Business
Cycles’ Characteristics of the Mediterranean Area Countries
Marco Gallegati, Mauro Gallegati, Wolfgang Polasek
Emails: marcog@dea.unian.it, polasek@ihs.ac.at
JEL classification numbers: E32, E31.
Keywords: Business Cycle Fluctuations, Mediterranean Countries, Economic Links
Abstract
In
this paper we investigate the characteristics of business cycles fluctuations
in the countries of the Mediterranean region by applying the
Christiano-Fitzgerald bandpass filter to the output series of 12 Mediterranean
countries over the period 1950-1998. The main properties of business cycle
fluctuations (persistence, volatility, asymmetry and synchronization) are
computed with reference to the deviation or growth cycle definition of the
business cycle. Overall, the results of our analysis suggest, as expected, the
existence of important differences in the characteristics of business cycle
fluctuations among countries belonging to different economic level of
development. Moreover, the average reduction of the degree of synchronization
among Mediterranean countries seems to suggest a weakening of the economic
links among Mediterranean countries, and thus a reduction of the economic
importance of the links in this area in comparison to the European continental
area.
The
overwhelming majority of empirical studies on business cycle fluctuations have
analysed stylized facts focussing on the cross-country differences and
similarities of macroeconomic fluctuations in developed countries (Kydland and
Prescott, 1990, Backus and Kehoe, 1992, Bergman et al., 1998, Correia et al.,
1992, Blackburn and Ravn, 1992, Fiorito and Kollintzas, 1992, Englund et al., 1992, Brandner and Neusser,
1990, Dimelis et al., 1992, and
Christodoulakis et al., 1995, Stock
and Watson, 1998, Basu and Taylor, 1999, Gallegati and Gallegati, 2001, 2003).
Much less attention has been devoted in the literature to examining the sources
of macroeconomic fluctuations and business cycle characteristics in developing
countries both individually (Alper, 2000, Metin-Ozcan, Voyvoda and Yeldan,
2001, and Turhan-Sayan and Sayan, 2001) and as a group (Kose and Riezman, 1998,
2001), as well as in comparison with the developed countries (Mendoza, 1995).
In our study we describe the
business cycle characteristics of a group of 12 Mediterranean countries
analyzing the main properties of the real GDP series, i.e. persistence, volatility, asymmetry and synchronization, over
the period 1950-1998. The analysis describes the key features of business cycle
fluctuations in the following countries:
The paper is as follows. After
establishing business cycle chronology in section 2, section 3 analyzes
persistence and volatility of business cycles output component. Section 4 and 5
provides evidence of business cycle asymmetry and synchronization,
respectively. Section 6 concludes the paper.
Dating
business cycles, i.e. identification
of turning points, recession and expansion phases, may be obtained determining
peaks and troughs in the level of a series, classical
cycles, or in the level of a detrended series, growth cycles. In this paper the reference cycle chronologies for
the 15 Mediterranean countries are established using the “growth rate” cycle
definition, which delineate periods of cyclical upswings and downswings around
an underlying trend. Growth cycles are more useful for business cycle analysis
in countries that experience sharp contractions and expansions in growth rates.
In a growth cycle a recession is defined as a phase where output is below its
trend, while an expansion is a phase where output is above its trend. The
procedure used to identify peaks and troughs in the growth rate cycle are
analogous to those used in identifying classical business cycle turning points,
the only difference being that they are applied to growth rates of the same
time series, rather than their levels (see Canova, 1994). Identified turning
points are selected using a minimum amplitude rule which requires the amplitude
from peak to trough and from trough to peak to be at least as large as one
standard error of the cyclical component of output.
Growth cycles, and then countries’ business cycle characteristics, depend on the method used for the trend-cycle decomposition. In this paper we isolate fluctuations at business cycle frequencies using the Christiano and Fitzgerald’s (1999) least squares optimal approximation of the ideal band pass filter. The filter, after removing the drift in the raw series, allows the extraction of the component of the raw data with periodicity between 2 and 8 years, i.e. a typical business cycle frequency range with annual data (see Stock and Watson, 1998). The advantage of using such a filter in our case is linked to the reduced number of data that have to be dropped from the beginning and end of the filtered series in comparison to, for example, the Baxter and King’s (1999) filter.[2] We examine the business cycle properties of real GDP series for 12 Mediterranean countries using annual data at constant prices (million 1990 international Geary-Khamis dollars) over the period 1950-1998 (Maddison, 2001).
The peaks and troughs dates for all 15 GDP series
are reported in Table 1. The information in Table 1 points to three major
periods of international recession, during 1958-1960, 1973-1975, and 1993-1995,
and three major periods of international expansion, 1956-1959, 1963-1965 and
1979-1981. In the time-span of our sample the countries have experienced from
6.5 to 11 cycles, which means that the typical or average cycle lasts from
about
Table 1 –
Growth cycle chronology for Mediterranean countries |
||||||||||||
|
ALG |
EGY |
FRA |
GRE |
ISR |
ITA |
JOR |
MOR |
SPA |
SYR |
TUN |
TUR |
Peak |
1954 |
|
|
1953 |
|
1953 |
1953 |
|
|
1954 |
1953 |
1953 |
Trough |
|
1955 |
1953 |
1954 |
1953 |
|
1955 |
1955 |
1954 |
1955 |
1955 |
1954 |
Peak |
|
1957 |
1957 |
1957 |
1959 |
|
1956 |
|
1958 |
1957 |
1956 |
1959 |
Trough |
1958 |
|
1959 |
1960 |
|
1960 |
1960 |
1960 |
1960 |
1960 |
1959 |
|
Peak |
1960 |
|
|
1961 |
|
|
1961 |
|
1962 |
1962 |
1961 |
|
Trough |
1962 |
1961 |
|
1962 |
1962 |
|
1963 |
|
|
|
1962 |
1961 |
Peak |
1965 |
1965 |
1964 |
1965 |
1965 |
1963 |
1965 |
1963 |
|
|
1965 |
1963 |
Trough |
1966 |
|
|
|
|
1965 |
1966 |
1965 |
1964 |
1966 |
|
1965 |
Peak |
|
|
|
|
|
|
1967 |
|
1966 |
|
|
1966 |
Trough |
|
1968 |
1968 |
1968 |
1967 |
|
1968 |
|
1967 |
|
1967 |
|
Peak |
1970 |
1971 |
|
|
1969 |
1969 |
1969 |
1971 |
1969 |
1969 |
1968 |
|
Trough |
1971 |
|
|
|
|
1972 |
1970 |
1972 |
1971 |
1971 |
1970 |
|
Peak |
1972 |
|
1973 |
1972 |
|
1974 |
1973 |
|
1974 |
1972 |
1972 |
|
Trough |
|
1974 |
1975 |
1974 |
|
1975 |
1975 |
|
1975 |
1973 |
1973 |
1974 |
Peak |
|
1977 |
|
1978 |
|
1976 |
1976 |
1976 |
|
1976 |
|
1976 |
Trough |
1976 |
|
|
|
1977 |
1978 |
1977 |
1979 |
|
1979 |
|
|
Peak |
1979 |
|
1979 |
|
1981 |
1980 |
1980 |
1980 |
1980 |
1981 |
1981 |
|
Trough |
1981 |
1981 |
1981 |
|
|
1982 |
|
1981 |
|
|
1982 |
1980 |
Peak |
|
|
|
|
|
|
|
1982 |
|
|
|
|
Trough |
|
|
|
1983 |
1984 |
|
1983 |
1983 |
|
1984 |
|
|
Peak |
1985 |
1985 |
1984 |
1985 |
|
1985 |
|
1986 |
|
|
1985 |
1984 |
Trough |
1988 |
1987 |
1987 |
1987 |
|
|
|
1987 |
1986 |
|
1986 |
1985 |
Peak |
|
|
1989 |
1989 |
1987 |
|
1988 |
|
|
1988 |
1987 |
1987 |
Trough |
|
|
|
1990 |
1989 |
|
|
|
|
1989 |
1989 |
1989 |
Peak |
1990 |
1990 |
|
|
|
|
|
1991 |
1991 |
|
|
1990 |
Trough |
|
1991 |
|
|
|
|
1991 |
|
|
|
|
1991 |
Peak |
|
1994 |
|
1992 |
|
|
1992 |
|
|
1993 |
1992 |
1993 |
Trough |
1994 |
1995 |
1993 |
1993 |
|
1993 |
|
1993 |
1993 |
|
1995 |
1994 |
Peak |
|
|
1995 |
|
1995 |
1995 |
|
1996 |
1995 |
|
|
|
Trough |
|
|
|
|
|
|
|
|
|
1996 |
|
|
In Table 2 we present the number of cycles characterizing Mediterranean
countries for the post-World War II period and for two sub-periods, before and
after the first oil-shock. During the second half of the XXth
century there are many differences among the countries of our sample, as we
have countries which experience less than eight cycles (Algeria, Egypt, France,
Israel and Italy and), between eight and ten cycles (Morocco, Spain, Syria and
Turkey), and more than ten cycles (Greece, Jordan, and Tunisia). But when we halve the whole period, the comparison of the two
sub-periods evidence that the number of cycles has changed significantly over
time across countries. In particular, the countries with the highest
number (and with the shortest length) of cycles, i.e.
Table 2 - Number of cycles in 1950-1998,
1950-1974 and 1975-1998
|
FRA |
ITA |
GRE |
SPA |
TUR |
SYR |
EGY |
MOR |
ISR |
ALG |
TUN |
JOR |
1950 1998 |
8 |
7.5 |
10 |
8.5 |
9.5 |
9.5 |
7.5 |
9 |
6.5 |
8 |
11 |
11 |
1950 1974 |
3.5 |
3.5 |
6 |
5.5 |
4 |
5.5 |
3.5 |
3 |
3.5 |
4.5 |
6.5 |
6.5 |
1975 1998 |
4.5 |
4 |
4 |
3 |
5.5 |
4 |
4 |
6 |
3 |
3.5 |
4.5 |
4.5 |
In this
section we briefly discuss the basic time-series properties of business cycles fluctuations
across Mediterranean countries investigating output persistence and volatility.
Output persistence can be measured in the time domain by the autocorrelation
function (ACF), which computes the correlation of GDP with its own past
previous time periods, while a simple measure of economic volatility for all
countries may be represented by the standard deviation of the cyclical
component of output. Recent studies of business
cycle fluctuations in developing countries (Mendoza, 1995, and Agenor et al., 1999) provide evidence of higher
output volatility than that typically observed in developed countries. Our
sample reveals a similar picture. Indeed, for the whole sample the standard
deviation of the cyclical component of output of the European countries is
between 0.8 (France) and 1.76 (
Indeed, there is evidence of stabilization of the Mediterranean economy
from the mid seventies as average output volatility decreases markedly from the
pre first oil-shock period and the post first oil-shock period (from 3.28 to
2.01), as a consequence of the generalized reduction in countries’ output
volatility [3] (the only exceptions are Jordan and Turkey, where it remains
almost unchanged, and Morocco, where it increases markedly).
The
analysis of persistence and volatility in figures 1 and 2 suggests some
similarities and some interesting changes in the main time-series properties of
Mediterranean countries through time. In particular, in the last quarter of the
previous century, according to a sort of stage of development and/or
geographical closeness clubs, similarities emerge among the European Western
Mediterranean countries, i.e. France, Italy, and Spain, which are characterized
by a combination of low persistence and low volatility; among Algeria, Greece and Israel, characterized by positive persistence and
high volatility (compared to the Western European Mediterranean countries); and
among Egypt and Tunisia, which are characterized by low or no persistence and
high (as before) volatility. As regards the other countries of the sample,
someone show high volatility and negative autocorrelation (
The turning points define the two main phases of each cycle, recessions
and expansions. A recession is defined as the period between a peak and a
trough in economic activity, while an expansion is defined as the period
between a trough and a peak. In this section we compare some basic
characteristics of recessions and expansions, such as duration, amplitude, steepness and deepness [4] of
business cycles phases across countries in order to verify the hypothesis of
business cycle asymmetry.
In order to derive descriptive statistics of business cycles asymmetry
we define a state variable St,
which equals one in recession phases, the year after a peak date to the date of
the trough, and zero in expansion phases. We define the length or duration of a
recession (expansion) as the number of years from peak to trough (trough to
peak), so the average duration of recessions and expansions are:
and
The amplitude is defined as the absolute value of the distance from peak
to trough (or vice versa), so that
the average amplitude equals:
and
with PTt and TPt
measuring the distance (in percentage terms) between the peak to trough and the
trough to peak values, respectively.
In thinking of a phase of a business cycle as a triangle with the
amplitude as height and the duration as the base, we can measure the steepness as the ratio between the
amplitude and the duration, i.e.
Moreover, we can calculate deepness
that pertains to relatives average levels of peaks and troughs and refers to
the characteristics that troughs are further below trend than peaks are above.
The results of the analysis of business cycle asymmetry for
Mediterranean countries are presented in Table 3. On average there is no
evidence of deepness, as the level of
peaks and troughs is identical (0.03), and no significant differences in the
distance between peak to trough and from trough to peak (0.064 versus 0.066).
But as expansions are longer than contractions (2.85 versus 2.45 years), there
is evidence of business cycle asymmetry as contractions are steeper than
expansions (0.038 versus 0.030). [5]
Table 3 – Analysis of business cycles asymmetry
|
Deepness |
Duration |
Amplitude |
Steepness |
||||
|
Recession |
Expansion |
Recession |
Expansion |
Recession |
Expansion |
Recession |
Expansion |
|
-0.064 |
0.051 |
2.625 |
2.714 |
0.084 |
0.116 |
0.057 |
0.054 |
|
-0.026 |
0.025 |
2.833 |
3.286 |
0.057 |
0.051 |
0.023 |
0.015 |
|
-0.012 |
0.011 |
2.625 |
3.571 |
0.023 |
0.023 |
0.010 |
0.007 |
|
-0.022 |
0.020 |
2.000 |
2.444 |
0.042 |
0.042 |
0.027 |
0.020 |
|
-0.038 |
0.039 |
3.333 |
4.000 |
0.080 |
0.066 |
0.035 |
0.019 |
|
-0.016 |
0.015 |
3.571 |
2.429 |
0.032 |
0.033 |
0.016 |
0.016 |
|
-0.043 |
0.046 |
2.300 |
2.000 |
0.089 |
0.086 |
0.050 |
0.058 |
|
-0.025 |
0.029 |
1.800 |
2.667 |
0.054 |
0.057 |
0.044 |
0.038 |
|
-0.032 |
0.030 |
2.755 |
2.921 |
0.058 |
0.060 |
0.031 |
0.027 |
|
-0.067 |
0.077 |
2.333 |
2.667 |
0.139 |
0.150 |
0.085 |
0.063 |
|
-0.024 |
0.030 |
1.500 |
2.875 |
0.056 |
0.061 |
0.043 |
0.029 |
|
-0.025 |
0.026 |
1.700 |
2.700 |
0.052 |
0.049 |
0.038 |
0.025 |
Average |
-0.033 |
0.033 |
2.448 |
2.856 |
0.064 |
0.066 |
0.038 |
0.031 |
With the exception of duration statistics that refers to number of years, all measurement is made in terms of percentage changes.
But a deeper look at individual countries’ statistics reveals the
existence of very large differences among the countries of our sample. In
particular, for some countries (
Cyclical amplitude of expansions and contractions is almost everywhere
the same (main exceptions are
Synchronization refers to the tendency of recessions and expansions in
one country to occur at about the same time as in other countries. In this
subsection we provide evidence in terms of linkage and synchronization of
fluctuations in economic activity for the Mediterranean countries looking at
the international nature of real GDP cyclical patterns across those countries.
The degree of synchronization between countries may be measured by the contemporaneous cross-correlation of the cyclical component of real GDP. Recently, Harding and Pagan (1999) has proposed the use of an index of concordance which measures the fraction of time spent in the same phase by two countries’ business cycles. The degree of concordance is defined as
Table 4 – Index of concordance and contemporaneous cross-correlations
|
FRA |
ITA |
GRE |
SPA |
TUR |
SYR |
EGY |
MOR |
ISR |
ALG |
TUN |
JOR |
FRA |
- |
0.51 |
0.68 |
0.57 |
0.46 |
0.30 |
0.64 |
0.49 |
0.38 |
0.56 |
0.38 |
0.52 |
ITA |
0.21 |
- |
0.41 |
0.57 |
0.46 |
0.53 |
0.40 |
0.67 |
0.40 |
0.50 |
0.50 |
0.63 |
GRE |
0.29 |
-0.20 |
- |
0.52 |
0.50 |
0.45 |
0.70 |
0.49 |
0.49 |
0.58 |
0.50 |
0.64 |
SPA |
0.41* |
0.33* |
-0.06 |
- |
0.43 |
0.50 |
0.38 |
0.51 |
0.59 |
0.39 |
0.43 |
0.52 |
TUR |
-0.20 |
-0.06 |
0.03 |
0.01 |
- |
0.55 |
0.56 |
0.49 |
0.53 |
0.41 |
0.50 |
0.42 |
SYR |
-0.26 |
0.07 |
-0.18 |
0.11 |
0.08 |
- |
0.44 |
0.57 |
0.53 |
0.37 |
0.50 |
0.60 |
EGY |
0.30* |
-0.43 |
0.41* |
0.01 |
0.12 |
0.03 |
- |
0.55 |
0.45 |
0.56 |
0.49 |
0.44 |
MOR |
0.06 |
0.10 |
-0.01 |
0.04 |
-0.25 |
0.07 |
0.23 |
- |
0.34 |
0.43 |
0.40 |
0.49 |
ISR |
0.27 |
0.06 |
0.03 |
0.35* |
-0.14 |
-0.09 |
-0.03 |
-0.09 |
- |
0.51 |
0.51 |
0.47 |
ALG |
-0.03 |
-0.06 |
0.27 |
-0.34 |
0.04 |
-0.20 |
0.09 |
-0.20 |
0.12 |
- |
0.54 |
0.49 |
TUN |
-0.33 |
-0.16 |
0.25 |
-0.10 |
0.20 |
0.08 |
0.08 |
-0.18 |
-0.09 |
0.36* |
- |
0.63 |
JOR |
0.08 |
0.05 |
0.21 |
0.13 |
-0.10 |
0.33* |
-0.02 |
-0.11 |
0.20 |
-0.06 |
0.24 |
- |
In Table 4 we present the results for the index of concordance (in the
upper triangle) and the contemporaneous cross correlation coefficients (in the lower
triangle) of real GDP among the business cycles of the Mediterranean countries
for the whole sample. The values of the contemporaneous cross-correlations
demonstrate the strength of the linkages among countries’ business cycles. The
results suggest the existence of several links among the following countries:
Table 5 – Index of concordance: average values
|
FRA |
ITA |
GRE |
SPA |
TUR |
SYR |
EGY |
MOR |
ISR |
ALG |
TUN |
JOR |
AV |
1950-98 |
0.50 |
0.51 |
0.53 |
0.49 |
0.49 |
0.51 |
0.50 |
0.49 |
0.48 |
0.48 |
0.50 |
0.53 |
0.50 |
1950-74 |
0.51 |
0.51 |
0.56 |
0.52 |
0.53 |
0.51 |
0.51 |
0.48 |
0.49 |
0.46 |
0.47 |
0.54 |
0.51 |
1975-98 |
0.47 |
0.51 |
0.51 |
0.46 |
0.43 |
0.45 |
0.49 |
0.50 |
0.45 |
0.50 |
0.50 |
0.52 |
0.48 |
Moreover,
we examined whether synchronization between the cyclical components of output of
all countries has changed over time calculating the average index of
concordance for each county changed before and after the first oil-shock. The
results show that the average concordance index decreases everywhere from the
first to the second sub-period, with the only exceptions of Algeria, Morocco,
Tunisia (increases), and Italy (unchanged) and the highest values of the
concordance numbers recorded for Greece and Jordan, 0.56 and 0.54 respectively,
before the mid seventies, and for Jordan in the last quarter of the XXth
century.
Finally
in order to examine the evolution of
synchronization over time, we compute the contemporaneous cross-correlation
coefficients using a 25-years rolling window. The main
findings of the rolling regression analysis may be summarised according to the
presence of a positive stable, increasing or decreasing relationships between
countries. A positive stable relationship emerges among
Figure 3 –
Thus, the evidence presented
about synchronization and its evolution over time show that there is a change
in the synchronization pattern across Mediterranean countries that involves
both a reduction in the coincidence of expansions and contractions over time,
and a change in the synchronization links which may determine the emergence of
clusters of countries characterized by similar levels of economic development.
In this paper we investigate
the characteristics of business cycle fluctuations (persistence, volatility,
asymmetry and synchronization) across 12 Mediterranean countries over
1950-1998. The main findings of the paper can be summarized as follows:
- Output
volatility varies markedly across Mediterranean countries according to their
stage of development. In the time span of our sample there is evidence of a generalized reduction in countries’ output volatility (the only
exceptions are Jordan and Turkey, where it remains almost unchanged, and
Morocco, where it increases markedly) and the emergence of clubs of countries
with similar characteristics based on their stage of
development and/or geographical closeness;
- On average there is no evidence of deepness as the level of peaks and
troughs is identical and no significant differences in the distance between
peak to trough and from trough to peak (i.e.
amplitude). But as expansions are longer than contractions there is evidence of
business cycle asymmetry as contractions are steeper than expansions. Looking
at individual countries’ statistics the empirical evidence from the
Mediterranean countries seems to suggest an inverse relationship between the
country’s development level and the amplitude and severity of business cycle
fluctuations. Indeed, both business cycles’ amplitude and steepness of Mediterranean developing countries are above the
average level of the sample (the opposite for the most developed Mediterranean
countries)
- From the
rolling regression analysis of countries’ cross-correlations and of the
concordance statistics derived from the concordance index emerge some changes
in the synchronization pattern across Mediterranean countries, as there is a
reduction in the coincidence of expansions and contractions over time, and a
change in the synchronization links among countries.
Overall, the results of our analysis
suggest, as expected, the existence of important differences in the
characteristics of business cycle fluctuations among countries belonging to
different economic level of development. Moreover, the average reduction of the
degree of synchronization among Mediterranean countries seems to suggest a
weakening of the economic links among Mediterranean countries, and thus a
reduction of the economic importance of the links in this area in comparison to
the European continental area.
Notes
[1] A-theoretical in the sense that we do not use a theoretical framework, such as the RBC e.g., as a guideline for our research, or evaluate which model “fits better” the data; using a band-pass filter implies assuming a certain set of characteristics about the cause of growth and the business cycle and their decomposition. Moreover, as Canova, 1991, points out the band-pass filter methodology may alter measures of relative variability, persistence and comovements of the series. Previous studies (Fiorito and Kollintzas, 1994, Christodoulakis et al., 1995) show that alternative detrending procedures do not affect basic results.
[2] Christiano and Fitzgerald’s (1999) approximate filter requires dropping two years at the beginning and end of the filtered series against the three years required by the Baxter and King’s (1999) filter.
[3] These results are, at least partially, with recent empirical works on output volatility in developing countries (see Kose et al. 2002)
[4] Steepness and deepness of business cycles phases are defined in Sichel (1993).
[5] Similar results have been obtained even in previous studies on European and G7 countries (see for example, Gallegati and Gallegati, 2001, 2003).
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