CAPITAL FLOWS AND GLOBAL LIQUIDITY - 2016...
-
Upload
truongthuy -
Category
Documents
-
view
220 -
download
0
Transcript of CAPITAL FLOWS AND GLOBAL LIQUIDITY - 2016...
IMF Note for G20 IFA WG
February 2016
CAPITAL FLOWS AND GLOBAL LIQUIDITY
1. INTRODUCTION
Cross-border capital flows are an important aspect of the global economy.1 Closer
integration has led to the development of growing trade and financial interlinkages across
economies. This has also helped economic and financial development in a number of economies.
But because capital flows can be volatile and, in some cases, large relative to the size of domestic
markets, they also carry risks. The increased financial interconnectedness associated with greater
capital flows can also exacerbate the transmission and spillover of shocks between economies.2
Both pull and push factors are important in dictating the scale and direction of capital
flows. This note looks at the evolution of domestic drivers and global liquidity over the past
decade, including a focus on G20 economies. It finds that gross global capital flows have picked
up in recent years, with increases in flows to advanced economies offsetting declines to
emerging market economies. Past capital flows have been associated with a rise in external debt,
particularly in G20 emerging market economies, which has increased risks. Global capital flows
have however weakened in the past year, especially in emerging market economies, owing to a
fall in portfolio and other investment flows. The note also discusses data gaps in capital flows,
external positions, and global liquidity that are affecting the assessment of risks in the
international monetary system.
2. WHAT DRIVES CAPITAL FLOWS?
International capital ebbs and flows according to the pull of local economic and financial
conditions.3 International capital should, ceteris paribus, be pulled towards economies in which
local conditions are such that investors expect to generate a higher return (or risk-adjusted
return), for example where current and expected interest rates are higher and where economic
growth expectations are better. Figure 2.1 illustrates how average growth and interest rate
differentials between the individual economies in the G20 have varied over time. Local economic
conditions also determine capital flows through the demand for international financing in
economies with larger current account deficits.
Capital flows are also pushed by common global factors. A key push factor is global liquidity,
which can be defined operationally as the ease of global financing.4 Global liquidity is observable
1 IMF, 2012.
2 Ostry et al, 2012.
3 Ghosh, Ostry and Qureshi, 2016.
4 IMF, 2014.
2
through the extent to which borrowing constraints are binding in accessing international funding
and can be captured in how conditions in the large financial centers—systemic, reserve currency
economies—are transmitted to other financially open economies through capital flows.
Figure 2.1 Pull factors for capital flows
1. Real economic growth differentials
Emerging market less advanced economy (percentage points)
2. Real interest rate differentials
Emerging market less advanced economy (percentage points)
Sources: Haver Analytics; and IMF staff calculations.
In this framing, global liquidity can be disassembled into three key aspects (Figure 2.2). The
first is global drivers, or the financial conditions prevailing in the large financial centers. This
comprises asset prices (including key policy rates, international money market rates and
benchmark bond rates), non-price factors (such as investor risk appetite, financial innovation and
leverage) and constraints faced by lenders and investors (for example, credit limits and margin
requirements). The second aspect is transmission, where these financial conditions are diffused
across economies by active financial intermediaries (such as G-SIFIs) and transactions in
international capital markets. This transmission can be seen through cross-border bank and
portfolio flows, as well as through asset price correlations. Third, global liquidity can have local
outcomes by affecting the level, cost and availability of credit, as well as relative levels of asset
prices. This generates a feedback in global liquidity. If the local asset prices being affected are in
a large financial center, this will impact the drivers of global liquidity, and restart the process.
Figure 2.2 Key aspects of global liquidity
-3
-2
-1
0
1
2
3
4
5
6
7
00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15
Max-Min
Median
-3
-2
-1
0
1
2
3
4
5
6
00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15
Max-Min
Median
PoliciesRisk appetite
Global bank leverageFinancial innovation
Cross-border bank flowsNon-core bank funding
International portfolio flowsInternational debt issuance
Drivers Transmission Outcomes
Credit growthCost of credit
Credit conditionsAsset prices
Feedback
3
Figure 3.1 Liquidity drivers, transmission channels and outcomes
Darker (lighter) shades of blue indicate looser (tighter) liquidity conditions, relative to the historical distribution of each variable over the 2005-13 period.
Sources: BIS; EPFR; Haver Analytics; and IMF staff calculations.
Most Liquid Least Liquid
Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep Dec Mar Jun Sep
Drivers
VIX
Broker Dealer Leverage
US Credit Manager's Index
US 10yr-3mth Spread
Euro 10yr-3mth Spread
Japan 10yr-3mth Spread
US M2
Euro M2
Japan M2
US Policy Rate
Euro Policy Rate
Japan Policy Rate
Transmission: Cross-border banking flows
USA
Euro Area
China
Brazil
India
Turkey
South Africa
Transmission: Portfolio Flows (Bonds)
USA
Germany n.a. n.a. n.a.
China
Brazil
India
Turkey
South Africa
Outcomes: Total Credit
USA n.a.
Euro Area n.a.
China n.a.
Brazil n.a.
India n.a.
Turkey n.a.
South Africa n.a.
201520142011 2012 201320102005 2006 2007 2008 2009
4
3. HOW HAS GLOBAL LIQUIDITY EVOLVED?
These three aspects of global liquidity can be monitored through a set of indicators. There
are a number of variables that can be used to track the development of the drivers of global
liquidity as well as its transmission and impact on local financial outcomes. These indicators can
be expressed as the number of standard deviations the different variables are from their
historical mean, for a selected set of systemic advanced and emerging market economies
(Figure 3.1). Large variations in their values can raise flags about the abundance or scarcity of
global liquidity. These indicators usefully illustrate four major phases of global liquidity over the
past decade: boom, bust, aftermath, and aftershock (Figure 3.2).
Figure 3.2 Global liquidity Standard deviations from mean 1. Global liquidity factors 2. Global liquidity drivers
3. Global liquidity transmission 4. Local credit outcomes
Sources: BIS; EPFR; Haver Analytics; and IMF staff calculations.
During the boom phase in the first part of the decade there was an abundance of global liquidity
(Figure 3.2, panel 1). This was reflected in liquidity drivers through a rise in risk appetite, a
reduction in asset price premia and a buildup of leverage (Figure 3.2, panel 2). Liquidity was
transmitted through a surge in cross-border flows and the widespread use of wholesale and
cross-border funding of banks (Figure 3.2, panel 3). The boom also generated a classic credit and
asset price reinforcement cycle (Figure 3.2, panel 4).
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
05 06 07 08 09 10 11 12 13 14 15
Transmission
Outcomes
Drivers
Boom Bust Aftermath Aftershock
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
05 06 07 08 09 10 11 12 13 14 15
Leverage
Bond
premia
Boom Bust Aftermath Aftershock
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
05 06 07 08 09 10 11 12 13 14 15
Bond
flows
Banking
flows
Boom Bust Aftermath Aftershock
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
05 06 07 08 09 10 11 12 13 14 15
Emerging market
economies
Advanced
economies
Boom Bust Aftermath Aftershock
5
In 2008 the boom turned to bust with the onset of the global financial crisis. Liquidity was
withdrawn, asset price premia spiked (Figure 3.2, panel 2), capital flows came to a sudden stop
(Figure 3.2, panel 3), the credit cycle went into reverse and banks started to deleverage, and
adverse market and funding liquidity dynamics poisoned local market conditions.
In the aftermath of the global financial crisis, while advanced economies were starting to engage
in unconventional monetary policies, capital flows picked up again, but this time they were
directed at emerging markets, who took the opportunity to increase leverage (see the deeper
blue shades in Figure 3.1 for cross-border banking flows and credit in Brazil, India and Turkey, in
particular). Figure 3.2, panel 3 highlights the rise in the transmission of global liquidity during this
period. Flows became less bank-related as advanced economy financial institutions were still in a
process of deleveraging, particularly in the euro area where the crisis entered into a new phase.
Capital flows to emerging market countries were then translated into a pick-up in local credit
conditions and a releveraging in some parts of the economy (Figure 3.2, panel 4).
The aftershock phase started with the “taper tantrum” in mid-2013—where asset price premia
rose suddenly (Figure 3.2, panel 2)—but has continued since. Figure 3.2, panel 1 shows that
global liquidity drivers, its transmission through capital flows, and local outcomes have been
below their average since the start of this period.
4. TRENDS IN GLOBAL CAPITAL FLOWS
Global capital flows showed signs of moderation in 2015.5 Global gross capital flows
amounted to US$3.6 trillion (5 percent of world GDP) in the twelve months to end-September
2015 (Figure 4.1), falling by about 2 percentage points of world GDP from a year earlier. The
majority of flows went to advanced economies (AEs), which accounted for 86 percent of total
flows (4.5 percent of world GDP), while emerging market and developing economies (EMDEs)
received 13 percent of total flows (0.7 percent of world GDP). Global gross flows comprised
mainly portfolio and direct investment (about 3 percent of world GDP each), while other
investment (including loans, deposits, trade credit, and derivatives) was negative.
Global capital flows experienced large swings since 2000. There have been significant
changes in volume and composition of global capital flows during the last 15 years. Global flows
rose rapidly during 2002-07, reaching a high of US$12 trillion (over 20 percent of world GDP) in
2007. They fell sharply in 2008-09 during the global financial crisis, and then recovered in 2010,
5 IMF Balance of Payments Statistics for 2000 Q1–2015 Q3. Gross capital inflows are defined as net changes in domestic
resident liabilities to nonresidents. Gross capital outflows are defined as net changes in foreign assets owned by domestic
residents, excluding reserve assets. Net capital inflows are defined as gross inflows minus gross outflows.
6
but never returned to the pre-2008 highs. In more recent years, global flows weakened in 2011-
12, which partly reversed in 2014. In 2015, global flows declined again (particularly to EMDEs).
Figure 4.1 Global gross capital inflows
Sources: IMF Balance of Payments Statistics and IMF staff calculations.
These capital flow phases had different features, which resulted in notable shifts in their
composition by country group and type of flow over time.
During 2002-07, both AEs and EMDEs experienced large increases in capital flows, and all
types of flows rose (particularly other investment). At their peak in 2007, capital flows to
AEs accounted for 88 percent of total flows, and other investment flows had the largest
share in total flows (42 percent), followed by portfolio flows (31 percent) and direct
investment (27 percent).
During 2008-09, other investment flows (which became negative) and portfolio flows
recorded the steepest declines, while direct investment flows were relatively more stable
and became the most important component of global capital flows.
Since 2010, flows to EMDEs increased their share in global capital flows, reaching
50 percent in 2013. In addition, other investment flows turned less important, while
portfolio flows became the largest component of total flows, with a share of over
50 percent in 2014-15.
-6000
-4000
-2000
0
2000
4000
6000
8000
10000
12000
14000
-6000
-4000
-2000
0
2000
4000
6000
8000
10000
12000
14000
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
World: Gross Capital Inflows(USD billion, four-quarter moving sum)
FDI Inflows Portfolio Inflows Other Inflows Total Inflows
-15
-10
-5
0
5
10
15
20
25
30
-15
-10
-5
0
5
10
15
20
25
30
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
World: Gross Capital Inflows(Percent of world GDP, four-quarter moving average)
FDI Inflows Portfolio Inflows Other Inflows Total Inflows
-2000
0
2000
4000
6000
8000
10000
12000
14000
-2000
0
2000
4000
6000
8000
10000
12000
14000
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
World: Gross Capital Inflows(USD billion, four-quarter moving sum)
Advanced Economies Emerging Markets and Developing Economies World
-5
0
5
10
15
20
25
30
-5
0
5
10
15
20
25
30
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
World: Gross Capital Inflows(Percent of world GDP, four-quarter moving average)
Advanced Economies Emerging Markets and Developing Economies World
7
In the past year, global capital flow trends have changed again, with EMDEs witnessing a
sharp decline in flows (particularly portfolio and other investment). As a result, the share
of EMDEs in total flows has fallen rapidly.
Capital flows were more variable in EMDEs than AEs. An analysis of the volatility of global
capital flows, as measured by their standard deviation from the trend as a share of GDP
(Figure 4.2), shows that:
Capital flow variations appear larger in EMDEs than AEs. Since the global financial crisis,
the standand deviation of net capital flows vis-à-vis their trend is 0.2 percent of GDP in
AEs compared to 0.7 percent of GDP in EMDEs.
The variability of net capital flows has increased in EMDEs (from 0.5 percent of GDP pre-
crisis to 0.7 percent of GDP post-crisis), while it has fallen slightly in AEs (from 0.3 percent
of GDP pre-crisis to 0.2 percent of GDP post-crisis).
Other investment flows is the most variable component of global capital flows, followed
by portfolio investment, while direct investment is relatively more stable. This is the case
for both AEs and EMDEs (see Figures 4.1, 4.3 and 4.4).
Figure 4.2 Variability of net capital flows
Sources: IMF Balance of Payments Statistics and IMF staff calculations.
Note: The long-term trend was extrapolated applying Hodrick-Prescott (HP) Filter on capital flow data from 2000 Q1 to 2015 Q3.
Capital flows to advanced economies (AEs)
AEs saw positive gross inflows but negative net inflows in 2015. Gross capital flows to AEs
totaled US$3.1 trillion (7 percent of AEs GDP) as of end-September 2015, comprising direct
investment and portfolio investment in approximately equal proportions, while other investment
was negative (Figure 4.3). Net capital flows to AEs, on the contrary, were negative, totaling
-US$370 billion (-0.8 percent of GDP) as a result of net outflows of portfolio investment (-0.6
percent of GDP) and direct investment (-0.2 percent of GDP).
-1
0
1
2
3
4
5
6
-1
0
1
2
3
4
5
6
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
Advanced Economies: Net Capital Inflows(Percent of GDP, four-quarter moving average)
Net Capital Inflows Trend
Standard deviation
2000-2008Q2: 0.3% of GDP
Standard deviation
2009Q3-2015Q3: 0.2% of GDP
-1
0
1
2
3
4
5
6
-1
0
1
2
3
4
5
6
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
EMDEs: Net Capital Inflows(Percent of GDP, four-quarter moving average)
Net Capital Inflows Trend
Standard deviation2000-2008Q2: 0.5% of GDP
Standard deviation2009Q3-2015Q3: 0.7% of GDP
8
Trends in gross and net flows diverged in AEs. Gross capital flows to AEs started to rise in
2013, from a low of 2.6 percent of GDP, driven by an increase in portfolio and direct investment
and lower negative other investment. Gross flows are, however, still well below previous peaks
(9.7 percent of GDP in 2011 and 26 percent of GDP in 2007). Net capital flows to AEs, on the
contrary, which had averaged about 1.5 percent of GDP in 2000-11, started declining in 2012,
and turned negative in 2013, owing to a sharp decrease in net portfolio and other investment.
Figure 4.3 Capital Flows to Advanced Economies
Sources: IMF Balance of Payments Statistics and IMF staff calculations.
Capital flows to emerging market and developing economies (EMDEs)
Gross capital flows to EMDEs were still positive, while net flows turned negative in 2015.
Gross capital flows to EMDEs amounted to US$475 billion (2 percent of EMDEs GDP) as of end-
September 2015, comprising mainly direct investment (2.5 percent of GDP) and portfolio
investment (0.5 percent of GDP), while other investment was negative (-1 percent of GDP)
(Figure 4.4). Net capital flows to EMDEs became negative at -US$200 billion (-0.8 percent of GDP)
as a result of net other investment outflows (-2 percent of GDP).
Both gross and net flows to EMDEs have declined rapidly in the past two years. Capital
flows to EMDEs dropped sharply in 2014 and 2015, mainly reflecting a fall in portfolio and other
investment. Net other investment reached a record low of -2 percent of GDP in 2015, while net
-6000
-4000
-2000
0
2000
4000
6000
8000
10000
12000
-6000
-4000
-2000
0
2000
4000
6000
8000
10000
12000
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
Advanced Economies: Gross Capital Inflows(USD billion, four-quarter moving sum)
FDI Inflows Portfolio Inflows Other Inflows Total Inflows
-15
-10
-5
0
5
10
15
20
25
30
-15
-10
-5
0
5
10
15
20
25
30
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
Advanced Economies: Gross Capital Inflows(Percent of group GDP, four-quarter moving average)
FDI Inflows Portfolio Inflows Other Inflows Total Inflows
-1000
-500
0
500
1000
1500
2000
-1000
-500
0
500
1000
1500
2000
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
Advanced Economies: Net Capital Inflows (USD billion, four-quarter moving sum)
Net FDI Inflows Net Portfolio Inflows Net Other Inflows Total Net Inflows
-2
-1
0
1
2
3
4
-2
-1
0
1
2
3
4
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
Advanced Economies: Net Capital Inflows(Percent of group GDP, four-quarter moving average)
Net FDI Inflows Net Portfolio Inflows Net Other Inflows Total Net Inflows
9
portfolio investment fell into negative territory for the first time since 2009 (from a peak of
1.5 percent of GDP in 2011).
Capital flows to EMDEs saw significant swings in recent years. Gross and net flows to EMDEs
showed similar patterns, though net flows were somewhat more variable. Net flows rose in 2006-
08 (reaching an all-time high of 5 percent of GDP in 2007), 2009-11, and 2012-13, and fell in
2008-09 (to zero), 2011-12, and 2014-15 (turning negative in 2015). Capital flow swings became
larger and more frequent from 2006, driven mainly by portfolio and other investment flows,
while FDI was relatively more stable. In periods of downturn, other investment flows decreased
the most among all types of flows, followed by portfolio flows.
Figure 4.4 Capital flows to emerging market and developing economies
Sources: IMF Balance of Payments Statistics and IMF staff calculations.
-500
0
500
1000
1500
2000
-500
0
500
1000
1500
2000
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
EMDEs: Gross Capital Inflows (USD billion, four-quarter moving sum)
FDI Inflows Portfolio Inflows Other Inflows Total Inflows
-2
0
2
4
6
8
10
12
-2
0
2
4
6
8
10
12
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
EMDEs: Gross Capital Inflows(Percent of group GDP, four-quarter moving average)
FDI Inflows Portfolio Inflows Other Inflows Total Inflows
-600
-400
-200
0
200
400
600
800
1000
-600
-400
-200
0
200
400
600
800
1000
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
EMDEs: Net Capital Inflows (USD billion, four-quarter moving sum)
Net FDI Inflows Net Portfolio Inflows Net Other Inflows Total Net Inflows
-3
-2
-1
0
1
2
3
4
5
6
-3
-2
-1
0
1
2
3
4
5
6
20
00
Q4
20
01
Q4
20
02
Q4
20
03
Q4
20
04
Q4
20
05
Q4
20
06
Q4
20
07
Q4
20
08
Q4
20
09
Q4
20
10
Q4
20
11
Q4
20
12
Q4
20
13
Q4
20
14
Q4
EMDEs: Net Capital Inflows (Percent of group GDP, four-quarter moving average)
Net FDI Inflows Net Portfolio Inflows Net Other Inflows Total Net Inflows
10
5. HOW HAVE EXTERNAL BALANCE SHEETS CHANGED?
The aggregate international investment position (IIP) for the G20 economies remains
sizeable. The gross IIP for the nineteen individual economies in the G20 represented around 130
percent of GDP in 2014 (Figure 5.1, panel 1). External debt—portfolio debt and other investment
liabilities—for the G20 economies as a whole stood at almost 80 percent of GDP. Net IIP has
continued to decline over the past few years, largely as the net bond portfolio investment
position has deteriorated.
This aggregate picture masks differences across countries. Figure 5.1, panel 2 shows that
there have been significant changes in external debt in a number of G20 economies. Countries
can be placed into three broad groups, based on these changes. In the first group, the
economies with the largest external debt positions—including France, Germany and the United
Kingdom—have reduced their cross-border borrowing significantly over the period 2010-14,
lowering their external vulnerabilities somewhat, though changes in exchange rates are also likely
to have affected the level of external debt. A second group, representing just under half of the
individual G20 economies, have increased external debt by around 5-15 percentage points of
GDP. This follows from the gross inflows of capital, largely to emerging market countries,
discussed above, plus valuation changes. In the third group there has been little change to the
external debt position.
Within the G20 economies, there does not appear to have been much change in the
composition of external debt. Countries with higher external borrowing have tended to
increase both bond and other investment liabilities (Figure 5.1, panel 3). Conversely, the
economies that have reduced external debt the most have done so largely through a decrease in
other investment liabilities, which reflects the deleveraging of the banking systems in these
countries.
In addition to the increase in external debt, there is significant foreign currency borrowing
by some emerging market companies. Figure 5.1, panel 4 shows the proportion of foreign
currency borrowing in total corporate borrowing (domestic and external).6 This foreign currency
borrowing exposes companies to two related, but distinct, risks: (i) an increase in the debt service
burden as a result of a depreciation of local currency exchange rates; and (ii) the risk that lenders
could decline to roll over funding if the borrower’s financial condition deteriorates.
6 IMF, 2015b.
11
Figure 5.1 External positions, corporate indebtedness and bond markets
1. G20 international investment position
Percent of GDP
2. Change in G20 country external debt, 2010-14
Sources: Haver; IMF BoP database; and IMF staff calculations.
Note: Based on USD IIP position and the level of GDP in USD.
Sources: Haver; IMF BoP database; and IMF staff calculations.
Note: Based on USD IIP position and the level of GDP in USD.
3. Change in G20 country bond and other liabilities,
2010-14 Percentage points of GDP
4. Foreign currency nonfinancial corporate debt
Percent of total corporate debt, 2014 Q4
Sources: Haver; IMF BoP database; and IMF staff calculations.
Note: Based on USD IIP position and the level of GDP in USD.
Source: IMF, 2015b.
5. Foreign holdings of emerging market local
currency public debt Billions of US dollars
6. Benchmark investors in emerging market local
currency bond markets, June 2015
Source: Arslanalp and Tsuda, 2015. Source: Arslanalp and Tsuda, 2015.
-40
-20
0
20
40
60
80
100
120
140
10 11 12 13 14 10 11 12 13 14 10 11 12 13 14
DirectEquityBondsOtherReserve assetsNet position
Assets Liabilities Net
USA
AUS
CAN
FRA
DEU
ITA
JPN
GBR
ARG
BRA
CHN
IND
IDN
MEX
KORRUS
ZAFTUR
-40
-30
-20
-10
0
10
20
0 50 100 150 200 250 300External debt 2014 (percent of GDP)
Change in external debt 2010-14 (percentage points of GDP)
-73
,
USA
AUS
CAN
FRADEU
ITA
JPN
GBR
ARG
BRACHN IND
IDN
MEX
KOR
RUS
ZAF
TUR
-25
-20
-15
-10
-5
0
5
10
15
-30 -20 -10 0 10 20Change in bond liabilities
Change in other investment liabilities
-52
0 10 20 30 40 50 60 70
China
India
Thailand
Malaysia
South Africa
Brazil
Philippines
Poland
Russia
Turkey
Chile
Mexico
Indonesia
Hungary
Bonds
Cross-border loans
Domestic loans
0
100
200
300
400
500
0
100
200
300
400
500
2010 2011 2012 2013 2014 2015
Benchmark-driven
UnconstrainedEuro area
debt crisisTaper
tantrum
MEX BRA
POL
TUR
MYSIDNZAF
HUN
RUS
PER
THA
COLROU
0
10
20
30
40
50
60
70
80
90
100
0 200 400 600 800 1000
Sh
are
of
ben
chm
ark
-dri
ven
inve
sto
rs
(as
perc
en
t of
tota
l fo
reig
n h
old
ings)
Total debt outsanding (billion U.S. dollars)
12
Aspects of bond markets also expose emerging market borrowers to risks. There has been a
growing prominence of benchmark-driven investors in local currency government bond
markets.7 These benchmark investors appear to have been more sensitive to shocks, such as the
“taper tantrum” than other (unconstrained) investors (Figure 5.1, panel 5). Furthermore, smaller
bond markets tend to have a greater share of benchmark investors than the more established
markets (Figure 5.1, panel 6). This suggests that these bond markets could be particularly
susceptible to the affects of financial shocks.
6. DATA GAPS
Robust and timely data on capital flows and external balance sheets are essential for
effective surveillance, as the global financial crisis demonstrated. While progress has been
made on data availability, data could still be further improved across three key dimensions.8
First, the timeliness of data on capital flows could be improved. Balance of payments data
are typically produced quarterly, with a lag, though there are some countries that compile
external accounts on a monthly basis. The crisis underlined the importance of more timely
(shorter reporting lag) and higher frequency economic and financial indicators (e.g., on leverage).
Second, the nature of statistics could be more useful for the assessment of risks. Data on
bilateral cross-border flows and financial positions could be improved. For example, it would be
helpful to track the direction of flows, including the extent to which recent capital flows to
advanced economies originated from other advanced economies versus emerging market
economies (and similarly for capital flows to emerging market economies). While bilateral data
are collected, for example in the CDIS, CPIS and BIS international banking statistics (see Annex),
there could be a broader participation across countries, and participants should be encouraged
to provide the full data breakdown (e.g., by sector, instruments, and currency of denomination).
Collecting additional information on foreign direct investment by sector, and on other
investment flows (e.g., bank flows and trade credit) would also be useful.
Third, the scope of the data could be broadened.9 More detailed information on balance
sheets would help assess vulnerabilities. For example, more comprehensive data on assets and
liabilities by sector, on foreign currency exposures, and on the remaining maturity of debt would
help enhance surveillance efforts. Furthermore, information on off-balance sheet data, such as
contingent assets and liabilities, guarantees and lines of credit, and hedging using financial
derivatives would help produce a more encompassing risk assessment. Better information on
7 Arslanalp and Tsuda, 2015.
8 IMF, 2014 and IMF, 2015a.
9 Information could be provided voluntarily without disclosing confidential business details of individuals or corporations.
13
holders of ultimate investment risk, particularly in financial centers where asset managers may be
working on behalf of investors in other countries, would also help to understand where risks
actually lie.
7. CONCLUSION
Capital flows are driven by a combination of pull and push factors. One key push factor is global
liquidity, which can be operationally defined as the ease of global financing. Indicators of global
liquidity can be used to highlight four key phases over the past decade: boom, bust, aftermath,
and aftershock. In recent years, gross global capital flows have picked up, with increases in flows
to advanced economies offsetting declines to emerging market economies. Past sizable capital
flows have been associated with an increase in external debt, particularly in G20 emerging
market economies. This has heightened risks, for example for corporates borrowing in foreign
currency and for bond markets that rely more on benchmark investors. In the past year, global
capital flows have weakened, especially in emerging market economies, reflecting a drop in
portfolio and other investment flows. Finally, continued efforts to close important data gaps,
including through the G-20 Data Gaps Initiative, would significantly improve the surveillance of
external vulnerabilities.10
References
Arslanalp and Tsuda, 2015, Emerging market portfolio flows: the role of benchmark-driven investors, IMF Working
Paper, WP/15/263.
Ghosh, Ostry, and Qureshi, 2016, When do inflow surges end in tears?, American Economic Review (paper
presented at the American Economic Association Annual Meeting, San Francisco, January).
IMF, 2012, The liberalization and management of capital flows: an institutional view,
http://www.imf.org/external/np/pp/eng/2012/111412.pdf.
IMF, 2014, Global liquidity: issues for surveillance, http://www.imf.org/external/np/pp/eng/2014/031114.pdf.
IMF, 2015a, Balance sheet analysis in Fund surveillance, http://www.imf.org/external/np/pp/eng/2015/061215.pdf.
IMF, 2015b, Global Financial Stability Report, Chapter 1: Three scenarios for financial stability, October,
http://www.imf.org/external/pubs/ft/gfsr/index.htm.
Ostry, Ghosh, Chamon, and Qureshi, 2012, Tools for managing financial stability risks from capital inflows, Journal
of International Economics, 88(2), pp. 407-421.
10 For background on the G-20 Data Gaps Initiative, see http://www.imf.org/external/ns/cs.aspx?id=290, http://www.imf.org/external/np/seminars/eng/2015/dgi/, and
http://www.imf.org/external/np/g20/pdf/2015/6thprogressrep.pdf.
14
Annex: Capital Flow Data Sources and Gaps
IMF Balance of Payments (BOP) and International Investment Position (IIP). The database
provides quarterly information on the stock (and the change in the stock) of assets and liabilities
vis-à-vis nonresidents. The data are classified by functional category (direct investment, portfolio
investment, financial derivatives, other investment, and reserve assets). Portfolio investment is
further split into equity and debt securities. Other investment is categorized into other equity;
currency and deposits; loans; insurance, pension, and standardized guarantee schemes; trade
credits and advances; other accounts receivable/payable; and special drawing rights. Portfolio
investment, financial derivatives and other investment are also broken down by sector (central
bank; monetary authorities; general government; deposit-taking corporations; other financial
corporations; and nonfinancial corporations, households, and nonprofit institutions serving
households). In addition, portfolio and other investment are broken down by original maturity
(short-term and long-term).
IMF Financial Flows Analytics (FFA). The data draw on the BOP database and provides cross-
country comparable quarterly time series on international capital flows since 1970, with the
breakdown provided by the BOP statistics (described above). Net capital flows are shown as net
inflows, defined as gross inflows (change in domestic resident liabilities to foreigners) minus
gross outflows (change in foreign assets owned by domestic residents).
Data gaps:11
The full data breakdown is not available for all countries.
The full breakdown of the BOP database is not available in the FFA database.
The direction of flows between individual countries or groups of countries is not fully
identifiable, e.g., capital flows to advanced economies from other advanced
economies versus from emerging market and developing economies (and similarly
for capital flows to emerging market and developing economies).
Direct investment data are not broken down by geographical location or sector.
Portfolio investment asset and liability data are not broken down by the geographical
location of debtors/creditors.
Data on currency composition of capital flows are not available.
Greater breakdown by maturity beyond short and long term is not available.
11
Second phase of the G-20 Data Gaps Initiative (DGI-2) recommends: G-20 economies to provide quarterly IIP data to the IMF,
consistent with the Balance of Payments and International Investment Position Manual, sixth edition (BPM6), and including the
enhancements such as the currency composition and separate identification of other (non-bank) financial corporations, introduced
in that Manual. IMF to monitor reporting and the consistency of IIP data, and consider separate identification of nonfinancial
corporations, in collaboration with IMF Committee on Balance of Payments Statistics (BOPCOM).
15
IMF Coordinated Direct Investment Survey (CDIS). The survey data provide information on
inward and outward direct investment positions reported by about 100 participating countries.
The data are of annual frequency from 2009. It is broken down by: (i) economy of residency of
the immediate investor/recipient; and (ii) instrument used to finance the direct investment (net
equity and net debt). There are additional breakdowns for net debt with resident financial
intermediaries and with resident enterprises; gross debt assets and liabilities; and equity or debt
with fellow enterprises abroad. Direct investment positions are presented as reported by
countries and as derived from the reports of counterparty countries. There is no breakdown
requested by sector of the investor (public or private sector, financial sector, manufacturing or
services), or by sector in the recipient country.
Data gaps:12
The data are not available for all countries.
Some countries do not report all the breakdowns (e.g., some countries report inward
direct investment only, omitting the outward component).
IMF Coordinated Portfolio Investment Survey (CPIS). It provides information on portfolio
investment holdings reported by about 80 participating countries. The data are of annual
frequency from 2001 to 2012, and semi-annual frequency since 2013. It is broken down by:
(i) instrument (equity and investment shares, short-term debt securities, and long-term debt
securities); (ii) residency of the nonresident issuer of the securities; (iii) sector of the holder
(central bank; deposit-taking corporations; insurance corporations and pension funds; money
market funds; other financial corporations; general government; nonfinancial corporations,
households, and nonprofit institutions serving households); and (iv) currency of denomination of
the securities held. Not all countries report data on portfolio investment liabilities. Portfolio
investment liabilities are presented as reported by participating countries (where available) and
as derived from creditor data.
Data gaps:13
The data are not available for all countries.
Some countries do not report all the breakdowns.
12 DGI-2 recommends: G-20 economies to participate in and improve their reporting of the IMF Coordinated Direct Investment
Survey, both inward and outward direct investment. IMF to monitor the progress.
13 DGI-2 recommends: G-20 economies to provide, on a semi-annual frequency, data for the IMF CPIS, including the sector of
holder table and, preferably, also the sector of nonresident issuer table. IMF to monitor the regular reporting and consistency of
data, to continue to improve the coverage of significant financial centers, and to investigate the possibility of quarterly reporting.
16
BIS International Banking Statistics (IBS). The database provides two sets of statistics on
international banking activity: locational and consolidated banking statistics.14
The data are of
quarterly frequency since December 1977. It captures outstanding cross-border claims and
liabilities of banks located in BIS-reporting countries. Locational banking statistics include intra-
group positions between offices of the same banking group, while the consolidated statistics
include the claims of banks’ foreign affiliates but exclude intra-group positions. The data are
broken down by: (i) residence of counterparties; (ii) currency denomination of claims and
liabilities; (iii) sector of counterparties (banks, nonbank financial sector, and nonbank nonfinancial
sector); and (iv) instrument (loans, short-term debt securities, long-term debt securities, and
other instruments). The data are presented both by residence of banks (regardless of the
nationality of the controlling parent) as well as by nationality of banks (regardless of the
residency of the banking offices).
Data gaps:15
The data are not available for all countries.
BIS International Debt Securities Statistics (IDSS). The database provides information on debt
securities issued in a market other than the local market of the country where the borrower
resides. The data are of quarterly frequency since December 1962. It is broken down by
(i) residence of issuer; (ii) sector of issuer (financial corporations, nonfinancial corporations, and
general government); (iii) interest rate type (fixed rate, floating rate, inflation-linked, and
exchange rate-linked); (iv) currency of denomination; and (v) maturity (short-term and long-
term). The data are presented by residence of issuers (regardless of its nationality) as well as by
nationality (regardless of its residency).
Data gaps:16
The full data breakdown is not available for all countries.
14
FSB Global Shadow Banking Monitor tracks developments in the shadow banking system, covering 26 jurisdictions and the
euro area as a whole, representing about 80 percent of global GDP and 90 percent of global financial system assets.
15 DGI-2 recommends: G-20 economies to provide enhanced BIS international banking statistics. BIS to work with all reporting
countries to close gaps in the reporting of IBS, to review options for improving the consistency between the consolidated IBS and
supervisory data, and to support efforts to make data more widely available.
16 DGI-2 recommends: G-20 economies to provide on a quarterly frequency debt securities issuance data to the BIS consistent with
the Handbook on Security Statistics (HSS) starting with sector, currency, type of interest rate, original maturity and, if feasible,
market of issuance. Reporting of holdings of debt securities and the sectoral from-whom- to-whom data prescribed for SDDS Plus
adherent economies would be a longer term objective. BIS, with the assistance of the Working Group on Securities Databases, to
monitor regular collection and consistency of debt securities data.
17
IIF Portfolio Flows Tracker.17
The database provides a monthly estimate of total nonresident
portfolio equity and debt flows for 30 emerging market countries. The estimates are based on
country-level portfolio flows data from 14 emerging market countries that make available high-
frequency data on nonresident purchases of domestic stocks and bonds, and regression analysis
based on a number of predictor variables. Total emerging market flows are estimated based on
the historical relationship between flows to these 14 countries and flows to the full group of 30
countries under consideration.
Data gaps:
The estimates are available only for 30 emerging market countries.
The tracker estimates nonresident portfolio flows and does not consider resident net
flows. Hence, it is an estimate of gross portfolio flows, not net portfolio flows.
EPFR Fund Flows Data.18
The data measure flows in and out of mutual funds and exchange-
traded funds (ETFs). It is based on direct reporting from the global mutual fund industry. EPFR
fund flows are not necessarily transactions between residents and nonresidents of a country.
Hence, they are not necessarily capital flows from a balance of payments perspective. They can
be transactions among two nonresidents of the country of residence of the issuer of the security.
Data gaps:
EPFR data cover transactions by the global mutual fund industry which includes very
few hedge funds or sovereign wealth funds. It also does not capture the activity of
investors who buy and sell emerging market assets directly, without going through a
fund. Hence, it tends to underestimate portfolio flows.
17
IIF Portfolio Flows Tracker FAQ, August 28, 2014 (https://www.iif.com/publication/portfolio-flows-tracker/portfolio-flows-
tracker-faq).
18 Ibid. There are also other private data sources for global investment funds, including for example Morningstar.