the third round of the euro area enlargement: are the
TRANSCRIPT
The Third Round of the Euro Area Enlargement: Are the Candidates Ready?
Milan Deskar-Škrbić, Karlo Kotarac, Davor Kunovac
Zagreb, July 2019
Working Papers W-57
PUBLISHERCroatian National Bank Publishing Department Trg hrvatskih velikana 3, 10000 Zagreb Phone: +385 1 45 64 555 Contact phone: +385 1 45 65 006 Fax: +385 1 45 64 687
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EDITOR-IN-CHIEFLjubinko Jankov
EDITORIAL BOARDVedran Šošić Gordi Sušić Davor Kunovac Tomislav Ridzak Evan Kraft Maroje Lang Ante Žigman
EDITORRomana Sinković
The views expressed in this paper are not necessarily the views of the Croatian National Bank.Those using data from this publication are requested to cite the source.Any additional corrections that might be required will be made in the website version.
ISSN 1334-0131 (online)
Zagreb, July 2019
WORKING PAPERS W-57
The Third Round of the Euro Area Enlargement: Are the Candidates Ready?
Milan Deskar-Škrbić, Karlo Kotarac, Davor Kunovac
The Third Round of the Euro Area Enlargement: Are the
Candidates Ready? ∗
Milan Deskar-Škrbic, Karlo Kotarac, Davor Kunovac
Modelling Department, Croatian National Bank
July 1, 2019
Abstract
In this paper, we study the readiness of Bulgaria, Croatia and Romania to adopt
the common monetary policy of the ECB in the context of the third round of euro area
enlargement. Following the later stages of the optimal currency area (OCA) theory we
focus on the coherence of economic shocks between candidate countries and the euro
area and analyse the relevance of euro area shocks for key macroeconomic variables in
these countries. Our results, based on a novel empirical approach, show that the overall
importance of those shocks that are relevant for the ECB is fairly similar in candidate
countries and the euro area. The cost of joining the euro area should, therefore, not be
pronounced, at least from the aspect of the adoption of the common counter-cyclical
monetary policy. This conclusion holds for all three candidates, despite important
differences in monetary and exchange rate regimes.
JEL classification : E32, E52, F45
Keywords: euro area enlargement, economic shocks, BVAR, common monetary pol-
icy, Mundellian trilemma
∗Authors want to thank Ljubinko Jankov, Alan Bobetko, Marina Kunovac, Maja Bukovšak, Enes Ðo-zovic, Nina Pavic, Ozana Nadoveza Jelic, Katarina Ott, Jan Bruha and Martin Feldkircher for useful com-ments and suggestions. Also, authors want to thank participants of the Economic workshop in CroatianNational Bank, participants of the 13th International Conference "Challenges of Europe" and participantsof the 25th Dubrovnik Economic Conference for additional useful comments and suggestions.
1 Introduction
Euro area enlargement is an ongoing process. After the first eleven countries adopted the
euro in 1999 and Greece joined the euro area in 2001, the second round of enlargement
started with Slovenia in 2007 and ended with the euro adoption in Lithuania in 2015.
Today, the euro area comprises nineteen countries, with more than 340 million people and
contributes around sixteen percent to total world output.
On the twentieth anniversary of the euro, EU offi cials intensified discussion on the
third round of the enlargement as Bulgaria, Croatia and Romania started preparations to
join the Exchange Rate Mechanism (ERM II) and the euro area in the near future. The
ERM II is sometimes referred to as a euro waiting room, in which candidate countries
have to prove their ability to maintain macroeconomic and fiscal stability for at least two
years prior to joining the euro area. Croatia adopted the Strategy for euro adoption in 2017
(Eurostrategy, 2017), Bulgaria sent a letter on ERM II participation in 2018 and Romanian
offi cials set the date for euro area membership in 2024 and organised a commission for euro
adoption. The three candidates, all small open economies1, have thus clearly expressed
their willingness to join the euro area. On the other hand, there is a lack of more formal
evidence in the literature on their (in)ability smoothly to adopt the common currency and
monetary policy of the European Central Bank (ECB).
The aim of this paper is, therefore, twofold. First, to provide a broader analytical back-
ground to the discussion on the third round of euro area enlargement in general. Second,
to address the readiness of the three candidate countries to adopt the euro and common
monetary policy of the ECB. Here, we focus on the key aspect of euro area enlargement for
the candidate countries and study the potential costs of the loss of monetary sovereignty
in these countries. More precisely, we are interested in whether the common countercycli-
cal monetary policy of the ECB is likely to be suitable for these countries once they join
the monetary union. This question is even more interesting as these countries are small
1Stylised facts on these economies are discussed in Appendix A.
1
open economies with free capital flows and they all have different exchange rate regimes.
According to the IMF classification, Bulgaria operates under the regime of currency board
(EUR), Croatia implements a stabilized arrangement with an exchange rate anchor (EUR)
and Romania pursues an inflation targeting strategy, with a (managed) floating exchange
rate (EUR).
In order to study the readiness of the three economies to adopt the common monetary
policy of the euro area, we focus on the coherence of economic shocks between the euro area
and the euro candidate countries and, therefore, build on the literature on the optimum
currency area (OCA) theory. The similarity of shocks, and policy responses to these shocks,
is almost a catch-all OCA property, or meta-property, capturing the interaction between
several other properties characterizing an optimal currency area, such as business cycle
synchronization, similarity of economic structure or flexibility and movement of factors of
production (Mongelli, 2000). For that reason we investigate the importance of those shocks
that are relevant for the ECB’s monetary policy decisions ("ECB - relevant shocks") to
macroeconomic developments in the euro candidate countries.
Common monetary policy is suitable for all members in a monetary union only if eco-
nomic shocks and their macroeconomic effects in both joining and participating countries
are suffi ciently similar. In other words, those shocks that dominantly drive the business
cycles in participating countries should also play an important role in economic develop-
ments in the candidate countries. The counter-cyclical monetary policy of the ECB would
then successfully smooth out their business cycles. In that case, the loss of an independent
monetary policy should not cause any significant costs, at least from the aspect of the
appropriate counter-cyclical monetary policy. However, the costs related to giving up an
autonomous monetary policy may well depend on the exchange rate regime. This paper
thus formally addresses four main questions:
1. Do standard economic shocks affecting the euro area have similar effects on the three
candidate countries?
2
2. How important are shocks relevant for ECB policy-making process for the three
candidate countries?
3. Do monetary policy shocks of the ECB have the expected counter-cyclical effects on
the euro candidate countries?
4. Does the exchange rate regime matter for the transmission of euro area shocks to the
candidate countries?
To address these questions we rely on a structural Bayesian VAR (BVAR) model.
Several domestic and euro area structural shocks are identified by imposing a large number
of rather uncontroversial short run and long run sign and zero restrictions. Such a model,
if suffi ciently rich, is suitable to assess the relative importance of domestic and euro area
shocks for the candidate countries and therefore to address the readiness of these countries
to adopt the common monetary policy of the ECB.
The main finding of our paper is that euro area (rather than country-specific) shocks
play a dominant role in the fluctuations of output and consumer inflation in Bulgaria,
Croatia and Romania. Such results indicate that the common monetary policy could be
suitable for these countries once they adopt the euro. However there are some differences
among the three countries. The contribution of common shocks to GDP and inflation
is stronger and more similar to the euro area in Bulgaria and Croatia than in Romania.
This can, at least partially, be attributed to the fact that Romania is the only country
among the three that operates under a floating exchange rate regime. However, the con-
tribution of euro area shocks to developments of macroeconomic variables in Romania is
far from negligible, suggesting that the cost of the loss of monetary sovereignty could be
less pronounced than the standard Mundellian trilemma theory suggests. Regarding the
macroeconomic effects of the ECB policy shock, our results show that the effects of mone-
tary policy shocks in Bulgaria, Croatia and Romania are similar to those in the euro area,
which additionally supports the view that the common monetary policy can be suitable
3
for these countries. Finally, although the main focus of our paper is clearly on the three
candidate countries, in order to position our results in a broader context we compare their
similarities with the euro area to those of the other non-euro area EU members - Czechia,
Denmark, Hungary, Poland, Sweden and the UK. Our results support the view that all the
countries under analysis share a large amount of common shocks with the euro area. The
contribution of common shocks to the developments of both GDP and inflation is however
less pronounced in those with floating exchange rate regimes, which supports the view that
floating exchange rates can act as shock absorbers in most of these countries (Farant and
Peersman, 2006; Artis and Ehrmann, 2006; Audzei and Bradzik, 2018).
This paper contributes to related literature along several directions. Most importantly,
this is the first in-depth analysis of the readiness of the three candidate countries to adopt
the common ECB monetary policy in the context of the third round of euro area enlarge-
ment. Secondly, instead of only comparing the correlations of shocks (as in e.g. Bayoumi
and Eichengreen 1992, 1993 and 1994) or considering the relative importance of the euro
area shocks for candidate countries (e.g. Mackowiak, 2006; Peersman 2011; Hanclova,
2012) we propose a methodology based on historical decomposition to directly compare
the overall importance of shocks relevant for ECB policy decisions for macroeconomic vari-
ables in the candidate countries and the euro area. Focusing on the results of historical
decomposition, and not only the correlation of structural shocks, we take into account the
importance of the transmission mechanisms of structural shocks to the economy. Regard-
ing our identification scheme, in contrast to related literature, it is purposely rather loose
- we impose no restrictions onto how domestic variables react to euro area shocks. Such
a modelling decision to let the data speak freely makes these estimates less dependent on
the imposed restrictions and thus clearly more reliable. Finally, we also analyse whether
differences in the relevance of external shocks for non-euro EU economies can be explained
by their exchange rate regimes thus contributing to the literature on the role of exchange
rates as shock absorbers or shock propagators. However, our approach is different from
4
the standard strategy of Clarida and Gali (1994) who study the main sources of variation
in exchange rates. For each country we first estimate the relative importance of foreign
shocks for domestic macroeconomic developments and then look at how these statistics
differ across countries with different exchange rate regimes and with various degrees of
exchange rate volatility. Thus, we contribute to the literature focusing on the relation
between transmission of external shocks and exchange rate regimes (e.g. Canova, 2005;
Iossifov and Podpiera, 2012).
2 OCA theory, external shocks and exchange rate regimes
The aim of this section is to position our research questions in the broader context of
international macroeconomics and explain our choice of the methodology with which to
address these questions.
Following the literature in the later stages of OCA theory (e.g. Bayoumi and Einhen-
green 1992, 1993, 1994; Frankel and Rose 1997, Mongelli 2002), in this paper we emphasize
the importance of the coherence of economic shocks in the context of the loss of the au-
tonomous monetary policy as the most important cost of euro adoption for joining countries
(Eudey 1998). OCA theory postulates that this cost should not be pronounced provided
economic shocks within the monetary union are suffi ciently coherent. This is because the
coherence of economic shocks can be seen as a "catch-all" property of OCA (Mongelli,
2002) as it captures the interaction between several OCA properties, such as business cycle
synchronisation, mobility of factors of production, similarity of economic structures and
so on. Thus, coherence of economic shocks suggests that common monetary policy could
be suitable for all countries in the monetary union. In addition, OCA theory posits that
the cost of losing monetary policy autonomy is low for those countries in which economic
activity is mostly driven by the same shocks driving economic developments in the mon-
etary union. For example, if a euro candidate country is predominantly affected by the
same economic shocks as the euro area and if these shocks affect the two economies in
5
a similar fashion, the common monetary policy can then be adequate for all countries.
On the other hand, if economic activity in a joining country is predominantly driven by
some country-specific shocks, a common monetary policy could be less effective or even
counter-productive.
To take these considerations into account we need to be able to isolate domestic (idio-
syncratic) shocks from those generated abroad (in a monetary union or globally). Those
external shocks are of special interest for this analysis - these are the shocks that the ECB
generally reacts to and calibrates its monetary policy accordingly, i.e. ECB - relevant
shocks. We rely on a structural BVAR to study the importance of these shocks for the
three candidate countries. First, we study how these shocks affect the candidate countries.
If they are also important for their economies we may label them as “common shocks”.
Once we have the common shocks identified, we compare the overall importance of these
shocks for candidate countries to that for the euro area. If the same economic shocks
drive both economies in a similar way, we conclude that common monetary policy could
be suitable for both countries, just as OCA theory suggests.
By focusing on the relevance of external shocks we also complement the literature that
investigates the role of external shocks for economic dynamics in small open European
economies, still outside the euro area. Results in this strand of literature mostly suggest
that euro area shocks play important roles in economic activity in countries like Czechia,
Hungary, Poland and Slovakia (Mackowiak, 2006; Horváth and Rusnák, 2009; Hanclova,
2012) and that the cost of euro adoption would not be pronounced in these countries
(Mackowiak, 2006). In this paper we join this discussion but take a step further by asking
whether differences in the contribution of external shocks to domestic economies among
non-euro area countries can be explained by their different exchange rate regimes.
This leads us to the old debate on the characteristics of fixed vs flexible exchange
rate regimes (McKinnon 1963; Giersch 1973; Ishiyama 1975). This literature views fixed
exchange rates as direct propagators of external shocks to small open economies, while
6
flexible exchange rates can serve as shock absorbers. The standard approach to the ex-
amination of the characteristics of exchange rates as shock absorbers or shock propagators
is based on structural decomposition of exchange rate developments on contributions of
real shocks and nominal shocks (Clarida and Gali, 1994; for CEE Audzei and Bradzik,
2018). Although our model allows us to follow this strand of literature, in this paper we
take a different approach and compare the contributions of common shocks in Bulgaria
and Croatia to those in Romania and study whether the contribution of common shocks is
more pronounced in the former countries (a pegger and a quasi-pegger) than in the latter
(a floater). To give more rigor to our conclusions we expand the analysis to some other
non-euro area peggers (Denmark) and floaters (Czechia, Hungary, Poland, Sweden and the
UK) and analyse whether there is a link between variability of the nominal exchange rate
and contribution of common shocks to GDP and inflation. For example, Iossifov and Pod-
piera (2012) showed that spillovers of euro area inflation are more pronounced in non-euro
area countries with more rigid exchange rate regimes.
This literature is also closely related to the Mundellian trilemma that posits that choice
of floating exchange rate regime, under free capital flows, allows the country to run an au-
tonomous monetary policy (Obstfeld, Shambaugh and Taylor 2005). However, this propo-
sition can be misleading if external shocks play an important role in the economy of the
floater. As Gosczek and Mycielska (2019) put it, full monetary policy autonomy in coun-
tries with floating regimes can be limited by exogenous factors, primarily global interest
rates (the fear-of-float argument) or by endogenous factors, such as strong trade and fi-
nancial integration and business cycle synchronization, which amplify the importance of
external shocks in small open economies. Thus we interpret our results through the lenses
of this challenging view for the Mundellian trilemma on a global level (Aizenman, Chinn
and Ito, 2016; Rey 2016) and European level (Gosczek and Mycielska, 2019).
Finally, after the analysis of the overall contribution of external shocks to GDP and
inflation in candidate countries, we also focus on the macroeconomic effects of one partic-
7
ularly interesting shock for our analysis - ECB monetary policy shock. Thus, in this sense
we also follow growing literature on the international transmission of the ECB monetary
policy shocks that points to notable spillovers of monetary policy shocks from the euro area
to non-euro area economies (e.g. Feldkircher, 2015; Potjagailo 2017 and Colabella 2019).
3 Methodology
In this section we briefly introduce the structural VAR we rely on throughout the analysis.
We also discuss the short run and long run sign and zero restrictions we impose in order
to identify structural shocks.
3.1 Model - Structural BVAR for a small open economy
3.1.1 Basic facts on Structural VARs
General SVAR with k lags we use can be written in usual form:
A0yt = µ+A1yt−1 + . . .+Akyt−k + εt, t = 1, . . . , T. (1)
where yt is an n×1 vector of observed variables, the Aj are fixed n×n coeffi cient matrices
with invertible A0, µ is n× 1 fixed vector and εt are structural economic shocks with zero
mean and covariance matrix In. Reduced form VAR model is obtained from (1) by pre
multiplying the equation by (A0)−1 :
yt = c+B1yt−1 + . . .+Bkyt−k + ut, t = 1, . . . , T, (2)
where Bj = A−10 Aj , c = A−10 µ and ut = A−10 εt.
Structural vector autoregression (SVAR) model is normally used to calculate the impulse
response function:2
2See Killian and Lütkepohl (2017) for more details about SVARs.
8
Ψh =∂yt+h∂εt
, h = 0, 1, 2, . . .
where element ψjk,h represents average response of variable j to shock k after h periods.
The historical decomposition in a SVAR decomposes each endogenous variable in a model
into contribution of each identified shocks. The contribution of shock k to variable j at
period t and can be calculated as:
ykjt =t−1∑h=0
ψjk,h · εk,t−h. (3)
3.1.2 Block exogeneity assumption in a BVAR
A crucial assumption implemented in our VAR is that of block exogeneity - shocks originat-
ing in big economy (euro area) impact the small economy, but not the other way around.3
Given the size of the euro area and the three candidate countries block exogeneity as-
sumption seems plausible assumption for our application. To impose this restrictions let
y1t be vector of external (big country) variables and y2t vector of domestic (small country)
variables so yt can be decomposed as y′t = [y1′t , y2′t ].
In our applications, external block variables (y1t ) are the same for all candidates and
include: euro area GDP, euro area prices and measure of the ECB monetary policy stance.
Monetary policy rate used is shadow rate constructed by Wu and Xia (2016) which corrects
EONIA rate by taking into account unconventional monetary policy actions of the ECB.
Variables included in domestic block (y2t ) however depend on the exchange rate regime in
the pertaining candidate countries which is discussed in the following section. Details on
data used in our analysis can be found in Appendix B. VAR models used in our analysis are
all specified in log differences and estimated at quarterly frequency on the period 2003Q1-
2018Q2 using four lags. We experimented with several other number of lags which did not
3Papers investigating the impact of foreign shocks to small open economies using these type of restrictionsare, for example, Cushman and Zha (1997) and Krznar and Kunovac (2010), among many others.
9
change our results importantly.
Matrices Aj from (1) now must have block lower triangular form
Aj =
Aj11 0
Aj21 Aj22
, j = 0, . . . , k, (4)
and it can be shown that coeffi cients matrices Bj inherit this block exogeneity form so that
Bj =
Bj11 0
Bj21 Bj
22
, j = 1, . . . , k. (5)
It is important to note that although (4) implies (5) the vice versa is not true. To get (4)
from (5) we need additional assumptions on A0 or equivalently (A0)−1 which is impulse
response function at impact. We will impose restriction on (A0)−1 by setting restrictions
that shocks originating in small economy cannot affect big economy at t = 0. The second
part of block exogeneity implementation is to shut down the impact of small economy
shocks on the external variables beyond the impact (h = 1, 2, . . .) by implementing (5). To
explain this implementation we write (2) in form more convenient for Bayesian simulation
of reduced form parameters
yt = X ′tβ + ut, (6)
where X ′t = In ⊗ [1, y′t−1, . . . , y′t−k] and β = vec([cB1 . . . Bk]
′). We want to restrict ele-
ments of β that correspond to zero block in coeffi cient matrices (5). Within the Bayesian
framework this can be achieved by assuming an appropriate prior distribution for restricted
parameters. Usual choice of natural conjugate (Normal inverse Wishart) prior won’t be
suitable for this purpose as it assumes that the prior covariance of coeffi cients in any two
equations are proportional to each other (see Koop and Korobilis 2010). However, Inde-
pendent Normal inverse Wishart prior will serve the purpose because here prior beliefs for
10
VAR coeffi cients and error covariance matrix are set independently:
β ∼ N(β, V β), Ω ∼ IW (M,γ).
Conditional posterior distributions p(β|y,Ω) and p(Ω|y, β) for this prior have the following
form
β|y,Ω ∼ N(β, V β), Ω|y, β ∼ IW (M,γ),
where
V β =
(V −1β +
T∑t=1
XtΩ−1X ′t
)−1, β = V β
(V −1β β +
T∑t=1
XtΩ−1yt
)
and
γ = T + γ, M = M +
T∑t=1
(yt −X ′tβ
) (yt −X ′tβ
)′.
A sample from the posterior of the reduced form parameters and residual covariance matrix
is drawn by using a Gibbs sampler.
Now, to implement (5) we can assume zero mean priors with extremely small variance
for all the small country parameters in every equation for the big country block, i.e. if we
want to restrict j-th element of β we can set(β)j
= 0 and(V β
)jj
= ε where ε is some small
positive number (e.g. ε = 10−9). This will put a dominant weight to the (zero mean) prior
parameters when calculating posteriors. In this way sample information is largely ignored
as the posteriors of these coeffi cients will be predominantly influenced by the prior. Other
elements of β and V β are set to shrink posterior parameters in spirit of Minnesota prior
(see for example Robertson and Tallman 1999). Shrinking hyperparamters of Minnesota
prior are set to λ1 = 100, λ2 = 100, λ3 = 2 and λ4 = 104, which suggests that we use loose
priors.
11
3.1.3 Set-identification of structural shocks
At each step of our Gibbs sampler, given a draw of reduced form parameters, we recover a
set of structural models satisfying the sign and zero restrictions imposed. The sign and zero
restrictions are imposed directly onto the impulse response function by using a procedure
proposed by Arias et al. (2014.). This algorithm may be effi ciently implemented in our
application where both the block exogeneity assumption and standard sign restrictions
are to be imposed. Arias et al (2018) also propose the updated version of the algorithm,
but now fully specified under a normal inverse Wishart prior only. As such, it cannot
be adjusted easily to accommodate the block exogeneity assumption - a feature of the
highest importance when modelling interactions between a small open economy and the
rest of the world. For that reason we rely on the procedure proposed by Arias et al.
(2014.) instead. In order to test whether the choice of the algorithm version (Arias et
al. (2014.) or Arias et al (2018)) affects our results we ran several specifications, without
block exogeneity assumption, and compared the output from the two specifications. The
results would always be almost identical, suggesting that the choice of the algorithm is not
of great importance in this case.4
4 Identification with sign and zero restrictions
Structural shocks are identified by imposing a number of sign and zero restrictions on the
impulse response function in the short run and the long run. Identification strategy is
largely based on the mainstream macroeconomic theory and the recent related literature
(see for example Forbes et al. 2018, Bobeica and Jarocinski 2017 and Comunale and
Kunovac 2017). Each shock belongs to one of the two main groups: external or domestic
(country specific) shocks. External shocks by definition (i.e. imposed restrictions) affect
the euro area. They may originate either in the euro area or globally (oil supply or global
4These are available upon request.
12
demand for example). For our purpose it is important only that these shocks affect the
euro area and are thus relevant for the ECB - we label them jointly euro area shocks. On
the other hand, domestic shocks are country specific and are identified by imposing block
exogeneity restrictions together with sign and zero restrictions. We impose no restrictions
on how domestic variables react to euro area shocks and thus let the data speak freely in
that regard. If, however, domestic variables do react to external shocks in a way similar to
the those of the euro area we may also correctly label the external shocks common shocks.
Identified euro area shocks are labelled the aggregate demand, aggregate supply and
monetary policy shocks. In the short run, an expansionary aggregate demand shock in-
creases both economic activity and prices in the euro area. Monetary policy then acts
counter-cyclically and raises the policy rate. In contrast, an aggregate supply shock has
the opposite effect on economic activity and prices in euro area - it raises GDP and low-
ers consumer inflation, while there reaction of monetary policy here is left unrestricted.
Finally, an expansionary monetary policy shock increases both economic activity and in-
flation. As for the long run restrictions, we assume that aggregate demand and monetary
policy shocks do not affect GDP in the long run.
For each of the three candidate countries we also identify several domestic shocks,
depending on the monetary and exchange rate regime in these countries. Specifications
for Croatia and Romania, in contrast to Bulgaria, which operates under a currency board
regime, include the exchange rate 5 of the domestic currency vis-a-vis euro. Also, Romania,
in contrast to the other two candidate countries, uses reference rate as a key monetary
policy instrument and the corresponding VAR thus includes domestic interest rate. For
all countries of interest (Bulgaria, Croatia and Romania) we identify short run domestic
aggregate supply and domestic aggregate demand shocks in similar fashion as for the euro
area: correlation of economic activity and prices is positive in the case of demand shock,
5Appreciation of domestic currency is represented as decrease of exchange rate level.
13
Table 1: Restrictions for identification of structural shocks
Short runk Shocks/Variables GDPEA HICPEA MPEA GDPD HICPD ERD MPD
External shocks1 Demand + + + ? ? ? ?2 Supply + — ? ? ? ? ?3 Monetary policy + + — ? ? ? ?
Domestic shocks (BG)4 Demand 0 0 0 + +5 Supply 0 0 0 + —
Domestic shocks (HR)4 Demand 0 0 0 + + ?5 Supply 0 0 0 + — ?6 Exchange rate 0 0 0 ? + +
Domestic shocks (RO)4 Demand 0 0 0 + + ? +5 Supply 0 0 0 + — ? ?6 Exchange rate 0 0 0 ? + + +7 Monetary policy 0 0 0 + + + —
Long runk Shocks/Variables GDPEA HICPEA MPEA GDPD HICPD ERD MPD
External shocks1 Demand 0 ? ? ? ? ? ?2 Supply ? ? ? ? ? ? ?3 Monetary policy 0 ? ? ? ? ? ?
Domestic shocks (BG)4 Demand ? ? ? 0 ?5 Supply ? ? ? ? ?
Domestic shocks (HR)4 Demand ? ? ? 0 ? ?5 Supply ? ? ? ? ? ?6 Exchange rate ? ? ? 0 ? ?
Domestic shocks (RO)4 Demand ? ? ? 0 ? ? ?5 Supply ? ? ? ? ? ? ?6 Exchange rate ? ? ? 0 ? ? ?7 Monetary policy ? ? ? 0 ? ? ?
Note: (+) = positive reaction; (-) = negative reaction; (0) = no reaction; (?) = reaction not restricted.
All shocks are normalized as expansionary. All restrictions are set at impact. k refers to ordering of
shocks in VAR models. Details about variables definition are given in table in the Appendix B.
14
and negative in the case of supply shock. Regarding demand shock, we assume that this
shock increases interest rate for Romania as a counter-cyclical reaction of monetary policy.
For Croatia and Romania we also identify exchange rate shock - exogenous depreciation
of domestic currency raises domestic inflation (pass-through effect) in both countries and
interest rate in Romania only. We do not impose any restrictions on the effects of domestic
demand shocks on exchange rate as the literature related to these effects is inconclusive.
6. Finally, for Romania we identify a domestic monetary policy shock similar to that in
the euro area, additionally assuming that a lower domestic interest rate depreciates the
domestic currency. A summary of our identification strategy is given in 1. As for the long
run restrictions in the domestic block, we assume that aggregate demand (BG, HR, RO),
exchange rate (HR, RO) and monetary policy (RO) shocks do not affect GDP in the long
run.
4.1 Relative and overall importance of individual shocks based on his-
torical decomposition
In this paper, importance of external shocks for domestic economies is quantified using
several statistics based on the historical decomposition from the estimated VARs presented
above. First, from historical decomposition (see (3), where ykjt represents contribution of
shock k to variable j at period t, we define measure of the relative importance (in absolute
terms) of some shock k to variable j at t as:
ykjt =
∣∣∣ykjt∣∣∣∑nl=1
∣∣∣yljt∣∣∣ . (7)
6Rising domestic demand can lead to increase of money demand and thus appreciate domestic currency.On the other hand, stronger domestic demand can widen trade deficit, which puts depreciation pressureson domestic currency. With no restrictions on the effect of domestic demand on exchange rate it is hard toseparate exchange rate shock from domestic demand shock (correlation between these shocks is pronounced).However, in our analysis we focus on the importance of external shocks and contribution of these shocks todevelopments of domestic macroeconomic variables is not affected by the structure of domestic shocks.
15
Now, our measure of the overall importance of external shocks (k = 1, 2, 3) for some
domestic macroeconomic variable j at period t is the sum of contributions of these shocks:
3∑k=1
ykjt. (8)
Second, to measure the similarity of contributions of some shock to a domestic (j) and
corresponding euro area (j′ ) variable (economic activity or prices) we look at the difference:
ykjt − ykj′t. (9)
This measure takes the value of 0 if the contribution of the given shock in the euro area
and the euro candidate country are identical, meaning that all values close to 0 indicate
the pronounced similarity of these contributions.
5 Results
In this section we present and discuss the results from the estimated structural BVARs.
First, we report the contributions of euro area shocks to GDP and inflation developments
in the three candidate countries. After that we compare these contributions to those in the
euro area. From these results, we discuss the adequacy of the common monetary policy
for the euro candidate countries through the lenses of the OCA theory and discuss the
differences among the countries through the prism of the Mundellian framework. Next,
in the context of the international monetary policy transmission, we report how the ECB
monetary policy shock affects macroeconomic variables in three candidate countries.
16
5.1 Relevance of common shocks for candidate countries and similarity
with the euro area
Impulse responses of all models together with 68% posterior error bands are given in
Appendix B (Figures 6 - 8). They broadly suggest that the three countries do react to
euro area shocks in a manner similar to that of the euro area and, thus, we may label these
shocks “common shocks”.
5.1.1 Overall contribution of common shocks to GDP and HICP
Figure 1 shows the overall contribution of common shocks (euro area AS, euro area AD
and euro area monetary policy shock) to GDP (a) and consumer inflation (b) in the euro
candidate countries 7 calculated with equation (8). These estimates of our overall im-
portance measure point to common shocks as the dominant drivers of GDP and inflation
developments in all three countries. Average contribution of common shocks to GDP is
high and stands at around 70% in Bulgaria and Croatia and 60% in Romania. As for the
HICP, share of common shocks is somewhat lower in all countries as CPI developments
are determined by many idiosyncratic shocks such as VAT changes, administrative price
changes etc. However, contributions are still pronounced as they contribute about 65% to
HICP developments on average, in Bulgaria and Croatia, and 50% in Romania. In line
with OCA theory, these results suggest that common monetary policy could be suitable
for these countries once they join the euro area. Less pronounced contribution of common
shocks in Romania could be, at least partially, attributed to different exchange rate regime,
as discussed in the previous sections.
Contributions of common shocks and exchange rate regimes I In this section we
are interested in potential differences in the contributions of external shocks in countries
with fixed exchange rate regimes in comparison to countries which operate under floating
7Historical decompositions of GDP and HICP for all countries and 68% posterior error bands for con-tributions are shown on Figure 9 and Figure 10 in Appendix C.
17
Figure 1: Contribution of common shocks to GDP and HICP in euro candidate countries
(a) GDP
0.0
0.2
0.4
0.6
0.8
1.0
05 06 07 08 09 10 11 12 13 14 15 16 17 18
BulgariaCroatiaRomania
(b) HICP
0.0
0.2
0.4
0.6
0.8
1.0
05 06 07 08 09 10 11 12 13 14 15 16 17 18
BulgariaCroatiaRomania
exchange rate regimes. Theoretically, one should expect the transmission of external shocks
to be stronger in countries that use fixed exchange rate or currency board regimes (Canova,
2005) as exchange rate cannot act as an absorber of external shocks. To put our results
in a broader international context we also calculate the contribution of common shocks
to GDP and inflation in some other EU countries that employ inflation targeting, with
floating exchange rates - Czechia, Hungary, Poland, Sweden and UK and one more pegger,
Denmark. Our results show that contribution of common shocks to developments of both
GDP and inflation is less pronounced in floaters. This is illustrated on the lower and upper
left panel of Figure 2, with countries that operate under floating exchange rate regimes
marked with red lines and countries that operate under (quasi) pegged regimes with blue
lines. To get a more insightful view on this matter, on the upper and lower right panel
of Figure 2 we present the relation between exchange rate volatility and the relevance of
common shocks for GDP and HICP developments in these economies.8. The fitted line
shows that countries with higher standard deviations of quarterly changes in exchange
rate (red points) mostly tend to have less pronounced contributions of common shocks
8Slope coeffi cients are statistically significant, with p-values standing at 0,06 for GDP and 0,004 forHICP.
18
Figure 2: Contribution of common shocks to GDP in (quasi) peggers and floaters
(a) Contributions to GDP
0.0
0.2
0.4
0.6
0.8
1.0
05 06 07 08 09 10 11 12 13 14 15 16 17 18
Bulgaria Croatia CzechiaDenmark Hungary PolandRomania Sweden UK
(b) Exchange rate volatility vscontributions to GDP
BG
CZ
HR
HU
PL
ROUKDK
SW
0.4
0.5
0.6
0.7
0.8
0.00 0.01 0.02 0.03 0.04
(c) Contributions to HICP
.1
.2
.3
.4
.5
.6
.7
.8
05 06 07 08 09 10 11 12 13 14 15 16 17 18
Bulgaria Croatia CzechiaDenmark Hungary PolandRomania Sweden UK
(d) Exchange rate volatility vscontributions to HICP
BG
CZ
HR
HU
PLRO
UK
DK
SW
0.4
0.5
0.6
0.7
0.8
0.00 0.01 0.02 0.03 0.04
Note: Grey shaded area represents 95% error band for linear fit
19
to GDP9 and inflation. These conclusions are broadly consistent with views that floating
exchange rates can be seen as shock absorbers in most of these countries (Audzei and
Bradzik, 2018). However, we present the relation between exchange rate volatility and the
relevance of common shocks for GDP and HICP developments in these economies.although
the contribution of common shocks in new EU member state floaters, Poland, Hungary
and Czechia, is somewhat less pronounced in comparison to their peers with more rigid
exchange rate regimes, Bulgaria and Croatia, this contribution is far from negligible. These
findings are in line with the related literature (Mackowiak, 2006; Horváth and Rusnák, 2009;
Hanclova, 2012) and can also serve as a framework for the discussion on euro adoption in
these countries. As Poland, Hungary and Czechia are obliged by their Treaties of Accession
to the European Union to introduce the euro eventually this issue is relevant for policy
makers despite the fact that the current political atmosphere in these countries is not
pro-euro oriented. Increasing financial and trade integration of these countries with the
euro area and ongoing euro area reforms could bring this question to the top of the policy
agenda in the near future. Our results can be also interpreted in terms of global business
(e.g. Kose, Otrok and Prasad 2012; Ductor and Leiva-Leon, 2016) and financial (Rey
2016) cycles synchronization literature, which suggests that in the era of globalization
and financial internationalization common global economic and financial shocks strongly
affect economic developments and economic policy decision making process in small open
economies.
5.1.2 Contribution of individual common shocks to GDP and HICP
Previously presented results on the overall contribution of common shocks to the devel-
opments of macroeconomic variables in euro candidate countries are rather informative.9The only outlier in the sample is GDP for Denmark, as contribution of euro area shocks in this pegger
country is among the lowest in the group. This deviation can be explained by the fact that Denmarkexperienced volatile growth rates in the pre-crisis period (even with negative quarterly figures) and recordeda technical recession in 2017, due to some idiosyncratic one-offs (primarily some patent payments whichincreased volatility of the growth rate in first two quarters of the year and temporary bottlenecks in carsales due to changes in tax system in September)
20
Table 2: Mean and standard deviations of the difference of contributions of common shocksto GDP and HICP
BG-EA HR-EA RO-EA
Shock mean std. dev. mean std. dev. mean std. dev.GDP EA AD -0.05 0.08 -0.10 0.05 -0.11 0.07
EA AS -0.10 0.08 -0.10 0.06 -0.20 0.09EA MP -0.10 0.07 -0.10 0.05 -0.11 0.07
HICP EA AD -0.13 0.07 -0.13 0.06 -0.21 0.09EA AS -0.10 0.06 -0.05 0.05 -0.15 0.07EA MP -0.14 0.05 -0.11 0.05 -0.11 0.05
However, in order to study the adequacy of common monetary policy in more detail we are
also interested in the comparison between contribution of individual euro area shocks in
euro candidate countries and the euro area. The reason for that is that the ECB will react
only to those shocks with important effects on economic developments in the euro area as
a whole. If the contribution of such shocks for a candidate country is very different from
that for the euro area, the reaction of the common monetary policy to these shocks would
not be adequate or could even be counter-productive for a small candidate country. For
example, if the ECB reacts to the euro area AD shock it is important that the contribution
of this shock for macroeconomic developments in the euro area and in the euro candidate is
as similar as possible. If the contribution of this shock in the euro area is much larger than
that in a candidate country then the direction and/or intensity of the ECB’s reaction may
not be adequate for that country. These contributions are, expectedly, more pronounced
in the euro area but they seem to be quite similar across countries and over time (Figures
11 and 12 in Appendix B).
In order to compare the relevance of each shock in the euro area and the candidate
countries, Table 2 presents the mean and dispersion of the similarity of contributions of
common shocks to GDP and inflation (see (9)). When the mean is equal to zero, there
is evidence suggesting that two contributions of that shock are, on average, identical in
the euro area and a candidate country. A negative mean, on the other hand, indicates
21
that contributions of common shocks are, on average, higher in the euro area than in
the candidate countries. Reported averages indicate that contributions of all shocks are,
expectedly, more pronounced in the euro area in the case of both GDP and inflation. The
contribution of common shocks to GDP is lower in the three countries compared to the euro
area - in Bulgaria and Croatia it is (on average) lower by 10pp and in Romania by 15pp.
The maximum difference is found in the case of the contribution of the common AS shock
in Romania, standing at around 20pp. As for inflation, the differences are somewhat more
pronounced, which is not surprising if we take into account various country-specific tax
and administrative price changes that directly affect inflation dynamics in these countries.
However, these differences are, in our view, still relatively modest. The contribution of
common shocks to inflation is around 12pp lower in Bulgaria, 10pp in Croatia and 14pp in
Romania than in the euro area. The maximum difference is again recorded in the case of
Romania, where the average contribution of common AD shock is 21pp lower, on average,
than in the euro area. More pronounced differences in contributions of common shocks in
the case of Romania can also be interpreted in terms of its different exchange rate regime.
In addition to average differences, we also report standard deviations which are in all cases
below 0.10, which suggests that the dynamics of contributions of common shocks in the
candidate countries and the euro area is quite similar. Figures 11 and 12 in Appendix
B show that changes in contributions of common shocks to GDP and inflation over time
in euro candidate countries and the euro area are synchronized. Thus, these results also
suggest that common monetary policy could be suitable for all countries.
5.2 Effects of the ECB’s monetary policy on macroeconomic variables in
candidate countries
In previous sections we discussed the adequacy of common monetary policy by focusing
on various aspects of the coherence of economic shocks. In this section we focus on the
monetary policy and directly compare the effects of the ECB policy actions on the euro
22
area and on the candidate countries.
Figure 3: Effects of the ECB monetary policy shock on GDP and inflation
(a) EA
5 10 15 20
-0.1
0
0.1
0.2
0.3
0.4
0.5
EA MP ==> gdp-ea
5 10 15 20
0.1
0.2
0.3
0.4
EA MP ==> hicp-ea
(b) BG
5 10 15 20
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
EA MP ==> gdp-bg
5 10 15 20-0.5
0
0.5
1
EA MP ==> hicp-bg
(c) HR
5 10 15 20
-0.5
0
0.5
EA MP ==> gdp-hr
5 10 15 20
0
0.1
0.2
0.3
0.4
0.5
0.6
EA MP ==> hicp-hr
(d) RO
5 10 15 20
-0.5
0
0.5
1
EA MP ==> gdp-ro
5 10 15 200
0.5
1
1.5
EA MP ==> hicp-ro
Note: Results are represented with point-wise median and 68% confidence bands.
Figure 3 shows the estimated impulse response functions, reflecting how expansionary
ECB monetary policy shock affects the GDP and consumer inflation in the candidate coun-
tries and the euro area. Importantly, impulse responses indicate that the effect of this shock
among countries is fairly similar and our results are broadly in line with related literature
(e.g. Feldkircher, 2015; Potjagailo 2017 and Colabella 2019). The similarity of responses of
GDP and inflation in the euro area and in the euro candidate countries reflects the strong
role of the so-called trade channel in international monetary policy transmission (Potjagailo
2017; Iacoviello and Navarro 2018). An expansionary monetary policy shock has a positive
short term effect on GDP in the euro area and in euro candidate countries, while this effect
fades away and/or becomes statistically insignificant in the longer run. On the other hand,
the effects of the ECB monetary policy shock on inflation in all countries are positive and
23
long-lasting. To give our conclusions more analytical rigor, we calculated differences of
impulse responses to ECB monetary policy shock between the candidate countries and the
euro area (Figure 14 in Appendix B). In most cases responses of GDP and inflation in
candidate countries and the euro area are statistically not different. There are only two
cases in which there are statistically significant differences in responses. Firstly, there is
short lasting statistically significant difference in responses for GDP between Bulgaria and
euro area. Secondly, the reaction of HICP in Romania to EA monetary policy shock is
constantly significantly higher than the reaction of EA HICP, which can, at least partially,
be explained by the fact that in the observed period Romania recorded the highest and
most volatile inflation rates. Comparable reactions of macroeconomic variables to the ECB
monetary policy shock indicate that common counter-cyclical policy could be effective in
euro candidate economies, especially if we take into account the endogeneity hypothesis of
the OCA theory (Frankel and Rose, 1998) suggesting that similarity of economic shocks
and reactions to these shocks could become even more pronounced once the candidates
join the euro area.
5.3 Robustness of the results
In order to test the robustness of our main results on the importance of euro area shocks
for the three candidate economies, we challenge our identification pattern. Having in mind
that the historical decomposition exercise in a SVAR may depend heavily on a particular
combination of restrictions imposed onto the impulse response function, we test whether
varying the identification pattern influences our main conclusions. First, when distinguish-
ing among shocks, the most challenging part was to distinguish between the aggregate
demand and the monetary policy shock and, to some extent, also the exchange rate shock.
The pattern of sign and zero restrictions needed for that purpose may overlap, making
reliable identification of structural shocks a rather challenging task. For that purpose we
tested several alternative patterns which would indeed slightly affect the relative impor-
24
tance of those shocks on candidate countries. However, this was largely irrelevant for our
main conclusions on the overall importance of euro area shocks for the three candidates.
Domestic shocks are distinguished from those originating abroad by imposing block exo-
geneity restrictions and the overall importance of the two groups of shocks would therefore
remain largely unchanged when varying the identification pattern within each group of
shocks (domestic or external). Similarly, instead of having a single foreign block we exper-
imented with a model with distinct euro area and global blocks. However, although such
a richer structure may help to explain the sources of shocks hitting the three candidate
countries better, this has not changed our results importantly. For simplicity, but without
important loss of generality, our final specification merged both euro area and global shocks
into a single block.
6 Conclusion
Returning to the research questions posed at the beginning, the results of our empirical
approach show that economic shocks hitting the euro area have similar effects on the three
candidate countries. Our measure of similarity of contributions shows that differences in
reactions to common shocks are rather small among the three countries, but somewhat
more pronounced in Romania. At least partially, this can be explained by the fact that
during the observed period Romania recorded significantly strong variations of the ex-
change rate compared to other two countries. This view was supported by comparison of
the contributions of common shocks in Romania and other floaters in the EU - Czechia,
Hungary, Poland, Sweden and UK with (quasi) peggers Denmark, Bulgaria and Croatia.
This comparison showed that the share of common shocks in the former group of countries
is smaller than that in the latter group. However, due to strong trade and financial link-
ages within the EU, the contribution of external shocks in floaters is far from negligible.
The same therefore will hold true for Romania. For that reason, we expect that costs
of giving up monetary sovereignty could be less pronounced than standard Mundellian
25
trilemma suggests. As for the introduction of a more rigid exchange rate regime in Roma-
nia, current developments show that the Romanian National Bank is making an effort to
keep the exchange rate relatively stable, which can probably be explained by the relatively
high level of financial euroisation in the country (Copaciu, Nalban and Bulete, 2015) and
the relatively pronounced exchange rate pass through effect (Stoian and Murarasu, 2015).
Despite the evidence that the exchange rate in Romania absorbs part of the real shocks
in the economy, the absorption capacity is limited by the structural characteristics of the
economy. Regarding the other two countries, monetary policies in Bulgaria and Croatia are
already fairly limited as they operate under a currency board (Bulgaria) and a managed
float with a tight margin (Croatia) exchange rate regime. Regarding the adequacy of the
ECB’s policy for these countries, impulse responses from BVAR point to expected counter-
cyclical effects in both euro area and euro candidate countries. These results also support
the view that the costs of euro adoption, in terms of loss of an autonomous counter-cyclical
monetary policy, should be relatively modest in all three countries, especially in Bulgaria
and Croatia.
Finally, it is important to emphasize that there are various other costs of euro adoption,
which are not addressed in this paper, such as price increase due to currency conversion,
one-off conversion costs and one-off costs arising from the participation in the Eurosystem
as well as the costs of participation in the provision of financial assistance to other member
states. However, as Eudey (1998) points out, loss of an autonomous counter-cyclical mon-
etary policy can be understood as the most important long lasting cost of euro adoption,
and our results suggest that this cost would not be pronounced in the three candidate
countries.
26
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32
Appendices
A Some stylized facts on Bulgarian, Croatian and Romanian
economy
Bulgaria, Croatia and Romania are all small open European transition economies. As
new member states, with an obligation to eventually introduce the euro, Bulgaria and
Romania joined the European Union in 2007 and Croatia did so in 2013. These countries are
strongly connected to the euro area economy, through various trade and financial linkages.
Euro area members are the main trading partners of these countries10, most of FDI flows
originate from the euro area, while banking systems are dominated by foreign-owned bank
subsidiaries, with parent banks mostly located in euro area countries. Strong trade and
financial integration with the euro area is reflected in the high degree of synchronization
of both GDP growth and business cycles (Figure 4).
As for the macroeconomic developments, like peers in the Central and Eastern European
(CEE) region, all three countries experienced a boom-bust cycles since the beginning of the
2000s. Growth in the early 2000s was strongly fuelled by accelerating domestic and foreign
lending and foreign capital inflows. The global financial crisis that spilled over to Europe
had similar effects in all countries, resulting in the recession in 2009. On the other hand,
dynamics of recovery was somewhat different across countries. Bulgarian GDP returned
to the positive region as early as 2010, but the economy was drawn into the next recession
in 2012 due to the European debt crisis. After that, the real activity started to recover
gradually. The Croatian economy recorded a prolonged, double deep recession, which lasted
from 2009 to 2014. In Romania, after a strong fall in 2009, the economy experienced a
gradual recovery and acceleration of growth rates from 2011 onwards. Despite the different
paths of the recovery in these countries, their business cycles stayed fairly synchronized
10According to data obtained from national statistical offi ces share of euro area countries in total exportsand imports in Croatia and Romania stands at around 55%-60%, while in Bulgaria 45%-50%.
33
with the euro area business cycle even after 2009.
Figure 4: Real GDP growth rates and business cycle synchronization
(a) GDP growth rate
-12
-8
-4
0
4
8
12
03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18
BulgariaCroatiaRomania
%
(b) Cyclical component of GDP
-4
-2
0
2
4
6
03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18
BulgariaEuro areaCroatiaRomania
%Source: Eurostat; authors’calculations
Note: To extract cyclical components of GDP we applied Christiano and Fitzgerald (2003) band-pass
filter with frequency range between 8 and 32 quarters.
Regarding other important characteristics of these economies, the focal point of this
paper is related to the different monetary and, especially, exchange rate regimes in these
countries. The choice of the exchange rate regime was largely shaped by specific historical
economic circumstances and a high degree of deposit and credit euroisation in the financial
sectors (see Dumicic, Ljubaj and Martinis, 2018). Bulgaria introduced a currency board in
1997 as a mean of stabilization after the country experienced a prolonged period of a near
hyperinflation and several unsuccessful stabilization policies (Gulde, 1999). The choice
of monetary and exchange rate regime in Croatia in the early 1990s, namely exchange
rate as nominal monetary policy anchor and managed floating exchange rate regime, was
motivated by the success of the stabilization program in 1993, based on anchoring infla-
tion expectations through a credible stabilization of the exchange rate. Due to persistent
euroisation and strong exposure of all institutional sectors to FX risk, monetary policy
makers in Croatia found such a framework to be the most supportive for maintaining price
34
Figure 5: Exchange rate vis-à-vis euro
-15
-10
-5
0
5
10
15
20
04 05 06 07 08 09 10 11 12 13 14 15 16 17 18
Bulgarian levCroatian kunaRomanian leu
%
Source: Eurostat
stability and financial stability. Finally, after years of monetary targeting, at the begin-
ning of the 2000s Romania, which at that time was having to cope with still high inflation
rates, started considering inflation targeting as a more favourable policy option. During
the period from 2003 to 2005 the Romanian central bank (NBRM), although still in the
monetary targeting regime, started to rely more on the interest rate as a policy instrument
(accompanied with FX interventions). In August 2005 the NBRM finally switched to direct
inflation targeting (Popa, 2008). As for the exchange rate regime in Romania, the IMF
classifies it as floating, while the NBRM refers to it as managed floating. Regardless of the
classification, Figure 5 illustrates that the Romanian leu has experienced strong volatility
over the observed period compared to the Croatian kuna. Variability of exchange rate
in Romania was especially pronounced during the period of the global recession and the
European debt crisis, when the Romanian leu recorded significant depreciation. Such a
reaction suggests that the exchange rate in Romania partially absorbs some of external
shocks. Consequently, this could be reflected in a lower contribution of these shocks to
domestic GDP and inflation developments. However, strong financial and trade linkages
35
with the euro area suggest that the contributions of external shocks in Romania could still
be fairly pronounced.
36
B Data and Figures
Table 3: Data description and sources
Variable Description Source
GDPEA Euro area real GDP, million euro, SA EurostatHICPEA Euro area prices, all items, 2015=100, SA ECBMPEA Wu and Xia shadow interest rate Cynthia Wu web pageGDPD Real GDP for Bulgaria, Croatia and Romania, million euro, SA EurostatHICPD HICP prices for Bulgaria, Croatia and Romania, 2015=100, SA EurostatERD Domestic exchange rate to euro for Croatia and Romania EurostatMPD Reference interest rate for Romania National Bank of Romania
Note: Prices are seasonally adjusted using X-11 procedure.
37
Figure 6: Impulse response functions for Bulgaria
510
1520
0
0.1
0.2
0.3
BG
AD
==>
gd
p-b
g
510
1520
0.6
0.81
1.2
1.4
1.6
1.8
BG
AD
==>
hic
p-b
g
510
1520
-202
10-6
BG
AD
==>
gd
p-e
a
510
1520
-101
10-6
BG
AD
==>
hic
p-e
a
510
1520
-505
10-5
BG
AD
==>
sh
ado
w
510
1520
0.6
0.81
1.2
1.4
1.6
BG
AS
==>
gd
p-b
g
510
1520
0
0.51
1.5
BG
AS
==>
hic
p-b
g
510
1520
-202
10-6
BG
AS
==>
gd
p-e
a
510
1520
-2-101210
-6B
G A
S =
=> h
icp
-ea
510
1520
-10110
-4B
G A
S =
=> s
had
ow
510
1520
-0.50
0.5
EA
MP
==>
gd
p-b
g
510
1520
-0.50
0.51
EA
MP
==>
hic
p-b
g
510
1520
0
0.2
0.4
EA
MP
==>
gd
p-e
a
510
1520
0.1
0.2
0.3
0.4
EA
MP
==>
hic
p-e
a
510
1520
-20
-100102030
EA
MP
==>
sh
ado
w
510
1520
0
0.51
1.5
EA
AD
==>
gd
p-b
g
510
1520
0.51
1.52
2.5
EA
AD
==>
hic
p-b
g
510
1520
-0.20
0.2
0.4
0.6
EA
AD
==>
gd
p-e
a
510
1520
0.2
0.3
0.4
0.5
0.6
EA
AD
==>
hic
p-e
a
510
1520
4050607080
EA
AD
==>
sh
ado
w
510
1520
0.51
1.52
2.53
EA
AS
==>
gd
p-b
g
510
1520
-1012
EA
AS
==>
hic
p-b
g
510
1520
0.51
1.5
EA
AS
==>
gd
p-e
a
510
1520
-0.6
-0.4
-0.20
EA
AS
==>
hic
p-e
a
510
1520
0204060
EA
AS
==>
sh
ado
w
Note: Results are represented with pointwise median and 68% confidence bands.
38
Figure 7: Impulse response functions for Croatia
510
1520
0
0.2
0.4
HR
AD
==>
gd
p-h
r
510
1520
0.1
0.2
0.3
0.4
HR
AD
==>
hic
p-h
r
510
1520
-0.4
-0.20
0.2
HR
AD
==>
eu
rhrk
510
1520
-1
-0.50
0.51
10-6
HR
AD
==>
gd
p-e
a
510
1520
-505
10-7
HR
AD
==>
hic
p-e
a
510
1520
-202
10-5
HR
AD
==>
sh
ado
w
510
1520
-0.20
0.2
HR
ER
==>
gd
p-h
r
510
1520
0.1
0.2
0.3
0.4
HR
ER
==>
hic
p-h
r
510
1520
-0.20
0.2
HR
ER
==>
eu
rhrk
510
1520
-505
10-7
HR
ER
==>
gd
p-e
a
510
1520
-4-2024
10-7
HR
ER
==>
hic
p-e
a
510
1520
-2-1012
10-5
HR
ER
==>
sh
ado
w
510
1520
0.6
0.81
1.2
1.4
HS
AS
==>
gd
p-h
r
510
1520
-0.20
0.2
HS
AS
==>
hic
p-h
r
510
1520
-0.6
-0.4
-0.20
HS
AS
==>
eu
rhrk
510
1520
-202
10-6
HS
AS
==>
gd
p-e
a
510
1520
-101
10-6
HS
AS
==>
hic
p-e
a
510
1520
-505
10-5
HS
AS
==>
sh
ado
w
510
1520
-0.50
0.5
EA
MP
==>
gd
p-h
r
510
1520
0
0.2
0.4
0.6
EA
MP
==>
hic
p-h
r
510
1520
-0.20
0.2
EA
MP
==>
eu
rhrk
510
1520
0
0.2
0.4
EA
MP
==>
gd
p-e
a
510
1520
0.1
0.2
0.3
0.4
EA
MP
==>
hic
p-e
a
510
1520
-20020
EA
MP
==>
sh
ado
w
510
1520
0
0.51
EA
AD
==>
gd
p-h
r
510
1520
0.2
0.4
0.6
0.81
1.2
EA
AD
==>
hic
p-h
r
510
1520
-0.20
0.2
0.4
EA
AD
==>
eu
rhrk
510
1520
-0.20
0.2
0.4
0.6
EA
AD
==>
gd
p-e
a
510
1520
0.2
0.4
0.6
EA
AD
==>
hic
p-e
a
510
1520
4050607080
EA
AD
==>
sh
ado
w
510
1520
123
EA
AS
==>
gd
p-h
r
510
1520
-1
-0.50
EA
AS
==>
hic
p-h
r
510
1520
-0.8
-0.6
-0.4
-0.20
0.2
EA
AS
==>
eu
rhrk
510
1520
0.51
1.5
EA
AS
==>
gd
p-e
a
510
1520
-0.6
-0.4
-0.20
EA
AS
==>
hic
p-e
a
510
1520
0204060
EA
AS
==>
sh
ado
w
Note: Results are represented with pointwise median and 68% confidence bands.
39
Figure 8: Impulse response functions for Romania
510
1520
-0.20
0.2
0.4
RO
MP
==>
gd
p-r
o
510
1520
0.2
0.4
0.6
0.81
1.2
1.4
RO
MP
==>
hic
p-r
o
510
1520
-0.50
0.51
1.5
RO
MP
==>
eu
rro
n
510
1520
-10-50
RO
MP
==>
i-ro
510
1520
-101
10-5R
O M
P =
=> g
dp
-ea
510
1520
-505
10-6R
O M
P =
=> h
icp
-ea
510
1520
-4-202410
-4RO
MP
==>
sh
ado
w
510
1520
-0.20
0.2
0.4
RO
AD
==>
gd
p-r
o
510
1520
0
0.51
RO
AD
==>
hic
p-r
o
510
1520
-1012
RO
AD
==>
eu
rro
n
510
1520
0510
RO
AD
==>
i-ro
510
1520
-10110
-5RO
AD
==>
gd
p-e
a
510
1520
-505
10-6R
O A
D =
=> h
icp
-ea
510
1520
-202
10-4R
O A
D =
=> s
had
ow
510
1520
-0.20
0.2
0.4
0.6
RO
ER
==>
gd
p-r
o
510
1520
0
0.51
RO
ER
==>
hic
p-r
o
510
1520
0.51
1.52
2.5
RO
ER
==>
eu
rro
n
510
1520
2468101214
RO
ER
==>
i-ro
510
1520
-20210
-5RO
ER
==>
gd
p-e
a
510
1520
-10110
-5RO
ER
==>
hic
p-e
a
510
1520
-505
10-4R
O E
R =
=> s
had
ow
510
1520
123
RO
AS
==>
gd
p-r
o
510
1520
-1
-0.50
RO
AS
==>
hic
p-r
o
510
1520
-101
RO
AS
==>
eu
rro
n
510
1520
-505
RO
AS
==>
i-ro
510
1520
-101
10-5R
O A
S =
=> g
dp
-ea
510
1520
-505
10-6R
O A
S =
=> h
icp
-ea
510
1520
-4-202410
-4RO
AS
==>
sh
ado
w
510
1520
-0.50
0.51
EA
MP
==>
gd
p-r
o
510
1520
0
0.51
1.5
EA
MP
==>
hic
p-r
o
510
1520
-101
EA
MP
==>
eu
rro
n
510
1520
-505
EA
MP
==>
i-ro
510
1520
0
0.2
0.4
EA
MP
==>
gd
p-e
a
510
1520
0.1
0.2
0.3
0.4
EA
MP
==>
hic
p-e
a
510
1520
-20020
EA
MP
==>
sh
ado
w
510
1520
012
EA
AD
==>
gd
p-r
o
510
1520
0.51
1.52
2.5
EA
AD
==>
hic
p-r
o
510
1520
-3-2-10
EA
AD
==>
eu
rro
n
510
1520
-50510
EA
AD
==>
i-ro
510
1520
0
0.2
0.4
0.6
EA
AD
==>
gd
p-e
a
510
1520
0.2
0.4
0.6
EA
AD
==>
hic
p-e
a
510
1520
406080
EA
AD
==>
sh
ado
w
510
1520
024
EA
AS
==>
gd
p-r
o
510
1520
-2-10
EA
AS
==>
hic
p-r
o
510
1520
-4-20
EA
AS
==>
eu
rro
n
510
1520
-10010
EA
AS
==>
i-ro
510
1520
0.51
1.5
EA
AS
==>
gd
p-e
a
510
1520
-0.6
-0.4
-0.20
EA
AS
==>
hic
p-e
a
510
1520
0204060
EA
AS
==>
sh
ado
w
Note: Results are represented with pointwise median and 68% confidence bands.
40
Figure 9: Historical decomposition of GDP and HICP for euro area (annual changes)
05 06 07 08 09 10 11 12 13 14 15 16 17 18-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06gdp-ea
data
baseline
EA MP
EA AD
EA AS
05 06 07 08 09 10 11 12 13 14 15 16 17 18-0.02
-0.01
0
0.01
0.02
0.03
0.04hicp-ea
data
baseline
EA MP
EA AD
EA AS
41
Figure 10: Historical decomposition of GDP and HICP for Bulgaria, Croatia and Romania(annual changes)
(a) GDP
05 06 07 08 09 10 11 12 13 14 15 16 17 18-0.1
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1gdp-bg
data
baseline
EA MP
EA AD
EA AS
BG AD
BG AS
(b) HICP
05 06 07 08 09 10 11 12 13 14 15 16 17 18-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14hicp-bg
data
baseline
EA MP
EA AD
EA AS
BG AD
BG AS
05 06 07 08 09 10 11 12 13 14 15 16 17 18-0.1
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08gdp-hr
data
baseline
EA MP
EA AD
EA AS
HR AD
HS AS
HR ER
05 06 07 08 09 10 11 12 13 14 15 16 17 18-0.04
-0.02
0
0.02
0.04
0.06
0.08hicp-hr
data
baseline
EA MP
EA AD
EA AS
HR AD
HS AS
HR ER
05 06 07 08 09 10 11 12 13 14 15 16 17 18-0.15
-0.1
-0.05
0
0.05
0.1
0.15gdp-ro
data
baseline
EA MP
EA AD
EA AS
RO AD
RO AS
RO ER
RO MP
05 06 07 08 09 10 11 12 13 14 15 16 17 18-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1hicp-ro
data
baseline
EA MP
EA AD
EA AS
RO AD
RO AS
RO ER
RO MP
42
Figure 11: Relative importance of euro area shocks to GDP
(a) Aggregate demand shock
0.0
0.2
0.4
0.6
0.8
1.0
2006 2008 2010 2012 2014 2016 2018
bg_ad hr_adro_ad ea_ad
(b) Aggregate supply shock
0.0
0.2
0.4
0.6
0.8
1.0
2006 2008 2010 2012 2014 2016 2018
bg_as hr_asro_as ea_as
(c) Monetary policy shock
0.0
0.2
0.4
0.6
0.8
1.0
2006 2008 2010 2012 2014 2016 2018
bg_mp hr_mpro_mp ea_mp
43
Figure 12: Relative importance of euro area shocks to HICP
(a) Aggregate demand shock
0.0
0.2
0.4
0.6
0.8
1.0
2006 2008 2010 2012 2014 2016 2018
bg_ad hr_adro_ad ea_ad
(b) Aggregate supply shock
0.0
0.2
0.4
0.6
0.8
1.0
2006 2008 2010 2012 2014 2016 2018
bg_as hr_asro_as ea_as
(c) Monetary policy shock
0.0
0.2
0.4
0.6
0.8
1.0
2006 2008 2010 2012 2014 2016 2018
bg_mp hr_mpro_mp ea_mp
44
Figure 13: Contribution of common shocks to GDP and HICP (median and 68% confidencebands)
(a) BG GDP
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
05 06 07 08 09 10 11 12 13 14 15 16 17 18
(b) HR GDP
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
05 06 07 08 09 10 11 12 13 14 15 16 17 18
(c) RO GDP
.1
.2
.3
.4
.5
.6
.7
.8
.9
05 06 07 08 09 10 11 12 13 14 15 16 17 18
(d) BG HICP
0.0
0.2
0.4
0.6
0.8
1.0
05 06 07 08 09 10 11 12 13 14 15 16 17 18
(e) HR HICP
.2
.3
.4
.5
.6
.7
.8
.9
05 06 07 08 09 10 11 12 13 14 15 16 17 18
(f) RO HICP
.0
.1
.2
.3
.4
.5
.6
.7
.8
05 06 07 08 09 10 11 12 13 14 15 16 17 18
45
Figure 14: Difference of IRFs of the ECB monetary policy shock on GDP and inflationbetween euro candidate countries and euro area
(a) BG
5 10 15 20-0.6
-0.4
-0.2
0
0.2
0.4
EA MP ==> gdp (bg-ea)
5 10 15 20
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
EA MP ==> hicp (bg-ea)
(b) HR
5 10 15 20
-0.4
-0.2
0
0.2
EA MP ==> gdp (hr-ea)
5 10 15 20
-0.1
0
0.1
0.2
0.3EA MP ==> hicp (hr-ea)
(c) RO
5 10 15 20
-0.5
0
0.5
1
EA MP ==> gdp (ro-ea)
5 10 15 20
0
0.5
1
1.5EA MP ==> hicp (ro-ea)
Note: Results are represented with pointwise median and 68% confidence bands.
46
The following Working Papers have been published:
No. Date Title Author(s)
W-1 December 1999 Croatia in the Second Stage of Transition, 1994–1999 Velimir Šonje and Boris Vujčić
W-2 January 2000 Is Unofficial Economy a Source of Corruption? Michael Faulend and Vedran Šošić
W-3 September 2000Measuring the Similarities of Economic Developments in Central Europe: A Correlation between the Business Cycles of Germany, Hungary, the Czech Republic and Croatia
Velimir Šonje and Igeta Vrbanc
W-4 September 2000Exchange Rate and Output in the Aftermath of the Great Depression and During the Transition Period in Central Europe
Velimir Šonje
W-5 September 2000 The Monthly Transaction Money Demand in Croatia Ante Babić
W-6 August 2001General Equilibrium Analysis of Croatia’s Accession to the World Trade Organization
Jasminka Šohinger, Davor Galinec and Glenn W. Harrison
W-7 February 2002 Efficiency of Banks in Croatia: A DEA Approach Igor Jemrić and Boris Vujčić
W-8 July 2002A Comparison of Two Econometric Models (OLS and SUR) for Forecasting Croatian Tourism Arrivals
Tihomir Stučka
W-9 November 2002Privatization, Foreign Bank Entry and Bank Efficiency in Croatia: A Fourier-Flexible Function Stochastic Cost Frontier Analysis
Evan Kraft, Richard Hofler and James Payne
W-10 December 2002 Foreign Banks in Croatia: Another Look Evan Kraft
W-11 October 2003 The Impact of Exchange Rate Changes on the Trade Balance in Croatia Tihomir Stučka
W-12 August 2004 Currency Crisis: Theory and Practice with Application to Croatia Ivo Krznar
W-13 June 2005 Price Level Convergence: Croatia, Transition Countries and the EU Danijel Nestić
W-14 March 2006 How Competitive Is Croatia’s Banking System? Evan Kraft
W-15 November 2006 Microstructure of Foreign Exchange Market in Croatia Tomislav Galac, Ante Burić, Ivan Huljak
W-16 December 2006 Short-Term Forecasting of Inflation in Croatia with Seasonal ARIMA Processes Andreja Pufnik and Davor Kunovac
W-17 February 2008 Modelling of Currency outside Banks in CroatiaMaroje Lang, Davor Kunovac, Silvio Basač and Željka Štaudinger
W-18 June 2008 International Business Cycles with Frictions in Goods and Factors Markets Ivo Krznar
W-19 December 2008Use of the Hedonic Method to Calculate an Index of Real Estate Prices in Croatia
Davor Kunovac, Enes Đozović, Gorana Lukinić, Andreja Pufnik
W-20 May 2009 Contagion Risk in the Croatian Banking System Marko Krznar
W-21 October 2009Optimal International Reserves of the CNB with Endogenous Probability of Crisis
Ana Maria Čeh and Ivo Krznar
W-22 December 2009 The Impact of the Financial Crisis and Policy Responses in CroatiaNikola Bokan, Lovorka Grgurić, Ivo Krznar, Maroje Lang
W-23 April 2010 Habit Persistence and International Comovements Alexandre Dmitriev and Ivo Krznar
W-24 April 2010Capital Inflows and Efficiency of Sterilisation – Estimation of Sterilisation and Offset Coefficients
Igor Ljubaj, Ana Martinis and Marko Mrkalj
W-25 April 2010 Income and Price Elasticities of Croatian Trade – A Panel Data Approach Vida Bobić
W-26 December 2010 Impact of External Shocks on Domestic Inflation and GDP Ivo Krznar and Davor Kunovac
W-27 December 2010 The Central Bank as Crisis-Manager in Croatia – A Counterfactual Analysis Tomislav Galac
W-28 January 2011 A Credit Market Disequilibrium Model And Periods of Credit CrunchAna Maria Čeh, Mirna Dumičić and Ivo Krznar
W-29 November 2011 Identifying Recession and Expansion Periods in Croatia Ivo Krznar
W-30 November 2011Estimating Credit Migration Matrices with Aggregate Data – Bayesian Approach
Davor Kunovac
W-31 November 2011 An Analysis of the Domestic Inflation Rate Dynamics and the Phillips Curve Ivo Krznar
W-32 January 2012Are Some Banks More Lenient in the Implementation of Placement Classification Rules?
Tomislav Ridzak
W-33 January 2012 Global Crisis and Credit Euroisation in Croatia Tomislav Galac
W-34 April 2012Estimating the Impact of Monetary Policy on Household and Corporate Loans: a FAVEC Approach
Igor Ljubaj
No. Date Title Author(s)
W-35 November 2012 Estimating Potential Output in the Republic of Croatia Using a Multivariate Filter Nikola Bokan and Rafael Ravnik
W-36 March 2013Pricing behaviour of Croatian Companies: results of a Firm survey and a Comparison with the eurozone
Andreja Pufnik and Davor Kunovac
W-37 April 2013 Financial Conditions and Economic Activity Mirna Dumičić and Ivo Krznar
W-38 August 2013The borrowing costs of selected countries of the European Union – the role of the spillover of external shocks
Davor Kunovac
W-39 September 2014 Nowcasting GDP Using Available Monthly Indicators Davor Kunovac and Borna Špalat
W-40 June 2014 Short-term Forecasting of GDP under Structural Changes Rafal Ravnik
W-41 December 2014Financial Stress Indicators for Small, Open, Highly Euroised Countries – the Case of Croatia
Mirna Dumičić
W-42 September 2015Determinants of Labour Cost Adjustment Strategies during the Crisis – Survey Evidence from Croatia
Marina Kunovac
W-43 September 2015 Financial Stability Indicators – the Case of Croatia Mirna Dumičić
W-44 July 2015Microeconomic Aspects of the Impact of the Global Crisis on the Growth of Non-financial Corporations in the Republic of Croatia
Tomislav Galac
W-45 January 2017 Delayed Credit Recovery in Croatia: Supply or Demand Driven? Mirna Dumičić and Igor Ljubaj
W-46 January 2017 Exchange Rate Pass-Through in the Euro AreaMariarosaria Comunale and Davor Kunovac
W-47 Febuary 2017 Are Sovereign Credit Ratings Overrated? Davor Kunovac and Rafael Ravnik
W-48 March 2017Effectiveness of Macroprudential Policies in Central and Eastern European Countries
Mirna Dumičić
W-49 April 2017What is Driving Inflation and GDP in a Small European Economy: The Case of Croatia
Goran Jovičić and Davor Kunovac
W-50 June 2017The Effects of Economic Integration on Croatian Merchandise Trade: A Gravity Model Study
Nina Ranilović
W-51 June 2017Corporate Debt Overhang in Croatia: Micro Assessment and Macro Implications
Ana Martinis, Igor Ljubaj
W-52 July 2017 Structure of Capital Flows and Exchange Rate: The Case of CroatiaMaja Bukovšak, Gorana Lukinić Čardić, Nina Ranilović
W-53 September 2017Coherence of Business Cycles and Economic Shocks between Croatia and Euro Area Member States
Karlo Kotarac, Davor Kunovac, Rafael Ravnik
W-54 January 2018How Competitive is Croatia’s Banking System? A Tale of Two Credit Booms and Two Crises
Evan Kraft and Ivan Huljak
W-55 June 2018 Financial Cycles in Euro Area Economies: A Cross-Country PerspectiveDavor Kunovac, Martin Mandler, Michael Scharnagl
W-56 July 2018Behavioural Model of Assessment of Probability of Default and the Rating of Non-Financial Corporations
Tomislav Grebenar
Guidelines to authors
In its periodical publications Working Papers, Surveys and Technical Papers, the Croatian National Bank publishes scien-tific and scholarly papers of the Bank’s employees and other associate contributors.
After the submission, the manuscripts shall be subject to peer review and classification by the Manuscript Review and Classification Committee. The authors shall be informed of the acceptance or rejection of their manuscript for publication within two months following the manuscript submission.
Manuscripts are submitted and published in Croatian and/or English language.
Manuscripts submitted for publication should meet the fol-lowing requirements:
Manuscripts should be submitted via e-mail or optical stor-age media (CD, DVD), accompanied by one printed paper copy. The acceptable text format is Word.
The first page of the manuscript should contain the article title, first and last name of the author and his/her academic degree, name of the institution with which the author is associ-ated, author’s co-workers, and the complete mailing address of the corresponding author to whom a copy of the manuscript with requests for corrections shall be sent.
Additional information, such as acknowledgments, should be incorporate in the text at the end of the introductory section.
The second page should contain the abstract and the key words. The abstract is required to be explicit, descriptive, writ-ten in third person, consisting of not more than 250 words (maximum 1500 characters). The abstract should be followed by maximum 5 key words.
A single line spacing and A4 paper size should be used. The text must not be formatted, apart from applying bold and italic script to certain parts of the text. Titles must be numerated and separated from the text by double-line spacing, without for-matting.
Tables, figures and charts that are a constituent part of the
paper must be well laid out, containing: number, title, units of measurement, legend, data source, and footnotes. The foot-notes referring to tables, figures and charts should be indi-cated by lower-case letters (a,b,c…) placed right below. When the tables, figures and charts are subsequently submitted, it is necessary to mark the places in the text where they should be inserted. They should be numbered in the same sequence as in the text and should be referred to in accordance with that numeration. If the tables and charts were previously inserted in the text from other programs, these databases in the Excel format should also be submitted (charts must contain the cor-responding data series).
The preferred formats for illustrations are EPS or TIFF with explanations in 8 point Helvetica (Ariel, Swiss). The scanned illustration must have 300 dpi resolution for grey scale and full colour illustration, and 600 dpi for lineart (line drawings, diagrams, charts).
Formulae must be legible. Indices and superscript must be explicable. The symbols’ meaning must be given following the equation where they are used for the first time. The equations in the text referred to by the author should be marked by a se-rial number in brackets closer to the right margin.
Notes at the foot of the page (footnotes) should by indicat-ed by Arabic numerals in superscript. They should be brief and written in a smaller font than the rest of the text.
References cited in the text are listed at the last page of the manuscript in the alphabetical order, according to the authors’ last names. References should also include data on the pub-lisher, city and year of publishing.
Publishing Department maintains the right to send back for the author’s revision the accepted manuscript and illustrations that do not meet the above stated requirements.
All contributors who wish to publish their papers are wel-comed to do so by addressing them to the Publishing Depart-ment, following the above stated guidelines.
The Croatian National Bank publications
Croatian National Bank – Annual ReportRegular annual publication surveying annual monetary and general economic developments as well as statistical data.
Croatian National Bank – Semi-annual ReportRegular semi-annual publication surveying semi-annual mon-etary and general economic developments and statistical data.
Banks BulletinPublication providing survey of data on banks.
Croatian National Bank – BulletinRegular monthly publication surveying monthly monetary and general economic developments and monetary statistics.
Croatian National Bank – Working PapersOccasional publication containing shorter scientific papers written by the CNB employees and associate contributors.
Croatian National Bank – SurveysOccasional publication containing scholarly papers written by the CNB employees and associate contributors.
Croatian National Bank – Technical PapersOccasional publication containing papers of informative char-acter written by CNB employees and associate contributors.
The Croatian National Bank also issues other publications such as, for example, numismatic issues, brochures, publica-tions in other media (CD-ROM, DVD), books, monographs and papers of special interest to the CNB as well as proceed-ings of conferences organised or co-organised by the CNB, ed-ucational materials and other similar publications.