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---------TRANSFORMATIONS IN --------
Savoiu, G., Dinu, V. (2012), “Solutions for the Statistical Analysis of
the Economic Phenomena Described as Opposed, Partially of Entirely
Compensated Fluxes: a Case Study on the Exports and Imports of
Romania and the Baltic States”, Transformations in Business &
Economics, Vol. 11, No 1 (25), pp.54-71.
BUSINESS & ECONOMICS
© Vilnius University, 2002-2012
© Brno University of Technology, 2002-2012
© University of Latvia, 2002-2012
SOLUTIONS FOR THE STATISTICAL ANALYSIS OF THE
ECONOMIC PHENOMENA DESCRIBED AS OPPOSED,
PARTIALLY OF ENTIRELY COMPENSATED FLUXES:
A CASE STUDY ON THE EXPORTS AND IMPORTS OF
ROMANIA AND THE BALTIC STATES
1
Gheorghe Savoiu
Department of Accounting and
Management Information Systems
Faculty of Economics
University of Pitesti
1st, Targul din Vale, Street
RO-110040, Pitesti, Arges County
Romania
Tel.: +40348453279
Fax: +4348453123
E-mail:[email protected]
2
Vasile Dinu
Department of Business, Consumer
Sciences and Quality Management
The Faculty of Commerce
Academy of Economic Studies
Bld. Dacia nr.41, sector 1 010404,
Bucharest
Romania
Tel.:+4 021 319.19.00
Fax:+4 021 319.19.96
E-mail:[email protected]
1
Gheorghe Savoiu, PhD, is Assoc. Professor at the Department of
Accounting and Management Information Systems, Faculty of
Economics, University of Pitesti (Romania). Dr. Săvoiu has graduated
with MBA from Bucharest Academy of Economic Studies (Commerce
Department – Commerce section), and acquired PhD degree in
Economic Science from Faculty of Economic Cybernetics, Statistics
and Informatics, Bucharest Academy of Economic Studies (Romania).
Besides pedagogical activities, he was in position of manager at
General Board of Statistics Argeş County – Pitesti. He is a member of
many statistical organizations including Regional Science Association
International (RSAI).
2
Vasile Dinu, PhD, is Full Professor at the Department of Business,
Consumer Sciences and Quality Management, Faculty of Commerce,
Bucharest Academy of Economic Studies Romania). He graduated
from the Faculty of Commerce, the Bucharest Academy of Economic
Studies (Romania), and has a doctorate in economics. Prof. Vasile Dinu
is founder and editor-in-chief of Amfiteatru Economic, which is
indexed in Thomson Reuters - ISI Web of Knowledge; Member in the
Consultation College of Associations and Foundations at the Office of
the Prime Minister; President of the Association for Consumer
Protection “UniversCons” and Member of the European Association for
Research on Services (RESER).
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Received: November, 2011
1st Revision: December, 2011
2nd Revision: February, 2012
Accepted: March, 2012
ABSTRACT. This study highlights the importance of partially or
integrally compensated fluxes, which are interrelated and complementary
from the perspective of economics, not only for reasons of theory, but also
through their statistical measurements. The first section presents the major
statistical methods and instruments concerning the economic fluxes. In the
second part, some economic and statistical concepts, like the terms foreign
trade indices, specialization and concentration are explained, followed by a
proposal for the extension of a new method for characterizing the import
and export fluxes, based on identifying the limits of these fluxes using
Damien Neven Index and Gini-Struck coefficient in ABC curve. The third
section is a brief analysis of the evolution of the Baltic States - Estonia,
Latvia and Lithuania - which are compared, both mutually, and with
Romania. The entire paper focuses on finding the best adequate theoretical
frame, method and instruments to deal with this statistical analysis.
KEYWORDS: economic fluxes, partially or integrally compensated,
international research method of foreign trade, concentration – specialization,
Romania, the Baltic States.
JEL classification: C43, C46, E 31, O24, P33, R12, P2.
Introduction
The object of study of contemporaneous sciences captures phenomena that are
frequently described as opposed fluxes or flows, partially or integrally compensated, very
much as is the case in economics, statistics, demography, geography, physics, biology,
medicine, etc., to enumerate only a few scientific domains. Incomes and expenses, or
revenues and payments in economics, exports and imports in the statistics of the trade
balance, or the system of national accountancy, immigration and emigration in demography,
flow and ebb or tide, in the geography of seas and oceans, action and reaction, of Newton’s
third law, the oxygen-charged, and the oxygen-depleted blood flows, reunited in pulmonary
and systemic circulation, all of the above have a common conceptual essence, a scientific
manner of thinking, specific and yet unitary, ensured by the statistical methods and
instruments of investigation.
Fluxes and their conceptual usefulness cannot be imagined without Isaac Newton’s
contribution, as the great man introduced them as a specific manner of thinking in differential
calculus (Buchanan, 2011). Fluxes represent either constitutive parts of a pragmatic
modelling, as in the case of the founding principle of the double recording in bookkeeping,
where the returns and the payment flows, which generated the notions of debit and credit, lead
to diminishing the errors and frauds (Thompson, 1998; Goldberg and Leech 2001; Birnberg,
2009), or cognitive reference points that give rise to laws, such as the well-known third law of
mechanics, where the specific fluxes, distinguished by the force of action and reaction,
defined by impulse and counter-impulse, underline the peculiar significance of the moment or
of time (Guicciardini, 2005), or of some paradigms that constantly create new theories – the
fluxes that are intensified in outside migration continuously nuance the demographic level and
structure (Massey et al., 2009), or of other types of integrating multidisciplinary
interpretations (Schuster and Hilgetag, 1994; Stauffer, 2006; Chan and Ping, 2011).
A distinct approach lies in the statistical procedure, proceeding from the specific
modality of thinking of that science, i.e. through investigational and interrogative cycles,
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successively renewed (Wild and Pfannkuch, 1999; Hoerl and Snee 2002; Stuart, 2003;
Savoiu, 2008) aiming to identify new methods and instruments of calculating, testing and
interpreting a reality, explicitly including, for the present article, the phenomenology of
fluxes. The methods and instruments of economic statistical analysis of fluxes begin, in this
article as elsewhere, with tackling them unilaterally, an approach subsequently completed by
the integrating investigation of the opposed fluxes, partially or integrally compensated. The
statistical instruments are multiple and they quantify the degree of coverage, or the partial or
total equivalence of the flows, the dynamics and the territoriality of the degree of coverage of
equivalence, identifying punctual modifications as destinations or sources, the assessment of
the processes of concentration and diversification, meant to highlight the structural changes in
the fluxes, dispersion estimates in the statistical populations a priori and a posterior affected
by the fluxes, etc, distinctly treating the uniformly structured phenomena with compensated
fluxes, and derived trade balance of the trade balance type, or demographic balance, in
relation to the complex (non-uniformly structured) phenomena, where an element is defined
by partially or integrally compensated balances, such as the gross domestic product calculated
according to the method of consumptions, where the stock variation and net export are
balances of this type, and so require very special statistical analysis instruments, which the
present article details, both theoretically and from the standpoint of application. The practical
illustrations of the methods and instruments have recourse to the export and import fluxes of
Romania, Lithuania, Latvia and Estonia.
1. A Succinct Repertory Drawing of the Analysis Methods and the Statistical
Instruments for Investigating Fluxes in Economy
A first approach to fluxes in economy lies in making use of the statistical indicators
specific to the chronological series; each flux can be analysed both separately, through the
agency of the indices of the values of the flux, of the physical volume and the prices per flux,
and by directly selecting the rhythms of mobile basis and making recourse, on account of its
practical simplicity, to the “statistical rule of 70”. The analysis per flux can serve to deepen,
in a hierarchical manner, the structural side of the fluxes, according to the respective
destinations, or in keeping with the provenance of each flux, by calculating the specific
weights per flux. All these static and non-correlated approaches will characterize any flux
relatively, without however catch their dynamics or tendencies, and thus being unable to
exceed descriptive analysis (Byers, Iscan and Lesser, 2000; Strauss, 2003; Lorraine and Peter
2004; Basti and Bayyurt, 2008; Silver, 2009).
The correlated or integrated knowledge of the fluxes, and access to prognoses having a
high degree of accuracy and veracity urgently call for changing the methodological system of
reference, and the statistical indicators of analysis. When the economic fluxes have opposed
economic and financial effects (of the type incomes and expenses, or returns and payments),
the simultaneous approach involves the analysis through systems of balances of the balances
of those fluxes (the balance of external payments being a statistical instrument of high
relevance to this effect), and the combined analysis of both a static type (through relevant
statistical instruments, called degrees of value coverage, both physical and concerning price),
and of a dynamic type, through indices of the degrees of value and physical coverage, or of
net transfer (i.e. index of the degree of coverage through prices) between fluxes (Korhonen,
2000; Banzhaf, 2004; Zanias, 2005; Ricardo, Jason, Dani, 2007; Coughlin, 2010).
The activity or the economy can be approached as states of equilibrium of the two
major fluxes, the demand, materialized at the micro- or macro-economic level, respectively
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the supply, achieved at the level of the agents, or aggregated regionally or nation-wide; these
fluxes are compensated temporally, resulting in the formation of a specific equilibrium price.
Thus, the phenomena of diversification appear as requirements of the flux of demand, while
those of concentration become desiderata of the supply; the statistical evaluation of the
processes of concentration and diversification evince structural changes, thresholds or limits
through a broad instrumental gamut, from the Gini index, whose applications have been
constantly developing for nearly a century, up to the present (Osberg and Xu, 2000; Biewen,
2002; Xu, 2000, 2004; Gonzales et al., 2010), going through standard forms of evaluation of
the territorial concentration and specialization (Lilien, 1982; Krugman,1991; Aiginger, 2004;
Rossi-Hansberg, 2005; Aiginger and Rossi-Hansberg, 2006; Davidson, 2009), through more
explicit limitative forms, redefined as Gini–Struck coefficients, and placed on the ABC curve
(Bickenbach and Bode, 2008; Savoiu et al., 2010a, 2010b), particularizing themselves
statistically, as calculation stages, through Hirschman indices (Hirschman, 1943; 1964),
Herfindahl indices (Acar and Sankaran, 1999; Liston-Hayes and Pilkington, 2004),
Herfindahl–Hirschman indices (Nauenberg, Basu and Chand, 1997; Alegria and Schaeck,
2008; Esteban and Ray, 2011) and Hannah-Kay indices (Curry and George, 1983); or
differentiating themselves as a distinct domain, the Grubel-Lloyd index, for the intraindustrial trade (Grubel and Lloyd, 1971; Zheng and Qi, 2007), cluster index Sternberg and
Litzenberger (Sternberg and Litzenberger 2004; Litzenberger and Sternberg 2006; Fritsch and
Mueller 2008; Bosma and Schutjens 2011), export similarity index Finger-Kreinin (Finger
and Kreinin, 1979; Belke and Heine, 2007; Yerger and Sawchuk, 2008; AndreossoO’Callaghan, 2009), the index of the comparatively revealed advantage Neven (Neven, 1995),
and many other indices, increasingly specialized through their destination and construction.
The degree of detail of the analyses has generated this extensive population of the statistical
measurement instruments, with the example of the Grubel-Llyod index, later turned into the
Brülhart, Greenaway, Hine and Milner indexes, etc., a relevant case in point of the impact of
the vertical and horizontal, intra and inter-industrial multiplication.
As a partial conclusion to the above succinct methodological repertory drawing, one
can state that the analysis of the economic fluxes has multiplied both the statistical methods
and instruments, and has increasingly particularized and personalized the respective
approaches; the immediate consequence for the contemporary studies has been that detailed
methodological and instrumental knowledge was made possible, as well as a careful selection
in relation to the concrete fluxes analyzed, in point of level, limits, hierarchy, structure, degree
of compensation, dynamism and impact.
2. The Method of Statistical Economic Analysis of the Opposed, Partially or Integrally
Compensated Fluxes Specific to Foreign Trade; Specific Instruments and Databases
The evolution of a national economy can be shown by foreign / external trading,
through the balance of the export and import fluxes, as well as the dynamics of that balance,
which has a direct impact on the level of the gross domestic product and that of foreign debt.
The specific method of analysis of the export and import fluxes, opposed, partially or
integrally compensated fluxes, is known by the name of the method of the exchange ratio
indicators; here are included the following statistical instruments, whose interpretation confers
cognitive valances, static and dynamic at the same time:
a) the index of the value exchange ratio (the index of percentage coverage of imports
by exports), or the index of the degree to which the import flux is covered by the export flux
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IV : IV
(ICXM = X M ), which underlines when ICXM >100,0% assumes a value of the export flux
that increases more rapidly than the value of the import flux, which has as an effect an
improvement in the trade balance (either a reduction in the balance deficit, or an increase in
the balance excess) and a comparative increase in the contribution of foreign trading or
commercialization within the gross domestic product;
b) the index of the gross exchange ratio (the “gross barter” terms of trade index), also
defined as an index of the quantitative exchange ratio (or ratio of the export quantum index to
IQ : IQ
the import quantum index) (IGB = X M ) signals a structural worsening of the export flux of
the economy when IGB>100,0%, showing that the export flux for raw materials, materials
and semi-finished products holds an increasing specific weight;
c) the index of the net exchange ratio (the “net barter” terms of trade index), or,
expressed synthetically, the index of the exchange term (or the terms of trade index) (INB =
UVI X : UVI M ) separates the effect of the variation of the prices on the foreign trading activity,
and when INB > 100,0%, it identifies the effect of a relative “cheapening” of the import flux
in time;
d) the foreign trade price shears, calculated in the conditions when INB<100% (FTPS
= INB – 100%), is the percentage expression of the losses that an economy sustains as a result
of the fact that the export prices cannot keep up with the variation or specific movement of the
import prices, and has as a main effect a gratuitous transfer, or a “leak” of newly created value
from the economy which registers INB < 100,0% towards the partner economy, which
registers, in the mutual transactions, an INB > 100,0% ;
e) the effect, in absolute value, of the deterioration of the net exchange ratio (the
absolute value of the losses) determined in conditions where there is a price shears (∆VL = ∆
UVIX - ∆ UVIM), detailing the influence of both fluxes;
Q
f) the purchasing power of exports index (IPP = I X × INB) estimates the realistic
X
potential evolution of the import flux, under the restrictions imposed by the export flux,
providing a theoretical limit known by the name of flux of imports obtainable at the
purchasing power of the export flux;
g) the factorial terms of trade index (IFTT = IW×INB) takes into account the index of
labour productivity, and shows the tendency to compensate the deterioration of the ratio of the
exchange term on the basis of the index of labour productivity at the level of the economy, in
order to maintain access to a number of international markets (it also allows to calculate the
limit of the efficiency of foreign trading, with the integral loss of the effect of increased
productivity defined by the reverse value of the index of labour productivity (1: IW)
Extending the analysis through the identification of the moment of evolutive change,
as an impact of the dynamics of the two fluxes, and completing the information with structural
elements forced the authors of the present paper to create and identify some additional
indicators, which may effectively increase the ability of the method to secure the
understanding of the partially or integrally compensated opposed fluxes, as a complex
mechanism in foreign trade, having a major action on the external equilibrium of an economy.
To identify the moments of inflexion in the evolution of the sold of the two fluxes, that of
export, and that of import, a special indicator was built, which was called the gap of the
rates of the mobile dynamics of export and import (the rate is assessed for the capacity of
unique synthesis within the subsystem of the classic relative indicators of the series of
chronological data): ΔR = Rt/t-1(X) - Rt/t-1(M), where Rt/t-1(X) and Rt/t-1(M) are the rates of the
export fluxes (X), or of the import fluxes (M), expressed as percentage. In order to assess the
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structural limits and know the impact of the structural changes, the Hirschman, and the Gini–
Struck indexes were resorted to, and additionally their values were circumscribed to curve
ABC, so as to allow the identification of some limits of concentration and diversification on
the international markets, thus creating a new statistical instrument (Table 1). Determining
the Hirschman index can be made through two methods (a classic, and a simplified one):
n
n
m
100
H=
× ∑ g i2
g i2
∑
m
-100
m
-100
i=1
and
(2)
H = i=1
(1)
100
n , and it evinces the lowest level of concentration, “n” defines the
where
number of structures generated by the destinations, sources, products, etc., and “gi” represents
the weight of the destination, the course, the product, totalling “i”.
The Gini index was improved by Struck R. with the aim of rigorously stabilizing its
belonging, and thus it became the Gini-Struck index, through an alteration of the lower
⎡1 ⎤
⎢ ;1⎥
unstable limit into a constant limit, which made its range of values ⎣ n ⎦ become [0;1].
The identification of a number of limits of concentration and diversification on the
international markets structured according to curve ABC provides the restrictions which are
missing from the method of the indicators of the change ratio:
m=
Table 1. Limitative evaluations of the fluxes on international markets structured in keeping with the ABC
curve
Excessively
diversified market
(gi)2
Diversified
concentrated gi (%)
A
0.60
0.333
60.0
0.3600
B
0.25
0.333
25.0
0.0625
C
0.15
0.333
15.0
0.0225
Total
1.00
1.000
100.0
0.4450
Note: The elements in the economy that generate structures at the level of
destinations, the products, etc.
Structure
Weight (gi) in market
n
starting from Hirschman index (H=
∑g
i=1
2
i
Excessively
concentrated market
(gi)2
gi (%)
33.33
0.1111
33.33
0.1111
33.33
0.1111
100.00
0.3333
the flux can be the sources, the
), and from the Gini–Struck index (G-
n
n ∑ g i2 − 1
i=1
S=
n −1
).
Table 2. Relative limits of the statistical indicators on international markets structured in keeping with the
ABC curve (concentrated or diversified)
Limits of the indicator
Concentrated markets
Diversified markets
Hirschman coefficient (n = 3)
0.212
0
Simplified Hirschman coefficient
0.667
0.577
Gini-Struck coefficient
0.409
0
The result represents a statistical instrument which plays the part of that of a signal, or
a structural threshold (Table 2).
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The last indicator introduced in the methodical analysis proposed was the index of
Damien Niven, or the revealed comparative advantage index, in order to identify, in the fluxes
analysed, a number of structures that are strongly dependent on, or independent, as to the
international market, which can be determined through the classic relation of calculus of the
⎛ Xi
Mi ⎞
⎜⎜
⎟
Xi ∑ Mi ⎟⎠
∑
⎝
, where i represents structures
World Bank Institute, namely RCAI =
generated by the destinations, sources, products, etc., and whose concrete determinations are
placed, in point of value, within the theoretical interval (-1,1), with a much more restricted
empiric interval (-0.1; 0.1).
The data bases subsequent to the year 2000 were taken from the Eurostat statistics,
especially from the site http://epp.eurostat.ec.europa.eu/tgm/table.do, and completed with
other international and national sources. The result of the current attempt is a new statistical
method of analysing the opposed fluxes that are partially or integrally compensated, specific
to foreign trade, and the verification of the impact of this method is made, in a practical
manner, in what follows, through the analysis of the foreign trade fluxes of Romania,
compared with those of the three Baltic states, respectively, Estonia, Latvia and Lithuania.
The data bases concerning the partially or integrally compensated opposed fluxes
specific to foreign trade assume a great diversity, in so far as both the form of the indicators is
concerned (absolute, relative and derived), and their level of aggregation, their initial
reference moments, and their periodicity. Thus, EUROSTAT provides statistical data about
the space of Europe, to the space of the EU, aggregated differently in keeping with their
availability (EU-16, EU-25, EU-27), and expressing their value was done in the spirit of the
monetary convergence in EURO, while the informational dominant is a pragmatic one,
revealing through natural units (see Table 3).
Table 3. External Trade, by Declaring Country, Total Product, in Million ECU/EURO
EU-27
EU-25
EU-16
Estonia
Latvia
Lithuania
Romania
2000
-142956
-138194
-29491
-1168
-1443
-1826
-2962
2001
-94436
-87962
38153
-1100
-1681
-1989
-4661
2002
-45068
-38916
90887
-1437
-1862
-2422
-4206
2003
-66028
-57890
63649
-1713
-2070
-2368
-5588
2004
-74567
-63055
65092
-1934
-2481
-2480
-7346
2005
-126849
-112125
6894
-2028
-2842
-3008
-10313
2006
-192686
-172238
-19281
-2992
-4290
-4167
-14895
2007
-194459
-164688
9796
-3406
-5117
-5303
-21762
2008
-256424
:
-52675
-2426
-4078
-5067
-23469
2009
-109333
:
15445
-783
-1501
-1326
-9863
2010
-152983
:
-8637
-488
-1587
-1934
-9500
Note* : = not available.
Source:
Information
selected
by
the
authors
using
EUROSTAT
Statistical
Database
(http://epp.eurostat.ec.europa.eu/tgm/ table.do?tab=table&init=1&language=en&pcode=tet00002&plugin=1)
Ensuring the international comparisons and the facilitation of the controversies in
analyzing the fluxes of foreign fluxes is reflected in the present paper by means of the
UNECE (United Nations Economic Commission for Europe) statistics, where the amounts are
expressed in US$, and made available on the UNECE official Web Site
(http://www.unece.org/), which is easy to access individual, and to aggregate, in keeping with
the end of this research, as can be seen in the example given in Table 4.
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Table 4. Balance of Payments Overview by Transaction, Country and Year, in Millions of US$, at Current
Exchange Rates
Goods:
exports
F.O.B.
Goods:
imports
F.O.B.
Estonia
Latvia
Lithuania
Romania
Estonia
Latvia
Lithuania
Romania
2000
3327
2087
4065
10366
4102
3143
5182
12050
2001
3359
2253
4895
11385
4148
3599
6004
14354
2002
3526
2552
6018
13876
4613
4031
7349
16487
2003
4586
3190
7662
17618
6144
5202
9345
22155
2004
5926
4257
9302
23485
7878
7068
11690
30150
2005
7898
5416
11807
27730
9827
8484
14741
37348
2006
9761
6189
14141
32336
12654
11341
18332
47172
2007
11145
8250
17144
40555
14766
15177
23008
65121
2008
12564
9606
23646
49760
15685
15595
29828
77942
2009
9137
7327
16454
40672
9916
9171
17641
50278
2010
11636
9032
20749
49411
11968
10717
22432
57216
Source: Information selected by the authors using UNECE Statistical Division Database, compiled from national
and
international
(CIS,
EUROSTAT,
IMF,
OECD)
from
official
sources
(http://www.unece.org/stats/profiles2011.html)
The dynamic approach, detailed at the level of each single flux is provided by World
Bank statistics, on its own site (http://www.worldbank.org/) under the chapter concerning the
indicators, where the indices are the predilection form of expression, which is in fact the
solution that comes closest to the theme of the method and of the paper itself (as can actually
be seen in Table 5).
Table 5. Export Volume Index and Import Volume Index, (2000 = 100)
Estonia
Export flux (X)
Import flux (M)
Latvia
Export flux (X)
Import flux (M)
Lithuania
Export flux (X)
Import flux (M)
Romania
Export flux (X)
Import flux (M)
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
80.9
103.9
84.0
110.9
85.3
126.8
79.8
146.3
100.9
173.0
120.8
216.2
117.0
223.5
118.5
201.4
94.1
141.8
119.8
165.6
108.2
112.1
118.4
120.6
128.4
134.9
148.0
159.4
181.0
181.7
195.2
218.8
213.1
251.8
225.5
227.5
199.6
155.0
238.8
179.2
124.2
120.6
154.2
149.8
191.6
179.8
229.0
208.8
253.6
233.0
286.1
270.9
315.6
320.0
363.5
331.4
288.1
227.6
340.9
266.7
112.6
122.1
138.1
140.9
167.2
176.8
204.8
221.7
221.3
251.9
245.7
299.4
286.6
387.0
310.1
409.4
265.9
285.2
313.9
310.9
Source: Information selected by the authors using World Bank data set fromWorld Development Indicators
(WDI)(http://data.worldbank.org/indicator/TM.VAL.MRCH.XD.WD?page=1).
The practical illustration of the new statistical method of analysing the partially or
integrally compensated opposed fluxes, specific to foreign trade, also turns to account other
national and international data bases, while verifying its impact through the concrete analysis
of the foreign trade fluxes of the group of the three Baltic states, viz. Estonia, Latvia and
Lithuania (Gogoneaţă, 2010), compared with those in Romania.
3. Case Study: The Foreign Trade of Group of the Three Baltic States and Romania
An overall approach to the fluxes of foreign trade in Romania and the Baltic states
called for the integration of the information concerning the general regulations (Essaji, 2008),
from some controversies related to the change domain of the export and import fluxes in
keeping with the unit value indices (Silver, 2010), as well as some realities in the transition of
these economies, plus a number of tendencies in the regions of the economies under analysis
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(Peschel, 1998; Paas, Tafenau, Scannell, 2004; Paas and Tafenau, 2005; Saboniene, 2009;
Caporale, Ciferri, Girardi, 2011).
A historical approach is restricted to the first two decades and a short inter-war period,
the main cause being the loss of the territorial comparability of the data due to the post-war
integral incorporation of the Baltic States as well as significant parts of Romania into the
territory of the ex-Soviet Union. The restrictions to a unitary analysis, having ensured
principles of comparability, characteristic of both the inter-war and the post-war period, up to
the last decade of the 20th century, refer to the lack of the detailed information apt to allow
the analysis of the partially or integrally compensated opposed fluxes (see the examples
provided in Table 6, processed in accordance with the data in Handbook of Central and East
Europe, 1937, where the authors found the insufficiency of the data of application of the new
method for characterizing the fluxes in that historical period in Europe), and also the nonexistence of rigorous methodological standards, starting from the absence of a common
monetary solution (the option between the pound sterling, and the German mark as potential
currency for comparison, being difficult), as well as the absence of economic activities and
products similarly classified at least on a medium term (so, ensuring the unitary criteria for
structuring of the fluxes is difficult to do for the inter-war historical data bases).
Table 6. General elements of historical analysis of the fluxes of foreign trade
1931
Estonia
Million Kroon
Exports (X)
71.1
Imports (M)
61.2
Latvia
1000 Lats
Exports (X)
:
Imports (M)
:
Lithuania
Million Litas (Lits.)
Exports (X)
273.1
Imports (M)
277.7
Romania
Million Lei
Exports (X)
:
Imports (M)
:
Note* : = not available in the handbook.
1932
1933
1934
1935
1936
42.6
36.9
45.6
39.0
69.0
55.3
80.1
68.8
83.2
86.8
:
:
81.5
91.2
85.3
94.9
98.7
101.0
:
:
189.1
166.5
160.2
141.6
174.2
138.7
:
:
:
:
:
:
:
:
13,656
13,209
16,756
10,846
19,691
11,535
Source: Composed by the authors with reference to Handbook of Central and East Europe, (1937), edited by
R.P. Stephen Taylor (Estonia, pp.253-278, Latvia, pp.447-474, Lithuania, pp.481-504, The Kingdom of
Rumania, pp.659-773).
It is the surplus or excess which characterises the trade balance over the period
described (except for Latvia), while the primary (vegetable or animal) agricultural products,
and the manufactured or industrially processed products represent most of the exportation of
these nations, yet complex analyses are virtually impossible to do duet o the lack of indicators
methodologically comparable to those of today (for instance, the cost of living index
substitutes the main price indices of today of the fluxes, in the inter-war statistics, while the
common European monetary standard did not exist). The principal sources of the import; and
destinations of the exportation were Germany and Great Britain for Estonia and Latvia,
Germany for Lithuania, and Great Britain, France, Italy for Romania. This example
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demonstrates that the method of analysis of the indicators of the exchange ratio could not yet
be applied at the time, nor could it be generalized, for objective reasons connected with
securing increased informational comparability, although it is certain that, at a national level,
there were such data bases, and even a number of restricted analyses, for each economy,
which were described in reference sources of the period. Such an analysis is synthesised in
Table 7, for Romania, by processing the data bases, in keeping with the present method,
restricted to only five indicators, using chiefly The Encyclopedy of Romania, the 1943 edition.
The practical achievement of comparing the results listed below, through the effort of the
authors of the present contribution, cannot be secured with respect to any similar study made
in the Baltic States, as an immediate consequence of the already mentioned non-homogeneous
methodological aspects of the statistical approaches of that day.
Table 7. Main statistical indicators processed in keeping with the method of the exchange ratio, between
1930 and 1938, in Romania
1930
1931
1932
1933
1934
1935
1936
1937
28,522
23,044
22,197
15,755
16,722
12,011
14,171
11,742
13,656
13,209
16,756
10,848
21,703
12,638
31,568 21,533
20,285 18,768
(Export Quantum Index)
143.8
169.4
142.7
131.1
126.4
137.6
161.3
132.4
115.3
(Import Quantum Index)
IGB (Gross Barter Index)
-%UVI Exports Index (X)
UVI Imports Index (M)
INB (Net Barter Index)
FTPS (price shears)
ICXM = IGB × INB
78.7
182.7
58.6
289.1
57.4
248.6
60.3
217.4
65.9
191.8
54.4
252.9
58.1
277.6
74.2
205.4
61.5
187.5
69.9
94.3
74.1
25.9
135.4
45.6
80.2
56.9
43.1
164.5
41.9
65.0
63.6
36.4
158.1
38.5
64.2
60.0
40.0
130.4
37.7
65.1
57.9
42.1
111.01
42.6
66.9
63.7
36.3
161.1
46.2
74.2
62.3
37.7
172.9
69.7
91.6
76.1
23.9
156.3
60.0
92.2
65.1
34.9
122.1
Million Lei
Exports (X) mil. lei
Imports (M) mil. lei
-%-
1938
Q
IX
IQM
IQ
IPPX = X × INB
106.1
96.4
90.8
78.7
73.2
87.7
100.5
100.8
75.1
Sources: Composed by the authors with reference to Dimitrie, G. (1943), Enciclopedia României, Economia
naţională, vol. IV, pp.477, 488 – 489 and to Axenciuc, V., (1991), Economia naţională în prima jumătate a
secolului XX, în Economia României. Secolul XX, Editura Academiei, Bucureşti, pp.117-125.
The method which is partially applied here proves useful in historical researches, too,
and, although lacking comparable information, it is however able to highlight the fact that,
structurally, Romania’s foreign trade was deeply deteriorated, not being centre don
scientifically based policies, but rather randomly, with losses of substance from the annual
transactions, and also non-correlated with the development of the economy:
- IGB, or “gross barter” terms of trade index, shows an export dominated by natural
resources and raw materials, conflicting with an import of manufactured goods having
substantial manual labour incorporated, as the economy was supporting, in full recession, the
functioning of some industrial sectors in the partner economies, and was lacking policies for
ensuring its own survival);
- INB, or “net barter” terms of trade index, underlines th effect of the relative “rise in
the price” of the imports from one year to the next; the export prices were no table to grow in
the same proportion as the import in the economy, which did not actually have products of
such high competitiveness to afford to promote that type of foreign trade;
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- FTPS, or foreign trade price shears, present all over the period analyzed,
characterized by an INB<100%, show the Romanian economy gratuitously cedes between
23.9% and 43.1% of the newly created value (the added value) to the economies which it
maintained open fluxes, which detain values of over 100% of the same indicator (a very high
price paid for being present on other national or international markets in the inter-war period,
markets that were subsequently lost so easily) (Vass, 2008);
- IPPX, or the purchasing power of exports index, though constituting a limit to stop
imports at (especially at the height of recession), was by no means an important decisionmaking instrument, or at least one valued as a signalling indicator in the policies of national
foreign trading in the period, etc.
Nevertheless, the method validated, for the period 2000–2010, in a new Europe,
redefined by a unitary methodological treatment, conferred by the European Union, where the
two regions can be easily confronted, by presenting a few important relative similarities,
connected with the geographic area or the surface (the Baltic states have 175,117 square
kilometres, and Romania 238,391), GDP per capita (10,665–16,615 US$), gross external debt
(the Baltic states have on aggregate a level of US$ 92,656 million, and Romania – US$
122,869), the average household size (2.3-2.9 members), and, more importantly, the
traditionalism of the household mentalities, in keeping with the percentage of the children
living in a three-generational household), from 5.4% in Estonia, to 15.5% in Lithuania, 24.4%
in Latvia şi la 23.1% in Romania.
The analysis of the foreign trade fluxes, partially or integrally compensated, through
the agency of the indicators of exchange ratio, shows many common aspects derived from the
status of the respective economies, both from older traditions, and from the new consumerist
mentalities, but also a lot of specific aspects, which individualize each single country.
The tendency in all the economies is ascending, on different plateaus in terms of level;
the aggregated flux of the Baltic states is comparable to that of Romania, and, in point of the
dynamics of the two specific fluxes, the import flux has a much steeper gradient, which
conduces to a deficit trade balance in the activity of foreign trade of all the four economies,
over the whole of the period analysed (Figure 1 and Figure 2).
60000
50000
40000
30000
20000
10000
0
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Estonia
Lithuania
Latvia
Romania
90000
80000
70000
60000
50000
40000
30000
20000
10000
0
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Estonia
Lithuania
Latvia
Romania
Source: Composed by the authors with reference to UNECE Statistical Division Database, compiled from
national
and
international
(CIS,
EUROSTAT,
IMF,
OECD)
from
official
sources
(http://www.unece.org/stats/profiles2011.html).
Figure 1. Goods: Exports F.O.B. (Millions of US$,
at Current Exchange Rates)
Figure 2. Goods: Imports F.O.B. (Millions of US$,
at Current Exchange Rates)
The analysis centre don the percentage dynamics puts to good use the export and
import volume indices, and identifies a permanent increase in the volume of both fluxes, up to
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the deep contraction that occurred after the year 2008, as an expression of the economic crisis,
and, subsequently, of the global recession, with the necessary mention that the imports
anticipated, through flattening, that involution at least one year in advance, in all the
economies (Figure 3 and Figure 4):
450
400
350
300
250
200
150
100
50
0
400
350
300
250
200
150
100
50
0
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Estonia
Lithuania
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Latvia
Romania
Estonia
Lithuania
Latvia
Romania
Source: Composed by the authors with reference to World Bank statistics and indicators selected by country
(http://data.worldbank.org/indicator/TM.VAL.MRCH.XD.WD?page=1).
Figure 3. Export Volume Index (2000=100)
Figure 4. Import Volume Index (2000=100)
The export flux of Lithuania is place don the highest level, generating a similarly high
degree of import coverage; the greatest gap between the fluxes characterises Latvia, and the
most reduced level of covering the export flux through export belongs to Estonia, while
Romanian maintains itself in an evolution comparable to the average of all the Baltic States
(see Table 8):
Table 8. Index of Percentage Coverage of Import Volume by Export Volume, in keeping with the method
of the exchange ratio, between 2001 and 2010, in the Baltic States and in Romania (2000=100)
Estonia
Latvia
Lithuania
Romania
2001
77.9
96.5
103.0
92.2
2002
97.3
98.2
102.9
106.3
2003
67.3
95.2
106.6
96.5
2004
54.5
92.8
109.7
92.4
2005
58.3
99.6
108.8
87.9
2006
55.9
89.2
105.6
82.1
2007
52.3
84.6
98.6
74.1
2008
58.8
99.1
109.7
75.7
2009
66.4
128.8
126.6
93.2
2010
72.3
133.3
127.8
101.0
Source: Composed by the authors with reference to World Bank statistics and indicators, selected by country.
(http://data.worldbank.org/indicator/TM.VAL.MRCH.XD.WD?page=1).
Analogously is determined the dynamics of the Index of Percentage Coverage of
Import Value by Export Value, and the specificity of the dynamics of the fluxes of each
economy is once again confirmed (see Table 9):
Table 9. Index of Percentage Coverage of Import Value by Export Value, in keeping with the method of
the exchange ratio, between 2001 and 2010, in the Baltic States and in Romania (2000=100)
Estonia
Latvia
Lithuania
Romania
2001
102.9
97.5
103.9
92.2
2002
99.8
96.2
102.2
106.2
2003
96.1
94.2
106.0
94.4
2004
78.7
96.5
110.5
90.5
2005
83.3
101.3
111.7
86.3
2006
79.7
91.0
107.4
79.9
2007
77.7
92.6
103.3
72.5
2008
86.0
107.2
111.8
74.2
2009
98.6
134.2
132.2
94.1
2010
104.5
140.3
131.0
100.4
Source: Composed by the authors with reference to World Bank statistics and indicators, selected by country.
(http://data.worldbank.org/indicator/TM.VAL.MRCH.XD.WD?page=1).
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The “net barter” terms of trade index, or the terms of trade index underline a
completely different evolution worldwide of the economies analysed. Latvia and Lithuania
detain the losses of the highest percentage level, from the activity of foreign trade, Romania i
sat the other extreme, with the lowest level, yet has, along with Estonia, longer periods of
gratuitous transfer, or “leaks” of newly created value (added value) to other partner economies
(see Table 10) .
Table 10. Net Barter Terms of Trade Index and Foreign Trade Price Shears
2001
2002
2003
(2000=100)
Estonia
132.0
131.7
142.8
Latvia
100.9
98.0
99.0
Lithuania
100.9
99.4
99.5
Romania
99.9
99.8
97.8
(Previous year =100)
Estonia
132.0
99.8
108.4
Latvia
100.9
97.1
101.0
Lithuania
100.9
98.5
100.1
Romania
99.9
99.9
98.0
The foreign trade price shears, INB<100%
Estonia
-0.02
Latvia
-2.9
Lithuania
-1.5
Romania
-0.01
-0.01
-2.0
2004
2005
2006
2007
2008
2009
2010
144.2
103.9
100.7
98.0
142.8
101.7
102.6
98.2
142.6
102.0
101.7
97.3
148.3
109.4
104.8
97.9
146.1
108.2
102.0
98.0
148.7
104.2
104.5
100.9
144.4
105.3
102.5
99.4
101.0
105.0
101.2
100.2
99.0
97.9
101.9
100.2
99.9
100.3
99.1
99.1
104.0
107.3
103.1
100.6
-1.0
-2.1
-0.01
98.5
101.8
97.1
98.9
96.3
101.1
97.3
102.5
98.1
100.1
103.0
98.5
(Previous year =100)
-1.5
-2.9
-1.1
-3.7
-2.7
-1.9
-1.5
-0.9
-0.9
Source: Composed by the authors with reference to World Bank statistics and indicators selected by country
(http://data.worldbank.org/indicator/TM.VAL.MRCH.XD.WD?page=1).
Quantifying the indicators of the type purchasing power of exports index and factorial
terms of trade index shows that all the economies in question practised, during the period of
prolonged crisis or recession, policies of foreign trade centre don these limitative instruments,
and the exports and imports evaluated per cent of GDP, identify four completely different
models of structuring in the economies analyzed; the importance of the fluxes increases
progressively from Romania towards Latvia, Lithuania and Estonia, nearl from simple to
double (see Figure 5 and Figure 6),
90
80
70
60
50
40
30
20
10
0
90
80
70
60
50
40
30
20
10
0
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Estonia
Estonia
Latvia
Lithuania
Romania
Latvia
Lithuania
Romania
Source: Composed by the authors with reference to World Bank statistics and indicators selected by country
(http://data.worldbank.org/indicator/).
Figure 5. Export, per cent of GDP
Figure 6. Import, per cent of GDP
Additional accuracy results from the dynamics of the gap of the chained rates, which
exhibits a high degree of clarity and informational promptness, is signalling the delicate
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evolutive moments, in the years 2002 and 2008, while also confirming the unusual amplitude
of the gap of the balance of the rates in the year 2009. The particularly interesting element in
the statistical description of the new method is the abnormality of the positive difference in
situations of relative imbalance, and the normality of the negative difference in situations of
relative balance, for an economy with a permanent, chronic trade deficit like that of Romania,
after 1990, and significantly worsened after 2000 (see Figure 7).
20
15
10
5
0
-5
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
-10
-15
Source: Composed by the authors with reference to World Bank statistics and indicators selected by country
(http://data.worldbank.org/indicator/).
Figure 7.Dynamics of the Gap of the Rates of Mobile Basis of the Export and Import Fluxes of Romania
(%)
To illustrate the usefulness of another instrument usable for the structural and
limitative quantification of the of the partially or integrally compensated opposed fluxes, the
Hirschman index is determined (in its simplified variant) within the export flux of the Baltic
states, interpreted in an aggregative manner, and a particular structural stability of the region
is found, an unchanged structural homogeneity in spite of the full recession, placed near to the
centre, in the interval delimited by means of the ABC curve, namely (0.577 - 0.667), as shown
in Table 11.
Table 11. Structure of the export fluxes in the Baltic Region
Estonia
Latvia
Lithuania
Total
g Xi
n
∑g
2
Xi
2001
0.3196
0.2144
0.4660
1.0000
2002
0.2915
0.2110
0.4975
1.0000
2003
0.2971
0.2066
0.4963
1.0000
2004
0.3041
0.2185
0.4774
1.0000
2005
0.3144
0.2156
0.4700
1.0000
2006
0.3244
0.2057
0.4699
1.0000
2007
0.3050
0.2258
0.4692
1.0000
2008
0.2742
0.2097
0.5161
1.0000
2009
0.2776
0.2226
0.4998
1.0000
2010
0.2809
0.2181
0.5010
1.0000
0.3653
0.3770
0.3773
0.3681
0.3662
0.3684
0.3641
0.3814
0.3764
0.3775
0.6044
0.6140
0.6142
0.6067
0.6051
0.6070
0.6034
0.6175
0.6135
0.6144
i=1
Hirschman Index
Source: Composed by the authors with reference to UNECE Statistical Division Database, compiled from
national
and
international
(CIS,
EUROSTAT,
IMF,
OECD)
from
official
sources
(http://www.unece.org/stats/profiles2011.html).
The Gini-Struck coefficient allows to evince a number of phenomena of concentration
and diversification, and, once circumscribed to curve ABC, it signals the fact that the limit of
the excessively concentrated market (0.409) was exceeded in the structure of the export flux
of Latvia and Lithuania, in relation with Russia, as the dependence on the exports having that
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destination has become ever more marked. The tendency is relatively accelerated between
2001 and 2008, up to the moment global recession began (see Table 12).
Table 12. Structure of the export Latvia’s and Lithuania’s Extra EU-27 in 2001 and 2008
Norway
Switzerland
Russia
United States
Mediteranean Basin
OPEC
Candidate countries
Latin America
Other economies
Total
g Xi
n
∑g
2001
0.066
0.016
0.273
0.134
0.093
0.103
0.007
0.045
0.271
1.000
2008
0.077
0.023
0.467
0.044
0.051
0.033
0.005
0.054
0.246
1.000
0.19187
0.293441
g Xi
n
2
Xi
Norway
Switzerland
Russia
United States
Canada
Mediteranean Basin
Candidate countries
Latin America
Other economies
Total
∑g
2
Xi
2001
0.052
0.023
0.357
0.147
0.014
0.070
0.059
0.007
0.271
1.000
2008
0.053
0.024
0.405
0.081
0.031
0.045
0.019
0.018
0.324
1.000
0.234358
0.282618
0.484
0.3723
0.532
0.4393
i=1
i=1
Hirschman Index
Gini-Struck Index
0.438
0.3014
0.542
0.4529
Hirschman Index
Gini-Struck Index
Source:
Information
selected
by
the
authors
using
EUROSTAT
Statistical
Database
(http://epp.eurostat.ec.europa.eu/portal/page/portal/product_details/publication?p_product_code=KS-GI-10-002).
The same analysis of the dependence or independence of Latvia’s economy,
simultaneously with respect to both export and import fluxes, with Russia as both the source
and destination, can also be realized by means of the Damien Neven index (the revealed
comparative advantage index); it will be found that the value of that instrument equals -0.026,
in 2008, before the global recession which confirms the fact it belongs to a much more
restricted empiric interval (-0.1 ; 0.1) of normality, the fluxes being compensated on the
general plane of foreign trade. Thus completed, the analysis suggests the complementary
character of these statistical instruments of concentration or diversification correlated with
those of the revealed comparative advantage type.
Conclusions
The method, consistently improved and detailed in the present paper, has an obvious
coefficient of originality and profoundness, through the elements exposed in addition to the
classic indicators of the exchange ratios. The method provides arguments for, and supports,
the advantages of the appearance and development, in EU, at the methodological level, of the
guarantee of compatibility, of convergent development rigorously argued for, from a scientific
point of view, through commercial exchanges, as well as those of globalisation on the whole,
as informational and decision-making impact of the policies related with the opposed
economic fluxes, partially or integrally compensated. This case study provides a number of
new pertinent solutions for the regional confrontations, and highlights the advantages of the
analyses with complementary indicators (concentration or diversification and revealed
comparative advantage), the satisfied need for limits or values of signalling some phenomena
which grow ever more sharp and become hard to reverse, as well as the necessity, fulfilled
practically, to turn to advantage indicators having a character of anticipation of the changes of
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flux (the major inflexions), as is the case of the gap of the enchained rates of the partially or
integrally compensated opposed fluxes.
The two regions analysed are comparable in point of their European impact in the new
architecture of the European Union, respectively the Baltic States and Romania, and further
studies can confirm this final remark.
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EKONOMIKOS FENOMENO, APIBŪDINAMO KAIP PRIEŠPRIEŠINIAI, DALINIAI AR VISIŠKAI
KOMPENSUOJAMI PREKIŲ SRAUTAI, STATISTINĖS ANALIZĖS SPRENDIMAI: RUMUNIJOS IR
BALTIJOS ŠALIŲ EKSPORTO IR IMPORTO ATVEJIS
Gheorghe Săvoiu, Vasile Dinu
SANTRAUKA
Šis tyrimas pabrėžia dalinės ar pilnos kompensacijos prekių srautų svarbą, kurie yra tarpusavyje susiję,
vertinant iš ekonominės perspektyvos, ne tik dėl teorinių priežasčių, bet taip pat dėl jų statistinių įverčių. Pirmas
straipsnio skyrius yra skirtas trumpam pagrindinių statistinių metodų ir instrumentų pristatymui, kurie yra susiję
su daline ar pilna kompensacinės ekonomikos srautų analize. Antroje dalyje yra paaiškintos ir detalizuotos kai
kurios specifinės ekonominės ir statistinės sąvokos, tokios kaip užsienio prekybos indeksai, specializacija ir
koncentracija ir t.t. Trečiame skyriuje pateikiama trumpa Baltijos šalių (Estijos, Latvijos ir Lietuvos)
ekonomikos vystymosi analizė, kuri yra palyginta su Rumunija. Straipsnyje susitelkiama ties geriausių ir
tinkamiausių teorinių metmenų, metodų ir instrumentų parinkimu, siekiant tinkamai pagrįsti statistinės analizės
tipą. Paskutinės pastabos ir išvados pateikiamos, pabrėžiant kompensuojamų prekių srautų Europoje prigimties
ekonomikoje savitumą dabartiniu laikotarpiu.
REIKŠMINIAI ŽODŽIAI: ekonominiai prekių srautai, dalinė ar visiška kompensacija, tarptautinis užsienio
prekybos tyrinėjimo metodas, koncentracija – specializacija, Rumunija, Baltijos šalys.
TRANSFORMATIONS IN BUSINESS & ECONOMICS, Vol. 11, No 1 (25), 2012