This slide highlights the main findings of the working paper Capital Flow Deflection Under the Magnifying Glass. In a financially interconnected world, individual countries’ policy choices affect other economies and can become a source of international shocks. Leveraging on a new quarterly dataset of capital control adjustments, we find renewed evidence that the introduction of capital controls in one economy increases capital inflows to other similar borrowing economies. Please visit here to read the paper https://doi.org/10.1787/398180d0-en For more information on OECD Capital Flows, please visit http://www.oecd.org/investment/codes.htm

1. CAPITAL FLOW DEFLECTION
UNDER THE MAGNIFYING GLASS
Etienne Lepers (OECD)
Joint with Filippo Gori (OECD) & Caroline Mehigan (Central
Bank of Ireland)
CEBRA Annual Conference
2nd September 2020
Views in the presentation are those of the authors and should not be attributed
to the OECD or the Central Bank of Ireland

2. MOTIVATION
2

3. 3
A financially interconnected world
Ex: Cross-border portfolio debt positions
Source: Finflows database as of September 2019 (described in
Nardo et al 2017)
Note: Stock data in 2017. Only bilateral exposures above 4 trillion
EUR are represented to limit the number of links represented.
The direction of the relationship is to be read clockwise going from
the source to the recipient countries.
2005
2017

4. 4
(Policy) spillovers in an integrated world
• In a financially integrated world, domestic economic
policies in one country may be source of international
spillovers through financial or trade channels
• Large literature on spillovers of US or EU monetary pol.
• Emerging literature on spillovers of macropru
 This paper focuses on capital flow spillovers from the
introduction (or tightening) of capital controls

5. 0
5
10
15
20
25
30
1999q2 2000q3 2001q4 2003q1 2004q2 2005q3 2006q4 2008q1 2009q2 2010q3 2011q4 2013q1 2014q2 2015q3 2016q4
5
A rising number of countries tightened
capital account policy since the 2008 crisis
Note: The figures shows the quarterly tightening of capital flow measures in a set of 62 advanced and emerging market economies for the period 2000-2017.
Source: Lepers and Mehigan (2019)
Number of tightening in
capital account policy
Global financial crisis

6. 6
Capital controls and deflection:
Examples
Examples of capital controls tightening (on inflows) in the dataset:
• Brazil: Tax on FX inflows (IOF) (2009/2010)
• Iceland: Special reserve requirements on debt inflows (2016)
• Peru: Reserve requirements on banks’ non-resident liabilities (2006)
• Turkey: Prohibition for residents to obtain FX credit from abroad (2009)
• Australia: Stamp duty for foreign buyers of real estate (2015/2017)

7. CAPITAL FLOW
DEFLECTION
7

8. • Forbes et al., (2016), Lambert, et. al.
(2011)
• Giordani, et. al. (2017), Ghosh, et. al.
(2014), Cerutti et. al (2018)
• Pasricha, et. al. (2018)
Country specific study on Brazil IOF
Annual data, aggregate capital account
openness index
Aggregate quarterly data, aggregate
capital control adjustments
Capital account policy spillovers:
the literature & gaps
This paper, leveraging on a new quarterly granular dataset of capital
control adjustments and a new bilateral capital flow dataset (FDI,
eq., debt, loans):
1. Tests whether all capital flows are deflected alike, and due to which
type of controls
2. Controls for the investing country and tests whether EMEs and AEs
investors react differently
3. Tests for a capital control “domino effect” and whether investors
anticipate it

9. New capital control database
Fernandez
et al (2015):
Us:
1 if operation
is restricted
0 otherwise
(free)
+1 if restriction
is introduced
+1 if restriction
is tightened
-1 if restriction
is removed
-1 if restriction
is eased
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
-160
-140
-120
-100
-80
-60
-40
-20
0
20
CFM_L CFM_T
CFM cumulative Capital account openness (RHS)
Example of India:
Capital Control data: Lepers & Mehigan
(2019) - 2300 adjustments, 51 econ, 2000-17

10. 10
Baseline model
𝑦𝑖,𝑡 = 𝜑 𝑦𝑖,𝑡−1 + 𝛽 𝐶𝐹𝑀 𝑱
𝒊,𝒕−𝟏 + 𝛿 𝐶𝐹𝑀𝑖,𝑡−1 + 𝛾 𝛺𝑖,𝜏
′
+ 𝛼𝑖 +
𝜀𝑖,𝑡
• 𝑦𝑖,𝑡: gross capital flows % of GDP
• 𝛺𝑖,𝜏
′
: Controls: inflation, GDP growth, domestic interest rate (all lagged)
+ VIX
• 𝛼𝑖: country FE
• Focus on major EMEs (13): Brazil, Chile, China, Colombia, Hungary,
India, Indonesia, Mexico, Poland, Russia, South Africa, Thailand and
Turkey
• Model run from 2000Q1-2017Q4
Spillover Variable:
Impact of capital controls in similar
countries on capital inflow

11. 11
The spillover variable
How to define similar countries? Region, Risk, Return …
• In this paper we define similarity on the basis of correlation of
capital inflows
• That is to say, countries are similar if international investors tend to
direct investment to both countries at the same time
• The spillover variable is the
weighted average of CFMs
where weights represent the
correlation between flows to
the domestic economy and flows
to the partner (8q RW)
International
Investors
A
B
Capital flows
to A and B
are correlated

12. 12
Pairwise correlations of inflows
matrix
Note: This matrix represents the pairwise correlations of capital inflows from 2004-2014.

13. (1) (2) (3) (4) (5) (6)
Capital Inflow Capital Inflow Capital Inflow Capital Inflow Capital Inflow Capital Inflow
Firstlag 0.137*** 0.137*** 0.131*** 0.130*** 0.130*** 0.125***
(0.031) (0.029) (0.028) (0.026) (0.025) (0.023)
Vix -0.632*** -0.695*** -0.724*** -0.733*** -0.731*** -0.871***
(0.166) (0.159) (0.169) (0.160) (0.171) (0.175)
Inflation (t-1) -0.548 -0.609 -0.568 -0.587 -0.587 -0.701
(0.493) (0.481) (0.490) (0.502) (0.535) (0.533)
Growth (t-1) 0.055** 0.060** 0.059** 0.058** 0.057** 0.060***
(0.021) (0.022) (0.021) (0.020) (0.019) (0.020)
Interestrate (t-1) -0.021** -0.018* -0.019** -0.020** -0.021** -0.017**
(0.009) (0.009) (0.008) (0.008) (0.008) (0.008)
CFM (t-1) 0.010 -0.001 -0.001 -0.002 0.015 -0.008
(0.018) (0.016) (0.016) (0.017) (0.019) (0.016)
CFM spillover (t-1) 0.146** 0.134*
(0.064) (0.062)
CFM spillover (t-2) 0.102* 0.064*
(0.048) (0.032)
CFM spillover (t-3) 0.090** 0.040*
(0.032) (0.021)
CFM spillover (t-4) 0.093 0.078
(0.069) (0.065)
Country set EME EME EME EME EME EME
Number ofcountries 13 13 13 13 13 13
Observations 927 927 916 905 894 894
13
Baseline
 Capital is deflected to
similar borrowing
economies following
intro/tight. inflow
controls
 Persistence of the
effect over a year time

14. 14
The role of portfolio and other
investment
(1) (2) (3) (4) (5) (6) (7) (8)
Capital Inflow Capital Inflow Capital Inflow Capital Inflow FDI Inflow Portfolio equity Inflow Portfolio debtInflow Other Inflows
Inflow CFM spillover (FDI) (t-1) 1.432 0.657
(0.949) (0.716)
Inflow CFM spillover (Portfolio equity) (t-1) 0.633*** 0.073**
(0.201) (0.033)
Inflow CFM spillover (Portfolio debt) (t-1) 0.179** 0.061+
(0.064) (0.035)
Inflow CFM spillover (Credit) (t-1) 0.395** 0.191***
(0.139) (0.048)
Type ofcontrols Type ofcontrols & flows
Only portfolio and
other investment
(bank) is deflected

15. 15
Volatility spillovers
• So far focus on capital flow (volume)
spillovers, but does a tightening of CFM affect
the volatility of capital flows to similar
countries?
• Same equation using the 4Q SD of capital
inflows as the dependent variable
 We find similar positive and significant
results:
 Volatility of capital flows increases in
similar countries after a tightening of
controls in one country
(1) (2)
Standard
Deviation of
Capital Inflow
Standard
Deviation of
Capital Inflow
First lag (t-4) 0.387***
(0.090)
Vix 0.015 0.070
(0.071) (0.046)
Inflation (t-1) 1.429*** 0.766**
(0.389) (0.276)
Growth (t-1) 0.023 0.034
(0.025) (0.020)
Interest rate (t-1) 0.008 0.001
(0.006) (0.004)
Inflow CFM (t-1) -0.016 -0.007
(0.019) (0.010)
Inflow CFM spillover (t-1) 0.050*** 0.022*
(0.015) (0.012)
Country set EME EME
Countries 13 13
Observations 883 848

16. 16
Robustness
Broadly robust to:
o Other global controls (global GDP growth, global liquidity, 10y
bond yield)
o Year FE
o Risk return weighted spillover variable
o Asset/Liab or GDP weighted spillover variable
o Fixed time inflow correlation weighted spillover variable

17. A BILATERAL
PERSPECTIVE
17

18. 18
A bilateral model
Where is the deflected capital coming from?
 Different countries are involved to varying degrees in different asset
classes
 Global financial system has significantly evolved over the past decades,
with notably a much stronger footprint of EMEs
𝑌𝑧𝑖,𝑇 = 𝐶𝐹𝑀 𝑖𝑛 𝑐 𝑠𝑖𝑚𝑖𝑙𝑎𝑟 𝑡𝑜 𝑖 + 𝐶𝐹𝑀_𝑖𝑛𝑓𝑖 + 𝐶𝐹𝑀_𝑜𝑢𝑡 𝑧 + 𝑐𝑜𝑛𝑡𝑟𝑜𝑙𝑠 + 𝛿 𝑧𝑖 + 𝑒 𝑧𝑖,𝑇
Bilateral flow from
country j to country i
(log)
Spillover
variable (L)
Controls
in and out (L)
Country pair FE
Using the new bilateral capital flow dataset from EC JRC Finflows
(Nardo et al. 2017)

19. Destination country sample:
Source country sample:
Bank flows Portfolio flows Bank flows Portfolio flows
Credit Inflow CFM spillover (t-1) 0.334** 0.205
(0.156) (0.144)
Portfolio Inflow CFM spillover (t-1) -0.092 0.181**
(0.069) (0.054)
Observations 1954 1784 1610 1568
EMEs
EMEs Advanced Economies
Destination country sample:
Source country sample:
Bank flows Portfolio flows Bank flows Portfolio flows
Inflow CFM spillover (t-1) 0.110** -0.031 0.111** 0.120**
(0.040) (0.044) (0.032) (0.033)
Observations 1954 1784 1610 1568
EMEs
EMEs Advanced Economies
19
AE and EME investors shift different
type of investments
AE’s investors
redirects portfolio and
other/bank flows
EME (banks) redirect
other flows

20. 20
The growing importance of
EME-EME banking
2005
2017
Source: Finflows database as of
September 2019 (described in Nardo
et al 2017)
Examples:
• Bank of China (CN): 36
countries, 24% of assets abroad
• Itau (BR): largest bank in Latam
• Sberbank (RU) in CIS and TK
= 42% of banking flows to EMEs in 2017
vs. 1% of equity flows & 8% of debt flows

21. RESPONSES TO
SPILLOVERS
21

22. 22
Policy reaction to spillovers
• Do countries receiving spillovers respond by tightening in turn their
capital account policy to stem inflows? (Y - Pasricha et al., 2018, N –
Giordani 2017)
𝑪𝑭𝑴 𝒕𝒊𝒈𝒉𝒕𝒆𝒏𝒊𝒏𝒈 = 𝛽 (𝑪𝑭𝑴 𝒊𝒏 𝒔𝒊𝒎𝒊𝒍𝒂𝒓 𝒄𝒐𝒖𝒏𝒕𝒓𝒊𝒆𝒔) + 𝛺′(𝑐𝑜𝑛𝑡𝑟𝑜𝑙𝑠)
• Probit model (1) (2) (3) (4)
Pr(CFM inf.
in t or t+1)
Pr(CFM inf. equity
in t or t+1)
Pr(CFM inf. bond in t
or t+1)
Pr(CFM inf. credit
in t or t+1)
Inflow CFM spillover (t-1) 0.048* 0.050 0.082** 0.060**
(0.028) (0.046) (0.029) (0.028)
Vix 0.098 0.242 -0.010 0.048
(0.165) (0.243) (0.191) (0.219)
Capital inflows (t-1) -0.019 0.015 -0.007 -0.013
(0.015) (0.009) (0.013) (0.014)
Interest rate (t-1) 0.007 -0.004 0.000 0.010*
(0.005) (0.007) (0.005) (0.005)
Growth (t-1) 0.003 0.035 -0.001 -0.003
(0.019) (0.028) (0.022) (0.022)
Country Set EME EME EME EME
Countries 13 13 13 13
Observations 914 914 914 914
 Countries tend to react to capital controls in similar borrowing
economies by tightening their capital account in turn

23. (1) 𝑐𝑎𝑝𝑖𝑡𝑎𝑙 𝑖𝑛𝑓. = 𝛽 CFM 𝑆𝑝𝑖𝑙𝑙𝑜𝑣𝑒𝑟 + 𝜃 𝑃𝑟 𝐶𝐹𝑀 𝑡𝑖𝑔ℎ𝑒𝑛𝑖𝑛𝑔 + 𝛺′ 𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠
Where 𝑃𝑟(𝐶𝐹𝑀 𝑡𝑖𝑔ℎ𝑒𝑛𝑖𝑛𝑔) is treated endogenously and estimated with
a treatment equation:
(2) 𝑃𝑟𝑜𝑏(𝐶𝐹𝑀 𝑡𝑖𝑔ℎ𝑡𝑒𝑛𝑖𝑛𝑔) = 𝑏 𝑆𝑝𝑖𝑙𝑙𝑜𝑣𝑒𝑟 + 𝛤′𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠
23
Do international investors incorporate this expectation when redirecting flows?
 Endogenous treatment model to decompose capital flow deflection
into:
1. a direct spillover effect (portfolio recomposition)
2. an effect originating from the expectation of a tightening in the
domestic economy
Do international investors react
too?
Direct
deflection effect
Effect due to expected CFM
tightening

24. Full MLE First Step
(1) (2)
Capital Inflow Pr (Inflow CFM (t, t+1))
Capital inflows (t-1) 0.160* -0.020
(0.087) (0.020)
Vix -0.883*** 0.008
(0.299) (0.161)
Inflation (t-1) -0.711***
(0.182)
Growth (t-1) 0.051 0.031
(0.035) (0.020)
Interest rate (t-1) -0.029*** 0.008*
(0.011) (0.004)
Inflow CFM (t-1) -0.005
(0.018)
Inflow CFM in previous year (t, t-3) 0.287***
(0.107)
Inflow CFM spillover (t-1) 0.106*** 0.040*
(0.040) (0.024)
[Probability of] CFM 4.608***
(1.340)
Country set EME EME
Countries 13 13
Observations 914 914
24
Direct
deflection effect
Effect due to
expected CFM
tightening
Do international investors react
too? (cont.)
International investors
frontload their
investment to the
spillover-receiving
country, expecting a
CFM tightening

25. CONCLUSIONS AND POLICY
IMPLICATIONS
25

26. 26
Summary of key results
Capital flow deflection
Policymakers and investors’ response to CFMs
Capital flows are deflected by inflow CFMs to similar economies:
 Differs by flow type: Only portfolio and other investment
 Differs by investor origin: EME banks redirect flows, AE investors
redirect portfolio and other investment
• Policy Reaction: Countries targeted by deflected capital tend to
respond by introducing CFMs
• Market Reaction: International investors respond to this expectation
frontloading (increasing) their inflows in new destination countries

27. 27
Policy implications:
A role for international cooperation?
 International cooperation on capital account policy
may be necessary to curb the possible realisation of
particularly negative end games and result in better
global outcomes
(Jeanne 2014, Pereira and Chui 2017, Blanchard 2017, Rajan and Mishra 2018)
 Value of multilateral framework for capital flow
management and dialogue platforms like the OECD
Capital Movements Code

28. THANK YOU!
etienne.lepers@oecd.org
https://www.oecd-ilibrary.org/economics/capital-flow-deflection-
under-the-magnifying-glass_398180d0-en
28