Study and measurement of International
Competitiveness of Republic of Moldova
Ph.D. Corneliu Gutu,a
AESM – Academy of Economic Studies of Moldova,
61, Street Mitropolit Banulescu Bodoni, Chisinau, MD 2005, Republic of Moldova
[email protected]
a
Abstract. The present paper studied the issues of increasing the competitiveness of specific
countries within the context of the post-crisis period. Among the best known and mostly used
models is the one from the World Economic Forum. Furthermore this model helped determine
the competitiveness factors and identify the most important of them. The countries of Eastern
and Central Europe, the same as Republic of Moldova, and the data for 2010-2013 were
chosen for the analysis. On one hand it analyses the econometric dependence of the
competitiveness and the dynamics of macroeconomic factors associated with economic
growth and standards of living, economic structure, the openness and innovativeness of the
economy, as well as the extent and forms of state regulation of the economy, the level of
transparency and efficiency of the state apparatus. Thus the accumulated experience in
enhancing the competitiveness will definitely be useful to other countries, including the
Republic of Moldova, which will go through all the stages of European integration in the
foreseeable future.
Keywords: competitiveness, competitive advantages, competitive disadvantages, the pillars
of competitiveness, European integration, foreign trade.
1 INTRODUCTION
In recent years, the notion of "competitiveness" is central to the assessment of the countries'
positions in the world economy. However, the economic research community has not
developed a sufficiently stable view of competitiveness and its determining factors.
The economic science has as an urgent task the identification of the competitiveness level in
individual countries. In the view of several economists the competitiveness of a country is
based on the competitiveness of various industries and/or enterprises. (Porter, 1990). The
competitiveness of a country depends on the competitiveness of enterprises and their
products. (Peura, 1979). This approach encompasses foreign trade indicators, such as exports
to GDP ratio and foreign trade balance to GDP ratio. A similar opinion is shared by the
American scientists D. Dollar and E. Wolf, claiming that a country is competitive when
combining the prosperity in international trade on the basis of high technology and
performance with high incomes and wages. (Dollar, Wolf, 2003).
Some equate competitiveness with the ability to achieve certain overall outcomes, such as a
high standard of living and economic growth. Other definitions focus on the ability to achieve
specific economic outcomes such as job creation, exports, or FDI. Yet other definitions see
competitiveness as defined by specific local conditions such as low wages, stable unit labor
costs, a balanced budget, or a ‘competitive’ exchange rate to support a current account
surplus. These different views of competitiveness have confused the public and scholarly
dialogue, and have obscured the development of an integrated framework to explain causes of
cross-country differences in economic performance. (Delgado, Ketels, 2011, Porter, Stern
2012).
OECD experts define the national competitiveness as the degree to which, under open market
conditions, a country can produce goods and services that meet the test of foreign competition
while simultaneously maintaining and expanding domestic real income. (OECD, 1996).
The competitiveness is defined as the ability of a country to acquire and maintain a market
share in international markets. (Figueroa, 1998). International competitiveness is usually
defined in terms of two levels, namely, the firm-industry level and the national level (Moon
and Peery, 1995, Dollar and Wolf, 1993, Porter 1990). This categorization, however, does not
seem to enclose all the diverse aspects of the concept, especially as it relates to the dynamics
of the concept’s determinant indicators. For example, competitiveness at the firm level clearly
indicates micro level competitiveness, while national level competitiveness reflects the macro
level. (Fidel, 2005).
A country’s international competitiveness is often judged in terms of its ability to maintain a
favorable position in its international (trade) transactions with the rest of the world. This
ranges from having a low-cost export production base to the attraction of large inflow of
foreign capital. A number of studies assert that a country would be losing international
competitiveness if it suffers from such factors as poor research and development (R&D)
record, a growing trade deficit in high-tech products, an ill-trained labour force, and declining
productivity. This would indicate an overall weakness in its ability to effectively compete
with its trading partners. (Fidel, 2005).
In our opinion, the most important contribution to the study of problems of competitiveness of
individual countries was made by the U.S. economist M. Porter - the founder of this field, the
author of the theory of competitive advantage. One of the main provisions of his theory is that
the competitiveness of the national economy is determined by the maintenance of the labour
productivity at a higher level than the competition, through the use of a continuous process of
innovation (Porter, 1993). The author notes that the high competitiveness of the country is not
achieved in all sectors of the economy, but only in a few, where the country has a competitive
advantage.
The competitive advantages at the macroeconomic level represent a high efficiency situation
of a country compared to others. Sustainable competitive advantage is achieved when the
same profit is achieved at lower cost to the economic entity compared to its competitors (cost
advantage), or when there are higher profits compared to those of competitors, on competitive
products (differentiation advantage) (Porter, 1990). The competitive advantage offers greater
value to the consumer (beneficiary) and at the same time generates a higher profit.
Due to the two types of cost and differentiation advantages, a country can hold a leadership
position, whose characteristic is to create a superior value, as a result of using its own
resources (patents, trademarks, know-how, good will, brands, reputation etc.) and the capacity
to use them efficiently within a system of value chains, positioned horizontally, and even
more, vertically.
2 METHODS AND RESULTS OF THE STUDY
To establish the global competitiveness level of Moldova, within regional and global context,
we chose some comparative benchmarks, including Central and Eastern European countries,
for 2010-2013, considering that they have a degree of representativeness for the purposes of
covering our analysis to determine the size of the gap in competitiveness of the new EU
countries from the Central and Eastern Europe that joined in the years of 2004-2007.
The most authoritative comparisons of countries' competitiveness is the research conducted
by the World Economic Forum (WEF). With the help of global competitiveness rankings, of
this prestigious organization, we can determine the current situation of the country in relation
to other countries, we can identify the strengths and weaknesses in the national economy,
determine the competitive advantages of national economies, evaluate the effectiveness of
economic policy in order to strengthen the position of the global economy.
Since 2005 the World Economic Forum GCI indicator has been used to measure the national
competitiveness for many states. GCI includes a multitude of factors, grouped into 12 pillars
of competitiveness, with average components weighting the above mentioned indicators, each
measuring an aspect of competitiveness. As a national partner of the WEF the author
conducted a qualitative research of the quantitative competitiveness of Moldova during 20092013, the results being published in Global Competitiveness Reports for the corresponding
years. According to the research conducted by the author, the most notable competitive
advantages of Moldova, according to its position within the 148 countries compared by the
World Economic Forum in 2013, were: most significant competitive disadvantage in the
analysed period were recorded on the following indicators.
In 2013, Republic of Moldova modestly occupied the 89 th place out of 148 countries in the
WEF ranking. Nevertheless, the data in Table 1 indicates that the global economic crises had
no appreciable effect on the position of the Republic of Moldova in the WEF ranking, as in
2013 the country has slightly improved its position in comparison with the year of 2010. It
has to be noted that in 2013 Estonia occupies the 32th position, Poland the 42th position, and
Turkey the 44th position. The Neighboring states that have become members of European
Union in 2007, Romania and Bulgaria occupies the 76th position and the 57th position
according to their competitiveness level. The Republic of Moldova has better positions
towards Albania and Serbia, countries that are at stage of association with the European
Union.
Table 1. The Ranks differences of Global Competitiveness Index in 2013-2010
Rank
Estonia
Poland
Turkey
Czech Republic
Lithuania
Latvia
Bulgaria
Slovenia
Hungary
Romania
Slovak Republic
R. Moldova
Albania
Serbia
2013
32
42
44
46
48
52
57
62
63
76
78
89
95
101
2012
34
41
43
39
45
55
62
56
60
78
71
87
89
95
2011
33
41
59
38
44
64
74
57
48
77
69
93
78
95
2010
33
39
61
36
47
70
71
45
52
67
60
94
88
95
Rank differences
2013-2011
2013-2010
-1
2
-1
-3
15
17
-8
-10
-4
-1
12
18
17
14
-5
-17
-15
-11
1
-9
-9
-18
4
5
-17
-7
-6
-6
Source: The Global Competitiveness Reports, 2010-2013
The disadvantages of the Republic of Moldova, as importance and number, are incomparably
higher compared to the competitive advantages. Making note of the fact that in the years of
2010-2013, along with the growth of the number of the competitiveness indicators and of the
countries taken into comparison, the position of the Republic of Moldova, according to the
global competitiveness indicator, has somehow ameliorated, according to the presented study,
we propose the following measures that should guide the attention of policy makers and other
stakeholders: Let’s note that the competitiveness of the Republic of Moldova continues to
deteriorate in the key area of “good market efficiency”. Under this indicator the country ranks
107 out of 148 possible positions, while Romania is on 117 rank and Bulgaria is on 81 rank.
In our opinion, this is largely determined by the inefficiency of the ongoing anti-monopoly
policy and the burden of customs procedures.
As the studies show, the following factors affect the competitiveness in a negative way:
“quality of roads” (148 rank), “state of cluster development” (147 rank), “company spending
on R&D” (142 rank), “judicial independence” (145 rank), “brain drain” (137 rank),
“agricultural policy cost” (138 rank), “quality of scientific research institutions (132 rank),
“availability of scientists and engineers” (131 rank), “extent of market dominance” (133
rank), “efficiency of anti-monopoly” (133 rank), “local supplier quantity” protection (127
rank), and during the past year these figures deteriorated. Furthermore, the Republic of
Moldova was among the outsiders on the following competitiveness pillars: “business
sophistication” (125 rank), “ innovation” (138 rank). All the above mentioned problems stop
the Republic of Moldova from stepping up and using its competitive advantages, such as
relatively low level of: “business impact of malaria” (1 rank), “business cost of terrorism” (10
rank), “imports as a percentage of GDP” (20 rank), “int’l internet bandwidth” (23 rank),
“legal rights index” (28 rank), “general government debt, % GDP” (29 rank), “flexibility of
wage determination” (34 rank), “pay and productivity” (34 rank) “total tax rate” (40
rank),”trade tariffs” (41 rank), and “time required to start a business” (43 rank) .
Figure 1. Interdependence of GDP based on purchasing-power-parity (PPP) per capita in US
dollars and Global competitiveness Index in 2013
Figures 1 and 2 shows the identified interrelationship trends between the reached
competitiveness levels and GDP based on purchasing-power-parity (PPP) per capita in US
dollars for individual EU countries, Japon, Israel and Turkey.
Figure 2. Interdependence of GDP based on purchasing-power-parity (PPP) per capita in US
dollars and Global Competitiveness Index in 2013 and 2012.
The specifics of the state economy of the Central and Eastern Europe states, including the
Republic of Moldova, is that along the sustainable development issues they are closely related
to European or regional integration. Moldova's political vector is oriented to the European
Union, and therefore the country's development in the future will mean development through
integration. Thus, on the one hand, it requires a continuous measurement in dynamic of the
real convergence to EU economic space and, on the other hand, there is the need to develop
the methodology for the assessment of the sustainable competitiveness of the country.
Based on these considerations a new concept for the measuring of the competitiveness is
described below.
The developed methodology focuses on the comparative studies by inclusion of Moldova in a
specific action (plan of reforms in transition, international projects, marketing strategy for EU
integration, regional cooperation, etc.) and taking into consideration the pro-European
aspirations of the Republic of Moldova, within this methodology the comparison with the EU
economic parameters is performed in the first place, is they serve as a benchmark for the
economic and social development of the Republic of Moldova, and “away from the standard”
category is used as a measurement criterion for the sustainable competitiveness and hence the
convergence / divergence of the community structures.
Such an approach defines a new metric of competitiveness, it interposes it in the process of
economic convergence evaluation, and furthermore it is part of the common set of valuesof
the European space: high quality of life, social protections, partnership, cohesion, dialogue,
sustainable growth, appropriate environment, etc. The most popular models in the field (in the
original notation) that have ties with the methodology discussed in this study are presented
below. It has to be mentioned that all of these start from the formula fOWA suggested by R.
Yager (Yager, 1994) at the end of the 80’s, based on the weighted averages wi of the
economic indicators xi:
fOWA (x1, ...xn) =

n
i 1
wi * xi,
wi € (0,1],

n
i 1
wi =1,
(1)
using it J. Sachs introduces the concept of Growth Competitiveness Index, later transformed
into Global Competitiveness Index by X. Sala-i-Martin, New Global Competitiveness Index
by M.E. Porter, Sustainable Competitiveness by Advisory Board on Sustainability and
Competitiveness, etc.
Sala-i-Martin Model. X. Sala-i-Martin is the author of the (GCI) ICG – indicator of the
global competitiveness, model which includes both micro and macro level factors of
competitiveness. GCI includes a multitude of factors, grouped into 12 pillars of
competitiveness, with weighted average components of indicators, each measuring an aspect
of competitiveness. The measuring unit is the score.
Scoring is done separately based on three groups of factors: essential, efficiency, innovation,
each group being limited from above as a share of state economic development of the country,
respectively it is mainly based on the production itself, production efficiency or innovation.
For example for Moldova, as a member of the group of states at first stadium development,
these determinants are crucial.
As a result the formula shows:
GCIR.R.M = 0.6*Basic R.M + 0.35*Efficiency R.M + 0.05*Innovation R.M
,
(2)
Basic Efficiency Innovation deals with the numeric value for the weighted average of
indicators of production groups, efficiency and innovation at the level of national economy,
calculated based on the statistical data, resulted from surveys results or derived from the data
of the two previous sources. Literature distinguishes the following groups of key factors for
different stages of economic and social development of countries, namely:
Indicators (factors)
1. Stage where the economy is dominated by production factors. Basic requirements:
institutions, infrastructure, macroeconomic stability, health and primary education
2. Stage where the economy is dominated by efficiency factors. Efficiency enhancers: higher
education and training; labour market and products efficiency, financial market sophistication,
technological readiness, market size
3. Stage dominated by innovation. Innovation and sophistication factors: Business
sophistication, innovation
Porter Model. M.E. Porter introduces the concept of the New Global Competitiveness Index
(New GCI), aiming to create a single integrated index that would replace those of the previous
model. The author hopes to evaluate more adequately the determinants of productivity, a
special emphasis being made on the role of clusters in the economic growth. The
measurement unit is the GDP per capita. Indicators are grouped as follows: economic
performances at the macro, middle and micro level of business, institutional policies, fiscal
and monetary policies, and infrastructure.
Krugman Model. By definition, the economy of an entity can be characterized by a set of
indicators, denoted by the vector x, the vector is determined by a certain structure, which is
not always the desirable one. As a result of implementation of the governmental or regional
economic policies, the economic indicators of the entity change, this will be the vector y,
which already has another structure, often called standard, target vector or standard structure.
Logically, the problem of quantitative assessment of structural changes of the vector x
appears, i.e. this vector components approach those components of the vector y.
The assessment of the convergence process, sector, economic activity or economy overall
here has been based on an analysis or, more generally, on the comparative economic research.
The comparative analysis allows us to perform the modern economic research pretty
thoroughly, very realistically, and the comparative tool has become a strong support of
analysis and forecasting.
The model on the degree of structural convergence proposed by Krugman for an economic
structure j, is calculated by summing the absolute values of the difference between values xji
and x0i, i  1, n , otherwise known as "the sum of distances between the parameters" and given
by
Kj =

n
i 1
│ xji – x0i│,
(3)
Where x0 represents the target vector, having as components standard targets x0i, i  1, n ,
Krugman used this model in many applications, from assessing differences between centre
and periphery and ending with the evaluation of the global demographic disparities between
cities and the deprived areas of the continents. Subsequently, this model was adapted to assess
the convergence of various European countries that have joined the EU. In the decision
making process, often K j is compared to a standard of"1" or 100%, used to consider the
structural homogeneity.
It should be noted that all the models listed here bear a specific character, some referring
exclusively to the competitiveness (Sala-i-Martin, Porter) to compile the ratings, rankings for
the international financial structures, others to the convergence, (Krugman) required to
develop the specifications and roadmaps for the economic integration.
Based on the above considerations we propose a new model for the assessment of the
competitiveness. The above mentioned model fully uses the methodology of comparative
analysis; moreover, it corresponds exactly to the requirements imposed by the new concept of
measuring the sustainable competitiveness. The analysis of the global economic development,
and namely of the causes and consequences of the crisis, shows a number of deviations from
the general principles, even ignoring the objective law, inherent to the development, primarily
from the postulate that starts any evolving economy, small or very large: maximum revenue
with minimum costs at every stage, at every level, etc. A higher profit is only achieved with
lower costs for an entity, and increased revenue and maximum profit is achieved only by
optimizing costs and revenues. Or the permanent increase in spending along with the income,
often in surpassed and in larger volumes, have discredited the idea of profit and
entrepreneurship, taxation became unbearable generating instability, stagnation and distrust.
A simple solution to end the crisis, as well as to improve the general economic situation,
would be the optimization of the development parameters of at all levels and in all fields. The
problem of minimizing the costs (revenue maximizing) is based on economic growth,
particularly minimizing the costs and maximizing the revenue is the assumption of
consolidation of full financial autonomy, and it lies in finding an optimal balance between
taxation and economic stimulus.
Within the above mentioned model the comparison of the indicators is done according to a
standard, which is used to calculate the homogeneity or the distance from the target. The
complete scheme of this model comprises to distinct stages:
First Stage: calculation of the optimal solution xj = xoptim . If this stage is avoided then xj will
not be the optimal one, but calculated in a different way. For the purposes of the above
calculation, furthermore for the calculation of the sustainable competitiveness it is very
important to take into account in the model, directly or indirectly, for instance the impact of
environmental factors, (airspace, water resources, soil resources, soil erosion, variety of
species of animal and vegetable kingdom, moisture regime, torrents danger, the danger of
landslides, etc..) to optimize their influence on the general economic indicators and namely on
the population’s living standards.
Second Stage: weighting of indicators xj; estimation of non-quantifiable indicators and their
weighting; application of the mathematical formula to generalize results and to calculate the
sustainable competitive index.
The model is one of optimization, the objective function min f (x), called the distance from the
standard
min f(x)= ║ x - x0║2 ,
(4)
During the optimization process the indicators of the vector x, or a part of them, will be bound
by linear and nonlinear dependencies gk , which in its general form shows: constraints in form
of equality
gk(x) = 0, k  1, m ,
(5)
is equivalent to the dependencies related to the relationships between different indicators;
the restrictions in the form of inequality are such:
0 ≤ xi ≤ ai , i  1, n ,
(6)
ai here is the high/low limit of the indicator i, and amounts to introducing the variation
intervals range for this phenomenon. From a methodological point of view, this model is
based on the method of the comparison using a standard, research is carried out based on a
systemic approach to business processes, and the optimization is the main support for analysis
and forecasting. From a mathematic point of view, model is a deterministic optimization
model, with nonlinear functions and belongs to a class of oversized models, i.e. the number of
restrictions being greater than the number of unknowns. From an economic point of view,
model enters the so-called class of large problems, a specific feature of economic problems
that automatically turns them into very difficult problems to solve, namely during the
numerical calculations. The model also has a great advantage related to the stability, because
the matrix subjected to the reversal has constant dimensions and relatively small in size, as
well as the complexity of the operations is minimum for the given class of optimization
problems.
Of the many possible mathematical formulas, according to the optimization method chosen,
the model is proposed to use the following formula:
L
SCI
x
l
k*
( 
1
)*
100
%

x
=
,
l
1
l
l0
2
(7)
L
x =(x ,…,x ,…x ) – represents the standard-structure, and xj = (x1,…,xl,…xn) the calculated
indicators of the structure xj, L is the number of indicators, L ≤ n. According to the formula of
the above mentioned comparative studies, the entity with a lower sustainable competitive
index (SCI) will be placed in rating.
Moldova’s place was recalculated, along with other countries, in the top World Economic
Forum (WEF), 2013, using the pattern described for 3 and respectively 12 indicators. The
competitiveness of EU member states was calculated as well according to the above
mentioned formula, based on data from The Global Competitiveness Report 2013, the three
key factors, namely basic requirements, efficiency enhancers and innovation and
sophistication factors. The maximum value of the three indicators for the world economy is
Switzerland served as standard, as Finland (3 rank) is the best placed of the European Union.
It is easy to see that most countries change their place in the competitiveness rating due to the
fact that the methodology developed takes into account the competitiveness index, as well as
the convergence with the EU standard.
The “distance from the standard” category, used to measure the sustainable competitiveness
and the convergence covers a very wide applicability at regional, national and international
level, and does not depend directly on the forecasting horizon; the elements of the developed
model are varied: list of indicators; scoring, GDP per capita; the application conditions are
quite flexible; the result – the optimal parameter respectively at the micro level, mezzo level,
and the macro level; the advantages consist of: unique evaluation concept, measurement unit on choice, optimization, multitude of solutions, minimum subjective factor. Within the GDP
formula, we can easily find the elements of the formulas, calculation schemes, as well as of
the organic links between Krugman, Porter and Sala-i-Martin indicators: directly those of
Krugman „x/xo - 1”, and Porter or Sala-i-Martin’s set of indicators are used in the
optimization process.
It has to be noted here that in principle, the list of economic indicators x of SCI formula may
be any of them, but a qualitative step within the comparative method occurred when Porter
first, then Sala-i-Martin came up with a set of well-thickened, well structured and hierarchical
indicators, especially with a description of links between them, which raised the value of the
method to a new level.
Therefore the proposed model emphasizes the use of this particular set of economic
indicators. In terms of a computer the proposed formula avoids a number of difficulties
specific to the other, by including only the ratio x/xo instead of their actual values, thus
bringing sizes to the same order and homogenizing the numerical calculations. In conclusion,
the value of SCI will concurrently serve as the size of the distance from the standard and as a
sustainable competitiveness index and the ranking will be based on a single indicator – SCI.
Based on the systemic approach, embodied in the unique concept of evaluation of the
economic competitiveness and the convergence, it proposes a new calculation formula where
0
0
l0
n0
the parameters related to the convergence appear simultaneously (x, x0, 1), which expresses on
the one hand, the distance of the parameters of development of an entity from the given
standard, on the other hand their optimization - the criteria already meeting the sustainable
competitiveness characteristics. Thus the proposed formula includes, as it is easily seen, the
qualities of the well-known formulas of the models listed above, destined separately for the
competitiveness (Sala-i-Martin, Porter) and convergence (Krugman), including them in a
single evaluation and calculation formula, thus generalizing them.
3 CONCLUSION
According to the research conducted by the author, the most notable competitive advantages
of Republic of Moldova, according to its position within the 148 countries compared by the
World Economic Forum in 2013, were: most significant competitive disadvantage in the
analysed period were recorded on the following indicators: business sophistication and
innovation.
The disadvantages of the Republic of Moldova, as importance and number, are incomparably
higher compared to the competitive advantages. Making note of the fact that in the years of
2010-2013, along with the growth of the number of the competitiveness indicators and of the
countries taken into comparison, the position of the Republic of Moldova, according to the
global competitiveness indicator, has somehow ameliorated, according to the presented study,
we propose the following measures that should guide the attention of policy makers and other
stakeholders:
- Regular monitoring and analysis of the place of the Republic of Moldova occupies
according to the global competitiveness indicator, as well as the 12 component groups of
indicators (pillars) so that, by their corroboration their priorities, emergency measures, as well
as coherent measures with a strategic character of the government, for the long-term
performance of the national economy, can be based;
- Calculation of the global and partial competitiveness indicators at a regional level (there are
4 development regions in the Republic of Moldova) in order to be able to identify the weakest
performance zones in the regional profile, to establish priorities and act on the causes of
underperformance;
- Making our own calculations of competitiveness indicators and sub-indicators at the national
level, based on the development of an appropriate new model, through the comparison of the
results with the indicators calculated by the World Economic Forum;
- Performing researches and specialised studies regarding the competitiveness metrics and
state in the Republic of Moldova, compared to EU candidate countries in priority areas, such
as: foreign trade, information and communication technologies, sustainable development and
environmental protection, research, development and innovation, education and health,
efficiency of public administration, foreign trade, tourism, etc..
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Corneliu Gutu: is the associate professor at the Academy of Economic Studies of Moldova.
He received BS and MS degrees in economics from the Plekhanov Russian University of
Economics in 1982, and Ph.D. degree in economics from the Plekhanov Russian University of
Economics in 1990. He is the author of more than 35 journal papers and book chapters. His
current research interests include: national competitiveness, macroeconomic environment,
innovation, European integration, foreign trade.