This slide highlights the main findings of the working paper Assessing the effectiveness of currency-differentiated tools: The case of reserve requirements This paper provides the first comprehensive analysis of benefits and side-effects of foreign-currency differentiated reserve requirements for a sample of 58 countries from 1999 to 2015. Departing from the existing literature on effectiveness which used binary variables to measure policy changes, the intensity of reserve requirement adjustments is captured by using the gap between foreign and local currency rates to isolate the impact of differentiation net of volume effects. Find out more at: https://doi.org/10.1787/e979a657-en

1. ASSESSING THE EFFECTIVENESS OF
CURRENCY-DIFFERENTIATED TOOLS:
THE CASE OF RESERVE REQUIREMENTS
A. De Crescenzio, E.Lepers (OECD), Z.Fannon (Oxford
University)
Disclaimer: The views in the presentation are those of the authors. No responsibility for them
should be attributed to the OECD or its Member countries.

2. Outline
I. Background on reserve requirements (RRs) and
currency-based measures (CBMs)
II. Conceptual framework and empirical model
III. Results and extensions
IV. Policy discussion and conclusions

3. 3
BACKGROUND ON RRs
AND
CURRENCY BASED MEASURES

4. Currency-based measures (CBMs) as
common policy tools post-2008
• Often used with a
prudential aim to limit risks
from currency exposures
• Booming post financial
crisis (De Crescenzio, Golin,
Ott 2015, Ahnert et al 2020)
• Over 90% of CBMs
implemented by EMEs
• >40% of CBMs target bank
liabilities
Source: Ahnert et al (2020)
DEFINITION
“Regulations that discriminate based on the currency denomination of capital
transactions”

5. CBMs: Macroprudential or capital flow
management tools?
CFMs
CBMs
MPMs
• Most often introduced with a prudential aim
But:
• Affect capital flows insofar as typically most cross-border
transactions are denominated in FX
Traditional
MPMs like
LCRs, LTVs
Discrimination
vs. non-
residents
FX reserve requirements,
FX derivatives limits,
levies on FX liabilities

6. FX Reserve Requirements: a particularly
frequent type of CBM
• RRs: Part of the monetary toolkit for a long time,
as a complement not substitute
• Increased use for financial stability purposes:
 First micro-prudential objectives
 Then with a macro-prudential objective to
dampen credit cycles when used counter-
cyclically
• FX- RR: Used against dollarisation, to reduce
currency risk in bank balance sheets.

7. FX-differentiated reserve requirements
have been widely used in Latin America..
0%
10%
20%
30%
40%
50%
60%
1999q1 2002q1 2005q1 2008q1 2011q1 2014q1
Brazil Colombia Peru Argentina
Chile Mexico Peru_FX Argent_FX
• Peru and Argentina: FX reserve requirements at times raised above 50%
and 40%, respectively
• Brazil and Colombia: adjustments of undifferentiated reserve requirements
• Chile: flat undifferentiated reserve requirement below 10%

8. …and in Emerging Europe..
• Turkey, Russia and Romania have used differentiated reserve
requirements, with Romania raising it above 30% in the periods preceding
and following the 2008 crisis
0%
10%
20%
30%
40%
50%
60%
1999q1 2002q1 2005q1 2008q1 2011q1 2014q1
Turkey Romania Russia Bulgaria
Turkey_FX Romania_FX Russia_FX

9. …while Asian economies use
undifferentiated reserve requirements
• Asian economies employ undifferentiated reserve requirements, with China
and the Philippines using them in the range of 20%, and other economies in
the region below 10%.
0%
10%
20%
30%
40%
50%
60%
1999q1 2002q1 2005q1 2008q1 2011q1 2014q1
India Indonesia Malaysia
Philippines Thailand China

10. 10
CONCEPTUAL FRAMEWORK &
EMPIRICAL MODEL

11. Related empirical work (1/2)
• Work on reserve requirements:
– Federico, Vegh, Vuletin (2014): developing countries used
RR countercyclically with monetary policy being procyclical
– Montoro and Moreno (2011): RR work like interest rates
but without attracting capital inflows
– Brei and Moreno (2018): ↑ RR associated with higher loan
rates while deposit rates remain unchanged
– Glocker and Towbin (2012): ↑RR lead to lower domestic
credit, exchange rate depreciation, price increase
– Camors et al (2019): ↑ RR lead to lower credit to non-
financial corporations (NFCs), but higher exposure to
riskier firms and circumvention by large banks

12. Related empirical work (2/2)
• Work on currency-based measures:
– De Crescenzio et al (2017): CBMs lead to reduction in
external debt of banks, esp. short term and interbank
– Lepers and Mehigan (2019): CBMs reduce both capital
inflows and domestic credit growth, esp. FX RRs and
FX lending regulations
– Ahnert et al (2020): CBMs reduce FX exposure and
sensitivity of banks to exchange rate, but shift the FX
vulnerability to other sectors
– Frost, Ito, Van Stralen (2020): CBMs reduce capital
inflows and likelihood of surges, while capital controls
do not.

13. Objectives of the paper and contributions
Issues with existing literature:
• Aggregation of very different policy tools
• Binary tightening/easing variables
• Focus on one or two core outcome variables
Contributions of the paper:
1. Cross-country analysis of the effectiveness of FX
RRs
2. Detailed assessment of direct and indirect effects
to identify transmission channels
3. Direct capture of the intensity of the policy,
economic magnitude for the effects

14. International
bond holders
International
banks
NFCs/ Households
Domestic
Banks
L L
A A
Domestic
currency
Foreign
currency
RR_FX
RR
Non-Banks
Deposit
dollarisation
Loan
dollarisation
Conceptual
Framework

15. Limitations of measuring macroprudential
effectiveness with binary indicators
• Binary variables (indices with +1/-1) not able to capture
the intensity of measures
• With such indices a tightening of an LTV cap from 90 to
60% would be coded exactly the same as a tightening from
90 to 6%
• Data on RR rates allows getting much closer to intensity
• Unlike other tools, FX RR designs are broadly
comparable across countries
• We look at the FX RR gap (Reserve ratio on FX
liabilities – Reserve ratio on LC liabilities) to capture
the impact of currency differentiation net of
volume effects

16. Model
𝑌𝑌𝑖𝑖𝑖𝑖
= 𝛼𝛼 + �
𝑘𝑘=0
3
𝛽𝛽1,𝑘𝑘 Δ𝑅𝑅𝑅𝑅𝑖𝑖,𝑡𝑡−𝑘𝑘
𝐹𝐹
− Δ𝑅𝑅𝑅𝑅𝑖𝑖,𝑡𝑡−𝑘𝑘
𝐿𝐿
+ �
𝑘𝑘=0
3
𝛽𝛽2,𝑘𝑘Δaverage𝑅𝑅𝑅𝑅𝑖𝑖,𝑡𝑡−𝑘𝑘 + �
𝑘𝑘=0
3
𝛾𝛾𝐿𝐿,𝑘𝑘(𝑅𝑅𝑅𝑅𝑅𝑅, 𝐶𝐶𝐶𝐶𝐶𝐶, 𝑀𝑀𝑀𝑀𝑀𝑀)𝑖𝑖,𝑡𝑡−𝑘𝑘
+ Γ𝑋𝑋𝑖𝑖,𝑡𝑡−1 + 𝛿𝛿𝑖𝑖 + 𝛿𝛿𝑇𝑇 + 𝑒𝑒𝑖𝑖𝑖𝑖
𝑌𝑌𝑖𝑖𝑖𝑖: outcome variable:
• Direct effect: Flows to banks, Δ FX loan share, Δ FX liability share, Δ net FX position
• Indirect effect: Itl NFC debt growth, Flows to non-banks, capital flows (eq, debt,
other), ER deviation from trends.
Δ𝑅𝑅𝑅𝑅𝑖𝑖,𝑡𝑡−𝑘𝑘
𝐹𝐹
− Δ𝑅𝑅𝑅𝑅𝑖𝑖,𝑡𝑡−𝑘𝑘
𝐿𝐿
: “RR Gap”: Change in the diff. between RR_FX and RR_LC
 Variable of interest, “composition” effect
Δaverage𝑅𝑅𝑅𝑅𝑖𝑖,𝑡𝑡−𝑘𝑘: Change in the average RR
 Controlling for the “volume” effect
• Effect over a year time (t to t-3)
• Controlling for : changes in other financial policies (𝑅𝑅𝑅𝑅𝑅𝑅, 𝐶𝐶𝐶𝐶𝐶𝐶, 𝑀𝑀𝑀𝑀𝑀𝑀), GDP
growth, ER growth, interest rate (level or diff), sovereign ratings
• Time and Country FE: 𝛿𝛿𝑖𝑖 + 𝛿𝛿𝑇𝑇

17. 17
RESULTS

18. Inflows
to banks
∆ FX
loans
share
∆ FX liab
share
∆ Net FX
position
Gap (∆RR_F-∆RR_L) (t,t-4) -0.10 -0.23 -0.111* -1.62***
N 2,773 891 1,029 797
Countries 49 25 29 35
Direct effect
A 1% increase in the
FX RR gap leads to:
- 0.1% reduction in
the FX liability
share
- 1.6% reduction in
the net FX
position
Over 1 year
Negative but insignificant effect on
cross-border flows to banks and FX liab
share

19. NFC debt
growth
Inflows
to non-
banks
Equity
Inflows
Debt
Inflows
Other
Inflows
Exchange
rate
Deviation
3Y
Exchange
rate
Deviation
5Y
Gap (∆RR_F-∆RR_L) (t,t-4) 0.00 -0.078** -0.025 -0.218*** -0.12 0.76 -1.44
N 2,826 2,773 2,702 2,703 2,763 2,545 2,196
Countries 51 49 48 48 49 48 48
Indirect effect
Broader impact on capital flows:
an increase in the gap leading to a reduction in flows to
non-banks and portfolio debt flows
No evidence of circumvention by NFCs
to other sources of funding
No evident
impact on ER
deviation from
trends

20. International spillovers
• Does tightening FX RR in country A lead to more inflows in country B?
 Estimate a model of capital inflows to country B as a function of the
weighted sum of FX RR tightening in “similar” economies
(See Gori, Lepers, Mehigan 2020)
No evidence of
spillover

21. Robustness check 1: Endogeneity
• Policymakers also adjust policy depending on changes in economic conditions
> Endogeneity
• Solution: Estimate more “exogenous” policy shocks through 2 stage
approach (Ahnert et al 2018):
– 1st stage estimating the likelihood of a policy change from a range of variables likely to
be followed by policymakers
– 2nd stage regressing the baseline replacing the policy variables by the residuals obtained
from 1st stage (i.e. variation of policy changes that is not explained by macro-financial
variables).
Even stronger results than baseline.
+ Flows to banks neg. and sign. Additional effect
on the ER
deviation
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
Dependent variable
CB to banks
Flows
∆ FX loans
share
∆ FX liab
share
∆ Net FX pos
FSI
NFC debt
growth
CB to nonbanks
Flows equity flow
portfolio debt
flow credit flow
ER deviation
3Y
ER deviation
5Y
sum coef [t;t-3] -0.28** -0.453 -0.194** -2.321*** 0.001 -0.113** -0.001 -0.288** -0.284 2.378*** -1.245
p value of sum test 0.037 0.365 0.015 0.001 0.950 0.022 0.980 0.020 0.160 0.002 0.507
Observations 2,491 808 882 694 2,430 2,491 2,431 2,432 2,491 2,392 2,098
R-squared 0.119 0.053 0.058 0.060 0.060 0.122 0.037 0.126 0.106 0.151 0.142
Number of ifs_code 47 24 25 32 45 47 46 46 47 47 47

22. Dependent variable Baseline
Scaled by
Av_RR
Baseline
Scaled by
Av_RR
Baseline
Scaled by
Av_RR
Baseline
Scaled by
Av_RR
sum coef [t;t-3] -0.104 -0.019 -0.226 -0.041 -0.111* -0.023** -1.62*** -0.267**
p value of sum test 0.319 0.261 0.443 0.452 0.083 0.049 0.008 0.033
Dependent variable Baseline
Scaled by
Av_RR
Baseline
Scaled by
Av_RR
Baseline
Scaled by
Av_RR
Baseline
Scaled by
Av_RR
Baseline
Scaled by
Av_RR
Baseline
Scaled by
Av_RR
Baseline
Scaled by
Av_RR
sum coef [t;t-3] -0.002 -0.001 -0.078** -0.014*** -0.025 -0.004 -0.218*** -0.037*** -0.119 -0.023 0.76 0.189** -1.44 -0.23
p value of sum test 0.792 0.800 0.046 0.009 0.233 0.373 0.007 0.001 0.392 0.242 0.200 0.050 0.369 0.421
portfolio debt flow credit flow ER dev 3Y ER dev 5Y
CB_tobanks_Flows ∆ FX_loans_share ∆ FX_liab_share ∆ Net_FX_pos_FSI
NFC debt growth
CB_tononbanks_Flo
ws
equity flow
Robustness check 2: Non-linearity
Slight evidence of non-linearity (higher
significance)
Robust results & some evidence that the higher the initial average
rate, the lower the impact of a change in the gap
• Effectiveness of a RR change may depend on the initial rate
 We run again the regressions, scaling by the initial level of the rate:
Δ𝑅𝑅𝑅𝑅_𝐺𝐺𝐺𝐺𝐺𝐺𝑖𝑖,𝑡𝑡−𝑘𝑘
𝐴𝐴𝐴𝐴_𝑅𝑅𝑅𝑅𝑖𝑖,𝑡𝑡−𝑘𝑘−1

23. rates binary rates binary rates binary rates binary
∆ FX RR rate (t,t-4) 0.00 0.09 -0.06 -0.15 -0.021 -0.086 -0.169** -0.631
∆ LC RR rate (t,t-4) -0.01 -0.07*** 0.121*** 0.399** 0.055* 0.20 0.369*** 1.045**
∆ single RR rate (t,t-4) 0.01 0.03** -0.03 -0.17 -0.04 0.03 -0.06 -0.22
N 2,826 2,826 2,773 2,773 2,702 2,702 2,703 2,703
Countries 51 51 49 49 48 48 48 48
rates binary rates binary rates binary
∆ FX RR rate (t,t-4) -0.153 -0.228 0.472 15.153* -1.656 -5.754
∆ LC RR rate (t,t-4) 0.09 0.34 -1.22 3.68 0.94 5.20
∆ single RR rate (t,t-4) 0.10 -0.19 -0.43 -1.13 -0.05 -0.03
N 2,763 2,763 2,545 2,545 2,196 2,196
Countries 49 49 48 48 48 48
Debt Inflows
Other Inflows Exchange rate Exchange rate
NFC debt growth
Inflows to non-
banks
Equity Inflows
rates binary rates binary rates binary rates binary
∆ FX RR rate (t,t-4) -0.078 -0.187 -0.065 0.146 -0.032 0.515** -1.594*** -2.068
∆ LC RR rate (t,t-4) 0.128 0.526 0.181 0.997* 0.235 0.629*** 0.831** 1.16
∆ single RR rate (t,t-4) 0.198 0.267 1.637 6.736 0.153 1.116 0.847 2.58
N 2,773 2,773 891 891 1,029 1,029 797 797
Countries 49 49 25 25 29 29 35 35
∆ FX liab share ∆ Net FX position
Inflows to banks ∆ FX loans share
Intensity-based measures vs. Binary variables
Importance of capturing
the intensity of policies to
measure effectiveness
Significant
differences between
binary and rate
indicators

24. 24
CONTRIBUTIONS
AND
POLICY CONCLUSIONS

25. Summary of the findings
CURRENCY
MISMATCH &
DOLLARISATION
CAPITAL
INFLOWS
inflows to non-banks and
portfolio debt inflows
on the
liability side
and net FX
position
CIRCUM
VENTION
No evidence
EXCHANGE
RATE
no evidence in the
baseline, but impact in
the rob. checks
1 What is the impact of a higher gap between FX and local currency RRs?
• The comparison between the results using a binary policy indicator vs. our
intensity based measure strongly highlights the need to consider the
intensity of measures.
• The significance of the results is strongly impacted by the choice of
indicator.
2

26. Implications
Within the macroprudential toolkit, FX RRs:
- can be effective tool with important benefits (e.g. reduction of
currency mismatches),
- but can have an impact on capital flows, and
- raising rates above a certain threshold may be less effective
Importance of considering more broadly the root causes of
dollarisation and how FX RRs fit within the broader policy toolkit
POLICY
ANALYTICAL WORK
- Shortfalls of using binary variables

27. 27
Thank you
DAFCodes@oecd.org
Full paper:
https://www.oecd-ilibrary.org/finance-and-
investment/assessing-the-effectiveness-of-currency-
differentiated-tools_e979a657-en