Б. О. Джолдошев а из Института автоматики и информационных технологий нан кр, г. Бишкек; «Cинтез кибернетических автоматических систем с использованием эталонной модели»

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Б. О. Джолдошев а из Института автоматики и информационных технологий нан кр, г. Бишкек; «Cинтез кибернетических автоматических систем с использованием эталонной модели»

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In this study the GCI captures by providing a weighted average of three groups of indicators: Basic requirements, Efficiency enhancers, Innovation and sophistication factors. Turn, they consist of 12 components: Institutions, Infrastructure, Macroeconomic stability, Health and primary education, Higher education and training, Goods market efficiency, Labor market efficiency, Financial market sophistication, Technological readiness, Market size, Business sophistication, Innovation. Each of which reflects one aspect of the complex concept that It's called competitiveness. The structure and weight of the indicators for the GCI and this group of indicators are presented in Tables 1-4. (Sala-i-Martin and Artadi, 2004; Sala-i-Martin et al., 2008; Sala-i-Martin et al., 2009).


2. Basic requirements
2.1 Institutions. The institutional environment is determined by the legal and administrative framework within which individuals, firms, and governments interact to generate income and wealth in the economy. The quality of institutions influences investment decisions and the organization of production and plays a central role in the ways in which societies distribute the benefits and bear the costs of development strategies and policies (Easterly and Levine, 1997; Acemoglu et al., 2001; Rodrik et al., 2002; and Sala-i-Martin and Subramanian, 2003; Shleifer and Vishny, 1997; Zingales, 1998).

Institutions scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: excessive bureaucracy and red tape (de Soto and Abbot, 1990), overregulation, corruption, dishonesty in dealing with public contracts, lack of transparency and trustworthiness, and the political dependence of the judicial system, and also improper management of the public finances. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 4,11 score, and this corresponds the Egypt (4.13) ranked 70th;

- mode is 3,24 score, and this corresponds Philippines ranked 88th; Serbia ranked 93rd; Cameroon ranked 111st; Madagascar ranked 120th and Timor-Leste ranked 26th;

- maximum is 6,15 score, and this corresponds Singapore ranked 3rd;

- minimum is 2,39 score, and this corresponds Venezuela ranked 113rd. Then interval is 3,76 score, also note that Germany (16th) is 5,6; for United States (34th) – 4,81; Kazakhstan (86th) – 3,64 and Turkey (95th) – 3,49 scores;

- skewness coefficient is 0,52, and this appropriate distribution of the institutions scores shift the mean significance to the right;

- kurtosis coefficient is 0,63, and this appropriate distribution relatively normal distribution is the upright.


2.2 Infrastructure. Efficient infrastructure is an essential driver of competitiveness. It is critical for ensuring the effective functioning of the economy, as it is an important factor determining the location of economic activity and the kinds of activities or sectors that can develop in a particular economy. Well-developed infrastructure reduces the effect of distance between regions, with the result of truly integrating the national market and connecting it at low cost to markets in other countries and regions. In addition, the quality and extensiveness of infrastructure networks significantly impact economic growth and reduce income inequalities and poverty in a variety of ways (Aschauer, 1989; Canning et al., 1994; Gramlich, 1994; and Easterly, 2002).

Infrastructure scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: ineffective modes of transport for goods, people, and services – such as quality roads, railroads, ports, and air transport, electricity shortages and also bad telecommunications network. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:



- mean is 3,894 score, and this corresponds the Slovak Republic (3,89) ranked 48th;

- mode is 2,91 score, and this corresponds Peru ranked 78th; Algeria ranked 82nd; Philippines ranked 88th and Ecuador ranked 104th;

- maximum is 6,59 score, and this corresponds Germany ranked 7th;

- minimum is 1,9 score, and this corresponds Chad ranked 131th. Then interval is 4,69 score, also note that Germany (1st) is 6,39; for United States (8th) – 5,92; Turkey (62nd) – 3,92 and Kazakhstan (75th) – 3,49 scores;

- skewness coefficient is 0,445, and this appropriate distribution of the infrastructure scores shift the mean significance to the right;

- kurtosis coefficient is -0,795, and this appropriate distribution relatively normal distribution is the horizontally direction.


2.3 Macroeconomic stability. The stability of the macroeconomic environment is important for the overall competitiveness of a country (Fischer, 1993).

Macroeconomic stability scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: macroeconomic disarray which harms the economy, high-interest payments, uncontrolled inflation rates. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 4,598 score, and this corresponds the Colombia (4,59) ranked 69th;

- mode is 5,24 score, and this corresponds Singapore ranked 3rd; Canada ranked 9th; New Zealand ranked 20th; Russian Federation ranked 63rd; Morocco ranked 73rd and Cameroon ranked 111th;

- maximum is 6,64 score, and this corresponds Brunei Darussalam ranked 32nd;

- minimum is 1,0 score, and this corresponds Zimbabwe ranked 132nd. Then interval is 5,64 score, also note that Germany (30th) is 5,28; Kazakhstan (59th) – 4,71; Turkey (63rd) – 4,66 and United States (93rd) – 4,31 scores;

- skewness coefficient is -0,946, and this appropriate distribution of the macroeconomic stability scores shift the mean significance to the left;

- kurtosis coefficient is 2,499, and this appropriate distribution relatively normal distribution is the upright.


2.4 Health and primary education. A healthy workforce is vital to a country’s competitiveness and productivity. Investment in the provision of health services is thus critical for clear economic, as well as moral, considerations (Sachs, 2001).

Health and primary education scores misalignment arose from the inhomogeneity and heterogeneity of the following fact: unavailability or the low quality of basic education, received by the population. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 5,22 score, and this corresponds the Kazakhstan (5,22) ranked 69th;

- mode is 6,22 score, and this corresponds Singapore ranked 3rd; Sweden ranked 4th; Netherlands ranked 10th and France ranked 17th;

- maximum is 6,46 score, and this corresponds Finland ranked 6th;

- minimum is 2,55 score, and this corresponds Chad ranked 131st. Then interval is 3,91 score, also note that Germany (24th) is 6,01; United States (35th) – 5,88; Turkey (74th) – 5,32 and Kazakhstan (80th) – 5,22 scores;

- skewness coefficient is -0,968, and this appropriate distribution of the health and primary education scores shift the mean significance to the left;

- kurtosis coefficient is 0,180, and this appropriate distribution relatively normal distribution is the small upright.


3. Efficiency enhancers
3.1 Higher education and training. Quality higher education and training is crucial for economies that want to move up the value chain beyond simple production processes and products (Schultz, 1961; Lucas, 1988; Becker, 1993; and Kremer, 1993).

Higher education and training scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: no educated workers, who are unable to adapt rapidly to their changing environment, and also the extent of staff training. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 4,032 score, and this corresponds the Sri Lanka (4,01) ranked 79th;

- mode is 2,78 score, and this corresponds Cambodia ranked 110th; Malawi ranked 121st and Paraguay ranked 124th;

- maximum is 5,97 score, and this corresponds Finland ranked 6th;

- minimum is 2,23 score, and this corresponds Chad ranked 131st. Then interval is 3,74 score, also note that United States (7th) – 5,57; Germany (22nd) is 5,07; Kazakhstan (59th) – 4,13 and Turkey (73rd) – 3,88 scores;

- skewness coefficient is 0,160, and this appropriate distribution of the health and primary education scores shift the mean to the right;

- kurtosis coefficient is -0,775, and this appropriate distribution relatively normal distribution is the horizontally direction.


3.2 Goods market efficiency. Countries with efficient goods markets are well positioned to produce the right mix of products and services given supply-and-demand conditions, as well as to ensure that these goods can be most effectively traded in the economy.

Goods market efficiency scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: burdensome taxes and discriminatory rules on foreign direct investment, and also government intervention in business activity. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 4,25 score, and this corresponds the Gambia, The (4,25) ranked 80th;

- mode is 4,24 score, and this corresponds Kuwait ranked 39th; Romania ranked 64th and Nigeria ranked 99th;

- maximum is 5,77 score, and this corresponds Singapore ranked 3rd;

- minimum is 2,88 score, and this corresponds Chad ranked 131st. Then interval is 2,89 score, also note that United States (12th) – 5,13; Germany (18th) is 5,01; Turkey (56th) – 4,30 and Kazakhstan (83rd) – 4,00 scores;

- skewness coefficient is 0,158, and this appropriate distribution of the goods market efficiency scores shift the mean to the right;

- kurtosis coefficient is -0,342, and this appropriate distribution relatively normal distribution is the horizontally direction.


3.3 Labor market efficiency. The efficiency of the labor market are critical for ensuring that workers are allocated to their most efficient use in the economy and provided with incentives to give their best effort in their jobs (Almeida and Carneiro, 2009; Amin, 2009; and Kaplan, 2009).

Labor market efficiency scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: no flexibility of labor markets to shift workers from one economic activity to another rapidly and at low cost, and to allow for wage fluctuations without much social disruption, and also unavailability of clear relationship between worker incentives and their efforts and unavailability of equity in the business environment between women and men. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 4,38 score, and this corresponds the El Salvador (3,36) ranked 77th;

- mode is 4,33 score, and this corresponds Germany ranked 7th; Saudi Arabia ranked 28th and Jamaica ranked 91st;

- maximum is 5,91 score, and this corresponds Singapore ranked 3rd;

- minimum is 2,91 score, and this corresponds Venezuela ranked 113rd. Then interval is 3,00 score, also note that United States (3th) – 5,76; Kazakhstan (18th) – 4,93; Germany (70th) is 4,33 and Turkey (120th) – 3,65 scores;

- skewness coefficient is 0,080, and this appropriate distribution of the labor market efficiency scores shift the mean to the right;

- kurtosis coefficient is 0,378, and this appropriate distribution relatively normal distribution is the upright.


3.4 Financial market sophistication. An efficient financial sector allocates the resources saved by a nation’s citizens as well as those entering the economy from abroad to their most productive uses. It channels resources to those entrepreneurial or investment projects with the highest expected rates of return, rather than to the politically connected. Economies require sophisticated financial markets that can make capital available for private-sector investment from such sources as loans from a sound banking sector, well-regulated securities exchanges, venture capital, and other financial products.

Financial market sophistication scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: no trustworthy and nontransparent of the banking sector, unavailability appropriate regulation of financial markets for protection of investors. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 4,23 score, and this corresponds the Guatemala (4,23) ranked 81st;

- mode is 4,40 score, and this corresponds Taiwan, China ranked 12nd; Romania ranked 64th and Malawi ranked 121st;

- maximum is 5,95 score, and this corresponds Hong Kong SAR ranked 11nd;

- minimum is 2,68 score, and this corresponds Burundi ranked 133rd. Then interval is 3,27 score, also note that United States (20th) – 4,96; Germany (36th) is 4,68; Turkey (81st) – 4,07 and Kazakhstan (112th) – 3,48 scores;

- skewness coefficient is -0,035, and this appropriate distribution of the financial market sophistication scores shift the mean to the left;

- kurtosis coefficient is -0,429, and this appropriate distribution relatively normal distribution is the horizontally direction.


3.5 Technological readiness. In today’s globalize world, technology has increasingly become an important element for firms to compete and prosper. In particular, information and communication technologies (ICT) have evolved into the “general purpose technology” of our time, 17 given the critical spillovers to the other economic sectors and their role as efficient infrastructure for commercial transactions. Therefore ICT access (including the presence of an ICT-friendly regulatory framework) and usage are included in the pillar as essential components of economies’ overall level of technological readiness (Aghion and Howitt, 1992 and Barro and Sala-i-Martin, 2003).

Technological readiness scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: the low level of technological readiness, and also shortages in finance and a more risk averse attitude of businesses. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 3,827 score, and this corresponds the Turkey (3,83) ranked 62nd;

- mode is 3,53 score, and this corresponds Mexico ranked 60th; Kazakhstan ranked 67th and Guatemala i ranked 81th;

- maximum is 6,15 score, and this corresponds Sweden ranked 11rd;

- minimum is 2,19 score, and this corresponds Timor-Leste ranked 126th. Then interval is 3,96 score, also note that Germany (11th) is 5,63; United States (13rd) – 5,61; Turkey (54th) – 3,83 and Kazakhstan (70th) – 3,53 scores;

- skewness coefficient is 0,525, and this appropriate distribution of the financial market sophistication scores shift the mean significance to the right;

- kurtosis coefficient is -0,860, and this appropriate distribution relatively normal distribution is the horizontally direction.


3.6 Market size. The size of the market affects productivity because large markets allow firms to exploit economies of scale. In the era of globalization, international markets have become a substitute for domestic markets, especially for small countries (Sachs and Warner, 1995; Frenkel and Romer, 1999; Rodrik and Rodriguez, 1999; Alesina et al., 2005; and Feyrer, 2009).

Market size scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: lack of trade and export, and also the barriers to trade. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 4,35 score, and this corresponds the Puerto Rico (3,79) ranked 42nd;

- mode is 3,53 score, and this corresponds Norway ranked 14th; Hungary ranked 57th and Peru ranked 78th;

- maximum is 6,93 score, and this corresponds United States ranked 2nd;

- minimum is 1,30 score, and this corresponds Timor-Leste ranked 126th. Then interval is 5,63 score, also note that United States (1st) – 6,93; Germany (5th) is 6,02; Turkey (15th) – 5,22 and Kazakhstan (55th) – 4,17 scores;

- skewness coefficient is 0,197, and this appropriate distribution of the market size scores shift the mean to the right;

- kurtosis coefficient is -0,365; and this appropriate distribution relatively normal distribution is the horizontally direction.


4. Innovation and sophistication factors
4.1 Business sophistication. Business sophistication is conducive to higher efficiency in the production of goods and services. This leads, in turn, to increased productivity, thus enhancing a nation’s competitiveness. Business sophistication concerns the quality of a country’s overall business networks as well as the quality of individual firms’ operations and strategies. It is particularly important for countries at an advanced stage of development, when the more basic sources of productivity improvements have been exhausted to a large extent.

Business sophistication scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: barriers to entry to the market for new firms, unavailability of opportunities for innovation, and also the low quality of a country’s business networks and supporting industries. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 4,117 score, and this corresponds the Mexico (4,15) ranked 60th;

- mode is 4,64 score, and this corresponds New Zealand ranked 20th; Slovenia ranked 37th and Brazil ranked 56th;

- maximum is 5,89 score, and this corresponds Japan ranked 8th;

- minimum is 2,97 score, and this corresponds Timor-Leste ranked 126th. Then interval is 2,92 score, also note that Germany (2nd) is 5,82; United States (5th) – 5,65; Turkey (53rd) – 4,28 and Kazakhstan (88th) – 3,70 scores;

- skewness coefficient is 0,527, and this appropriate distribution of the business sophistication scores shift the mean significance to the right;

- kurtosis coefficient is -0,540, and this appropriate distribution relatively normal distribution is the horizontally direction.


4.2 Innovation. Innovation is particularly important for economies as they approach the frontiers of knowledge and the possibility of integrating and adapting exogenous technologies tends to disappear (Romer, 1990; Grossman and Helpman, 1991; and Aghion and Howitt, 1992).

Innovation scores misalignment arose from the inhomogeneity and heterogeneity of the following facts: insufficient investment in research and development, and also absence of high-quality scientific research institutions. Indeed, based on analysis of data of the Global Competitiveness Report 2009-2010 we obtain the following:

- mean is 3,369 score, and this corresponds the Italy (3,38) ranked 47th;

- mode is 2,95 score, and this corresponds Mauritius ranked 58th; Argentina ranked 85th; Trinidad and Tobago ranked 86th and Madagascar ranked 120th;

- maximum is 5,77 score, and this corresponds United States ranked 2nd;

- minimum is 2,97 score, and this corresponds Paraguay ranked 124th. Then interval is 3,63score, also note that United States (1st) – 5,77; Germany (7th) is 5,11; Kazakhstan (64th) – 3,15 and Turkey (69th) – 3,13 scores;

- skewness coefficient is 1,137, and this appropriate distribution of the innovation scores shift the mean significance to the right;

- kurtosis coefficient is -0,540, and this appropriate distribution relatively normal distribution is the horizontally direction.


5. Conclusions

This study shows that the statistical analysis of empirical data Global Competitiveness Report 2009-2010 is subjected to varying degrees of inhomogeneity and heterogeneity that determines the misalignment of the GCI.

The value distribution of score indicators of competitiveness directed to the left are:

- Macroeconomic stability,

- Health and primary education,

- Financial market sophistication. Them here relatively normal distribution the upright is:

- Macroeconomic stability, as normal distribution is:

- Health and primary education. And normal distribution the horizontally direction is:

- Financial market sophistication.

The value distributions of score indicators of competitiveness to the not significance directed are:

- Higher education and training,

- Goods market efficiency,

- Labor market efficiency,

- Market size. Them here relatively normal distribution the upright is:

- Labor market efficiency. And normal distribution the horizontally direction are:

- Higher education and training,

- Goods market efficiency,

- Market size.

The value distribution of score indicators of competitiveness directed to the right are:

- Institutions,

- Infrastructure,

- Technological readiness,

- Business sophistication,

- Innovation. Them here relatively normal distribution the upright is:

- Innovation. And normal distribution the horizontally direction are:

- Institutions,

- Infrastructure,

- Technological readiness,

- Business sophistication.

Thus, this statistical analysis shows that the measures of competitiveness factor and a statistical analysis methods have significant negative impact, while these characteristics, as inhomogeneity and heterogeneity, and the underlying theoretical models of competitive factors all have significant positive impact on measures misalignment of the GCI.



References:

Acemoglu, D., S. Johnson, and J. Robinson. 2001. “The Colonial Origins of Comparative Development: An Empirical Investigation.” American Economic Review 91: 1369–1401.

Aghion P. and P. Howitt. 1992. “A Model of Growth through Creative Destruction.” Econometrica LX: 323–51.

Aghion P. and P. Howitt. 1992. “A Model of Growth through Creative Destruction.” Econometrica LX: 323–51.

Alesina, A., E. Spolaore, and R. Enrico. 2005. “Trade, Growth and the Size of Countries.” In P. Aghion and S. Durlauf, eds., Handbook of Economic Growth, 1st Edition, Volume 1. Amsterdam: Elsevier. 1499–1542.

Almeida, R., and P. Carneiro, 2009. “Enforcement of Labor Regulation and Firm Size.” Journal of Comparative Economics 37 (1): 28–46.

Amin, M. 2009. “Labor Regulation and Employment in India’s Retail Stores.” Journal of Comparative Economics 37 (1): 47–61.

Aschauer, D. A. 1989. “Is Public Expenditure Productive?” Journal


of Monetary Economics 23 (2): 117–200.

Barro, R. J. and X. Sala-i-Martin. 2003. Economic Growth, 2nd Edition. Cambridge, MA: MIT Press.

Becker, G. S. 1993. Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education, 3rd Edition. Chicago: University
of Chicago Press.

Canning, D., M. Fay, and R. Perotti. 1994. “Infrastructure and Economic Growth.” In M. Baldarassi, L. Paganetto, and E. Phelps, eds. International Differences in Growth Rates. New York: Palgrave Macmillan.

De Soto, H. and J. Abbot. 1990. The Other Path: The Economic Answer
to Terrorism. New York: Harper Perennial.

Easterly, W. 2002. The Elusive Quest for Growth. Cambridge,


MA: MIT Press.

Easterly, W. and R. Levine. 1997. “Africa’s Growth Tragedy: Policies and Ethnic Divisions.” Quarterly Journal of Economics CXII: 1203–50.

Feyrer, J. 2009. “Trade and Income: Exploiting Time Series in Geography.” NBER Working Paper No. w14910. Cambridge, MA: National Bureau
of Economic Research.

Fischer, S. 1993. “The Role of Macroeconomic Factors in Growth.” Journal of Monetary Economics 32 (3): 485–512.

Frenkel, J. and D. Romer. 1999. “Does Trade Cause Growth?” American Economic Review 89 (3): 379–99.

Gramlich, E. M. 1994. “Infrastructure Investment: A Review Essay.” Journal of Economic Literature 32 (3): 1176–96.

Grossman, G. and E. Helpman. 1991. Innovation and Growth in the World Economy. Cambridge, MA: MIT Press, Chapters 3 and 4.

Kaplan, D. 2009. “Job Creation and Labor Reform in Latin America.” Journal of Comparative Economics 37 (1): 91–105.

Kremer, M. 1993. “The O-Ring Theory of Economic Development.” Quarterly Journal of Economics 108 (3): 551–75.

Lucas, R. E. 1988. “On the Mechanics of Economic Development.” Journal of Monetary Economics 22 (1): 3–42.

Rodrik, D. and F. Rodriguez. 1999. “Trade Policy and Growth: A Skeptics’ Guide to Cross National Evidence.” NBER Working Paper No. 7081, April. Cambridge, MA: National Bureau of Economic Research.

Rodrik, D., A. Subramanian, and F. Trebbi. 2002. “Institutions Rule:


The Primacy of Institutions over Geography and Integration in Economic Development.” Mimeo, Harvard University, October.

Romer, P. 1990. “Endogenous Technological Change.” Journal of Political Economy 98 (October): X71–S102.

Sachs, J. 2001. Macroeconomics and Health: Investing in Health
for Economic Development: Report of the Commission on Macroeconomics and Health. Geneva: World Health Organization.

Sachs, J. and A. Warner. 1995. “Economic Reform and the Process


of Economic Integration.” Brookings Papers on Economic Activity 1995 (1):
1–118.

Table 5: Descriptive statistics of the distribution of score for
the Global Competitiveness Index's and its factors



Structure__Mean__Standard_error__Me-_dian'>Structure

Mean

Standard
error


Me-
dian


Mode

Standard
deviation


1

2

3

4

5

6

Global Competitiveness Index (GCI)

4,170

0,058

4,08

4,30

0,664

Basic requirements (BAR)

4,454

0,070

4,38

4,26

0,812

Efficiency enhances (EFE)

4,084

0,060

4,05

4,08

0,693

Innovation and sophistication factors (ISF)

3,743

0,066

3,57

3,21

0,756

Institutions (INS)

4,110

0,079

3,88

3,24

0,913

Infrastructure (INF)

3,894

0,104

3,84

2,91

1,204

Macroeconomic stability (MES)

4,598

0,080

4,62

5,24

0,920

Health and primary education (HPE)

5,215

0,079

5,41

6,22

0,916

Higher education and training (HET)

4,032

0,078

3,93

2,78

0,898

Goods market efficiency (GME)

4,250

0,051

4,2

4,24

0,586

Labor market efficiency (LME)

4,386

0,048

4,39

4,33

0,553

Financial market sophistication (FMS)

4,228

0,061

4,23

4,40

0,708

Technological readiness (TCR)

3,827

0,094

3,55

3,53

1,088

Market size (MRS)

3,790

0,102

3,69

4,35

1,177

Business sophistication (BSS)

4,117

0,063

4,03

4,64

0,726

Innovation (INN)

3,369

0,071

3,12

2,95

0,818

Table 6: Descriptive statistics of the distribution of score for
the Global Competitiveness Index's and its factors

Structure

Sampling
variance


Kurto-
sis


Skew-
ness


Inter-
val


Mini-
mum


Maxi-
mum


1

7

8

9

10

11

12

l Competitiveness Index (GCI)

0,441

-0,505

0,296

3,02

2,58

5,60

Basic requirements (BAR)

0,659

-0,773

0,162

3,55

2,49

6,04

Efficiency enhances (EFE)

0,480

-0,678

0,279

2,98

2,68

5,66

Innovation and sophistication factors (ISF)

0,571

0,024

0,866

3,08

2,63

5,71

Institutions (INS)

0,834

-0,628

0,520

3,76

2,39

6,15

Infrastructure (INF)

1,449

-0,795

0,445

4,69

1,90

6,59

Macroeconomic stability (MES)

0,846

2,499

-0,946

5,64

1,00

6,64

Health and primary education (HPE)

0,839

0,180

-0,968

3,91

2,55

6,46

Higher education and training (HET)

0,807

-0,775

0,160

3,74

2,23

5,97

Goods market efficiency (GME)

0,343

-0,342

0,158

2,89

2,88

5,77

Labor market efficiency (LME)

0,306

0,378

0,080

3,00

2,91

5,91

Financial market sophistication (FMS)

0,501

-0,429

-0,035

3,27

2,68

5,95

Technological readiness (TCR)

1,184

-0,860

0,525

3,96

2,19

6,15

Market size (MRS)

1,384

-0,361

0,197

5,63

1,30

6,93

Business sophistication (BSS)

0,527

-0,540

0,527

2,92

2,97

5,89

Innovation (INN)

0,669

0,657

1,138

3,63

2,14

5,77

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  • 2 . Basic requirements 2.1 Institutions.
  • 2.3 Macroeconomic stability.
  • 2.4 Health and primary education.
  • 3 . Efficiency enhancers 3.1 Higher education and training.
  • 3.2 Goods market efficiency.
  • 3.3 Labor market efficiency.
  • 3.4 Financial market sophistication.
  • 3.5 Technological readiness.
  • 4 . Innovation and sophistication factors 4.1 Business sophistication.
  • 5 . Conclusions
  • Structure Mean Standard error Me- dian
  • Structure Sampling variance Kurto- sis Skew- ness