Spillovers from the ECB's non-standard monetary policy measures on south-eastern Europe.
Date: 2017-08-31
Institutions: European Central Bank
Subjects: Central and Eastern European countries, European Central Bank, European Monetary System, European integration, econometrics, economic integration, economic model, euro area, macroeconomics, monetary policy

Working Paper Series 

Isabella Moder 

Spillovers from the ECB's  
non-standard monetary policy 
measures on south-eastern Europe 

No 2095 / August 2017 

Disclaimer: This paper should not be reported as representing the views of the European Central Bank 
(ECB). The views expressed are those of the authors and do not necessarily reflect those of the ECB. 

Abstract

This paper is the ﬁrst to comprehensively assess the impact of the euro area’s non-standard

monetary policy measures on south-eastern Europe. By employing bilateral BVAR models, I

am able to estimate the response of output and prices for each country, as well as to shed more

light on potential shock transmission channels. The results suggest that the ECB’s non-standard

monetary policy measures have had pronounced price eﬀects on all south-eastern European

countries, and output effects on approximately half of them. While I also ﬁnd exports to be

a relevant transmission channel in most cases, the interbank market rate responds signiﬁcantly

only in a few cases as the region was subject to signiﬁcant cross-border bank deleveraging after

the crisis. Furthermore, the results suggest that the exchange rate regime does not play a role

in determining the sign and magnitude of price level and output responses. This is in line with

the absence of distinct exchange rate responses in the model output, suggesting that exchange

rates did not act as buﬀers for spillovers of euro area non-standard monetary policy measures

on south-eastern Europe.

Keywords: Unconventional monetary policy, international shock transmission, BVAR, EU

integration

JEL-Classiﬁcation: C11, C32, E52, F42

ECB Working Paper 2095, August 20171Non-technical summary

In this paper I investigate the international effects of the ECB’s monetary policy. More specif-

ically, I am interested in the period between 2008 and 2015, during which the ECB has in-

troduced several new instruments for conducting monetary policy under special circumstances.

The geographical focus are eight countries of south-eastern Europe (namely Albania, Bosnia

and Herzegovina, Bulgaria, Croatia, the former Yugoslav Republic of Macedonia, Montenegro,

Romania and Serbia). With this focus I seek to ﬁll a gap in the literature, which has not com-

prehensively assessed the impact of the ECB’s non-standard monetary policy measures on this

region yet.

The nature of international effects of ECB monetary policy is of great interest for policy

makers in small countries in order to design optimal policy responses. South-eastern Europe is

connected with the euro area in several ways. Firstly, the euro area is the most important trade

partner for these countries, both on the export as well as the import side, which constitutes a

real channel of shock transmission. Secondly, a large part of investment in south-eastern Europe

stems from the euro area, which creates a ﬁnancial link between those two regions. Moreover,

a signiﬁcant number of euro area banks operate in the countries of south-eastern Europe and

correspondingly the oﬃcial and unoﬃcial use of the euro is widespread in the region. Despite

their similarities, the south-eastern European countries operate under diﬀerent exchange rate

regimes, which makes this an interesting test case for investigating whether the exchange rate

regime shapes the response to a euro area monetary policy shock.

I conduct separate estimations for each country in the period between January 2008 to

December 2015 by employing BVAR models with monthly data. Besides a number of euro

area variables that measure ECB monetary policy and its implications for the euro area itself,

I include a number of variables for each south-eastern European country. I do not only test

the response of macroeconomic variables like output and prices, but also aim to develop an

understanding on how the mechanism of international transmission works.

The results suggest that each country in south-eastern Europe has been aﬀected by the ECB’s

non-standard monetary policy measures. The price response to an expansionary non-standard

monetary policy shock is positive for all countries and in some cases the inﬂationary effect is

even stronger than for the euro area itself. Similarly, in approximately half of the countries

output responds positively to such a shock. Moreover, I ﬁnd evidence for the existence of an

ECB Working Paper 2095, August 20172export transmission channel, while the interbank interest rate clearly responds to the shock only

in two countries, which is related to the signiﬁcant cross-border deleveraging these countries

experienced after the crisis. With respect to the exchange rate regime, I ﬁnd no evidence that

it inﬂuences how a country reacts to the non-standard monetary policy shock, which is in line

with the ambiguous response of exchange rates in the model output and might be driven by

relatively stable exchange rates during the sample period.

ECB Working Paper 2095, August 201731 Introduction

Since October 2008 the European Central Bank (ECB) has introduced a number of non-standard

monetary policy measures, which are unprecedented in nature, scope and magnitude; and have

ranged from signiﬁcant changes in the operational framework to large bond purchasing pro-

grammes. Assessing potential spillovers from monetary policy measures of advanced economies

has become important in a globalised world; and it does not only incorporate potential spillovers

via real channels like trade links and remittance ﬂows, but more and more also the impact of

ﬁnancial spillovers, as monetary policy measures often generate sizable changes in capital ﬂows

and exchange rate dynamics. This mechanism could be very well observed in the so-called ‘taper

tantrum episode’ in mid-2013, when the Fed announced to gradually turn off its bond-buying

programme, which provoked a pronounced shift in market sentiment vis-`a-vis emerging markets

(see Sahay et al., 2014). Quantifying the direction and magnitude of international spillovers

caused by advanced economies’ monetary policy measures – and identifying the main transmis-

sion channels – is thus of utmost importance for policy makers in order to design optimum policy

responses, both to spillovers from the introduction of such measures as well as to spillovers from

their potential reversal.

The focus of interest for this paper lies in potential spillovers of ECB monetary policy

measures to European countries that are not yet part of the euro area, or are in the process

of EU accession. More speciﬁcally, this paper deals with the countries of south-eastern Europe

(SEE)1, that can be regarded as transition countries with respect to their economic development

stage2. SEE countries are interlinked with the euro area through various channels. High trade

integration and sizable remittance ﬂows constitute potential real transmission channels, while

the presence of a number of euro area headquartered bank subsidiaries and (correspondingly) a

high degree of euroisation3 represent ﬁnancial links.

Additionally, the heterogeneous monetary policy regimes of SEE countries provide an inter-

esting case for cross-country comparisons with regard to the role of exchange rate regimes in

shaping spillovers: exchange rate regimes in SEE range from inﬂation targeters with (managed)

1Albania, Bosnia and Herzegovina, Bulgaria, Croatia, the former Yugoslav Republic of Macedonia, Montenegro,

Romania and Serbia

2In contrast to Baltic and central European countries, where convergence towards the ‘old’ EU member states

progressed further than in SEE countries.

3Either through high unofﬁcial asset and liability euroisation of the banking systems or, in the case of Mon-
tenegro, through the use of the euro as the legal tender, see European Central Bank (2016) for more information.

ECB Working Paper 2095, August 20174ﬂoating exchange rates (Albania, Romania and Serbia), to stabilised arrangements with the euro

as a reference currency (Croatia and the former Yugoslav Republic of Macedonia), to euro-based

currency boards (Bosnia and Herzegovina as well as Bulgaria), to the unilateral adoption of the

euro as the sole legal tender (Montenegro).

The aim of this paper is thus to answer three questions: First, in what direction and to

which magnitude have the ECB’s non-standard monetary policy measures been affecting the

SEE countries? Second, through which channels are these shocks transmitted to SEE? Third,

do diﬀerent exchange rate regimes play a role in shaping the SEE countries’ responses to a

non-standard monetary policy shock?

The main contribution of this paper to the literature is the systematic examination of

spillovers from the ECB’s non-standard monetary policy measures to the whole SEE region.

While its three EU countries (Bulgaria, Croatia, Romania) have already been covered to a cer-

tain extent in the spillover literature, no research has been undertaken yet for the remaining

countries, which are ﬁve candidate and potential candidate countries to the EU4. By employing

impulse response functions in a structural BVAR setting, the effect of non-standard monetary

policy shocks on each country’s output, price level, exchange rate and key policy rate (if appli-

cable), short-term interest rate, exports and trade partners’ output is estimated.

The results show that the price level of all countries is positively aﬀected by an expansionary

non-standard monetary policy shock originating in the euro area, and for approximately half

of the countries output also responds positively. Furthermore, spillovers seem to be mostly

transmitted via exports, while only in a few cases via a ﬁnancial channel (as measured by

interbank interest rates). Additionally, the results suggest that the exchange rate regime does

not play a role in determining spillovers, which is in line with the muted exchange rate responses

in the model output that might be driven by relatively stable exchange rates during the sample

period.

The structure of the paper is as follows: Section 2 provides an overview of the literature,

while section 3 introduces the methodological approach. The corresponding results and potential

transmission channels are discussed country by country and from a cross-country perspective

in section 4. Section 5 documents robustness tests undertaken in order to cement the results.

Section 6 concludes.

4Due to data limitations, the remaining prospective EU member Kosovo cannot be included in the empirical

analysis.

ECB Working Paper 2095, August 201752 Related literature

A vast amount of literature on cross-border monetary policy spillovers has emerged in the

past decades, which in the beginning focused mostly on spillovers between advanced economies.

Canova (2005) was among the ﬁrst ones to investigate monetary policy spillovers from an ad-

vanced economy (the US) to emerging economies (eight countries in Latin America), followed by

other papers modelling spillovers from US monetary policy to Latin America, Canada and Asian

economies (see e.g. Ma´ckowiak, 2007), and from euro area monetary policy to other European

countries (both emerging and advanced, see e.g. Ma´ckowiak, 2006; Jaroci´nski, 2010; Benkovskis

et al., 2011). On SEE countries, the literature of conventional monetary policy spillovers is less

abundant, which is mainly related to the short time series available. Nevertheless, available

results are very heterogeneous and seem to depend on the model and speciﬁcations used (see

Jim´enez-Rodriguez et al., 2010; Minea and Rault, 2011; Feldkircher, 2015; H´ajek and Horv´ath,

2016; Petrevski et al., 2015; Potjagailo, 2017, using near-VAR, VAR, GVAR, SVAR and FAVAR

models). Moreover, to the best of my knowledge, four SEE countries5 have not yet been covered

in the spillover literature at all.

The introduction of non-standard measures in October 2008 and the continuous ongoing ex-

pansion of several different unconventional instruments brought a new angle into the academical

and policy discussion of euro area monetary policy spillovers to countries outside the euro area6.

However, given that the global experience with non-standard monetary policy is restricted (with

a few exceptions) to the aftermath of the global ﬁnancial crisis, the literature on spillovers from

advanced economies’ non-standard or unconventional monetary policy measures to emerging

markets is relatively scarce. It can be divided into two categories: One strand investigates the

impact of monetary policy announcements (and in some cases also actions) on high-frequency

ﬁnancial indicators (e.g. sovereign bond yields, stock market indices, CDS spreads or exchange

rates); see for example Fratzscher et al. (2016) for spillovers of US, and Georgiadis and Gr¨ab

(2015) as well as Falagiarda et al. (2015) for spillovers of euro area non-standard monetary policy.

The latter examine the effects of more than seventy announcement-related events on ﬁnancial

assets of four non euro area EU countries. For Romania, which is the only SEE country covered,

they ﬁnd a signiﬁcant effect on the short-term money market rate and an especially pronounced

5Namely Albania, Bosnia and Herzegovina, Montenegro and Serbia.
6For the purpose of this paper only spillovers outside the euro area are discussed. For an assessment of the

effects within the euro area see e.g. Peersman (2011); Boeckx et al. (2017); Burriel and Galesi (2016).

ECB Working Paper 2095, August 20176effect on long-term government bond yields, while the exchange rate seems not to respond im-

mediately to an ECB announcement. Ciarlone and Colabella (2016) test the effect of the ECB’s

asset purchase programmes on a panel of eleven countries in central, eastern and south-eastern

Europe, including all countries covered in this paper. They ﬁnd signiﬁcant short-term spillover

effects on ﬁnancial variables as well as long-term spillovers on portfolio and cross-border banking

ﬂows.

Focusing on longer-lasting macroeconomic effects instead, the second strand of literature

has been following the methods of the literature on ‘conventional’ monetary policy spillovers by

using some kind of VAR model to assess spillovers on macroeconomic variables. The literature

on non-standard monetary policy spillovers from the euro area to central and eastern Europe

(CEE) is scarce, whereas it is non-existent for most countries in SEE. Babeck´a Kucharˇcukov´a

et al. (2016) investigate spillovers on six EU non-euro area countries, among them three in CEE

(Czech Republic, Hungary, Poland). They conclude that the spillovers of unconventional shocks

are transmitted differently compared to conventional shocks, and while exchange rates respond

quickly, the effect on inﬂation is ambiguous. Bluwstein and Canova (2016) use a Bayesian

mixed-frequency VAR to incorporate both high-frequency ﬁnancial as well as low-frequency

macroeconomic data. They ﬁnd that output effects of unconventional monetary policy measures

were insigniﬁcant for CEE (Czech Republic, Hungary, Poland), and slightly negative for SEE

(Bulgaria, Romania), and that the impact on inﬂation was slightly positive for both groups.

With regard to the exchange rate channel, they conclude that it does not seem to shape the

response of macroeconomic variables in the case of unconventional monetary policy shocks, as

opposed to the case for conventional monetary policy. Halova and Horv´ath (2015) employ a

PVAR model for eleven CEE and SEE countries (among them Bulgaria, Croatia and Romania).

On the contrary to Bluwstein and Canova (2016) and Babeck´a Kucharˇcukov´a et al. (2016), their

results suggest sizable spillovers and that a signiﬁcant amount of output ﬂuctuations in the CEE

and SEE countries can be explained by the euro area’s non-standard monetary policy measures.

Ultimately, whether a country beneﬁts from or is negatively aﬀected by spillovers of a foreign

monetary policy shock depends on whether its business cycle is in the same position as that of

the ‘core country’ (Chen et al., 2015).

Another open issue that has been discussed in the spillover-literature is what shapes the re-

sponse of an economy to a foreign monetary policy shock (both conventional and non-standard).

The role of the exchange rate regime has featured prominently in the spillover discussion, fol-

ECB Working Paper 2095, August 20177lowing the argument that ﬂexible exchange rates are better suited to buffer real external shocks

(based on Meade, 1951; Friedman, 1953). Other potential determinants identiﬁed by the litera-

ture are the degrees of trade and ﬁnancial openness (see e.g. Miniane and Rogers, 2007). More

recently, Georgiadis (2016) systematically examines U.S. monetary policy spillovers and ﬁnds

that the role of the exchange rate regime is non-linear, and that non-advanced economies op-

erating under an inﬂexible exchange rate regime experience larger spillovers the more strongly

they are integrated in global trade. Furthermore, the results suggest that trade integration

ampliﬁes spillovers to non-advanced economies if the share of manufactured goods in aggregate

output is large and the country participates in global value chains. Crespo Cuaresma et al.

(2016) additionally ﬁnd that macroeconomic vulnerabilities such as a high external imbalances

tend to amplify spillovers from US monetary policy shocks. For spillovers of euro area monetary

policy, Potjagailo (2017) presents some evidence that spillovers on other EU countries’ output

are larger if the exchange rate regime is ﬁxed.

3 Methodology

The methodology used in this paper follows the strand of literature that investigates the effects

of non-standard monetary policy measures on the real economy by employing some speciﬁcation

of a VAR model. There are two reasons to choose this approach: First, although event studies

could identify signiﬁcant ﬁnancial market spillovers for some European countries outside the euro

area, this does not necessarily imply that the real economy is equally affected, since ﬁnancial

variables often exhibit overshooting behaviour that does not necessarily transmit into the real

economy. Second, the event study approach requires developed ﬁnancial markets to investigate

the behaviour of high-frequency indicators. This is a major drawback in the case of emerging

markets in general and SEE in particular, as these countries have very shallow ﬁnancial markets

in line with their small economic size and comparatively low GDP per capita levels.

3.1 Issues in dealing with non-standard monetary policy

Empirically assessing non-standard monetary policy measures brings a number of additional

challenges compared to conventional monetary policy. First, as the key monetary policy rate does

not incorporate non-standard measures, alternative indicators for the stance of non-standard

monetary policy have to be found. Those used in the literature so far have been the term

ECB Working Paper 2095, August 20178spread between government bonds of different maturities (e.g. Chen et al., 2012), central bank

balance sheet assets (e.g. Gambacorta et al., 2014), or shadow rates that are supposed to be

directly comparable to key policy rates (Lombardi and Zhu, 2014; Krippner, 2015; Wu and Xia,

2016). In this paper I use Eurosystem balance sheet assets as the main measure of non-standard

monetary policy. In the upper chart of ﬁgure 1, inverted Eurosystem balance sheet assets are

plotted together with the key policy rate. It can be seen that the key policy rate was decreased

in various steps to 1 percent in May 2009, from where it slowly and gradually moved towards

the zero lower bound, which was reached in March 2016. In contrast, the Eurosystem balance

sheet assets started to increase already with the switch of liquidity operations to a ﬁxed rate

tender with full allotment in October 2008, and thereafter ﬂuctuated with the introduction

and phase-out of the different programmes. In this paper I use additionally the shadow rate

developed by Wu and Xia (2016) for robustness testing. It is calculated by assessing bond prices

in a framework of a multifactor term structure model; and is directly comparable to the key

policy rate as both interest rates are equal in conventional times (see the lower chart of ﬁgure

1).

In contrast to balance sheet assets, this indicator also includes announcement effects of

non-standard monetary policy measures whenever they affect bond yields.

Second, the way some of the ECB’s non-standard monetary policy measures have been

designed makes it necessary to ﬁnd an empirical strategy that disentangles exogenous monetary

policy shocks from endogenous or demand-driven monetary expansions. Since the change in

the operational framework from standard tender-based allotment to ﬁxed-rate full allotment in

October 2008, monetary policy operations have been essentially endogenous or demand-driven,

as banks have unlimited access to liquidity at the interest rate on the main reﬁnancing operations

(MRO) under the condition that they can provide enough collateral (Boeckx et al., 2017).

Moreover, the (targeted) longer-term reﬁnancing operations, which were increased in duration

and size in October 2008, are also endogenous to a certain extent since the ECB only ﬁxes the

upper ceiling of these operations, whereas banks decide how much to draw upon that limit. This

paper deals with endogeneity issues in several ways. First, I follow the approach proposed by

Boeckx et al. (2017), who complement the Eurosystem’s balance sheet assets as the main measure

for non-standard monetary policy measures with certain assumptions on shock identiﬁcation (see

subsection 3.3). Moreover, I perform robustness checks by using only the position ‘Securities held

for monetary policy purposes’ (A070100) of the Eurosystem’s balance sheet, which incorporates

all securities purchased under the various purchasing programmes. Compared to other positions

ECB Working Paper 2095, August 20179of the Eurosystem balance sheet, this is the most exogenous part since the size and frequency

of bond purchases are ex-ante determined by the ECB and not shaped by banks’ behaviour.

However, with the start of the extended asset purchase programme (APP) in January 2015,

combined monthly asset purchases of EUR 60 billion were pre-announced, meaning that they

were in fact fully anticipated. Therefore, I also conduct robustness checks with a shorter sample.

3.2 Model

To model spillovers from the euro area’s non-standard monetary policy to SEE countries, the

following structural BVAR model with a monthly frequency is employed for each SEE country:





p
(cid:88)

s=0

A11(s) A12(s)

y1(t − s)

A21(s) A22(s)

y2(t − s)











 +





c11

c21



 =









ε1(t)

ε2(t)

(1)

where y1(t) represents a vector of macroeconomic variables of the SEE country, y2(t) a vector

of macroeconomic variables of the euro area, and the vectors c11, c21 constants. The vectors
ε1(t) ∼ N (0, Σ1) and ε2(t) ∼ N (0, Σ2) denote structural shocks of domestic and euro area origin,

respectively.

For each s, A21(s) = 0, implying that the variables of the SEE country are set to be exogenous

to the variables of the euro area under the assumption that neither current nor past economic

developments in the SEE countries inﬂuence developments in the euro area. This so-called

‘block exogeneity’ feature introduced by Cushman and Zha (1997) has been used frequently in

the literature (see e.g. Canova, 2005; Ma´ckowiak, 2007; Benkovskis et al., 2011) and is well suited

for modelling spillovers from large to small economies, as it helps to identify spillovers from the

viewpoint of the small open economy and reduces the number of parameters to be estimated

(Cushman and Zha, 1997).

The vector y1 consists of the following seven variables:

(cid:16)

y1 =

ySEE
t

xSEE
t

pSEE
t

iSEE
t

y∗
t

rSEE
t

et

(cid:17)(cid:48)

(2)

where ySEE

t

denotes output, xSEE

t

exports to the euro area, pSEE

t

prices and iSEE

t

the interbank

market rate of the respective SEE country. y∗

t represents global developments and is constructed

as the weighted average of the output of the ﬁve most important export partners for each

ECB Working Paper 2095, August 201710country7. It is included to control for indirect spillovers that would otherwise not be covered

in a bilateral model set-up. The key policy rate rSEE

t

as well as the exchange rate of the

local currency vis-`a-vis the euro, et, are included only for countries that are operating under an
inﬂation targeting regime8. Otherwise the vector y1 consists of only ﬁve variables. The vector

y2 represents the euro area and includes six variables:

(cid:16)

y2 =

yEA
t

pEA
t

assetsEA

t

CISSt

spreadEA

t M ROt

(cid:17)(cid:48)

(3)

and pEA

t

where yEA

t
and assetsEA

t

again denote output and prices, respectively, but this time for the euro area

represent Eurosystem balance sheet assets as the main measure for non-standard

monetary policy (as discussed in subsection 3.1). Moreover, following Gambacorta et al. (2014);

Boeckx et al. (2017); Burriel and Galesi (2016), I include the CISS-indicator developed by Holl´o

et al. (2012) (CISSt), which serves two purposes: First, it controls for the impact of euro area

ﬁnancial stress and economic risk, which is important to capture in the model as it has had

pronounced effects on euro area macroeconomic developments. Second, the inclusion of the

CISS-indicator helps to disentangle exogenous balance sheet movements from endogenous ones

and thus enables a proper identiﬁcation of monetary policy shocks (see subsection 3.3). For

the same purpose, I also include the spread between the EONIA and the MRO-rate (denoted

spreadEA

t

). To disentangle conventional from non-standard monetary policy shocks, the model

incorporates additionally the MRO-rate (M ROt).

The chosen estimation procedure is Bayesian, because it is very well suited for shorter data

sets. I use an independent normal-Wishart prior and obtain the scale matrix S0 from individual

AR regressions. Estimations are carried out by employing the BEAR toolbox developed by

Dieppe et al. (2016) in MatLab. The autoregressive coefﬁcient of the prior is set to 1, since

the variables enter the model in levels. This speciﬁcation is possible in Bayesian models, where

the prior can account for unit root behaviour by including an autoregresssive coefﬁcient on the

ﬁrst own lag of each variable, and it has the advantage of avoiding the transformation bias that

occurs when data enter transformed into ﬁrst differences. The remaining hyperparameters that

specify the prior are chosen following Dieppe et al. (2016). The posterior is derived by Gibbs

sampling with a total number of 5,000 iterations and a burn-in sample of 1,000 iterations. The

7The respective countries are chosen according to their export share in the country’s exports in 2015, which is

also used for creating the weighted average.

8The two additional variables are therefore included in the bilateral models for Albania, Romania and Serbia.

ECB Working Paper 2095, August 201711Bayesian information criterion (BIC) suggests a lag length of 1; however, testing for autore-

gressive behaviour of the residuals suggests that a model speciﬁcation of 4 lags is best to avoid

residual autocorrelation. Therefore I deﬁne p = 4.

3.3

Identiﬁcation

In order to generate impulse response functions, the identiﬁcation of shocks is carried out via

sign and zero restrictions, following the method proposed by Arias et al. (2014) (see Dieppe

et al., 2016). The non-standard monetary policy shock is the only identiﬁed shock in the model

and takes the following form:

assetsEA

t

CISSt

spreadEA

t

M ROt

yEA
t

pEA
t

iSEE
t

+

1-1

−

0-1

−

0-1

0

0

0

·

et

·

rSEE
t

ySEE
t

xSEE
t

pSEE
t

0

0

0

0

y∗
t

0

Note: 0 indicates that the immediate response is restricted, while + (−) indicate that only a positive (negative)
reaction is permitted in the respective period (see third row).
· denotes that no restriction is placed on the
variable.

The ﬁrst six variables deﬁne the non-standard monetary policy shock and its effects on the

euro area, while the remaining variables apply to the respective SEE country and its trade part-

ners. An expansionary non-standard monetary policy shock increases the Eurosystem balance

sheet assets at least in the ﬁrst month following the shock (I do not put a restriction on impact to

allow for announcement eﬀects which are followed by the policy action in the subsequent month),

while both the CISS-indicator as well as the spread between the EONIA and the MRO decrease

immediately (on impact) and in the ﬁrst month after the shock. These identifying assumptions

are taken to distinguish demand-driven from exogenous balance sheet shocks, following Boeckx

et al. (2017) and Burriel and Galesi (2016). More speciﬁcally, in periods of ﬁnancial stress or

other shocks increased demand for liquidity expands the balance sheet, implying that the CISS-

indicator as well as the EONIA increase (see Boeckx et al., 2017). Vice versa, a balance sheet

expansion that is caused by an ECB monetary policy measure should not increase but decrease

both ﬁnancial stress and the demand for liquidity, which is assumed in the sign restrictions

above. Finally, the zero restriction of the MRO rate ensures that the balance sheet increase is

orthogonal to a conventional monetary policy shock. For the response of output and prices, I

ECB Working Paper 2095, August 201712follow the standard approach of deﬁning conventional monetary policy shocks by imposing zero

restrictions to disentangle it from other shocks.

Turning to the respective SEE country, I stay agnostic about potential spillovers on the

domestic interest rate and exchange rate vis-`a-vis the euro (if applicable). To distinguish a

spillover from euro area monetary policy from a domestic monetary policy action9 I impose a zero

restriction on the domestic policy rate rSEE

t

for ﬂoaters, analogous to the zero restriction put on

the MRO-rate. For the potential effect on exports, output, price level and trade partners’ output

I use zero restrictions to disentangle the spillover from domestic real economy disturbances.

Through the choice of variables and structural identiﬁcation, I can investigate the spillover on

each country’s output and price level, as well as the role of the ﬁnancial and real transmission

channels. The acceptance rates of the structural matrices are depicted in table 1.

3.4 Data

The time span of the baseline model covers the period between January 2008 and December

2015. As a measure of output I use GDP, interpolated by the Chow-Lin method with industrial

production10 to obtain data with monthly frequency. The price level is measured as the consumer

price inﬂation (harmonised consumer price inﬂation in the case of EU countries) index expressed

in 2010 levels. As indicator for a potential ﬁnancial channel I use short-term interest rates, as

asset prices or longer-term interest rates are not available. More speciﬁcally, I include monthly

end-of-period values of three-month interbank market rates, with the exception of Bosnia and

Herzegovina as well as Montenegro, which do not publish interbank market rates. In the case

of Montenegro, an unweighted average of three-month and six-month government T-bill rates is

used as a proxy for interbank market rates. For Bosnia and Herzegovina, no such short-term in-

terest rate exists. Therefore, following the approach of Cerutti et al. (2010), I create a composite

series that consists to two-thirds of retail deposit rates and to one-third of retail lending rates,

both in the corporate sector. All exchange rates are expressed in average local currency vis-`a-vis

the euro, so an increase in the exchange rate depicts a depreciation and vice versa. Exports

to the euro area are limited to merchandise exports, which means that service exports are not

9Between January 2008 and December 2015, SEE countries operating under an inﬂation targeting regime have
substantially lowered their key policy rates: cumulatively rates were decreased by 450 bps in Albania, 575 bps in
Romania and 550 bps in Serbia.

10With the exception of Montenegro, where GDP is not available for the whole time span and therefore industrial

production is used for output.

ECB Working Paper 2095, August 201713captured in the model. Export data is derived from the IMF’s direction of trade statistics and

converted from dollars into euros. All variables enter the model in monthly frequency and in

levels. Moreover, all variables are seasonally adjusted by the U.S. Census Bureaus X-13 seasonal

adjustment procedure in EViews and are transformed into their natural logs (with the exception

of ﬁnancial variables). The data sources are national central banks, national statistical ofﬁces,

Eurostat, the ECB, the IMF’s direction of trade statistics and Bloomberg.

4 Results

4.1 The effect of a non-standard monetary policy shock on the euro area

economy

I start by looking at the transmission of an expansionary balance sheet shock within the euro

area. The impulse response functions of the euro area are displayed in ﬁgure 2, where the

continuous line depicts the median posterior response and the shaded area represents 68 percent

of the credibility interval. Because the variables enter the model in natural logs, the y-axis

reports percentage changes, except for ﬁnancial variables which are depicted in percentage point

changes. The one standard deviation (0.7 percent increase) balance sheet shock seems to be very

persistent, as it does not fade out completely even after two years. The accompanying decline

of the CISS indicator lasts for approximately 15 months, and the decrease of the EONIA-MRO

spread has a half life of approximately four months. Turning to the macroeconomic effects, the

impulse responses suggest that output rises gradually with a peak increase of 0.02 percent after

eight months, and a complete fade-out after 21 months. The price level increase reaches the

peak of 0.02 percent after 13 months and, in line with economic theory, the response seems to

be relatively persistent.

4.2 Results for individual SEE countries

The response of the Albanian economy to a non-standard monetary policy shock is shown in

ﬁgure 3. An expansionary euro area balance sheet shock does not signiﬁcantly aﬀect the Albanian

output, while the price level responds with an increase of 0.02 percent after twelve months. The

exchange rate of the lek vis-`a-vis the euro does not show a pronounced response to the shock,

which is in line with the fact that it has ﬂuctuated only slightly against the euro in the sample

ECB Working Paper 2095, August 201714period11. The transmission of a euro area balance sheet shock on the Albanian interbank interest

rate is uncertain in the short term, while in the medium term the interest rate rises in line with

the increase of the policy rate. Albania’s exports rise as a response to the balance sheet shock,

while the signiﬁcant output response of Albania’s trade partners suggests that spillovers might

also be indirectly transmitted.

In the case of Bosnia and Herzegovina, the economic response to a non-standard euro area

monetary policy shock is depicted in ﬁgure 4.

It is puzzling, as output seems to contract

following the shock with a trough of 0.01 percent that fades out after two years. However, it

should be noted that this response might by blurred by some structural breaks in the underlying

data, related to severe ﬂoods in 2014 and the termination of the IMF-programme in 2015.

Notwithstanding the negative output response, the price level increases gradually with a peak

increase of 0.02 percent after twelve months, which seems to be relatively persistent. The

interest rate – which in Bosnia and Herzegovina’s case is a composite retail rate – does not seem

to respond signiﬁcantly to the shock. Exports, on the other hand, react relatively strongly with

a peak increase of 0.3 percent after ﬁve months, as does the output of Bosnia and Herzegovina’s

trade partners.

For Bulgaria (see ﬁgure 5), the output response is positive (not strictly signiﬁcant, but

the mass of posteriors lies above zero), with a peak after eleven months. The price level also

increases as a response to the shock, reaching the peak of 0.3 percent after 13 months. Regarding

potential transmission channels, it seems that the monetary policy shock is not transmitted via

the Bulgarian interbank market rate, since its posterior mass is relatively widespread. Also,

the export channel does not seem to play a role in transmitting non-standard monetary policy

shocks to Bulgaria, as both exports as well as trade partners’ output do not exhibit a signiﬁcant

response to the shock. However, one should keep in mind that exports denote only merchandise

exports here, while service exports are not taken into account. The pronounced reaction of

output and prices in Bulgaria are in line with the results of H´ajek and Horv´ath (2016) for

conventional monetary policy spillovers.

In the case of Croatia (see ﬁgure 6), the response of output is positive and peaks at 0.05

percent after eight months, which makes it one of the strongest output responses in the region

(see subsection 4.3). The response of the price level is also positive and signiﬁcant with a peak at

0.03 percent after 24 months. Both the output as well as the price responses are in line with what

11Between 2008 and 2015 the average monthly ﬂuctuation against the euro amounted to 0.5 percent.

ECB Working Paper 2095, August 201715H´ajek and Horv´ath (2016) ﬁnd for conventional monetary policy spillovers12. Croatia’s interbank

market rate exhibits an initial increase, although not at signiﬁcant levels, which turns into a

signiﬁcant negative response after four months with a trough at 0.05 percentage points. This

relatively pronounced response suggests that the ﬁnancial channel plays a role in transmitting

shocks from the euro area to Croatia. Conversely, exports respond negatively to the shock,

despite the fact that the output of Croatia’s trade partners increases. However, as service

exports are not accounted for, the response of exports might be not entirely captured.

The response of the economy of the former Yugoslav Republic of Macedonia is depicted

in ﬁgure 7. The results suggest that the euro area non-standard monetary policy shock does

not trigger a signiﬁcant output response, while the price level response is strongly positive

with a peak of 0.05 percent after eight months. The increased euro area liquidity seems to be

immediately transmitted to the interbank market rate, which decreases by a maximum of 0.05

percentage points after ﬁve months. Exports increase – although not strictly signiﬁcantly –

relatively strongly at 0.4 percent after eight months, and indirect trade links might also play a

role as the positive output response of the country’s trade partners suggests. The results for

the interest rate response are in line with Petrevski et al. (2015) for a conventional euro area

interest rate shock; however, they ﬁnd a diﬀerent response of the price level.

For Montenegro, an exogenous expansion of the Eurosystem’s balance sheet translates into

a pronounced rise of industrial production by 0.5 percent after four months. The price level also

increases and peaks after eleven months. The euro area monetary policy shock does not seem

to transmit into the short-term interest rate, which is in the case of Montenegro a composite of

three- and six-month T-bill rates. Montenegro’s exports seem to rise by 0.4 percent after ﬁve

months, while its trade partners’ output also increases as a response to the shock.

Spillovers to Romanian output from the non-standard monetary policy shock seem to be

muted (compare ﬁgure 9). This result is diﬀerent from the ﬁndings of H´ajek and Horv´ath

(2016) and Bluwstein and Canova (2016), who conclude that a contractionary conventional euro

area monetary policy shock initially increases Romanian output (or that an expansionary non-

standard monetary policy output decreases Romanian output, respectively). The response of

prices, on the other hand, is positive with a peak increase of 0.04 percent after eleven months.

The exchange rate does not signiﬁcantly react to the euro area shock, which is in line with

12Conversely, Petrevski et al. (2015) ﬁnd that a contractionary conventional euro area interest rate shock

increases Croatia’s price level.

ECB Working Paper 2095, August 201716the relative exchange rate stability of the lei vis-`a-vis the euro since mid-201213. Similarly,

the response of the interest rate is uncertain in the short run and turns signiﬁcantly positive

some months after the shock. The exchange rate response conﬁrms the outcome of the event

study by Falagiarda et al. (2015), while according to them the short-term money market rate is

signiﬁcantly affected, which is not reﬂected in the results. Exports seem to react negatively to

the shock and the trade partners’ output seems to be isolated from the euro area shock, which

might explain the overall muted output response of the Romanian economy.

Serbia’s output (see ﬁgure 10) increases with a peak of 0.05 percent after eight months, which

is one of the strongest output responses compared to the other countries in the region. Equally,

the price response is very pronounced with a peak increase of 0.07 percent after eight months,

which inter alia can be explained by the strong contribution of euro area import prices to

inﬂation pressures in the past (see e.g. International Monetary Fund, 2011). Both the interbank

interest rate as well as the exchange rate14 do not seem to be aﬀected signiﬁcantly by the shock,

while Serbia’s key policy rate rises in the medium term. Exports seem to react positively to the

shock and the trade partners’ output also rises in the medium term after an initial period of

uncertainty.

4.3 Cross-country comparison and discussion

In this subsection a horizontal comparison of the countries’ responses to a non-standard monetary

policy shock is undertaken. Following the euro area shock, all countries exhibit a distinct price

level response (see ﬁgure 11), where it can be observed that the peak response is by far the

strongest for Serbia, followed by the former Yugoslav Republic of Macedonia, Romania and

Bulgaria. The relatively strong price responses, which are for around half of the countries

stronger than the euro area response itself, are in line with the high share of imports from the

euro area that range from around one third to over 50 percent of all imports in SEE countries.

Output responses to a euro area expansionary non-standard monetary policy shock are pos-

itive for approximately half of the countries, where it can be observed that the output response

is largest for Croatia, followed by Serbia and Bulgaria. Montenegro’s output also responds pos-

itively, but is measured in industrial production, thus the effect on GDP is unknown. While the

13From mid-2012 to end-2015 the average monthly ﬂuctuation against the euro amounted to 0.7 percent, as

compared to 1.2 percent from 2008 up to mid-2012.

14Compared to Albania and Romania, Serbia’s exchange rate ﬂuctuated relatively strong vis-`a-vis the euro in

the sample period with an average monthly ﬂuctuation of 1.1 percent.

ECB Working Paper 2095, August 201717output of the Albanian, former Yugoslav Republic of Macedonian and Romanian economies does

not respond signiﬁcantly to the shock, Bosnia and Herzegovina seems to be the only country

that is negatively affected. Compared to the transmission of the balance sheet shock within the

euro area, the spillovers are sizable and in the case of Croatia and Serbia even larger than in

the euro area itself.

Comparing the peak responses across countries, the results suggest that the exchange rate

regime does not play a signiﬁcant role in shaping the size and magnitude of output and price

spillovers, as countries with ﬂexible exchange rates lie on opposite ends of the range. This result

is not surprising, as for the three countries operating under a ﬂexible exchange rate regime none

of the domestic exchange rates shows a pronounced response to the euro area balance sheet shock

in the model output, which is in line with the very stable exchange rates in the case of Albania

and Romania in the sample period. Thus, in south-eastern Europe ﬂexible exchange rates did

not seem to act as shock absorbers during the time period covered. This ﬁnding is in line with

Bluwstein and Canova (2016), who argue that the exchange rate channel is not important for

unconventional monetary policy transmission (which is different from the conventional case).

Regarding potential transmission channels, the comparison suggests that the impact of a

non-standard monetary policy shock on SEE exports to the euro area is the largest for the

former Yugoslav Republic of Macedonia and Montenegro, followed by Bulgaria, Serbia and Al-

bania. On the other hand, the real transmission channel does not seem to be considerable in

Bulgaria, where no signiﬁcant increase of exports can be observed, and in Croatia and Roma-

nia where exports react negatively to the balance sheet shock. Taking into account both the

ﬁnancial and the real transmission channels, it seems that for a majority of countries spillovers

are transmitted via exports, while the interest rate channel plays a signiﬁcant role only in two

countries. This result reﬂects the signiﬁcant bank cross-border deleveraging many SEE coun-

tries experienced after the crisis. In some countries (e.g. Albania, Romania), spillovers via both

transmission channels might work in opposite directions and therefore lead to a non-signiﬁcant

output response. However, a word of caution is necessary here: both indicators, exports and

interest rates, suffer from drawbacks due to data availability. Exports here denote only merchan-

dise exports, since exports of services are not available, which might underestimate the export

channel in countries with a high share of service exports, e.g. Croatia. In the case of ﬁnancial

ﬂows, changes in the interbank market rate might not capture foreign direct or portfolio inﬂows,

and therefore underestimate the role of the ﬁnancial channel in transmitting shocks.

ECB Working Paper 2095, August 201718With regard to indirect spillovers, the composite output of trade partners responds especially

strongly in the case of Bosnia and Herzegovina, the former Yugoslav Republic of Macedonia and

Albania, while the response seems to be smaller for Montenegro, Croatia and Serbia, and absent

for Bulgaria and Romania. However, the approach taken can only give an idea of the possible

role of indirect spillovers, as I do not test for spillovers of the trade partners’ output on SEE

countries.

5 Robustness testing

To test whether the results hold for different model speciﬁcations or variable choices, I perform

a number of robustness checks. As discussed in subsection 3.1, besides balance sheet assets,

shadow rates can also be used as an indicator for non-standard monetary policy measures.

To see whether the results are robust to an expansionary shadow rate shock (where I use the

shadow rate developed by Wu and Xia, 2016), I keep all other variables and the shock identiﬁ-

cation unchanged. The only difference is that an expansionary shock implies that the shadow

rate decreases, which means that the sign restriction for the shadow rate is turned into negative.

Moreover, the period for the restriction is changed to impact and the ﬁrst month following the

shock. This is based on the fact that the shadow rate incorporates also announcement effects,

which is not the case for balance sheet assets, and thus is expected to immediately react to the

shock.

shadowEA

t

CISSt

spreadEA

t

M ROt

yEA
t

pEA
t

iSEE
t

-

0-1

−

0-1

−

0-1

0

0

0

·

et

·

rSEE
t

ySEE
t

xSEE
t

pSEE
t

0

0

0

0

y∗
t

0

Note: 0 indicates that the immediate response is restricted, while + (−) indicate that only a positive (negative)
reaction is permitted in the respective period (see third row).
· denotes that no restriction is placed on the
variable.

The results of a one standard deviation shadow rate shock for the euro area are depicted

in ﬁgure 12. The double lines represent the credibility interval of the shadow rate shock, while

the shaded area indicates the credibility interval of the baseline model. Compared to a balance

sheet shock (see ﬁgure 2), the shadow rate shock is more short-lived, as it fades out completely

after approximately twelve months. Regardless of the diﬀerent time horizon, the responses of

ECB Working Paper 2095, August 201719the ﬁnancial variables (CISS, EONIA-MRO spread and MRO) are very similar. The effects on

output and prices are also in line with the baseline model, although the credibility intervals are

larger when using the shadow rate as an indicator for non-standard monetary policy measures.

The spillovers to output and price levels of the SEE countries are depicted in ﬁgures 13 and 14.

The outcome is qualitatively in line with the baseline model, with the notable exception of the

price level response of Serbia, which turns negative if the shadow rate is taken as an indicator for

non-standard monetary policy measures. Interestingly, an appreciation of the exchange rate can

now be observed in the shadow rate model output15, that might cause disinﬂationary pressures

on the price level response. This result conﬁrms the prior ﬁndings that the exchange rate regime

only inﬂuences the shock response if the exchange rate also shows a distinct response.

Moreover, I re-estimate all models by using only the position ‘Securities held for monetary

policy purposes’ (A070100) of the Eurosystem’s balance sheet. As discussed in subsection 3.1,

this balance sheet position reﬂects the most exogenous non-standard monetary policy measure

and therefore serves as another robustness test for exogenous monetary policy shocks. Further-

more, I can also infer from the results whether spillovers of securities purchases are different

to composite spillovers of all programmes. The results are robust with the exception of the

Serbian price level response, which is similar to the previous robustness test. Finally, since the

monthly balance sheet expansions have been pre-announced from the start of the APP, implying

that they are anticipated, I additionally conduct a robustness check with a shorter sample until

December 2014 (instead of December 2015). The results obtained from the shorter sample are

in line with the baseline model.

6 Conclusion

This paper is the ﬁrst one to comprehensively assess the economic impact of the euro area’s

non-standard monetary policy measures on the countries of south-eastern Europe (SEE). By

employing bilateral structural BVAR models, I are able to identify macroeconomic spillovers

as well as potential transmission channels for each country individually. Three questions are

addressed in this paper: ﬁrst, how have the ECB’s non-standard monetary policy measures

been affecting the SEE countries? Second, which channels are transmitting these shocks to

SEE? Third, do diﬀerent exchange rate regimes play a role in the SEE countries’ responses to

15For brevity reasons the responses of all variables are not displayed here, but are available upon request from

the author.

ECB Working Paper 2095, August 201720the shock?

The results show that the price level of all countries is positively affected by an expansionary

non-standard monetary policy shock originating in the euro area, in line with the importance of

euro area imports in total imports. Compared to the euro area response of the price level, the

inﬂationary effect on SEE is larger for around half of the countries. With regard to the output

response, the shock has an expansionary effect in approximately four out of eight countries,

which is in some cases also more pronounced than the euro area output response. These results

are conﬁrmed by a number of robustness checks.

Regarding possible transmission channels, I ﬁnd that spillovers seem to be mostly transmitted

via the export channel, while only in two countries the interest rate channel plays a signiﬁcant

role, in line with the signiﬁcant bank cross-border deleveraging many SEE countries experienced

after the crisis. Nevertheless, ﬁnancial ﬂows in the form of foreign direct or portfolio investments,

which are not captured in the model, still might play a role.

With respect to the exchange rate regime, I ﬁnd no inﬂuence of it on the price level or output

responses. This is in line with the absence of a distinct exchange rate response in the model

output for the countries under a ﬂexible regime, which can in turn be explained by the very

stable exchange rate the respective currencies have exhibited vis-`a-vis the euro in the past years.

Therefore, it seems that ﬂexible exchange rates did not act as buﬀers to mitigate spillovers.

The current work could be extended into various directions. A comparison between the

spillovers of euro area non-standard and euro area conventional monetary policy measures could

indicate whether these measures have different international effects. Moreover, future research

might include additional variables to shed more light on potential transmission channels; espe-

cially the role of ﬁnancial transmission could be further explored and other channels not covered

here could be added (e.g. conﬁdence channel). Finally, a comparison with spillovers from non-

standard monetary policy measures undertaken by the central banks of other large advanced

economies (notably the US) would shed light on the relative importance of euro area non-

standard monetary policy, and be helpful for policymakers to design optimal policy responses

to advanced economies’ monetary policy measures and their (potential) reversal.

ECB Working Paper 2095, August 201721Tables and Figures

Table 1: Acceptance rates of structural matrices

Albania
Bosnia and Herzegovina
Bulgaria
Croatia
Former Yugoslav Republic of Macedonia
Montenegro
Romania
Serbia

19.52%
16.95%
18.19%
16.30%
19.58%
20.51%
15.43%
19.51%

Figure 1: Indicators of non-standard monetary policy measures

Sources: ECB, Wu and Xia (2016)

00.511.522.533.5-6-4-2024682007200820092010201120122013201420152016Key policy rate in % (lhs)Balance sheet assets in EUR tn (rhs)-6-4-2024682007200820092010201120122013201420152016Key policy rate in %Shadow rate in %ECB Working Paper 2095, August 201722Figure 2: Euro area: Response to a balance sheet shock

Note: Response of variables to an expansionary one standard deviation Eurosystem balance sheet shock. The
shaded regions report pointwise 68 percent credibility intervals. The x-axis reports months, the y-axis monthly
growth rates in percent for all variables except for ﬁnancial variables, where percentage point changes are depicted.

-0.500.511.506121824Eurosystem balance sheet assets-0.02-0.0100.0106121824CISS-0.04-0.03-0.02-0.0100.0106121824EONIA-MRO spread-0.0100.010.0205101520MRO (Key policy rate)-0.04-0.0200.020.040.0606121824Output-0.0100.010.020.030.0406121824Price levelECB Working Paper 2095, August 201723Figure 3: Albania: Response to a balance sheet shock

Note: Response of variables to an expansionary one standard deviation Eurosystem balance sheet shock. The
shaded regions report pointwise 68 percent credibility intervals. The x-axis reports months, the y-axis monthly
growth rates in percent for all variables except for interest rates, which depict changes in percentage points.

-0.04-0.0200.020.040.0606121824Output-0.0500.050.106121824Price level-0.2-0.100.10.206121824Exchange rate-0.04-0.0200.020.0406121824Interest rate-0.6-0.4-0.200.20.40.606121824Exports-0.100.10.206121824Trade partners-0.0100.010.0206121824Policy rateECB Working Paper 2095, August 201724Figure 4: Bosnia and Herzegovina: Response to a balance sheet shock

Note: Response of variables to an expansionary one standard deviation Eurosystem balance sheet shock. The
shaded regions report pointwise 68 percent credibility intervals. The x-axis reports months, the y-axis monthly
growth rates in percent for all variables except for the interest rate, which depicts changes in percentage points.

-0.06-0.04-0.0200.0206121824Output-0.0500.050.106121824Price level-0.1-0.0500.050.106121824Interest rate-0.4-0.200.20.40.60.806121824Exports-0.100.10.206121824Trade partnersECB Working Paper 2095, August 201725Figure 5: Bulgaria: Response to a balance sheet shock

Note: Response of variables to an expansionary one standard deviation Eurosystem balance sheet shock. The
shaded regions report pointwise 68 percent credibility intervals. The x-axis reports months, the y-axis monthly
growth rates in percent for all variables except for the interest rate, which depicts changes in percentage points.

-0.04-0.0200.020.040.0606121824Output-0.0500.050.106121824Price level-0.04-0.0200.020.0406121824Interest rate-0.4-0.200.20.406121824Exports-0.15-0.1-0.0500.050.106121824Trade partnersECB Working Paper 2095, August 201726Figure 6: Croatia: Response to a balance sheet shock

Note: Response of variables to an expansionary one standard deviation Eurosystem balance sheet shock. The
shaded regions report pointwise 68 percent credibility intervals. The x-axis reports months, the y-axis monthly
growth rates in percent for all variables except for the interest rate, which depicts changes in percentage points.

-0.0500.050.10.1506121824Output-0.0200.020.040.0606121824Price level-0.2-0.100.10.20.306121824Interest rate-0.8-0.6-0.4-0.200.20.406121824Exports-0.100.10.206121824Trade partnersECB Working Paper 2095, August 201727Figure 7: Former Yugoslav Republic of Macedonia: Response to a balance sheet shock

Note: Response of variables to an expansionary one standard deviation Eurosystem balance sheet shock. The
shaded regions report pointwise 68 percent credibility intervals. The x-axis reports months, the y-axis monthly
growth rates in percent for all variables except for the interest rate, which depicts changes in percentage points.

-0.04-0.0200.020.040.0606121824Output-0.0200.020.040.060.0806121824Price level-0.1-0.0500.0506121824Interest rate-0.500.5106121824Exports-0.100.10.206121824Trade partnersECB Working Paper 2095, August 201728Figure 8: Montenegro: Response to balance sheet shock

Note: Response of variables to an expansionary one standard deviation Eurosystem balance sheet shock. The
shaded regions report pointwise 68 percent credibility intervals. The x-axis reports months, the y-axis monthly
growth rates in percent for all variables except for the interest rate, which depicts changes in percentage points.

-0.500.5106121824Industrial production-0.0200.020.040.0606121824Price level-0.2-0.100.10.206121824Interest rate-1-0.500.511.506121824Exports-0.100.10.206121824Trade partnersECB Working Paper 2095, August 201729Figure 9: Romania: Response to a balance sheet shock

Note: Response of variables to an expansionary one standard deviation Eurosystem balance sheet shock. The
shaded regions report pointwise 68 percent credibility intervals. The x-axis reports months, the y-axis monthly
growth rates in percent for all variables except for interest rates, which depict changes in percentage points.

-0.1-0.0500.050.106121824Output-0.0500.050.106121824Price level-0.4-0.3-0.2-0.100.10.20.306121824Exchange rate-0.3-0.2-0.100.10.206121824Interest rate-0.6-0.4-0.200.20.406121824Exports-0.3-0.2-0.100.10.20.306121824Trade partners-0.0200.020.0406121824Policy rateECB Working Paper 2095, August 201730Figure 10: Serbia: Response to a balance sheet shock

Note: Response of variables to an expansionary one standard deviation Eurosystem balance sheet shock. The
shaded regions report pointwise 68 percent credibility intervals. The x-axis reports months, the y-axis monthly
growth rates in percent for all variables except for interest rates, which depict changes in percentage points.

-0.0500.050.106121824Output-0.100.10.206121824Price level-0.4-0.200.20.406121824Exchange rate-0.2-0.100.10.206121824Interest rate-0.4-0.200.20.40.606121824Exports-0.2-0.100.10.206121824Trade partners-0.0500.050.106121824Policy rateECB Working Paper 2095, August 201731Figure 11: Comparison of responses to a non-standard monetary policy shock

Note: Peak response to expansionary balance sheet shock within the ﬁrst 12 months in percent. * denotes not
strictly credible responses. ** For Montenegro the response of industrial production is depicted.

-0.0200.020.040.060.080.1ALBA*BG*HRMKME**RORSEA*Output00.010.020.030.040.050.060.070.08AL*BA*BGHRMKMERO*RS*EAPrice level-0.06-0.04-0.0200.020.04ALBABGHRMKMERORSInterest rates-0.3-0.2-0.100.10.20.30.40.5AL*BABGHR*MK*ME*RO*RS*Exports00.020.040.060.080.10.120.14ALBABGHR*MKME*RORSTrade partnersECB Working Paper 2095, August 201732Figure 12: Euro area: Response to a shadow rate shock

Note: The shaded area represents the 68 percent credibility interval of the benchmark model, while the double
lines indicate the credibility interval of the response to an expansionary one standard deviation shadow rate shock.

-0.3-0.2-0.100.106121824Shadow rate-0.03-0.02-0.0100.0106121824CISS-0.05-0.04-0.03-0.02-0.0100.0106121824EONIA-MRO spread-0.0100.010.020.0306121824MRO (Key policy rate)-0.08-0.06-0.04-0.0200.020.040.0606121824Output-0.03-0.02-0.0100.010.020.030.040.0506121824Price levelECB Working Paper 2095, August 201733Figure 13: Response to a shadow rate shock: eﬀect on output

Note: The shaded area represents the 68 percent credibility interval of the benchmark model, while the double
lines indicate the credibility interval of the response to an expansionary one standard deviation shadow rate shock.
For Montenegro industrial production is taken as a measure for output.

-0.1-0.0500.050.106121824Albania-0.08-0.06-0.04-0.0200.020.0406121824Bosnia and Herzegovina-0.06-0.04-0.0200.020.040.0606121824Bulgaria-0.1-0.0500.050.10.1506121824Croatia-0.0500.050.10.1506121824FYR Macedonia-0.500.511.506121824Montenegro-0.1-0.0500.050.10.1506121824Romania-0.0500.050.10.150.206121824SerbiaECB Working Paper 2095, August 201734Figure 14: Response to a shadow rate shock: eﬀect on price level

Note: The shaded area represents the 68 percent credibility interval of the benchmark model, while the double
lines indicate the credibility interval of the response to an expansionary one standard deviation shadow rate shock.

-0.1-0.0500.050.10.1506121824Albania-0.06-0.04-0.0200.020.040.0606121824Bosnia and Herzegovina-0.1-0.0500.050.106121824Bulgaria-0.0200.020.040.0606121824Croatia-0.0200.020.040.060.0806121824FYR Macedonia-0.0500.050.106121824Montenegro-0.1-0.0500.050.106121824Romania-0.3-0.2-0.100.10.206121824SerbiaECB Working Paper 2095, August 201735References

Arias, J. E., Rubio-Ramirez, J. F., and Waggoner, D. F. (2014).

Inference based on SVAR

identiﬁed with sign and zero restrictions: Theory and applications. CEPR Discussion Paper

9796, Centre for Economic Policy Research.

Babeck´a Kucharˇcukov´a, O., Claeys, P., and Vaˇs´ıˇcek, B. (2016). Spillover of the ECB’s mone-

tary policy outside the euro area: How diﬀerent is conventional from unconventional policy?

Journal of Policy Modeling, 38:199–225.

Benkovskis, K., Bessonovs, A., Feldkircher, M., and W¨orz, J. (2011). The transmission of euro

area monetary shocks to the Czech Republic, Poland and Hungary: Evidence from a FAVAR

model. Focus on European Economic Integration, 2011(3):8–36.

Bluwstein, K. and Canova, F. (2016). Beggar-thy-neighbor? The international eﬀects of ECB

unconventional monetary policy measures. International Journal of Central Banking, 12:69–

120.

Boeckx, J., Dossche, M., and Peersman, G. (2017). Eﬀectiveness and transmission of the ECBs

balance sheet policies. International Journal of Central Banking, 13:297–333.

Burriel, P. and Galesi, A. (2016). Uncovering the heterogeneous eﬀects of ECB unconventional

monetary policies accross euro area countries. Working Paper 1631, Banco de Espan˜a.

Canova, F. (2005). The transmission of US shocks to Latin America. Journal of Applied

Econometrics, 20:229–251.

Cerutti, E., Ilyina, A., Makarova, Y., and Schmieder, C. (2010). Bankers without borders? Im-

plications of ring-fencing for European cross-border banks. IMF Working Paper WP/10/247,

International Monetary Fund.

Chen, Q., Filardo, A., He, D., and Zhu, F. (2012).

International spillovers of central bank

balance sheet policies. In Are central bank balance sheets in Asia too large?, volume 66, pages

220–264. Bank for International Settlements.

Chen, Q., Filardo, A., He, D., and Zhu, F. (2015). Financial crisis, US unconventional mon-

etary policy and international spillovers. BIS Working Paper 494, Bank for International

Settlements.

ECB Working Paper 2095, August 201736Ciarlone, A. and Colabella, A. (2016). Spillovers of the ECB’s non-standard monetary policy

into CESEE economies. Occasional Paper 351, Banca d’Italia.

Crespo Cuaresma, J., Doppelhofer, G., Feldkircher, M., and Huber, F. (2016). US monetary

policy in a globalized world, mimeo.

Cushman, D. O. and Zha, T. (1997).

Identifying monetary policy in a small open economy

under ﬂexible exchange rates. Journal of Money, Credit and Banking, 39:433–448.

Dieppe, A., Legrand, R., and van Roye, B. (2016). The BEAR toolbox. ECB Working Paper

1934, European Central Bank.

European Central Bank (2016). The international role of the euro. Technical report, ECB.

Falagiarda, M., McQuade, P., and Tirp´ak, M. (2015). Spillovers from the ECB’s non-standard

monetary policies on non-euro area EU countries: evidence from an event-study analysis. ECB

Working Paper 1869, European Central Bank.

Feldkircher, M. (2015). A global macro model for emerging europe. Journal of Comparative

Economics, 43:706–726.

Fratzscher, M., Duca, M. L., and Straub, R. (2016). On the international spillovers of US

quantitative easing. The Economic Journal.

Friedman, M. (1953). Essays in Positive Economics, chapter The case for ﬂexible exchange

rates. University of Chicago Press.

Gambacorta, L., Hofmann, B., and Peersman, G. (2014). The eﬀectiveness of unconventional

monetary policy at the zero lower bound: A cross-country analysis. Journal of Money, Credit

and Banking, 46:615–642.

Georgiadis, G. (2016). Determinants of global spillovers from US monetary policy. Journal of

International Money and Finance, 67:41–61.

Georgiadis, G. and Gr¨ab, J. (2015). Global ﬁnancial market impact of the announcement of

the ECB’s extended asset purchase programme. Working Paper 232, Federal Reserve Bank

of Dallas Globalization and Monetary Policy Institute.

ECB Working Paper 2095, August 201737H´ajek, J. and Horv´ath, R. (2016). The spillover eﬀect of euro area on Central and Southeastern

European economies: A global VAR approach. Open Economies Review, 27:359–385.

Halova, K. and Horv´ath, R. (2015). International spillovers of ECBs unconventional monetary

policy: The eﬀect on Central and Eastern Europe. IOS Working Paper 351, Institut f¨ur Ost-

und S¨udosteuropaforschung.

Holl´o, D., Kremer, M., and Duca, M. L. (2012). CISS - a composite indicator of systemic stress

in the ﬁnancial system. ECB Working Paper 1426, European Central Bank.

International Monetary Fund (2011). Republic of Serbia: Seventh review and inﬂation consul-

tation under the Stand-By Arrangement. IMF Country Report 11/95.

Jaroci´nski, M. (2010). Responses to monetary policy shocks in the east and the west of Europe:

a comparison. Journal of Applied Econometrics, 25:833–868.

Jim´enez-Rodriguez, R., Morales-Zumaquero, A., and `Egert, B. (2010). The VARying eﬀect of

foreign shocks in Central and Eastern Europe. Journal of Policy Modeling, 32:461–477.

Krippner, L. (2015). A comment on Wu and Xia (2015), and the case for two-factor Shadow

Short Rates. CAMA Working Paper 48/2015, Centre for Applied Macroeconomic Analysis.

Lombardi, M. and Zhu, F. (2014). A shadow policy rate to calibrate US monetary policy at the

zero lower bound. BIS Working Paper 452, Bank for International Settlements.

Ma´ckowiak, B. (2006). How much of the macroeconomic variation in Eastern Europe is at-

tributable to external shocks? Comparative Economic Studies, 48:523–544.

Ma´ckowiak, B. (2007). External shocks, U.S. monetary policy and macroeconomic ﬂuctuations

in emerging markets. Journal of Monetary Economics, 54:2512–2520.

Meade, J. (1951). The Theory of International Economic Policy, Vol. 1: The Balance of Pay-

ments. Vol. 2: Trade and Welfare, with “Mathematical Supplements.”. Oxford University

Press.

Minea, A. and Rault, C. (2011). External monetary shocks and monetary integration: Evidence

from the bulgarian currency board. Economic Modelling, 28:2271–2281.

ECB Working Paper 2095, August 201738Miniane, J. and Rogers, J. H. (2007). Capital controls and the international transmission of

U.S. money shocks. Journal of Money, Credit and Banking, 39:1003–1035.

Peersman, G. (2011). Macroeconomic eﬀects of unconventional monetary policy in the euro

area. ECB Working Paper 1397, European Central Bank.

Petrevski, G., Exterkate, P., Tevdovski, D., and Bogoev, J. (2015). The transmission of foreign

shocks to South Eastern European economies: A Bayesian VAR approach. Economic Systems,

(39):632–643.

Potjagailo, G. (2017). Spillover eﬀects from euro area monetary policy across the EU: a factor-

augmented VAR approach. Journal of International Money and Finance, 72:127–147.

Sahay, R., Arora, V., Arvanitis, T., Faruqee, H., N’Diaye, P., and Mancini-Griﬀoli, T. (2014).

Emerging market volatility: Lessons from the taper tantrum.

IMF Staﬀ Discussion Note

SDN/14/09, International Monetary Fund.

Wu, J. C. and Xia, F. D. (2016). Measuring the macroeconomic impact of monetary policy at

the zero lower bound. Journal of Money, Credit and Banking, 48:253–291.

ECB Working Paper 2095, August 201739Acknowledgements 

I would like to thank Martin Feldkircher, Philipp Harms, Éva Katalin Polgár, Georgios Georgiadis, the members of the ESCB's 
International Relations Committee, participants of the JGU Mainz Brown Bag Seminar and of an internal ECB seminar, and an 
anonymous referee for helpful comments and suggestions; and Li Savelin for data assistance. The views expressed in this paper are 
mine and do not necessarily reflect those of the ECB or of the ESCB. 

Isabella Moder 
European Central Bank, Frankfurt am Main, Germany; email: isabella.moder@ecb.europa.eu 

© European Central Bank, 2017 

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ISSN 
ISBN 

1725-2806 (pdf) 
978-92-899-2817-5 (pdf)

DOI 
EU catalogue No 

10.2866/830401 (pdf) 
QB-AR-17-107-EN-N (pdf)