4835
Views
2999
Downloads |
Effectiveness of macroprudential policies in Central and Eastern European countries
Mirna Dumičić* 
Article | Year: 2018 | Pages: 1 - 19 | Volume: 42 | Issue: 1 Received: November 28, 2017 | Accepted: January 13, 2018 | Published online: March 8, 2018
|
FULL ARTICLE
FIGURES & DATA
REFERENCES
CROSSMARK POLICY
METRICS
LICENCING
PDF
|
Loans to
household sector
|
Loans to
corporate sector
|
|
Spec 1
|
Spec 2
|
Spec 3
|
Spec 4
|
|
Constant
|
3.1541
|
2.9472
|
2.8112
|
2.8919
|
|
(0.8938)**
|
(0.7543)*
|
(0.5792)*
|
(0.5257)**
|
|
Loan
(–1)
|
0.6637
|
0.6655
|
0.2618
|
0.2602
|
|
(0.0681)*
|
(0.0701)*
|
(0.0669)*
|
(0.0669)**
|
|
GDP
|
0.4432
|
0.3302
|
0.7261
|
0.7290
|
|
(0.1567)*
|
(0.1140)*
|
(0.2003)*
|
(0.2000)**
|
|
Interest rate
(–1)
|
–1.1239
|
–1.0660
|
–0.1613
|
–0.1763
|
|
(0.4253)*
|
(0.4292)**
|
(0.2490)
|
(0.2490)
|
|
Total level
of macroprudential policy – d (–1)
|
–0.4958
|
|
0.1538
|
|
|
(0.2277)**
|
|
(0.0572)
|
|
|
Total level
of macroprudential policy – step (–1)
|
|
–0.1694
|
|
0.0660
|
|
(0.0775)**
|
|
(0.0572)
|
|
Observations:
|
264
|
264
|
332
|
332
|
|
R2:
|
0.75
|
0.75
|
0.33
|
0.33
|
|
F-statistic:
|
55.8
|
55.68
|
10.98
|
10.98
|
Note: Total level of macroprudential policy – d represents the sum of binary variables or the number of used macroprudential measures and instruments in a given moment. Total level of macroprudential policy – step represents the sum of constructed step indicators for individual macroprudential measures. All estimations are made using OLS; period SUR panel-corrected standard errors in parentheses. * significant at 1%, ** significant at 5%, *** significant at 10%. Source: Author's calculations.
|
|
Credit growth limit – level
(–1)
|
Capital requir. – level
(–1)
|
Limited currency mismatch – level
(–1)
|
Marginal reserve requir. – level
(–1)
|
Increas. provis. requir. – step
(–1)
|
General reserve requir. – level
(–1)
|
Increas. risk weights – step
(–1)
|
DSI – level
(–1)
|
LTV – level
(–1)
|
|
Loans to
household sector
|
–0.0780
|
–0.6255
|
–1.3082
|
0.0011
|
–0.5950
|
–0.2438
|
–0.2339
|
–0.0920
|
–0.0360
|
|
(0.0440)***
|
(1.5199)
|
(0.8867)
|
(0.0131)
|
(0.5827)
|
(0.1424)***
|
(0.4523)
|
(0.0397)**
|
(0.0108)*
|
|
Loans to
corporate sector
|
–0.0956
|
–0.2122
|
3.2680
|
0.0201
|
0.9993
|
0.0268
|
0.6130
|
|
|
|
(0.0561)*
|
(0.7119)
|
(1.3952)*
|
(0.0144)
|
(0.4000)**
|
(0.0691)
|
(0.5168)
|
|
|
Note: This table presents only the estimated coefficients on macroprudential variables; for complete results see Appendix Tables 4 and 5. Level presents the actual value of a specific instrument (i.e. general reserve requirement of 2%). All estimations are made using OLS; period SUR panel-corrected standard errors in parentheses.
* significant at 1%, ** significant at 5%, *** significant at 10%. Source: Author's calculations.
|
Study
|
Sample
|
Period
|
Research
questions
|
Main
findings
|
|
Lim et al. (2011)
|
49
countries actively using macroprudential instruments
|
2000–10
|
Effectiveness
of macroprudential instruments in achieving their objectives.
Factors
affecting the choice of instruments.
Circumstances
in which instruments are used.
|
Many
instruments can effectively reduce systemic risk in the financial sector.
Their
effectiveness does not necessarily depend on the stage of economic
development or the type of exchange rate regime.
Emerging
markets with fixed exchange rate regimes or managed floats use
macroprudential measures more often.
Emerging
markets facing large capital inflows, with shallow financial markets, and
those with bank-centric systems also use macroprudential tools more often.
Macroprudential
instruments can be just as effective when used in advanced economies with
flexible exchange rate regimes.
|
|
Quereshi et al.
(2011)
|
51
EMEs
|
1995–2008
|
Can
macroprudential policy and capital controls help enhance financial stability
in periods of large foreign capital inflows?
Construct
new indices for macroprudential measures dealing with currency risk and
capital controls for the financial sector.
|
Macroprudential
policy and capital controls reduce the riskiness of external borrowing and
domestic foreign currency lending.
Policies
that do not discriminate on the basis of currency or residency can also be
effective in mitigating excessive credit growth.
|
|
Schou-Zibell,
Albert and Song (2012)
|
41
EMEs in Asia, Latin America and Europe, plus 18 advanced economies
|
1993–2008
|
Identify
most important determinants of financial soundness and stability capital
adequacy, asset quality, earnings, profitability) in EMEs.
|
The
relationship between financial soundness indicators and macroeconomic
indicators varies depending on the stage of economic and financial
development.
|
|
Tovar,
Garcia-Escribano and Martin (2012)
|
Five
Latin American economies
|
January
2003 – April 2011
|
Effectiveness
of reserve requirement in reducing credit growth.
Construct
a composite indicator of reserve requirements used in different countries.
Study
how credit to the private sector, market and policy interest rates, and
exchange rates react to changes in
average reserve requirements, marginal reserve requirements and other
macroprudential instruments.
|
Reserve
requirements and other macroprudential instruments led to a slowdown in
growth of bank credit to the private sector.
Panel
data VAR including a binary macroprudential policy variable, industrial
production and private credit growth also suggests that macroprudential tools
limit credit growth.
|
|
Vandenbussche,
Vogel and Detragiache (2012)
|
16
countries in Central, Eastern and Southeastern Europe
|
Early
2000s – 2011 Q1
|
On
a panel of 16 countries, the authors explore the impact of macroprudential
policy measures on housing price inflation.
|
Tightening
of minimum capital adequacy requirements and nonconventional measures used to
guarantee liquidity, such as marginal reserve requirements on foreign funding
sources and excessive credit growth, contributed to a slowdown in housing
prices.
|
|
Nier et al. (2012)
|
15
developed economies and 21 emerging market economies
|
|
How
macroprudential measures affect credit activity, house prices, economic
activity and capital inflows.
How
these effects depend on the stages of economic cycle.
|
Capital
requirements and reserve requirements contribute to a slowdown in credit
growth.
Loan-to-value
and debt-to-income ratios effective in EMEs.
|
|
Medas et al.
(2013)
|
25
economies
|
2000–11
|
Effectiveness
of loan-to-value and debt-to income ratios; greater risk weights; and higher
provisioning requirements in restraining credit growth and real estate
prices.
Construct
variables that reflect the intensity of use of individual macroprudential
measures as these are tightened or loosened.
|
Greater
risk weights and higher loan-to-value and debt-to income ratios are
successful in dampening growth of credit and real estate prices.
|
|
Cerutti, Claessens
and Laeven (2015)
|
119
countries
|
2000-13
|
Relationship
between the use of macroprudential policies and developments in credit and
housing markets.
Effectiveness
of macroprudential policies in dampening financial cycles.
|
Emerging
countries use macroprudential policies more often, especially FX related
measures, while advanced countries primarily rely on borrower-based measures.
These
policies generally result with lower credit growth, primarily for households.
Macroprudential
policies can help manage financial cycles, but they work better in the boom
than in the bust phase.
|
All estimations are made using OLS; period SUR panel-corrected standard errors in parentheses. * significant at 1%, ** significant at 5%, *** significant at 10%. Source: Author᾿s calculations.
Beck, N. and Katz, J., 1995. What to Do (and Not to Do) with Time-Series Cross-Section Data. American Political Science Review, 89(3), pp. 634–647 [ CrossRef]
Beck, N. and Katz, J., 1996. Nuisance Vs. Substance: Specifying and Estimating Time-Series-Cross-Section Models. Political Analysis, 6, pp. 1–36 [ CrossRef]
Beck, N. and Katz, J., 2004. Time-Series–Cross-Section Issues presented at the 21st Annual Summer Meeting of the Society for the Political Methodology, 29-31 July 2004, Stanford, pp. 1–35.
Cerutti, E., Claessens, S. and Laeven, L., 2015. The Use and Effectiveness of Macroprudential Policies: New Evidence. IMF Working Paper, No. 15/61 [ CrossRef]
ESRB, 2014. Flagship Report on Macro-Prudential Policy in the Banking Sector. Frankfurt am Main: European Systemic Risk Board.
Geršl, A. and Jašova, M., 2014. Measures to Tame Credit Growth: Are They Effective. Economic Systems, 38(1), pp. 7–25 [ CrossRef]
Gupta, S., Mulas-Granados, C. and Baldacci, E., 2009. How Effective is Fiscal Policy Response in Financial Crises?. Fiscal issues and central banking in emerging economies. IMF Working paper, WP/09/160.
Kristensen, I. P. and Wawro, G., 2003. Lagging the Dog?: The Robustness of Panel Corrected Standard Errors in the Presence of Serial Correlation and Observation Specific Effects. Presented at the Summer Methods Conference.
Laeven, L. and Valencia, F., 2012. Systemic Banking Crises Database : An Update. IMF Working Paper, No. 12/163 [ CrossRef]
Lim, C. H. [et al.], 2011. Macroprudential Policy: What Instruments and How to Use Them? Lessons from Country Experiences. IMF Working Paper, No. 11/238.
Lim, C. H. [et al.], 2013. The Macroprudential Framework: Policy Responsiveness and Institutional Arrangements. IMF Working Paper, No. 13/166 [ CrossRef]
Reinhart, C. M. and Rogoff, K. S., 2014. Recovery from Financial Crises: Evidence from 100 Episodes. American Economic Review: Papers & Proceedings, 104(5), pp. 50–55 [ CrossRef]
Rohatinski, Ž., 2009. Economic Crisis and Monetary Policy. Speech prepared for a round table at the HAZU Department of Social Sciences: Crisis and Economic Policy Frameworks, Zagreb, 7 July 2009.
Tovar, C. E., Garcia-Escribano, M. and Martin, M. V., 2012. Credit Growth and the Effectiveness of Reserve Requirements and other macroprudential instruments in Latin America. IMF Working Paper WP/12/142.
Vandenbussche, J., Vogel, U. and Detragiache, E., 2012. Macroprudential Policies and Housing Prices - A New Database and Empirical Evidence for Central, Eastern, and Southeastern Europe. IMF Working Paper, WP 12/303.
|
|
March, 2018
I/2018
|
