Business Cycles Synchronization between Baltic and Western European
Countries
RIMAS ZIENIUS1, ELISABETH T. PEREIRA2
1Department of Economics, Management, Industrial Engineering and Tourism,
University of Aveiro,
Campus Universitario de Santiago, 3810-193 Aveiro,
PORTUGAL
2Research Unit in Governance, Competitiveness and Public Policies,
Department of Economics, Management, Industrial Engineering and Tourism,
University of Aveiro,
Campus Universitario de Santiago, 3810-193 Aveiro,
PORTUGAL
Abstract: - This study examines the synchronisation of the business cycles between the Baltic States and the
countries of Western Europe. The study covers the following countries: Latvia, Lithuania, France, the United
Kingdom, Germany, and Estonia; and the quarterly GDP growth data during the period 1995-2017. The GDP
growth data have been modified using the Hodrick-Prescott and Baxter filters to distinguish business cycles. To
measure the synchronisation between the business cycles of the selected countries, the correlation between the
business cycles of the countries was used. The results show that the business cycles of the Baltic and Western
European countries were more synchronised in 2009-2014 than in 1998-2014. It shows that the Baltic
economies are becoming more related to the European Union countries and less related to the post-Soviet
countries.
Key-Words: - Business cycles, Synchronization, Baltic countries, Western European countries, Post-communist
countries, Economic growth.
Received: May 19, 2023. Revised: October 26, 2023. Accepted: November 9, 2023. Published: November 24, 2023.
1 Introduction
After years of economic instability and financial
crises, the world is paying more attention to the
economic situation. In this context, economic and
business cycle indicators play an important role
today, not only for governments but also for
companies. [1], argue that knowing in advance the
possible economic direction of a country and the
occurrence of its events will improve the process of
decision-makers. Government policymakers,
economists, businessmen, investors, employees, and
consumers all rely on forecasts to make future
judgments and base their strategic decisions on the
information, [2]. Over the last decade, most
European countries have experienced changes in the
business cycles. The situation has shown that
financial crises and periods of economic recovery
can be regional and worldwide. Therefore, analysing
the synchronisation of the Baltic countries' business
cycles with the Western European countries can
show how much the economies of these countries
are related to each other and whether the Baltic
countries' economies have become more related to
the Western European countries during the last
decades.
This study is relevant for understanding how
different business cycle movements in the Baltic
countries compare with those in Western European
countries, and how the business cycles between
these countries are more or less synchronised. It
contributes to the knowledge of the development
and economic process of countries that recently
changed their economic system from a planned to a
market economy in the 1990s. And its importance is
also underlined by the fact that research studies on
the Baltic countries' business cycles are scarce, so
the results of this work can be useful for policy and
investment decisions. At the same time, this paper
contributes to the improvement of economic
knowledge by comparing the differences in business
cycle synchronisation between the post-Soviet
countries and the Western European countries.
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Rimas Zienius, Elisabeth T. Pereira
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After this introduction, section 2 presents the
literature review on the topics under study with a
characterisation of cooperation after the collapse of
the Soviet Union; and section 3 presents the data
and methodology. The following section presents
and discusses the results obtained, and section 5
concludes.
2 Literature Review
[3], explain that one of the reasons for the change in
synchronisation between post-communist countries
was regional cooperation, which helps to exploit the
comparative advantages of all these countries and
allows them to present themselves as part of a whole
at the global level, thus defending their common
interests. For example, [4], [5], say that the Baltic
countries have moved from strong cooperation with
Russia to cooperation with the European Union
(EU). In this study, we have chosen to analyse the
Baltic countries as three post-communist countries:
Lithuania, Estonia, and Latvia.
According to, [6], "Business cycle
synchronisation is the correlation of output growth -
the correlation of aggregate productivity growth
between two trading partners - with different
measures of international trade (trade volume,
extensive trade margin, and intensive trade
margin)". [7], finds a positive effect of financial
integration and trade on business cycle
synchronisation. He shows that countries that have
trade relations are related by their business cycle
movements. Moreover, [8], makes research on
business cycle synchronisation, economist
decomposes the variance of growth into global,
European, and country-specific factors. The results
showed that the European component of the
business cycle has a strong influence among
European countries. Furthermore, [9], say that at the
EU level, where there is an Economic and Monetary
Union (EMU), the regional component influences
the national one, which explains a large component
of national European cycles (around 30%).
It was found that not only the EMU business
cycles have influenced the business cycles of the EU
member states, but also these shocks that occurred
in the EMU business cycles are reflected in the
national economies of the euro area members. It
shows that business cycles in the EU and its
member states can be synchronised. According to,
[10], the GDP growth of EMU member states
differs from that of the EU due to specific
differences in their business cycles, but national
business cycles also respond to shocks to EU
business cycles. Furthermore, [11], using one-way
and two-way ANOVA techniques, found that
common shocks are more important than country-
specific shocks for most EMU members.
Thus, in general, the business cycles of the EU
member states depended on the country's integration
into the EU and trade relations, in the case of the
Baltic countries, according to the research results of,
[4], on Lithuania, Latvia, Estonia, during the period
1993-2002, at the beginning Russian and Baltic
economies have a strong relationship because of
trade, but later the relationship became weaker, and
the Baltic economies' relations started to strengthen
with Western countries. It shows that belonging to a
particular union in the period of integration affects
your trade relations and together economic business
cycles begin to be related to that union, which in the
case of the Baltic countries was the EU countries.
This supports that in this study we have chosen the
EU-28 as one of the variables influencing the
business cycles of the Baltic countries, France,
Germany, and the United Kingdom.
3 Data and Methodology
In this research, nominal GDP growth has been used
to measure economic growth and business cycles. In
the literature review analysis, the majority of
authors use GDP to measure economic growth and
business cycles movements, [12], [13], [14], [15],
[16]. Another reason for choosing nominal GDP
growth as an indicator was the availability of
quarterly data. The selected research period under
analysis is 1995-2017. The data were collected from
the OECD database.
Six countries were selected for the research
sample: Latvia, Lithuania, Estonia, Germany, the
United Kingdom, and France. These countries were
chosen to be able to compare the characteristics of
business cycle dynamics between post-communist
and Western European countries. Moreover, the
reasons for comparing these countries were
differences in geographical location, level of
economic development, and time of using the
market economy system.
There are several different methods to identify
business cycle stages. [17], mentions that the most
commonly used are the Hodrick-Prescott (HP) filter
and the Baxter-King filter, [18], and, [19], estimated
business cycles using a Markov switching factor
model with time-varying transition probabilities.
According to, [19], the Markov switching model can
detect the phases of the classical cycle, the model
indicates some differentiation in the growth rate of
the economy. [20], points out that it is possible to
consider a VAR model with parameters depending
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DOI: 10.37394/23207.2023.20.222
Rimas Zienius, Elisabeth T. Pereira
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Volume 20, 2023
on a common Markov chain. This method describes
the data as futures of the different phases of the
economy and can be useful to provide information
about the phases of economic cycles and to show
how they evolve. [21], also agree that the Markov
switching vector autoregressive (MS-VAR) model
can be successfully used to identify turning points of
business cycles and phases of business cycles.
[17], and, [22], point out that the Hodrick-
Prescott (HP) filter is the most commonly used
method to identify the stages of the business cycle.
This filter is a smoothing technique that decomposes
the time series yt into two components: a trend
component gt and a cyclical component ct, hence
yt = gt + ct. According to, [23], the HP filter is one
of the most widely used econometric methods for
measuring business cycles and potential output in
empirical research. It is also a smoothing method
that belongs to a very general class of non-
parametric smoothing procedures that depend on a
tuning parameter that determines the properties of
the smoother, [24], [25]. Finally, based on two
criteria: literature review and availability of the
method with the GRETL software, we chose to use
the HP filter over the Markow switching model. [5],
explain the HP filter method by the expression (1):
(1)
"The first term above is the sum of the squares of the
cyclical components ct = yt - gt. The second term is
a multiple λ of the sum of squares of the second
differences of the trend component. This second
term penalises fluctuations in the trend component's
growth rate: the larger the value of λ, the higher the
penalty and hence the smoother the trend series",
[26].
To measure the synchronisation of cycles, we
use the method of, [27]. We calculate the correlation
between the cyclical components of output across
countries, where a higher correlation implies a
higher degree of cycle synchronization. This method
was also used by, [28]. Following, [28], we use the
Baxter and King filter to remove cyclical
components. We fit this model with quarterly data
from 1995-2017 and with 2006-2017 to check how
the synchronisation between countries has changed.
Due to the fact that we lost some years of the data
sample by using the Baxter and King filter, the
comparison of business cycle synchronisation is
between 1998 and 2014.
4 Results and Discussion
4.1 Business Cycles Synchronization between
Western European and Baltic Countries
In this section, we have used graphical analysis and
correlation between business cycles to identify the
synchronisation of business cycles between the
Western and Baltic countries. Using the Hodrick-
Prescott and Baxter & King filters, we plotted the
business cycle movements in selected countries in
Figure 1 and Figure 2. The synchronisation between
the business cycles of France and Germany was
found (Figure 1). Figure 2 shows that the UK
business cycle is less synchronised with the French
and German business cycles.
[29], emphasize the perception of a cyclically
coherent group consisting of Eurozone countries
(Germany, France, and Italy) and that the UK is
more synchronized with the United States and
Canada than with EU member states. [25], points to
the existence of a high degree of business cycle
synchronisation among members of the monetary
union. France, Germany, and the Baltic states have
the same currency, the euro, while the UK has the
British pound as its currency. This is one of the
reasons pointed out to explain why the UK business
cycle is not synchronised with France and Germany.
Fig. 1: Business cycles synchronization in Germany,
France, and UK.
Source: Figure made by authors using GRETL program.
The Baltic business cycles are synchronised
(Figure 2). They have coincident turning points in
their business cycles (1999 and 2009 are troughs
and 2004 is a peak). [30], argue that the Baltic
countries experience asymmetric shocks with the
Western European countries, as the structure and
processes they go through are significantly different
from euro members such as Germany or France.
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Fig. 2: Business cycle synchronization in Baltic
countries.
Source: Figure made by authors using GRETL program
Figure 1 and Figure 2 show that the
synchronisation of Baltic countries and Western
European countries differs in terms of business
cycle turning points. In 1999, the Baltic countries
are in recession, while the Western European
countries are in expansion. In 2004, Germany
overcomes its recession and the Baltic countries
have an expansion phase of the business cycle. The
differences in business cycle synchronisation
between the Baltic and Western European countries
can also be explained by trade relations. The Baltic
countries have more trade relations with Russia and
other post-Soviet countries, while Germany and
France have more trade relations with North
American countries. That's why in 1998-1999
Russian financial crisis affected Baltic countries'
business cycle movements, but not Western
European countries, while in 2001-2004 the
slowdown of world economic growth did not affect
Lithuania, Latvia, and Estonia's GDP growth, but
Germany's.
According to, [31], the decline in output and
income of trading partners will reduce imports and
negatively affect business cycle co-movements.
[32], believe that the increase in trade and financial
linkages between developed and emerging
economies is associated with the emergence of
group-specific cycles. The Baltic countries have all
adopted the euro currency since 2015, so their level
of integration with the EU is increasing. According
to, [27], economic and monetary integration should
stimulate intra-industry trade relations, which in
turn will lead to related business cycles between
countries.
Finally, we compute the correlation between the
cyclical components of output in countries. As a
result, we find that the synchronisation of business
cycles between the Baltic countries is higher than
between the Western European countries during the
period 1998Q3 - 2014Q3 (Table 1). Furthermore,
we found a high correlation of 0.85 between the
business cycles of Estonia and Germany. The
business cycles of Germany and France were found
to be less correlated with the UK (correlation
coefficient of 0.79), compared to the correlation of
0.93 between the business cycles of France and
Germany.
Table 1. GDP correlation after adapting Baxter and
King Filter during 1998Q3 – 2014Q3.
Lithuania
Latvia
Estonia
Germany
France
UK
Lithuania
1
0.84
0.85
0.74
0.64
0.71
Latvia
0.84
1
0.87
0.68
0.61
0.61
Estonia
0.85
0.87
1
0.85
0.76
0.72
1
Germany
0.74
0.68
0.85
1
0.93
0.79
France
0.64
0.61
0.76
0.93
1
0.79
UK
0.71
0.61
0.72
0.79
0.79
1
Table 2. GDP correlation after adapting Baxter and
King Filter during 2009Q1 – 2014Q3.
Lithuania
Latvia
Estonia
Germany
France
UK
Lithuania
1
0.92
0.98
0.9
0.89
0.8
6
Latvia
0.92
1
0.9
0.71
0.72
0.6
3
Source. Table made by authors using GRETL.
During the period 2009Q1-2014Q3, there was a
strong synchronisation of business cycles between
all countries except Latvia (Table 1). Latvia was
highly correlated with the Baltic countries, but less
correlated with the Western countries (Table 2). The
strong synchronization during 2009Q1-2014Q3 can
be explained by the global financial crisis in 2008
and the subsequent recovery phase.
4.2 Business Cycle Stages Comparison
between Western and Baltic Countries
We use the HP filter to distinguish business cycle
phases. This method does not show any complete
business cycle in France during the period 1995-
2017 (Appendix 1). However, using the BK filter,
we found two business cycles during 1998-2014.
Moreover, using the Markov switching factor
model, [33], found three business cycles in France
during 1993-2015. Appendix 1 shows the GDP
growth of France during different stages of business
cycles. France's business cycle has the same peak
point, in 1999Q1, and trough point, in 2008Q2, as
Germany's. We find that France has long periods of
slowdown and expansion, while downturns and
recoveries were shorter by only a few years during
the period 1995-2017. However, France's GDP
growth during expansion periods remains relatively
low, around 0.5% per quarter until 2008 (Figure 3).
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During the 2008Q3-2009Q1 downturn, GDP fell by
an average of -0.97% per quarter (Appendix 1).
Fig. 3: France's GDP growth during the business
cycle stages 1995-2017.
Source. Figure made by authors using data from OECD
database.
During the period 1995-2017, using the HP filter,
we distinguish two expansion and two slowdown
stages in the UK (Appendix 2). During the
expansion period 1995Q1-1999Q4, the average
GDP growth per quarter was 0.76%, during the
slowdown period 2000Q1-2008Q1 the average GDP
growth per quarter was 0.67% (GDP growth is
shown in Appendix 3). After the 2008-2009 crisis,
growth rates decreased, during the 2009Q4-2014Q4
expansion growth per quarter was 0.53% and during
the 2015Q1-2017Q2 slowdown GDP growth per
quarter was 0.41%. There was a downturn in 2008-
2009, during which average quarterly GDP growth
was -1.56%. Using the HP filter, we distinguish a
full business cycle in the UK from the peak in
1999Q4 to the peak in 2014Q4. GDP volatility is
similar to France and the UK, but lower than in the
Baltic countries. It is possible that the economic
slowdown in the UK from 2015 was the
consequence of Brexit. According to, [34], Brexit is
reflected in several effects on the UK economy:
higher trade costs, and lower foreign direct
investment. In the opinion of, [35], the main
consequences of Brexit are the decrease in trade in
goods and services between the UK and the EU27
countries.
Using the HP filter method, two complete
business cycles were distinguished in Germany
(Appendix 2). From the peak in 1999 Q1 to the peak
in 2006Q2 and from 2006Q2 to the peak in 2011Q3.
According to, [36], business cycles in Germany are
characterised by an interval between 2.1 and 7.5
years.
During 1995-2017, there were two downturns and
three recovery periods in Germany, when economic
growth was negative or close to 0 (Appendix 4). The
downturns in Germany were during 2008Q3-
2008Q4 (average GDP growth was -2.26 per
quarter) and during 2001Q3-2003Q1 (average GDP
growth was -0.17% per quarter). Downturn periods
have usually been followed by 1-2 years of recovery
and a few years of expansion when GDP growth is
boosted (Appendix 5).
Moreover, Germany is only one of the selected
Western countries to have experienced a downturn
and a recovery in the period 2001-2005 (Appendix
4). France and the UK also experienced lower
economic growth in 2002, but not as low as
Germany. [37], says that the stagnation in Germany
in 2001-2004 was caused by uncertainty in
expectations of future economic growth. This
uncertainty was largely due to the rise in world oil
prices, the 11 September attacks in the USA, the
changeover of the national currency to the euro, and
the stock market crisis in Germany. These events
make companies concerned about future growth and
they reduce production levels, which reduces
consumption, which increases unemployment. [38],
explains that the 2001-2004 stagnation in Germany
was caused by the global decline in economic
activity. According to, [38], Germany is
characterised by very close relations with the US,
that's why any downturn in the US negatively
affected Germany's GDP growth. On the other hand,
the Baltic countries' GDP grew during 2001-2004.
Baltic countries are small open economies and their
main trade relations are continental with Russia (the
main exporting country, foreign direct investment,
energy resources) and European countries.
Furthermore, the evidence for the different
business cycles in Germany and the Baltic countries
is the business cycle correlation between selected
countries. We have tested the correlation of
Germany's business cycle with the business cycles
of other selected countries. The results show that
Germany's business cycle is highly correlated with
France 0.93, UK 0.79, and Estonia 0.85 and less
correlated with Lithuania and Latvia.
Using the HP filter method, we constructed
Appendix 7 to show the dynamic movements of the
Latvian business cycle. Appendix 7 and Appendix 8
shows that during 1995-2008 there were expansion
and contraction phases of the business cycle in
Latvia. The growth during the 1995Q2-2004Q1
expansion stage was 1.39%, and during the 2004Q2-
2007Q3 slowdown stage was 2.66%. After a long
period of GDP growth, the Latvian economy
experienced a downturn during 2007Q4-2009Q3.
-2
-1,75
-1,5
-1,25
-1
-0,75
-0,5
-0,25
0
0,25
0,5
0,75
1
1,25
1,5
1995 1997 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018
Quaterly GDP growth
mean GDP growth
Expansion Slowdown Downturn Retrieval Expansion
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During the downturn, the average GDP growth rate
in Latvia was -2.46 % per quarter. Even recovery
after crises was fast for Latvia's economy, but the
country did not exceed the same growth rates as in
the 2000-2008 period. From 2010Q4 to 2017Q2
Latvia's GDP growth rate was 0.9 % per quarter.
On the other hand, Appendix 9 shows the
business cycle stage of Estonia, where it is observed
that during 1995-2008 expansion and slowdown
business cycle stages occurred in Estonia. The GDP
growth during the 1995Q2-19997Q3 expansion
stage was 1.83%, and during the 1997Q4-1998Q2
slowdown stage was 0.95%, while during the
1998Q3-2007Q4 expansion stage was 1.45% per
quarter. After a long period of GDP growth, the
Estonian economy experienced a downturn during
2008Q1-2009Q1. During this downturn, the average
GDP growth rate was -3.23% per quarter.
According to, [39], Estonia has hardly experienced
past crises due to speculative bubbles in asset and
financial markets.
Based on the HP filter method, a full business
cycle was distinguished in Lithuania from the 1999
Q1 trough to the 2009 Q3 trough. During 1995-
2017, the main business cycle phases were
slowdown and expansion, which have a positive
output gap (Appendix 11). The average GDP growth
during the expansion phases in Lithuania was
1.16%. The average GDP growth during slowdown
periods was 1.63% (Appendix 11 shows Lithuania's
GDP growth during different business cycle
periods). As represented in Appendix 11 and
Appendix 12, we can observe that during the
periods 1998-1999 and 2008-2010, Lithuania had
slowdown and expansion stages when the output
gap was negative, which, according to, [25], was
caused by the Russian crisis in 1998 and the
financial crisis in 2008-2009. During the 2008Q2-
2009Q3 downturn, Lithuania's quarterly GDP
growth rate was -2.5%. Lithuania survived the last
crises with hard consequences, by decreasing GDP,
increasing unemployment, increasing migration, and
decreasing capital flows, while the 1998-1999
downturn was a temporary decrease in exports.
Using the HP filter method, we found a
downturn period in 1998-1999 only in Lithuania,
but Latvia and Estonia also verified a decline in
their GDP growth in the same period. This was
explained by, [39], [40], and, [41], by the impact of
the Russian economic downturn when the Russian
currency was devalued, which affected Baltic
exports. Even in 1998, the Baltic countries and
Russian business cycles were strongly related, from
that time the Baltic countries integrated into the EU
and established relations with Western European
countries, which means that the Russian influence
on the Baltic countries' business cycle dynamics is
decreasing in these days.
As can be seen in Appendix 6 and Appendix 13,
the Baltic countries and the selected Western
European countries passed through a downturn
phase in 2008-2009. However, the decline in GDP
in the Baltic countries is higher than in the Western
European countries. [38], explains this fact on the
basis of stronger recession in Baltic countries as a
result of an overheated economy. According to this
author, between 2000 and 2008, the economies of
Lithuania, Latvia, and Estonia verified economic
growth due to high domestic consumption, easy
access to cheap credit, and rapid inflow of foreign
investment. Foreign investment between 1994 and
2008 averaged about 8% of GDP in Estonia, more
than 5% in Latvia, and almost 4% in Lithuania. This
made the Baltic countries particularly sensitive to
changes in external markets. However, the financial
crises reduced all foreign capital inflows, especially
in the financial and banking sectors. The loss of
exports, foreign capital inflows, and high debt levels
were factors in the deepest recession in the EU in
2008-2009.
5 Conclusion
After analysing the obtained results, we can say that
the business cycle dynamics of the Baltic countries
are dependent on external shocks, which is in line
with the main conclusions of, [25]. We tested the
business cycle correlation between the Baltic
countries and the Western European countries, and
the results show that the Baltic countries are highly
correlated with each other, above 0.85. These results
are also consistent with those of, [25], who
explained that there is a high business cycle
correlation between Baltic countries because these
countries trade extensively with each other and have
common import and export markets. Finally, the
correlation between the business cycles of the Baltic
countries and the business cycles of the Western
European countries was examined. Estonia's
business cycle was most correlated with the
business cycles of the Western countries (0.85 with
France, 0.74 with Germany, and 0.72 with the UK),
while Latvia's business cycle correlated with France
and the UK around 0.6, with Germany 0.68 and
Lithuania's business cycle correlated with Germany
0.74, with the UK 0.71 and with France 0.64.
So, in conclusion, we found that the business
cycles of the Baltic countries and Western European
countries are becoming more synchronised, as the
correlation coefficients between these countries are
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higher in 2009-2014 than in 1998-2014. However, if
we look at the period 1995-2017, we can see that
there are similar movement dynamics of business
cycles during some periods between Baltic countries
and Western European countries, but the business
cycles of Baltic countries have different movement
dynamics than Western European countries. The
evidence of this is the different business cycle
expansions, downturn phases between these
Western and Baltic countries, and higher correlation
of business cycles between Baltic countries, proving
their economic, social, and cultural symmetries
compared to Western European countries.
Acknowledgment:
The authors would like to thanks the comments of
the three reviewers.
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APPENDIX
Appendix 1. France's business cycle by HP filter during 1995-2017.
Source. Figure made by authors using GRETL modified data from OECD database
Appendix 2. UK business cycle by HP filter during 1995-2017.
Source. Figure made by authors using GRETL modified data from OECD database
Appendix 3. UK GDP growth during business cycle stages 1995-2017.
Source. Figure made by authors using data from OECD database
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Appendix 4. Germany's business cycle by HP filter during 1995-2017.
Source. Figure made by authors using GRETL modified data from OECD database.
Appendix 5. Germany's GDP growth during the business cycle stages 1995-2017.
Source. Figure made by authors using GRETL modified data from OECD database.
HP-Filter method Germany
HP-Filter method France
HP-Filter method UK
Stage
Duration
Economy
growth %
Stage
Duration
Economy
growth %
Stage
Duration
Economy
growth %
Retrieval
1995Q1-1997Q1
0.19
Expansion
1995Q1-1999Q1
0.58
Expansion
1995Q1-1999Q4
0.76
Expansion
1997Q2-1999Q1
0.50
Slowdown
1999Q2-2008Q2
0.54
Slowdown
2000Q1-2008Q1
0.67
Slowdown
1999Q2-2001Q2
0.68
Downturn
2008Q3-2009Q1
-0.97
Downturn
2008Q2-2009Q1
-1.56
Downturn
2001Q3-2003Q1
- 0.17
Retrieval
2009Q2-2009Q3
0.01
Retrieval
2009Q2-2009Q3
-0.08
Retrieval
2003Q2-2005Q2
0.18
Expansion
2009Q4-2017Q2
0.31
Expansion
2009Q4-2014Q4
0.53
Expansion
2005Q3-2006Q2
0.93
Slowdown
2015Q1-2017Q2
0.41
Slowdown
2006Q3-2008Q2
0.65
Downturn
2008Q3-2008Q4
- 2.26
Retrieval
2009Q1-2009Q3
0.53
Expansion
2009Q4-2011Q3
0.98
Slowdown
2011Q4-2013Q1
0.00
Expansion
2013Q2-2017Q2
0.48
Full cycle
length (2):
6.375 Years
Full cycle
length:
No full cycle
Full cycle
length:
15 years
Appendix 6 . Germany, France and UK business cycle stages during 1995 – 2017 using HP filter.
-5,10
-4,80
-4,50
-4,20
-3,90
-3,60
-3,30
-3,00
-2,70
-2,40
-2,10
-1,80
-1,50
-1,20
-0,90
-0,60
-0,30
-
0,30
0,60
0,90
1,20
1,50
1,80
2,10
2,40
Qauterly GDP change
Average GDP
Retrieval Expansion Slowdown Down. Retr. Expan. Slow. Down. Expan. Slow. Expan.
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Appendix 7. Latvia business cycle by HP filter during 1995-2017
Source. Figure made by authors using data from OECD database.
Appendix 8. Latvia GDP growth during business cycles stages 1995-2017.
Source. Figure made by authors using data from OECD database.
Appendix 9. Estonia business cycle by HP filter during 1995-2017.
Source. Figure made by authors using data from OECD database.
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
1995
1996
1997
1997
1998
1999
2000
2001
2002
2002
2003
2004
2005
2006
2007
2007
2008
2009
2010
2011
2012
2012
2013
2014
2015
2016
2017
GDP quaterly growth
GDP growth mean
Expansion Slowdown Downturn Retrieval Expansion
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Appendix 10. Estonia GDP growth during business cycles stages 1995-2017.
Source. Figure made by authors using data from OECD database.
Appendix 11. Lithuania business cycle by HP filter during 1995-2017.
Source. Figure made by authors using GRETL modified data from OECD database.
Appendix 12. Lithuania GDP growth during business cycles stages 1995-2017.
Source. Figure made by authors using data from OECD database.
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
GDP quaterly growth
Mean of GDP growth
-15
-14
-13
-12
-11
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
1
2
3
4
5
6
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
GDP quaterly growth
data
GDP growth mean
Slowdown Expansion
Downturn
and Retrieval
Expansion Slowdown
Downturn
and Retrieval
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HP-Filter method Lithuania
HP-Filter method Latvia
HP-Filter method Estonia
Stage
Duration
Economy
growth %
Stage
Duration
Economy
growth %
Stage
Duration
Economy
growth %
Slowdown
1995Q2-1998Q3
1.68
Expansion
1995Q2-2004Q1
1.39
Expansion
1995Q2-1997Q3
1.83
Downturn
1998Q4-1999Q1
-0.92
Slowdown
2004Q2-2007Q3
2.66
Slowdown
1997Q4-1998Q2
0.95
Retrieval0
1999Q2-1999Q4
-0.31
Downturn
2007Q4-2009Q3
-2.46
Expansion
1998Q3-2003Q1
1.45
Expansion
2000Q1-2003Q4
1.91
Retrieval
2009Q4-2010Q3
-0.17
Slowdown
2003Q2-2007Q4
1.78
Slowdown
2004Q1-2008Q1
1.88
Expansion
2010Q4-2017Q2
0.90
Downturn
2008Q1-2009Q1
-3.23
Downturn
2008Q2-2009Q3
-2.50
Retrieval
2009Q2-2010Q3
-0.73
Retrieval
2009Q4-2010Q1
-0.28
Expansion
2010Q4-2017Q2
0.89
Expansion
2010Q2-2017Q2
0.91
Full cycle
length (2):
6.375 Years
Full cycle
length:
No full cycle
Full cycle
length:
No full cycle
Appendix 13. Baltic countries business cycle stages during 1995 – 2017 using HP filter.
Source. Figure made by authors using data from OECD database.
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed in the present
research, at all stages from the formulation of the
problem to the final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
This work was in part financially supported by the
research unit on Governance, Competitiveness and
Public Policy (UID/CPO/04058/2019), funded by
national funds through FCT - Fundaao para a
Cien ia e a Tecnologia, Portugal.
Conflict of Interest
The authors have no conflicts of interest to declare.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
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Creative Commons Attribution License 4.0
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