Economic Complexity Index

The Economic Complexity Index (ECI) is a holistic measure of the productive capabilities of large economic systems, usually cities, regions, or countries. In particular, the ECI looks to explain the knowledge accumulated in a population and that is expressed in the economic activities present in a city, country, or region. To achieve this goal, the ECI defines the knowledge available in a location, as the average knowledge of the activities present in it, and the knowledge of an activity as the average knowledge of the places where that economic activity is conducted. The product equivalent of the Economic Complexity Index is the Product Complexity Index or PCI.

Rank in the Economic Complexity Index (2015)

Higher economic complexity as compared to country's income level drives economic development. Many low-income countries, including Bangladesh, Venezuela, and Angola have failed to diversify their knowhow and face low growth prospects. Others like India, Turkey, and the Philippines have successfully added productive capabilities to enter new sectors and will drive growth over the coming years.[1]

Background

The ECI was developed by Cesar A. Hidalgo, from the MIT Media Lab and Ricardo Hausmann, from Harvard University's Kennedy School of Government. ECI data is available in The Observatory of Economic Complexity. The original formulation of the Economic Complexity Index was published in PNAS in 2009.[2]

Formulation

In its strict mathematical definition, the ECI is defined in terms of an eigenvector of a matrix connecting countries to countries, which is a projection of the matrix connecting countries to the products they export. Since the ECI considers information on the diversity of countries and the ubiquity of products, it is able to produce a measure of economic complexity containing information about both the diversity of a country's export and their sophistication. For example, Japan or Germany, with high ECIs, export many goods that are of low ubiquity and that are produced by highly diversified countries, indicating that these are diverse and sophisticated economies. Countries with low ECI, like Angola or Zambia, export only a few products, which are of relatively high ubiquity and which are exported by countries that are not necessarily very diversified, indicating that these are countries that have little diversity and that the products that they export are not very sophisticated.

Utility

Hidalgo and Hausmann propose the concept of ECI not only as a descriptive measure, but also as a predictive tool for economic growth and income inequality. According to the statistics models presented in their Atlas of Economic Complexity (2011),[3] the ECI is a more accurate predictor of GDP per capita growth than traditional measures of governance, competitiveness (World Economic Forum's Global Competitiveness Index) and human capital (as measured in terms of educational attainment). ECI also shows a strong negative correlation with income inequality, suggesting that more knowledge intense productive structures are more inclusive in terms of income distribution, and providing a statistically more powerful explanation of cross-national variations in income inequality than Kuznets Curve.[4]

Economic development requires the accumulation of productive knowledge and its use in both more and more complex industries. Many low-income countries, including Bangladesh, Venezuela, and Angola have failed to diversify their knowhow and face low growth prospects. Others like India, Turkey, and the Philippines have successfully added productive capabilities to enter new sectors and will drive growth over the coming years.[1]

Country rankings
Country Complexity Rankings[5]
Rank Country Economic complexity index (2018) Change in 5 years
(2013-18)		 Change in 10 years
(2008-18)
1  Japan 2.43
2   Switzerland 2.17 1 1
3  South Korea 2.11 4 8
4  Germany 2.09 2 2
5  Singapore 1.85 1
6  Austria 1.81 2 1
7  Czech Republic 1.80 1 2
8  Sweden 1.70 3
9  Hungary 1.66 5
10  Slovenia 1.62 3 3
11  United States 1.55 1 1
12  Finland 1.55 2 1
13  United Kingdom 1.51 2 5
14  Italy 1.44 2 3
15  Slovakia 1.41 1
16  France 1.37 2 1
17  Ireland 1.36 7
18  China 1.34 6
19  Mexico 1.29
20  Israel 1.20 6 3
21  Belgium 1.18 1 1
22  Thailand 1.17 2 9
23  Poland 1.10 2
24  Denmark 1.09 3 6
25  Romania 1.09 5
26  Malaysia 1.03 3 1
27  Netherlands 0.98 5
28  Estonia 0.96 2 4
29  Belarus 0.89 7 1
30  Croatia 0.87 1 1
31  Lithuania 0.86 5 10
32  Spain 0.83 4 7
33  Portugal 0.80 1 1
34  Latvia 0.70 3 6
35  Philippines 0.67 3 10
36  Saudi Arabia 0.67 33 71
37  Bosnia and Herzegovina 0.67 4 1
38  Serbia 0.67 1 2
39  Canada 0.65 2
40  Turkey 0.64 2 2
41  Bulgaria 0.55 1 5
42  India 0.54 10 8
43  Norway 0.44 8 8
44  Ukraine 0.37 1
45  Lebanon 0.35 2
46  Tunisia 0.34 2 8
47  Costa Rica 0.33 4 10
48  Bahrain 0.30 10 37
49  Brazil 0.21 2 1
50  Cyprus 0.18 4 24
51  Jordan 0.17 1 2
52  Vietnam 0.14 11 11
53  El Salvador 0.13 2 7
54  New Zealand 0.13 5 3
55  Greece 0.11 2 3
56  Colombia 0.10 4 3
57  North Macedonia 0.07 11 8
58  Trinidad and Tobago 0.05 24 23
59  Kyrgyzstan 0.04 11 8
60  Uruguay 0.02 6 5
61  Indonesia 0.02 1 1
62  United Arab Emirates -0.01 18 6
63  South Africa -0.02 7 7
64  Russia -0.04 1 3
65  Georgia -0.04 1 21
66  Egypt -0.06 1 4
67  Eswatini -0.08 6 34
68  Tanzania -0.09 25 28
69  Mauritius -0.17 3 3
70  Dominican Republic -0.18 4 6
71  Moldova -0.18 18 13
72  Chile -0.18 1
73  Argentina -0.21 14 14
74  Panama -0.24 42 37
75  Qatar -0.31 14 36
76  Albania -0.32 7
77  Kenya -0.34 2 1
78  Sri Lanka -0.36 1 9
79  Armenia -0.39 8 32
80  Uzbekistan -0.41 18 9
81  Namibia -0.43 3 15
82  Guatemala -0.45 9 11
83  Oman -0.48 14 17
84  Botswana -0.48 11 9
85  Mali -0.49 33 8
86  Uganda -0.50 2 5
87  Australia -0.53 3 5
88  Burkina Faso -0.55 12 28
89  Paraguay -0.55 2 1
90  Cambodia -0.56 1 12
91  Morocco -0.56 6 4
92  Jamaica -0.58 11 18
93  Kazakhstan -0.59 16 1
94  Zambia -0.62 15 12
95  Senegal -0.63 7 2
96  Laos -0.63 12 5
97  Ethiopia -0.66 19 7
98  Honduras -0.67 4 1
99  Pakistan -0.68 3 20
100  Kuwait -0.70 19 33
101  Iran -0.71 31 21
102  Togo -0.78 16 12
103  Ghana -0.80 4 2
104  Peru -0.81 12 20
105  Nicaragua -0.84 3 7
106  Turkmenistan -0.84 11 2
107  Monaco -0.88 13 11
108  Bangladesh -0.88 2 14
109  Zimbabwe -0.93 2 26
110  Ivory Coast -0.96 1 5
111  Myanmar -0.97 4 6
112  Ecuador -0.97 7 13
113  Madagascar -1.01 12 18
114  Mauritania -1.03 18 13
115  Bolivia -1.04 1 12
116  Tajikistan -1.09 4 3
117  Cuba -1.11 41 37
118  Malawi -1.12 15 6
119  Venezuela -1.14 2 1
120  Liberia -1.15 16 10
121  Mozambique -1.25 8 7
122  Algeria -1.31 7 2
123  Yemen -1.31 1 4
124  Azerbaijan -1.37 1 3
125  Republic of the Congo -1.42 3 3
126  Gabon -1.43 4
127  Guinea -1.43 4 2
128  Libya -1.46 5 1
129  Cameroon -1.60 19 20
130  Papua New Guinea -1.68 3 3
131  Angola -1.71 7
132  Democratic Republic of the Congo -1.80 6 9
133  Nigeria -1.90 2 3

See also

References
  1. "India tops list of fastest growing economies for coming decade: Harvard study". The Economic Times. 2020-05-04. Retrieved 2020-10-31.
  2. Cesar A. Hidalgo, Ricardo Hausmann (2009). "The Building Blocks of Economic Complexity". Proceedings of the National Academy of Sciences. PNAS. 106 (26): 10570–10575. arXiv:0909.3890. Bibcode:2009PNAS..10610570H. doi:10.1073/pnas.0900943106. PMC 2705545. PMID 19549871.
  3. Ricardo Hausmann, Cesar Hidalgo; et al. "The Atlas of Economic Complexity". Puritan Press, Cambridge MA. Archived from the original on 18 May 2012. Retrieved 26 April 2012.
  4. Dominik Hartmann, Miguel Guevara, Cristian Jara-Figueroa, Manuel Aristaran, Cesar Hidalgo (2018), "Linking Economic Complexity, Institutions, and Income Inequality", World Development, 93: 75–93, arXiv:1505.07907, doi:10.1016/j.worlddev.2016.12.020CS1 maint: multiple names: authors list (link)
  5. "Complexity rankingsThe Atlas of Economic Complexity". Harvard' Growth Lab Viz Hub. Retrieved 2020-10-31.
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