The different approaches to competitiveness discussed above produce different diagnostics for cross-country competitiveness benchmarking. The two main competitors of the CIP index in the field of competitiveness benchmarking are the new GCI produced by the WEF and the WCS by the IMD. These two institutions, WEF and IMD, used to jointly publish a competitiveness index in the World Competitiveness Report.
Following the decision to go their separate ways in 1996, WEF places relatively greater emphasis on ‘soft’
data while IMD focuses on ‘hard’ data. While the WEF’s competitiveness analysis is widely cited in policy and academic debates, the IMD’s ranking is more widely used in business schools.
World Economic Forum: The New Global Competitiveness Index
Competitiveness indices promoted by the WEF have been widely publicized by mass media, although some scholars have stressed the lack of transparency of the benchmarking exercise and have expressed some doubts about the competitiveness rankings produced(Lall, 2001b; Godin, 2004). The WEF embraces what we call here the national competitiveness approach. Since 2005, countries’ national competitiveness has been assessed through a composite index called Global Competitiveness Index (GCI). This index underwent a major revision in the WEF 2008/9 Report. The majority of the individual indicators used in the various editions of the WEF Global Competitiveness Reports have been incorporated into the current GCI. How these sub-indicators are combined has drastically changed due to the adoption of a new ‘hierarchical model’
for the assessment of competitiveness and more rigorous statistical methodologies.
To capture the institutions, policies and factors responsible for the overall level of productivity of a given
11 For a discussion on these issues, see Andreoni, 2011a.
country (i.e. its competitiveness), the WEF uses a ‘12 pillars’ schema (see Table 2). Each of these pillars captures one distinct determinant of national competitiveness and consists of sub-categories. For each of these sub-categories, a list of sub-indicators mixing qualitative and quantitative data, as well as input and output variables are considered. All these sub-indicators are included in the final composite index (GCI) in accordance with the pillar they belong to.12
The relevance of each determinant is dependent on the country’s stage of development and is reflected in the weight of each pillar in the composite index. In the WEF classification, countries are divided into three categories based on stage of development: factor-driven, efficiency-driven and innovation-driven. The distinction is made based on GDP (gross domestic product) per capita and whether a country’s exports are factor-driven.13 Thus, it is assumed that countries need to focus on different sub-groups of pillars according to their stage of development.
Table 2: The World Economic Forum’s 12 pillars of competitiveness
Source: WEF, 2012:8.
12 As some indicators traverse different pillars, the methodology adopted assigned half-weights to avoid double counting.
13 Exports are factor-driven when the share of exports of mineral goods in total exports is higher than 70 percent.
Institute for Management Development: World Competitiveness Scoreboard
The IMD World Competitiveness Scoreboard (WCS) has been published without interruption since 1989.
It aims to rank and analyse “how nations and enterprises manage the totality of their competences to achieve increased prosperity” (IMD, 2011:480). The analysis is carried out at the national level, because national environments shape the ability of firms to compete both domestically and internationally. To determine the overall competitiveness of nations, the WCS 2012 utilizes 4 competitiveness input factors, 20 sub-factors and 329 criteria. Among the criteria, 247 criteria (quantitative data: 131 and perception data: 116) are taken into consideration to determine the overall competitiveness ranking, while 82 criteria are used as background information (Table 3). Irrespective of the number of individual factors they include, each of the 20 sub-factors is given a weight of 5 percent in the composite indicator through which the scoreboard is produced.
Table 3: The IMD competitiveness factors
Source: IMD, 2011:480.
The individual measures consist both of hard and soft data. The latter is perception-based information about countries’ competitiveness in areas such as management practices and labour relations. The percep-tions of the business community are collected through an Executive Opinion Survey (EOS) conducted every year in each of the ranked economies. Differently from the WEF and UNIDO ranking, the IMD covers only 59 countries.
Countries’ movements across competitiveness rankings
What makes these benchmarking exercises particularly relevant in the current policy debate is that govern-ments include them in their goal statement, very often without realizing that the different composite indices by which these rankings are constructed cannot provide a neutral account of competitiveness. This is because the construction of a composite index relies on a sequence of subjective choices about the relevant dimensions to be included in the index, the focus on input or output measures, their proportional
relationships and weights. The more dimensions such as institutional and structural aspects and macroeco-nomic conditions are included, the lower the transparency of the final composite index. Institutional aspects are intrinsically qualitative features whose assessment depends on subjective and perception-based evalua-tions. Some structural aspects of economies, such as the technological complexity of their production base, rely on some form of technological classification of sectors.
According to the concept of competitiveness and empirics adopted, three completely different global sce-narios emerge. Notably, given the particular emphasis the CIP index assigns to the manufacturing sector, countries specializing in agriculture, resource-based manufacturing (including mining) or in services perform much better in the WEF and IMD rankings than in the CIP index ranking. By contrast, newly industrial-ized countries do comparatively better in UNIDO’s CIP index ranking because they are experiencing processes of industrial upgrading. Table 4 shows the high degree of diversity in the assessment of world competitiveness rankings on account of the three major differences pointed out above and the underlying distinctions in understanding competitiveness.
20 Czech Republic 39 -19 33 -13 6
21 Malaysia 25 -4 14 7 11
UNIDO
36 Russian Federation 67 -31 48 -12 19
37 Saudi Arabia 18 19 NA
51 Venezuela (Bolivarian Republic of) 126 -75 59 -8 67
52 Estonia 34 18 31 21 3
53 Ukraine 73 -20 NA
54 Viet Nam 75 -21 NA
55 Iran (Islamic Republic of) 66 -11 NA
56 Costa Rica 57 -1 NA
UNIDO
84 The f. Yugosl. Rep of Macedonia 80 4 NA
85 Swaziland 135 -50 NA
92 Bolivia (Plurinational State of) 104 -12 NA
93 Jamaica 97 -4 NA
106 United Republic of Tanzania 120 -14 NA
107 Azerbaijan 46 61 NA
UNIDO
The World Economic Forum also includes the following countries: 24 United Arab Emirates; 28 Brunei; 31 Puerto Rico;
35 Barein; 76 Seychelles; 92 Namibia; 105 Dominican Republic; 108 Nicaragua; 109 Guyana; 111 Liberia; 113 Lybia;
119 Benin; 128 Mali; 132 Zimbabwe; 133 Burkina Faso; 134 Mauritania; 136 Timor-Leste; 137 Lesoto; 139 Chad; 141 Guinea; 143 Sierra Leone.
Source: UNIDO Report 2012/13; WEF Report 2012/3; IMD Report 2012/3.