Human Capital Index
The Human Capital Index (HCI) is an annual measurement prepared by the World Bank.[1] HCI measures which countries are best in mobilizing their human capital, the economic and professional potential of their citizens. The index measures how much capital each country loses through lack of education and health. The index ranges between 0 and 1, with 1 meaning maximum potential is reached.[2] HCI is used in country studies of employment and wages, for example in Ukraine after Russia's invasion.[3]
Methodology
[edit]The applications to measuring human capital were developed in research by Noam Angrist, Simeon Djankov, Pinelopi Koujianou Goldberg, and Harry Patrinos in the scientific journal Nature.[4][5] These findings were popularized in a 2021 article.[6] HCI is grounded on the following three pillars:[7]
Survival
- Percentage of children surviving past the age of 5
School
- Quantity of education (Expected years of schooling by age 18)
- Quality of education (Harmonized test scores)
Health
- Adult survival rates (Percentage of 15-year-olds who survive until age 60)
- Healthy growth among children (Stunting rates of children under 5)
History
[edit]The Human Capital Index was first published as part of the World Bank's World Development Report 2019, directed by Simeon Djankov and World Bank chief economist Federica Saliola (https://live.worldbank.org/en/experts/f/federica-saliola
). Nobel Prize winner Paul Romer started the measurement.
List of countries by HCI
[edit]Rank | Country / Region | Score (% of potential reached) |
---|---|---|
1 | Singapore | 0.88 |
2 | Hong Kong | 0.81 |
3 | Japan | 0.80 |
4 | South Korea | 0.80 |
5 | Canada | 0.80 |
6 | Finland | 0.80 |
7 | Macao | 0.80 |
8 | Sweden | 0.80 |
9 | Ireland | 0.79 |
10 | Netherlands | 0.79 |
11 | United Kingdom | 0.78 |
12 | Estonia | 0.78 |
13 | New Zealand | 0.78 |
14 | Slovenia | 0.77 |
15 | Norway | 0.77 |
16 | Australia | 0.77 |
17 | Portugal | 0.77 |
18 | France | 0.76 |
19 | Belgium | 0.76 |
20 | Switzerland | 0.76 |
21 | Cyprus | 0.76 |
22 | Denmark | 0.76 |
23 | Poland | 0.75 |
24 | Czech Republic | 0.75 |
25 | Germany | 0.75 |
26 | Austria | 0.75 |
27 | Iceland | 0.75 |
28 | Israel | 0.73 |
29 | Spain | 0.73 |
30 | Italy | 0.73 |
31 | Croatia | 0.71 |
32 | Malta | 0.71 |
33 | Latvia | 0.71 |
34 | Lithuania | 0.71 |
35 | United States | 0.70 |
36 | Belarus | 0.70 |
37 | Greece | 0.69 |
38 | Vietnam | 0.69 |
39 | Luxembourg | 0.69 |
40 | Hungary | 0.68 |
41 | Russia | 0.68 |
42 | Serbia | 0.68 |
43 | United Arab Emirates | 0.67 |
44 | Slovakia | 0.66 |
45 | China | 0.65 |
46 | Bahrain | 0.65 |
47 | Chile | 0.65 |
48 | Turkey | 0.65 |
49 | Qatar | 0.64 |
50 | Albania | 0.63 |
51 | Montenegro | 0.63 |
52 | Seychelles | 0.63 |
53 | Ukraine | 0.63 |
54 | Costa Rica | 0.63 |
55 | Kazakhstan | 0.63 |
56 | Brunei | 0.63 |
57 | Uzbekistan | 0.63 |
58 | Mauritius | 0.62 |
59 | Mongolia | 0.61 |
60 | Bulgaria | 0.61 |
61 | Mexico | 0.61 |
62 | Malaysia | 0.61 |
63 | Thailand | 0.61 |
64 | Oman | 0.61 |
65 | Peru | 0.61 |
66 | Colombia | 0.61 |
67 | Trinidad and Tobago | 0.60 |
68 | Saint Lucia | 0.60 |
69 | Argentina | 0.60 |
70 | Uruguay | 0.60 |
71 | Sri Lanka | 0.60 |
72 | Kyrgyzstan | 0.60 |
73 | Antigua and Barbuda | 0.60 |
74 | Ecuador | 0.59 |
75 | Iran | 0.59 |
76 | Palau | 0.59 |
77 | Saint Kitts and Nevis | 0.59 |
78 | Romania | 0.58 |
79 | Moldova | 0.58 |
80 | Palestine | 0.58 |
81 | Bosnia and Herzegovina | 0.58 |
82 | Armenia | 0.58 |
83 | Azerbaijan | 0.58 |
84 | Saudi Arabia | 0.58 |
85 | Georgia | 0.57 |
86 | Kosovo | 0.57 |
87 | Grenada | 0.57 |
88 | Kuwait | 0.56 |
89 | North Macedonia | 0.56 |
90 | Jordan | 0.55 |
91 | Brazil | 0.55 |
92 | Samoa | 0.55 |
93 | Kenya | 0.55 |
94 | El Salvador | 0.55 |
95 | Dominica | 0.54 |
96 | Indonesia | 0.54 |
97 | Jamaica | 0.53 |
98 | Algeria | 0.53 |
99 | Saint Vincent and the Grenadines | 0.53 |
100 | Tonga | 0.53 |
101 | Paraguay | 0.53 |
102 | Tunisia | 0.52 |
103 | Philippines | 0.52 |
104 | Lebanon | 0.52 |
105 | Fiji | 0.51 |
106 | Nauru | 0.51 |
107 | Nicaragua | 0.51 |
108 | Federated States of Micronesia | 0.51 |
109 | Nepal | 0.50 |
110 | Morocco | 0.50 |
111 | Tajikistan | 0.50 |
112 | Dominican Republic | 0.50 |
113 | Panama | 0.50 |
114 | Guyana | 0.50 |
115 | Egypt | 0.49 |
116 | India | 0.49 |
117 | Kiribati | 0.49 |
118 | Cambodia | 0.49 |
119 | Honduras | 0.48 |
120 | Myanmar | 0.48 |
121 | Bhutan | 0.48 |
122 | Zimbabwe | 0.47 |
123 | Bangladesh | 0.46 |
124 | Guatemala | 0.46 |
125 | Gabon | 0.46 |
126 | Laos | 0.46 |
127 | Vanuatu | 0.45 |
128 | Timor-Leste | 0.45 |
129 | Ghana | 0.45 |
130 | Tuvalu | 0.45 |
131 | Haiti | 0.45 |
132 | Namibia | 0.45 |
133 | Togo | 0.43 |
134 | Papua New Guinea | 0.43 |
135 | South Africa | 0.43 |
136 | Marshall Islands | 0.42 |
137 | Gambia | 0.42 |
138 | Senegal | 0.42 |
139 | Solomon Islands | 0.42 |
140 | Republic of the Congo | 0.42 |
141 | Botswana | 0.41 |
142 | Malawi | 0.41 |
143 | Iraq | 0.41 |
144 | Pakistan | 0.41 |
145 | Comoros | 0.40 |
146 | Lesotho | 0.40 |
147 | Benin | 0.40 |
148 | Afghanistan | 0.40 |
149 | Cameroon | 0.40 |
150 | Zambia | 0.40 |
151 | Madagascar | 0.39 |
152 | Tanzania | 0.39 |
153 | Burundi | 0.39 |
154 | Uganda | 0.38 |
155 | Burkina Faso | 0.38 |
156 | Ethiopia | 0.38 |
157 | Mauritania | 0.38 |
158 | Ivory Coast | 0.38 |
159 | Rwanda | 0.38 |
160 | Sudan | 0.38 |
161 | Yemen | 0.37 |
162 | Eswatini | 0.37 |
163 | Guinea | 0.37 |
164 | Democratic Republic of the Congo | 0.37 |
165 | Sierra Leone | 0.36 |
166 | Angola | 0.36 |
167 | Mozambique | 0.36 |
168 | Nigeria | 0.36 |
169 | Liberia | 0.32 |
170 | Mali | 0.32 |
171 | South Sudan | 0.31 |
172 | Chad | 0.30 |
173 | Niger | 0.29 |
See also
[edit]- Human capital
- World Development Report
- HCI Singapore https://databankfiles.worldbank.org/public/ddpext_download/hci/HCI_2pager_SGP.pdf
References
[edit]- ^ Gatti, Roberta (2022-10-15). "Human Capital Project". World Bank.
- ^ Edwards, Sophie (2019-04-01). "Q&A: World Bank human capital index gathers momentum". Devex.
- ^ Blinov, Oleksiy; Djankov, Simeon (2022-11-17). "Ukraine's wages and job loss trends during the war". CEPR.
- ^ Angrist, Noam (2021-03-10). "Measuring human capital using global learning data". Nature. 592 (7854). Nature: 403–408. doi:10.1038/s41586-021-03323-7. PMC 8046667. PMID 33692542.
- ^ Angrist, Noam; Djankov, Simeon; Goldberg, Pinelopi K.; Patrinos, Harry A. (2019). "Measuring Human Capital". World Bank. doi:10.1596/1813-9450-8742.
- ^ Angrist, Noam; Djankov, Simeon; Goldberg, Pinelopi; Patrinos, Harry (2021-04-09). "Measuring human capital: Learning matters more than schooling". CEPR.
- ^ Kraay, Aart (2018-09-25). Methodology for a World Bank Human Capital Index. Policy Research Working Papers. The World Bank. doi:10.1596/1813-9450-8593. hdl:10986/30466. S2CID 170011611.
- ^ "Human Capital". World Bank. Retrieved 2021-04-20.