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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

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 70 - mode is 3,24 score, and this corresponds Philippines ranked 88 - maximum is 6,15 score, and this corresponds Singapore ranked 3 - minimum is 2,39 score, and this corresponds Venezuela ranked 113 - 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 48 ^{th};
- mode is 2,91 score, and this corresponds Peru ranked 78 - maximum is 6,59 score, and this corresponds Germany ranked 7 - minimum is 1,9 score, and this corresponds Chad ranked 131 - 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 69 - mode is 5,24 score, and this corresponds Singapore ranked 3 - maximum is 6,64 score, and this corresponds Brunei Darussalam ranked 32 - minimum is 1,0 score, and this corresponds Zimbabwe ranked 132 - 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 69 - mode is 6,22 score, and this corresponds Singapore ranked 3 - maximum is 6,46 score, and this corresponds Finland ranked 6 - minimum is 2,55 score, and this corresponds Chad ranked 131 - 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 79 - mode is 2,78 score, and this corresponds Cambodia ranked 110 - maximum is 5,97 score, and this corresponds Finland ranked 6 - minimum is 2,23 score, and this corresponds Chad ranked 131 - 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 80 - mode is 4,24 score, and this corresponds Kuwait ranked 39 - maximum is 5,77 score, and this corresponds Singapore ranked 3 - minimum is 2,88 score, and this corresponds Chad ranked 131 - 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 77 - mode is 4,33 score, and this corresponds Germany ranked 7 - maximum is 5,91 score, and this corresponds Singapore ranked 3 - minimum is 2,91 score, and this corresponds Venezuela ranked 113 - 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 81 - mode is 4,40 score, and this corresponds Taiwan, China ranked 12 - maximum is 5,95 score, and this corresponds Hong Kong SAR ranked 11 - minimum is 2,68 score, and this corresponds Burundi ranked 133 - 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 62 - mode is 3,53 score, and this corresponds Mexico ranked 60 - maximum is 6,15 score, and this corresponds Sweden ranked 11 - minimum is 2,19 score, and this corresponds Timor-Leste ranked 126 - 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 42 - mode is 3,53 score, and this corresponds Norway ranked 14 - maximum is 6,93 score, and this corresponds United States ranked 2 - minimum is 1,30 score, and this corresponds Timor-Leste ranked 126 - 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 60 - mode is 4,64 score, and this corresponds New Zealand ranked 20 - maximum is 5,89 score, and this corresponds Japan ranked 8 - minimum is 2,97 score, and this corresponds Timor-Leste ranked 126 - 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 47 - mode is 2,95 score, and this corresponds Mauritius ranked 58 - maximum is 5,77 score, and this corresponds United States ranked 2 - minimum is 2,97 score, and this corresponds Paraguay ranked 124 - 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:
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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
Table 6: Descriptive statistics of the distribution of score for
the Global Competitiveness Index's and its factors
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