However, it is not questionable that inside the subjectivity, our proposed index is less manipulable for humans as no survey opinions are included. At the same time, other countries relative competitiveness improved from one period to the next: Austria, Germany, Estonia (Europe), and Oman (Asia). report global competitiveness economic weforum pakistan ranked reports gcr www3 One part of the report is the Executive Opinion Survey, which is a survey of a representative sample of business leaders in their respective countries. global competitiveness report reports methodology These are: In the factor-driven stage countries compete based on their factor endowments, primarily unskilled labor and natural resources. No, Is the Subject Area "Macroeconomics" applicable to this article? Therefore, we call this factor Inflation and ease of doing business, which is identified with C2 for the 201011 period and explains 9.6% (9.7%) of the total variability. competitiveness global report 2002 economic 2001 According to the structure of said factor (which is common to both periods), a possible name could be Human development and ease of communication. This factor explains 28.4% (31.5%) of the total variability. Values of the KMO measurement below 0.5 are not acceptable [24]. Depend on the economic and political interest of countries: from the USAs point of view, from Switzerlands point of view or Singapores perspective, among other countries. Please help this article by looking for better, more reliable sources. This table shows that competitiveness can be synthesized in seven factors for the two analyzed periods, according to the criteria based on selecting the factors associated with higher eigenvalues than the unit [21]. In summary, and in terms of the evolution of the countries positioned in the first and fifth quintiles, it is noteworthy that for both periods, the majority of the least competitive countries are located in Africa, except for Cambodia, while the most competitive countries are located in Australia (Oceania), United States (America), Singapore (Asia), and others in Central and Northern Europe (Denmark, Finland, Holland, Norway, Sweden, and Switzerland). In turn, the country distribution considering their scores in the GCI and CSI for the two analyzed periods is shown in Figs 2, 3, 4, and 5. No, Is the Subject Area "Factor analysis" applicable to this article? The geographic representation is based on the quintiles (values that divide the corresponding distribution into five types, each with the same number of countries, approximately). "Global Competitiveness Report 2014-2015 - Reports - World Economic Forum", "Global Competitiveness Network: Frequently Asked Questions", http://www3.weforum.org/docs/WEF_GCR_Report_2011-12.pdf, http://www.columbia.edu/~xs23/papers/WEC_00220_00701_Snowdon.pdf, https://imd.cld.bz/IMD-World-Competitiveness-Booklet-2022/34/, "Global Competitiveness Report 2017-2018", "Global Competitiveness Report 2016-2017", "Global Competitiveness Report 2015-2016", http://www3.weforum.org/docs/WEF_GlobalCompetitivenessReport_2013-14.pdf, http://www3.weforum.org/docs/WEF_GlobalCompetitivenessReport_2012-13.pdf, "US Competitiveness Ranking Continues to Fall; Emerging Markets Are Closing the Gap | World Economic Forum - US Competitiveness Ranking Continues to Fall; Emerging Markets Are Closing the Gap", "Table 4: The Global Competitiveness Index 20102011 rankings and 20092010 comparisons", "Table 4: The Global Competitiveness Index 20092010 rankings and 20082009 comparisons", "The Global Competitiveness Index rankings and 20072008 comparisons", "Interactive Global Competitiveness Report", Top 20 countries of 2010 by competitiveness, International Institute for Management Development publications, Timeline of geopolitical changes (before 1900), Timeline of geopolitical changes (1900present), https://en.wikipedia.org/w/index.php?title=Global_Competitiveness_Report&oldid=1100274132, All articles with bare URLs for citations, Articles with bare URLs for citations from March 2022, Articles with PDF format bare URLs for citations, Short description is different from Wikidata, Articles lacking reliable references from June 2019, Creative Commons Attribution-ShareAlike License 3.0, This page was last edited on 25 July 2022, at 02:23. The Global Competitiveness Report 2018[10] and 2019[11] used the ecological footprint as a context indicator, but the footprint was not included in the scoring algorithm that determines the ranking. Yes Yes If the partial correlation coefficients approach said theoretical coefficients, they must be close to zero and, therefore, the value of the KMO index should be close to 1. In 2012, Loo states the need for a third organization to measure competitiveness in order to conciliate both results WEF and IMD. https://doi.org/10.1371/journal.pone.0265045.t005, In regard to the interpretation of the retained factors, it should be noted that the only factor that is common to both periods (C5) is the one that includes the variables related to the macroeconomic environment (Pillar 3), with the exception of inflation (Pillar3X3). Respondent numbers have increased every year and is currently just over 13,500 in 142 countries (2010).[7]. Artadi. Is the Subject Area "Statistical data" applicable to this article? No, Is the Subject Area "United States" applicable to this article? The Global Competitiveness Report (GCR)[1] is a yearly report published by the World Economic Forum. here. Meanwhile, other factors related to the 200708 period, such as C3, C4, and C6, could be identified in 201011 with C2, C3, and C6, respectively, since the variables that have higher correlations with each of these factors are the same for both periods. 1011, respectively), very close to zero, indicate the existence of linear dependence between the indicators included in this study for both of these periods and the non-existence of redundant indicators; in other words, they are the perfect linear combination of others that are also included in the analysis. Companies compete on the basis of prices and sell basic products or commodities, with their low productivity reflected in low wages. Yes No, Is the Subject Area "Geographic distribution" applicable to this article? Moreover, in any elaboration of an index, there is subjectivity as humans are involved in the process. The loading for this factor, C3, for the 200708 period also includes the variable that quantifies the costs of layoffs (Pillar 7), although it is less significant than those previously mentioned. Meanwhile, the most competitive countries for both periods belong to Oceania (Australia), America (United States), Central and Northern Europe (Denmark, Finland, Holland, Norway, Sweden, and Switzerland), and Asia (Singapore). In memoriam to Mara Dolores Sarrin-Gavilan. Similarly, all of the countries classified in the last quintile for the 200708 period, except for Israel, remain in the same quintile for the 201011 period. This comparison is based on the data in common among 22 countries: Germany, Austria, Belgium, Denmark, Spain, Estonia, Finland, France, Greece, Holland, Hungary, Ireland, Italy, Latvia, Lithuania, Norway, Poland, Portugal, United Kingdom, Czech Republic, Sweden, Switzerland. Based on a review of the methodology used by the WEF to compute the global competitiveness index, we can conclude that there is a very high percentage of qualitative data in the total data used (approximately 75%), which results in the subjectivity of the index. Based on these determinants, we have calculated the values of the effective dependence coefficients associated with them, D07-08(R) = 0.6366 and D10-11(R) = 0.6345, which indicate the existence of a considerable degree of linear dependence between the variables involved in each of the analyzed periods. We believe that this is the only way to eliminate any political biases or individual interests. Table 5 shows the factor loading matrices after the varimax rotation or rotated component matrices, which are formed by the linear correlation coefficients between the factors and the indicators used to estimate them. The rankings provided by the proposed index (CSI) present a high degree of association with the rankings from the Global Competitiveness Index (GCI) for the two analyzed periods. In addition, what creates productivity in Sweden is necessarily different from what drives it in Ghana. According to the factor analysis model, the theoretical correlation coefficients calculated between each pair of unique factors are null by hypothesis. Similarly, although it may seem obvious, the two indices provide different rankings, both in terms of the majority of the countries that are classified as the most competitive according to the WEF-GCI (the first 20 countries) and the majority of the countries that are classified as the least competitive (the last 20 countries), which remain in the same group according to the alternative index CSI. Finally, the CSI shows a very similar evolution as mentioned in the previous paragraph (see Figs 3 and 5).

Therefore, in the calculation of the GCI, pillars are given different weights depending on the per capita income of the nation. https://doi.org/10.1371/journal.pone.0265045.t006. Considering the classification presented in Table 7, according to the CSI, we can see that the most competitive countries for the two analyzed periods are Singapore and Norway.

This coefficient quantifies the degree of association between the two rankings and indicates their direction, as well as the association between the WEF-GCI for the countries analyzed in this study, which is statistically significant, positive and high. Theoretically, we cannot establish as clear of a correspondence for the remaining factors in the 200708 period and the 201011 period as those described in the previous paragraph. Note it presents a weak, negative correlation with the normalized variable that quantifies the total tax rate (Pillar6X1) for the 200708 period, while it appears to be correlated with the Gross National Savings for the 201011 period (Pillar3X2). Be aware, there is not included hard data into the following pillars: the Pillar 1 Institutions, the Pillar 2 Financial market development, the Pillar 11 Business sophisticationand the Pillar 12Innovation.

Accordingly, the majority of the least competitive countries maintain their position in the two analyzed periods and are generally African countries. This subjectivity is accentuated by the arbitrary selection of weights, both for those that quantify the percentage of the different indicators in the corresponding pillar and those that indicate the importance of each pillar in the total, where the latter are also almost exclusively dependent on the countrys income level. The Global Competitiveness Index integrates the macroeconomic and the micro/business aspects of competitiveness into a single index. The report has twelve pillars of competitiveness. In regard to the WEFs methodology, we lean toward a competitiveness index based on official, quantitative data that is computed using statistical and/or mathematical procedures, which considers weights that can be implicitly determined by the inherent structure of the data. Depending on what indicators are used to measure competitiveness, the outcome will be different. The following section presents an analysis of the results of said indicator for the two analyzed periods. Table 4 includes the eigenvalues associated with the retained factors, the percentage of the total explained variance for each of these factors after the varimax rotation and the accumulated percentage. Finally, the relevant advantages of using this index are the transparency of the information of WEF-GCI (freely available online) and continuation in yearly published since 1979. The association between the rankings based on the scores of said indices, measured by Spearmans correlation coefficient, is considered to be statistically significant, positive, and high for the different pairs considered in this study, as shown in Table 10. https://doi.org/10.1371/journal.pone.0265045.t010. One year later, in 2013, the first report of SolAbility-GSCI [13] only using quantitative indicators was published by this South Korean company and maintains the publication currently but from the perspective of sustainability. Table 7 shows the rankings from the CSI and WEF-GCI for the analyzed countries and periods. Moreover, Loo states there is still a controversial opinion concerning the different rankings provided by WEF and IMD, both Switzerland-based institutions. Moreover, the 2012 GSCI report [13] indicates that countries in northern Europe are the leading countries: Denmarkrank 1, Swedenrank 2 Norwayrank 3 have the highest rakings, although this index is proposed from a sustainable perspective. Since 2004, the report ranks the world's nations according to the Global Competitiveness Index,[2] based on the latest theoretical and empirical research.

Table 9 presents a summary of the countries that are among the least competitive (first quintile) and the most competitive (last quintile), respectively, for the two analyzed periods, according to both indices. The report "assesses the ability of countries to provide high levels of prosperity to their citizens". To maintain competitiveness at this stage of development, competitiveness hinges mainly on well-functioning public and private institutions (pillar 1), appropriate infrastructure (pillar 2), a stable macroeconomic framework (pillar 3), and good health and primary education (pillar 4). However, C1 presents intense correlations with the variables related to infrastructure (Pillar 2), innovation (Pillar 9), education (Pillars 4 and 5), per capita income (Anc2) and some health-related variables (infant mortality, Pillar4X4, and life expectancy, Pillar4X5) for both periods. https://doi.org/10.1371/journal.pone.0265045.t007. The comparison of the dependence coefficient with these extreme cases can give us a good idea of the degree of linear dependence between the indicators used [23]. According to the above, Factor C2 (200708) could be called Health, but we cannot find an appropriate name or clear interpretation for Factor C4 (201011).



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