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.

Higher economic complexity as compared to country's income level drives economic development.

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.^[1]

Formulation

In its strict mathematical definition, the ECI is defined in terms of an eigenvalue 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 exports and their sophistication. For example, Japan or Germany, with high ECIs, export many goods that are less common and that are produced by highly diversified countries, indicating that these are diverse and sophisticated economies. Countries with low ECI, like Angola or Botswana, 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),^[2] 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.^[3]

Economic development requires the accumulation of productive knowledge and its use in both more and more complex industries. According to this metric, many low-income countries, including Bangladesh, Venezuela, and Angola have failed to diversify their knowhow and face low growth prospects while those like India, Turkey, and the Philippines have added productive capabilities to enter new sectors and are expected by some drive growth over the coming years.^[4]

The Economic Complexity Index was initially developed using trade data but its application has expanded to include other data sources, such as patents^[5] and scientific publications^[6], enabling a broader examination of economic and innovation ecosystems.

Country rankings 2021

Country Complexity Rankings ^[7]
Rank	Country	Index (2021)	5-year change	10-year change
1	Japan	2.06
2	Switzerland	1.94		1
3	Taiwan	1.93	4	9
4	South Korea	1.82	2	2
5	Germany	1.81		1
6	Singapore	1.74	2	1
7	Czechia	1.56	1	2
8	Sweden	1.54		3
9	Austria	1.50		5
10	United States	1.46	3	3
11	United Kingdom	1.43	1	1
12	Slovenia	1.42	2	1
13	Finland	1.42	2	5
14	Hungary	1.36	2	3
15	France	1.35		1
16	Slovakia	1.31	2	1
17	Ireland	1.29		7
18	Belgium	1.28		6
19	Italy	1.27
20	Israel	1.21	6	3
21	Hong Kong	1.16	1	1
22	Netherlands	1.09	2	9
23	Mexico	1.09		2
24	Malaysia	1.09	3	6
25	China	1.07		5
26	Romania	1.07	3	1
27	Denmark	1.02		5
28	Poland	1.01	2	4
29	Thailand	0.97	7	1
30	Lithuania	0.91	1	1
31	Saudi Arabia	0.90	5	10
32	Canada	0.90	4	7
33	Belarus	0.84	1	1
34	Croatia	0.81	3	6
35	Spain	0.78	3	10
36	Serbia	0.74	33	71
37	Philippines	0.72	4	1
38	Norway	0.69	1	2
39	Bosnia and Herzegovina	0.65	2
40	Bulgaria	0.63	2	2
41	India	0.61	1	5
42	Turkey	0.61	10	8
43	Portugal	0.56	8	8
44	Ukraine	0.49	1
45	Russia	0.46		2
46	New Zealand	0.46	2	8
47	Lebanon	0.35	4	10
48	Kuwait	0.34	10	37
49	Brazil	0.33	2	1
50	Greece	0.32	4	24
51	Panama	0.31	1	2
52	Costa Rica	0.24	11	11
53	Tunisia	0.22	2	7
54	North Macedonia	0.20	5	3
55	United Arab Emirates	0.16	2	3
56	Colombia	0.14	4	3
57	Uruguay	0.10	11	8
58	Vietnam	0.10	24	23
59	South Africa	0.10	11	8
60	Argentina	0.07	6	5
61	Indonesia	0.04	1	1
62	Jordan	0.03	18	6
63	Dominican Republic	−0.00	7	7
64	Georgia	−0.01	1	3
65	Moldova	−0.02	1	21
66	El Salvador	−0.04	1	4
67	Iran	−0.09	6	34
68	Egypt	−0.10	25	28
69	Kyrgyzstan	−0.12	3	3
70	Qatar	−0.17	4	6
71	Armenia	−0.19	18	13
72	Albania	−0.19		1
73	Oman	−0.20	14	14
74	Chile	−0.22	42	37
75	Jamaica	−0.23	14	36
76	Guatemala	−0.24	7
77	Kazakhstan	−0.28	2	1
78	Morocco	−0.28	1	9
79	Uzbekistan	−0.38	8	32
80	Paraguay	−0.38	18	9
81	Sri Lanka	−0.39	3	15
82	Australia	−0.41	9	11
83	Kenya	−0.46	14	17
84	Honduras	−0.50	11	9
85	Azerbaijan	−0.52	33	8
86	Turkmenistan	−0.55	2	5
87	Pakistan	−0.55	3	5
88	Senegal	−0.59	12	28
89	Benin	−0.61	2	1
90	Niger	−0.62	1	12
91	Peru	−0.63	6	4
92	Cambodia	−0.64	11	18
93	Botswana	−0.67	16	1
94	Tajikistan	−0.69	15	12
95	Laos	−0.70	7	2
96	Zambia	−0.74	12	5
97	Namibia	−0.77	19	7
98	Zimbabwe	−0.78	4	1
99	Ethiopia	−0.80	3	20
100	Togo	−0.81	19	33
101	Bangladesh	−0.85	31	21
102	Burma	−0.85	16	12
103	Algeria	−0.88	4	2
104	Ecuador	−0.89	12	20
105	Uganda	−0.92	3	7
106	Bolivia	−0.97	11	2
107	Republic of the Congo	−1.02	13	11
108	Nicaragua	−1.03	2	14
109	Madagascar	−1.07	2	26
110	Venezuela	−1.08	1	5
111	Tanzania	−1.09	4	6
112	Iraq	−1.12	7	13
113	Yemen	−1.15	12	18
114	Libya	−1.18	18	13
115	Cote d'Ivoire	−1.19	1	12
116	Afghanistan	−1.20	4	3
117	Mongolia	−1.23	41	37
118	Ghana	−1.27	15	6
119	Mauritania	−1.32	2	1
120	Sudan	−1.33	16	10
121	Cameroon	−1.36	8	7
122	Mozambique	−1.36	7	2
123	Gabon	−1.41	1	4
124	Angola	−1.37	1	3
125	Mali	−1.43	3	3
126	Nigeria	−1.53	4
127	Burkina Faso	−1.79	4	2
128	Democratic Republic of the Congo	−1.81	5	1
129	Papua New Guinea	−1.84	19	20
130	Guinea	−1.84	3	3
131	Chad	−1.93	7

References

^ Cesar A. Hidalgo, Ricardo Hausmann (2009). "The Building Blocks of Economic Complexity". Proceedings of the National Academy of Sciences. 106 (26). PNAS: 10570–10575. arXiv:0909.3890. Bibcode:2009PNAS..10610570H. doi:10.1073/pnas.0900943106. PMC 2705545. PMID 19549871.
^ 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.
^ 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.2016.12.020, S2CID 45386522{{citation}}: CS1 maint: multiple names: authors list (link)
^ "India tops list of fastest growing economies for coming decade: Harvard study". The Economic Times. 2020-05-04. Retrieved 2020-10-31.
^ Balland, Pierre-Alexandre; Rigby, David (January 2017). "The Geography of Complex Knowledge". Economic Geography. 93 (1): 1–23. doi:10.1080/00130095.2016.1205947. ISSN 0013-0095.
^ Balland, Pierre-Alexandre; Jara-Figueroa, Cristian; Petralia, Sergio G.; Steijn, Mathieu P. A.; Rigby, David L.; Hidalgo, César A. (March 2020). "Complex economic activities concentrate in large cities". Nature Human Behaviour. 4 (3): 248–254. doi:10.1038/s41562-019-0803-3. ISSN 2397-3374.
^ "Complexity rankings The Observatory of Economic Complexity". OEC. Retrieved 2023-05-02.

[1] Cesar A. Hidalgo, Ricardo Hausmann (2009). "The Building Blocks of Economic Complexity". Proceedings of the National Academy of Sciences. 106 (26). PNAS: 10570–10575. arXiv:0909.3890. Bibcode:2009PNAS..10610570H. doi:10.1073/pnas.0900943106. PMC 2705545. PMID 19549871.

[2] 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.

[3] 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.2016.12.020, S2CID 45386522{{citation}}: CS1 maint: multiple names: authors list (link)

[ET-4] "India tops list of fastest growing economies for coming decade: Harvard study". The Economic Times. 2020-05-04. Retrieved 2020-10-31.

[5] Balland, Pierre-Alexandre; Rigby, David (January 2017). "The Geography of Complex Knowledge". Economic Geography. 93 (1): 1–23. doi:10.1080/00130095.2016.1205947. ISSN 0013-0095.

[6] Balland, Pierre-Alexandre; Jara-Figueroa, Cristian; Petralia, Sergio G.; Steijn, Mathieu P. A.; Rigby, David L.; Hidalgo, César A. (March 2020). "Complex economic activities concentrate in large cities". Nature Human Behaviour. 4 (3): 248–254. doi:10.1038/s41562-019-0803-3. ISSN 2397-3374.

[ECIranks-7] "Complexity rankings The Observatory of Economic Complexity". OEC. Retrieved 2023-05-02.

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