National Wealth and High-Quality Research

In a response to my previous post “Geography of High-Quality Science” Rasmus Persson has raised an interesting question: to what extent does or does not national GDP correlate with the “research output”? Here I try to answer it and analyze trends.

To plot GDP values vs respective weighted fractional counts (WFCs) for each country covered by Nature Index, I have taken the same WFCs as in my previous post and GDP estimates derived from purchasing power parity (PPP) calculations as listed in the CIA World Factbook (in billions of international dollars, data retrieved from the Wikipedia article, the GDP for Vatican is derived from National Geographic page). Keep in mind that GDP values are different in different sources, but the general trends must be similar.

All these values together with countries ranking in GDP and WFC are given in the table below. I also list some countries from the CIA World Factbook that do not appear in Nature Index at all.

Country GDP WFC #GDP #WFC Δ#
 United States 16720.000 19473.09 1 1 0
 China 13390.000 5908.76 2 2 0
 India 4990.000 951.8 3 13 -10
 Japan 4729.000 3448.67 4 4 0
 Germany 3227.000 4116.16 5 3 2
 Russia 2553.000 378.72 6 19 -13
 Brazil 2416.000 239.07 7 23 -16
 United Kingdom 2387.000 3382.24 8 5 3
 France 2276.000 2270.55 9 6 3
 Mexico 1845.000 80.29 10 36 -26
 Italy 1805.000 1056.52 11 11 0
 South Korea 1666.000 1183.85 12 9 3
 Canada 1518.000 1600.64 13 7 6
 Spain 1389.000 1156.67 14 10 4
 Indonesia 1285.000 6.2 15 63 -48
 Turkey 1167.000 71.23 16 38 -22
 Australia 998.300 1004.63 17 12 5
 Iran 987.100 68.73 18 39 -21
 Saudi Arabia 927.800 72.75 19 37 -18
 Taiwan 926.400 522.81 20 17 3
 Poland 814.000 230.8 21 24 -3
 Argentina 771.000 103.94 22 30 -8
 Netherlands 699.700 754.76 23 14 9
 Thailand 673.000 25 24 42 -18
 South Africa 595.700 83.13 25 34 -9
 Pakistan 574.100 15.5 26 47 -21
 Egypt 551.400 14.08 27 51 -24
 Colombia 526.500 9.56 28 55 -27
 Malaysia 525.000 14.72 29 49 -20
 Nigeria 478.500 1.48 30 84 -54
 Philippines 454.300 2.65 31 77 -46
 Belgium 421.700 345.62 32 20 12
 Venezuela 407.400 2.24 33 79 -46
 Sweden 393.800 529.52 34 16 18
 Switzerland 371.200 1241.6 35 8 27
 Austria 361.000 324.51 36 21 15
 Vietnam 358.900 8.74 37 57 -20
 Peru 344.000 5.75 38 65 -27
 Singapore 339.000 539.81 39 15 24
 Ukraine 337.400 37.47 40 41 -1
 Chile 335.400 94.86 41 33 8
 Bangladesh 324.600 1.74 42 82 -40
 Romania 288.500 20.42 43 44 -1
 Czech Republic 285.600 121.44 44 29 15
 Algeria 284.700 4.77 45 67 -22
 Norway 282.200 146.73 46 26 20
 Israel 273.200 492.93 47 18 29
 United Arab Emirates 269.800 9.61 48 54 -6
 Greece 267.100 99.42 49 31 18
 Iraq 249.400 1.05 50 94 -44
 Kazakhstan 243.600 2.06 51 80 -29
 Portugal 243.300 131.33 52 27 25
 Denmark 211.300 323.5 53 22 31
 Qatar 198.700 5.92 54 64 -10
 Hungary 196.600 82.38 55 35 20
 Finland 195.500 200.17 56 25 31
 Ireland 190.400 125.31 57 28 29
 Morocco 180.000 2.99 58 74 -16
 Kuwait 165.800 3.08 59 71 -12
 Ecuador 157.600 3.06 60 72 -12
 Belarus 149.200 7.72 61 61 0
 New Zealand 134.200 98.85 62 32 30
 Slovakia 134.100 10.7 63 53 10
 Sri Lanka 128.400 1.07 65 93 -28
 Cuba 121.000 3.04 66 73 -7
 Uzbekistan 112.600 0.89 67 96 -29
 Syria 107.600 0.32 68 120 -52
 Tunisia 107.100 2.78 69 76 -7
 Bulgaria 105.500 7.4 70 62 8
 Ethiopia 105.000 0.81 71 98 -27
 Dominican Republic 100.400 0.13 72 136 -64
 Azerbaijan 98.360 1.11 73 91 -18
 Oman 91.540 2 74 81 -7
 Myanmar 90.930 0.46 75 111 -36
 Sudan 86.670 0.33 76 119 -43
 Ghana 83.740 0.43 77 112 -35
 Serbia 80.020 18.04 78 46 32
 Guatemala 79.970 0.06 79 142 -63
 Croatia 79.690 24.59 80 43 37
 Libya 78.630 0.26 81 126 -45
 Kenya 77.140 5.63 82 66 16
 Tanzania 75.070 1.41 83 88 -5
 Lithuania 66.080 14.22 84 50 34
 Lebanon 64.220 3.19 86 70 16
 Costa Rica 59.790 2.89 88 75 13
 Slovenia 58.910 41.99 89 40 49
 Panama 58.020 8.32 90 59 31
 Bolivia 56.140 1.1 91 92 -1
 Uruguay 54.670 8.03 92 60 32
 Cameroon 51.610 0.85 93 97 -4
 Uganda 51.270 1.73 94 83 11
 Luxembourg 42.920 8.72 98 58 40
 Nepal 41.220 1.47 100 86 14
 Cote d’Ivoire 39.600 0.13 102 135 -33
 Jordan 39.290 0.54 103 108 -5
 Latvia 37.880 2.45 105 78 27
 Cambodia 37.250 1.26 106 89 17
 Bosnia and Herzegovina 32.030 0.25 109 127 -18
 Botswana 31.060 0.34 110 116 -6
 Estonia 29.570 19.39 111 45 66
 Trinidad and Tobago 27.140 0.38 113 113 0
 Senegal 27.100 0.71 115 100 15
 Mozambique 26.690 0.11 117 139 -22
 Georgia 26.450 3.6 118 68 50
 Gabon 25.910 0.61 119 103 16
 Jamaica 25.620 0.26 120 125 -5
 Burkina Faso 24.690 0.6 121 104 17
 Zambia 24.360 0.12 122 137 -15
 Cyprus 24.000 11.02 123 52 71
 Macedonia 22.190 0.9 124 95 29
 Brunei 22.040 0.15 125 134 -9
 Madagascar 21.760 0.76 126 99 27
 Mauritius 20.530 0.3 128 123 5
 Armenia 19.970 9.49 129 56 73
 Papua New Guinea 19.410 1.24 132 90 42
 Congo, Republic of the 19.410 0.6 133 105 28
 Mali 18.280 0.19 134 131 3
 Tajikistan 18.040 0.03 135 144 -9
 Namibia 17.030 0.58 136 106 30
 Benin 15.840 0.35 137 115 22
 Mongolia 15.440 1.47 139 85 54
 Malawi 14.500 0.16 140 133 7
 Kyrgyzstan 13.500 0.33 142 118 24
 Niger 13.340 0.5 143 109 34
 Iceland 13.040 15.33 145 48 97
 Moldova 12.360 3.24 147 69 78
 Malta 11.450 1.42 148 87 61
 Sierra Leone 8.412 0.47 153 110 43
 West Bank 8.022 0.62 154 102 52
 Montenegro 7.461 0.24 156 128 28
 Zimbabwe 7.366 0.31 157 122 35
 Barbados 7.169 0.03 158 143 15
 Swaziland 6.345 0.2 161 129 32
 Monaco 5.748 0.11 164 138 26
 Bermuda 5.600 0.37 165 114 51
 Bhutan 5.036 0.56 168 107 61
 Fiji 4.373 0.29 171 124 47
 Gambia, The 3.459 0.31 175 121 54
 Liechtenstein 3.200 0.08 176 140 36
 Seychelles 2.355 0 185 145 40
 Cape Verde 2.214 0.33 188 117 71
 Greenland 2.133 0.66 189 101 88
 Tonga 0.801 0.17 205 132 73
 British Virgin Islands 0.500 0.06 212 141 71
 Vatican City State (Holy See) 0.020 0.2 225 130 95
Countries that do not appear in Nature Index
 Angola 130.400 64
 Puerto Rico 64.840 85
 Yemen 60.060 87
 Turkmenistan 49.750 95
 Macau 47.190 96
 El Salvador 47.090 97
 Paraguay 41.550 99
 North Korea 40.000 101
 Honduras 38.420 104
 Afghanistan 34.290 107
 Bahrain 33.630 108
 Congo, Democratic Republic of the 28.030 112
 Albania 27.110 114
 Nicaragua 27.010 116
 Chad 21.000 127
 Equatorial Guinea 19.600 130
 Laos 19.520 131
 Rwanda 15.740 138
 Kosovo 13.590 141
 Haiti 13.150 144
 Guinea 12.370 146
 Bahamas, The 11.240 149
 Timor-Leste 11.230 150
 South Sudan 10.620 151
 New Caledonia 9.280 152
 Mauritania 7.824 155
 Togo 7.024 159
 Suriname 6.874 160
 Guyana 6.256 162
 Somalia 5.896 163
 Burundi 5.578 166
 Jersey 5.100 167
 Guam 4.600 169
 Eritrea 4.468 170
 Lesotho 4.131 172
 Isle of Man 4.076 173
 Central African Republic 3.955 174
 Andorra 3.163 177
 Curaçao 3.128 178
 Maldives 3.106 179
 Belize 3.083 180
 Guernsey 2.742 181
 Liberia 2.719 182
 Aruba 2.516 183
 Djibouti 2.418 184
 Cayman Islands 2.250 186
 Saint Lucia 2.233 187
 Guinea-Bissau 1.963 190
 Solomon Islands 1.922 191
 Antigua and Barbuda 1.605 192
 Faroe Islands 1.471 194
 Grenada 1.467 195
 San Marino 1.371 196
 Saint Vincent and the Grenadines 1.312 197
 Gibraltar 1.275 198
 Vanuatu 1.251 199
 Samoa 1.146 200
 Dominica 1.018 201
 Saint Kitts and Nevis 0.946 202
 Western Sahara 0.906 203
 Comoros 0.887 204
 Sint Maarten 0.798 206
 Micronesia, Federated States of 0.766 207
 Northern Mariana Islands 0.733 208
 Kiribati 0.636 209
 Turks and Caicos Islands 0.632 210
 American Samoa 0.575 211
 Marshall Islands 0.481 213
 Sao Tome and Principe 0.408 214
 Palau 0.221 215
 Saint Pierre and Miquelon 0.215 216
 Cook Islands 0.183 217
 Anguilla 0.175 218
 Falkland Islands 0.165 219
 Nauru 0.060 220
 Wallis and Futuna 0.060 221
 Montserrat 0.044 222
 Tuvalu 0.037 223
 Saint Helena, Ascension and Tristan da Cunha 0.031 224
 Niue 0.010 226
 Tokelau 0.002 227

Those countries that do not appear in the Nature Index have very small economies (GDP below $130 billion dollars) and generally are so poor or war-torn that they cannot provide stable conditions for expensive high-quality research. Nevertheless, there are many countries with small economies that produce considerable amount of good publications, via providing stable conditions, financial support, collaborations with other countries and due to scientific tradition.

GDP (PPP) in billions of international dollars vs WFC

GDP (PPP) in billions of international dollars vs WFC

When GDP is plotted versus WFC, the correlation is far from being ideally linear (R2 = 0.81), but the general trend is observed: the bigger economy, the bigger research output. Those countries that are far below the trend line are likely to invest larger part of their GDP for the research & development to be more competitive in the future. For instance, the United States expenditure was 2.79% of GDP, while for instance China’s investment was 1.98% in 2012 (the World Bank data). Nevertheless, China has realized long ago the important of R&D and it drastically increased its expenditure for R&D by 0.22% of GDP only in two years (from 2010 to 2012).

More striking outliers are India and Switzerland. India has economy 13 times bigger than Swiss economy, it has very low expenditure for R&D (around 0.8%), not to mention the difference in population. Remarkably, Swiss WFC is larger than Indian (1241.6 vs 951.8). Thus Switzerland has very large positive difference between rankings in GDP and WFC (+27), while India—negative (−10).

Other important reason is that despite the big economy, GDP (PPP) per capita in India is pretty low: it is only Int$4000 in contrast to Int$54800 in Switzerland, and India is bound to improve in the first place well-being of citizens rather than investing more into R&D.

In order to look at this question more closely, GDP (PPP) per capita (retrieved from this Wikipedia article, the GDP per capita for Vatican is taken from National Geographic page) is plotted versus WFC per capita (WFCpm, see my previous post for definition). All data are given in the table below.

Country Population, millions* GDP per capita WFCpm
Category A
Luxembourg 0.550 77900 15.86
Bermuda 0.064 86000 5.76
Monaco 0.037 85500 2.98
Qatar 2.270 102100 2.61
Liechtenstein 0.037 89400 2.15
Category B
Vatican City State (Holy See) 0.001 25500 238.38
Switzerland 8.212 54800 151.20
Singapore 5.470 62400 98.69
United States of America (USA) 320.132 52800 60.83
Israel 8.282 36200 59.52
Denmark 5.656 37800 57.20
Sweden 9.738 40900 54.38
United Kingdom (UK) 64.106 37300 52.76
Germany 80.783 39500 50.95
Iceland 0.328 40700 46.71
Canada 35.676 43100 44.87
Netherlands 16.884 41400 44.70
Australia 23.701 43000 42.39
Austria 8.527 42600 38.06
Finland 5.472 35900 36.58
France 66.100 35700 34.35
Belgium 11.233 37800 30.77
Norway 5.156 55400 28.46
Ireland 4.610 41300 27.18
Japan 127.070 37100 27.14
Spain 46.508 30100 24.87
South Korea 50.424 33200 23.48
Taiwan 23.425 39600 22.32
New Zealand 4.553 30400 21.71
Slovenia 2.065 27400 20.33
Italy 60.782 29600 17.38
Estonia 1.316 22400 14.74
Cyprus 0.858 24500 12.84
Portugal 10.478 22900 12.53
Greenland 0.056 38400 11.72
Czech Republic 10.522 27200 11.54
Greece 10.993 23600 9.04
Poland 38.496 21100 6.00
Lithuania 2.923 22600 4.86
Malta 0.416 27500 3.41
Saudi Arabia 31.521 31300 2.31
Virgin Islands (British) 0.028 42300 2.14
Slovakia 5.416 24700 1.98
United Arab Emirates 9.577 29900 1.00
Kuwait 3.268 42100 0.94
Oman 4.088 29800 0.49
Brunei 0.393 54800 0.38
Trinidad and Tobago 1.328 20300 0.29
Barbados 0.285 25100 0.11
Seychelles 0.090 25900 0.00
Category C
Hungary 9.879 19800 8.34
Croatia 4.268 17800 5.76
Chile 18.006 19100 5.27
China 1367.510 9800 4.32
Armenia 3.014 6300 3.15
Russia 146.300 18100 2.59
Serbia 7.147 11100 2.52
Argentina 43.132 18600 2.41
Uruguay 3.404 16600 2.36
Panama 3.713 16500 2.24
Tonga 0.103 8200 1.65
South Africa 54.002 11500 1.54
Latvia 1.990 19100 1.23
Brazil 203.692 12100 1.17
Romania 19.943 13200 1.02
Bulgaria 7.246 14400 1.02
Turkey 76.668 15300 0.93
Moldova 3.558 3600 0.91
Iran 78.020 12800 0.88
Ukraine 42.965 7400 0.87
Belarus 9.475 16100 0.81
Georgia 4.491 6100 0.80
Lebanon 4.104 15800 0.78
India 1264.990 4000 0.75
Bhutan 0.756 7000 0.74
Mexico 121.006 15600 0.66
Cape Verde 0.518 4400 0.64
Costa Rica 4.773 12900 0.61
Mongolia 3.000 5900 0.49
Malaysia 30.453 17500 0.48
Macedonia 2.066 10800 0.44
Montenegro 0.620 11900 0.39
Thailand 64.871 9900 0.39
Gabon 1.751 19200 0.35
Fiji 0.859 4900 0.34
Namibia 2.113 8200 0.27
Cuba 11.210 10200 0.27
Tunisia 10.983 9900 0.25
Mauritius 1.261 16100 0.24
Colombia 47.940 11100 0.20
Ecuador 15.904 10600 0.19
Peru 31.152 11100 0.18
Swaziland 1.106 5700 0.18
Botswana 2.025 16400 0.17
Papua New Guinea 7.399 2900 0.17
Gambia 1.882 2000 0.16
Egypt 87.792 6600 0.16
Palestine 4.550 2900 0.14
Congo 4.671 4800 0.13
Algeria 39.500 7500 0.12
Kenya 46.749 1800 0.12
Kazakhstan 17.397 14100 0.12
Azerbaijan 9.553 10800 0.12
Bolivia 11.411 5500 0.10
Vietnam 90.730 4000 0.10
Jamaica 2.718 9000 0.10
Morocco 33.486 5500 0.09
Pakistan 188.611 3100 0.08
Cambodia 15.405 2600 0.08
Jordan 6.675 6100 0.08
Sierra Leone 6.319 1400 0.07
Venezuela 30.620 13600 0.07
Bosnia and Herzegovina 3.792 8300 0.07
Kyrgyzstan 5.777 2500 0.06
Senegal 13.509 2100 0.05
Sri Lanka 20.359 6500 0.05
Nepal 28.038 1300 0.05
Uganda 34.857 1400 0.05
Cameroon 20.387 2400 0.04
Libya 6.317 11300 0.04
Madagascar 21.842 1000 0.03
Burkina Faso 17.323 1500 0.03
Benin 10.315 1600 0.03
Tanzania 47.422 1700 0.03
Uzbekistan 30.493 3800 0.03
Iraq 36.005 7100 0.03
Philippines 100.806 4700 0.03
Niger 19.268 800 0.03
Indonesia 255.462 5200 0.02
Zimbabwe 13.061 600 0.02
Ghana 27.043 3500 0.02
Syria 22.265 5100 0.01
Dominican Republic 10.378 9700 0.01
Mali 16.259 1100 0.01
Bangladesh 157.609 2100 0.01
Malawi 16.310 900 0.01
Ethiopia 90.076 1200 0.01
Myanmar 51.419 1700 0.01
Sudan 38.435 2600 0.01
Nigeria 183.523 2800 0.01
Zambia 15.474 1800 0.01
Ivory Coast 23.821 1800 0.01
Mozambique 25.728 1200 0.00
Guatemala 15.807 5300 0.00
Tajikistan 8.161 2300 0.00
GDP (PPP) in international dollars per capita per year vs WFCpm

GDP (PPP) in international dollars per capita per year vs WFCpm

In the scatter plot of GDP per capita vs WFCpm no such clear trend is observed as in the plot of GDP vs WFC. This is due to the fact that countries total research output depend directly on the expenditure from the total GDP, while wellness of country’s citizens do not directly affects research output “per capita”.

Nevertheless, it is obvious from the plot that countries, where standard of living is relatively low, the majority of population also lacks means and motivation to take part in the research in this country. This boundary somewhat arbitrary may be drawn near $20000 per capita per year. Countries with GDP per capita below this line fall into Category C. These countries have WFCpm below 9.

It does not mean that those countries have low total GDP or low total WFC. For instance China is the second in the world in both total GDP and WFC. On the other hand, Russia that also falls in Category C is sixth in the world by GDP, but 19th by WFC. This is due to the fact that Russia is rich in natural resources, but it fails to use this advantage to invest more money in R&D (1.12% of GDP in 2012) and to improve the standard of living of its own citizens. Such countries often depend only on something that nature provides, but have not really sustainable economies.

Another extreme is very rich countries with GDP per capita over $70000 (Category A). There only five such countries with very small population. These countries have generally their incomes from sources other than R&D: for instance Qatar has huge oil and gas reserves, Monaco is tax haven. Thus, they have quite small WFCpm below 5, with a remarkable exception of Luxembourg that has also developed R&D and WFC over 15.

The backbone of the world’s R&D is mostly formed by the countries from the Category B that have reasonably high standard of living (GDP per capita $20000–70000) and thus have capacities to invest in R&D without sacrificing wellness of their citizens. Here the extremely large range of WFCpm is observed: from 238 in Vatican (see my previous post about that phenomenon) and to 0 in Seychelles for comparable GDP per capita around $25000.

One may argue that high standard of living in countries with relatively large population and low WFC values depend on the natural resources rather than on their technology advances and if they do not start to invest in R&D their standard of living will deteriorate as the natural resources deplete. Understanding of this issue plausibly was among the reasons for Saudi Arabia to use their natural resources for building amazing KAUST.

On the other hand, those that invest in R&D and have high WFC ensure their high standard of living by technology advances and depend less on their own deposits of natural resources. Examples are Japan and South Korea.

In summary, development of national R&D and economy is interdependent. The bigger economy has more capacity for supporting expensive research, but advantages in science and technologies also improve economy. Poorer, less technologically developed countries are in vicious circle: they are too poor to really increase their expenditures for science, but their technological development is too low to increase their competitiveness in the world market. These countries require measures similar to those done during the rise of the Asian Tigers or need a help from other countries through programs similar to Marshall Plan.

Note

As Nature Index is published for the rolling 12-month window under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0), this analysis can be used under the same conditions.

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2 comments on “National Wealth and High-Quality Research
  1. Rasmus Persson says:

    Seeing as this post was made in response to a comment by me, I think I should contribute with my view of things :). First, I obviously do not think that there is not a positive correlation between GDP and research output. Obviously, research costs money and so a short supply of it means that there cannot be as much research done. I am interested in to what extent does new research (especially the kind of research indexed by the Nature index) contribute to a countries economic development? Let’s look at your last graph, for instance, where you have plotted the GDP per head vs the WFCpm. Assuming for the sake of argument that the GDP per head is at least partly the effect *caused* by the WFCpm (i. e. “Nature Index” research breeds economic development), I discern a clear maximum at around 100 WFCpm. An indication, to me, that more research is not always necessarily better. There is an optimum level. In the same vein, looking at your first graph, I would say that China and India are the big “winners” (they lie far above the trend line), in that they get a higher GDP out of less research, whereas America is a loser (it lies below the trend line): Americans do not get as large a return on investment on their research in terms of GDP.

    • Pavlo Dral says:

      I think it is not enough to be just satisfied with current GDP vs WFC ratio, as the US may have at the moment less return from investment in R&D, but it will pay off in the future. When you just have a “perfect” balance for the moment, “competitor” countries may over-invest in their R&D at the moment and get less GDP and GDP per capita, but this competitor is likely to have later larger market than you and even take part of your market. That’s why China increase its research funding much faster than many other countries. Some countries may over-invest in R&D, but it is still better investment than disproportionally high investment in military, for instance. Anyway, as we have seen from the post, GDP depend not just from R&D and many other factors play important role, so it is speculative to say that China gets more from less. I agree with you that it is likely that after some WFCpm value, the standard of living does not really improve. One must also keep in mind that the current GDP is a result of *past* and not current R&D achievements and WFC, so GDP is kind of delayed. Thus more important analyzes would be compare dynamics of GDP vs WFC over years and see how they correlate over time.

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