic structure of low-inflation EMEs.
• What matters is the way that high-inflation EMEs take the GL shock.
Concluding Remarks
1. Contribution and key message of Edwards (2015)
•
U.S. monetary policy affects EMEs’ policy rates: “policy contagion”
•
Macro-economic stability in EMEs could be subject to the
gravity of cross-border pass-through of policy rates
2. Related issues: composition of capital flows, diverging
impacts and policy responses would matter
3. Looking forward: policy-rate pass-through may depend
on policy space and the mix of policy tools in the face of
interest rate hikes
•
E.g., policy rate adjustments would be constrained by their
impacts through leverage channels
Thank You!
29