Introduction

What is the biggest predictor of a country’s scientific output, industrial capacity and military prowess? It is not geographic size. For instance, Kazakhstan and Mongolia are huge compared to Israel and Switzerland, yet Israel and Switzerland far outdistance them in all measures of intellectual, technological and military attainment.

It is not population. India’s 1.28 billion people are close in number to China’s 1.4 billion. And India has been a West-connected capitalist country since its independence in 1947, while China only started in the 1980’s. Yet China far outstrips India in all measures of technological and military power.

It is not natural resources. Russia has vastly more natural resources than Germany. Yet Germany’s economy is many times that of Russia, and its scientific output is double that of Russia, even though Russia’s population is close to double that of Germany.

The most important predictor of a country’s power and accomplishment is the nature of its population. A country’s most precious natural resource is its citizens. It is the genetic makeup of a population, enabled by supportive cultures, institutions and infrastructure, that predicts the country’s military-industrial power and capacity for innovation.

The book IQ and the Wealth of Nations by the professors Richard Lynn and Tatu Vanhanen makes a powerful argument for the importance of IQ in predicting a country’s power and prosperity, with IQ being a highly heritable (genetically-mediated) trait. While some of the data they use is not reliable, the general force of their argument is undeniable. The data used by Adam Smith and Charles Darwin were none too reliable either, but that didn’t stop their theories from being world-class accomplishments.

IQ is not everything. Japan’s IQ is in the same league as Germany and Sweden. Yet Swedes produce four times more science per citizen than the Japanese (measured in scientific papers published in peer-reviewed journals). Germans produce double the amount of science per citizen than the Japanese. An argument can be made that Japan’s infrastructure has yet to catch up with that of Western Europe. But Japan has had more than enough time (seven decades, in fact) to catch up. And a look at Japan’s infrastructure shows that they might even be ahead of Western Europe when it comes to infrastructure.

The factors that lead to Japan’s low accomplishment relative to Western Europe could be other genetic factors not widely studied. One factor could be Japan’s low testosterone levels compared to Europe, with testosterone being a significant contributor toward the drive for accomplishment¹. Another factor could be aging. An aging population is going to be less productive than a younger one. Another factor could be non-genetic; for example cultural practices and ideals, although these factors are not independent of genetics and should be considered together with genetics².

The Human Genetic-Cultural Quality Index

The HQI, short for the Human Genetic-Cultural Quality Index, takes account of both genetic and cultural factors to accurately predict a country’s real scientific, economic and military potential. It is a measure of the quality of human capital, a nation’s most important natural resource, and provides a single number that can be used to compare the quality of the human capital of different nations.

The math of the HQI will be explained below. For now, I will offer certain examples from it to illustrate the concept. Ukraine has an HQI of 129, while Russia’s HQI is 311. This means that a Russian citizen adds 2.6 times more value to Russia’s economy and scientific output than a Ukrainian citizen adds to Ukraine’s economy and scientific output. The quality of Russia’s human capital is 2.4 times that of Ukraine’s human capital. Even if Russia and Ukraine had exactly the same population (let’s say each had a population of 150 million), Russia would still be 2.4 times as powerful as Ukraine. Today, Russia’s population is 3.15 times as large as Ukraine’s (143.5 million vs. 45.49 million). Multiplying this by the 2.4 times HQI advantage, we arrive at a factor of 7.59. Russia is, or will be, 7.59 times as powerful as Ukraine when both countries reach their near-full development potential, perhaps in the next 30 years.

China’s HQI is 855. India’s is 162. Even if both countries had the same population, China would still be 5.2 times as powerful as India once both countries reach their near-full development potential.

The HQI uses two data points as predicting variables:

1. Scientific papers per capita, which refers to the number of scientific papers published in a year by the nation, divided by its population. This measures the intellectual capacity of the nation’s population.
2. Real economic growth rate. When a nation’s economy is growing fast (such as that of China), it shows that the nation’s institutions and infrastructure haven’t reached their full potential. The economic growth rate is used to correct for this fact. For instance, China’s papers per capita is only three times that of India’s. But China’s real 12-year average annual economic growth rate is 10.5%, while India’s is 7%. This means that the economic and scientific potential of China’s human capital has significantly more room to grow than India’s, as will be further illustrated down below.

The (real) economic growth rate of a nation expresses elasticity of human potential for a given nation. If growth is faster, improvements in infrastructure and institutions lead to big gains in the human potential of the nation, i.e. that the human potential of the nation is being held back by infrastructure and institutions, and that as these improve, so will the output of the nation’s human capital.

A slow economic growth rate indicates one of two things:

1. The nation has reached close to its full potential, so that its human capital is already working at its full capacity. This is the case with slow-growing developed nations like Japan and the Netherlands.
2. The quality of the nation’s human capital is so low that while theoretically there is much room for growth given the nation’s circumstances, that growth is being held back by human capital that’s not capable of achieving it. This is true in the case of various African and Latin American countries that have everything they could possibly need for growth, except a population that’s actually capable of said growth.

The history of colonization shows the importance of the genetic and cultural factors that go into the HQI. Any nation that becomes colonized by a high HQI population will quickly grow to reflect the home population’s intellectual prowess rather than the native population’s destitution. This has been true in the United States, Australia, Argentina, New Zealand and South Africa.

The most recent example comes from Israel. When Israel was colonized by Ashkenazi Jews that had been selected for high IQ in Europe during their 2000 year stay there³, Israel’s economy quickly grew to reflect a developed European nation, rather than a typical Middle Eastern one. It grew even above Eastern European nations, though it doesn’t seem likely it can surpass Germanic nations, as it has already had all the time and help it needs to achieve this.

The Mathematical Model

For any given nation and year, this is how the HQI basis number is calculated:
With a being the number of peer-reviewed scientific journal articles published in the year, b being the 12-year min-max average of economic growth⁴ for that year and the preceding 11 years, and c being the population of the nation in that year.

China published 416,409 peer-reviewed scientific journal papers in 2015. Its annual economic growth rate was 10.545 for the period 2004-2015 inclusive. And its population in 2015 was 1,401,586,609 (1.4 billion). The equation to calculate the HQI basis number thus becomes:

This results in a number of 0.001162729158. Since this is not a user-friendly number, the numbers for all nations are all multiplied by the arbitrary value of 735853.761, which gives an HQI of 1 to the lowest HQI country. This provides an easy-to-follow ground to which other countries can be compared. China’s HQI thus becomes 855.59. This means that a Chinese citizen adds a value to China’s economy that is 855.59 times greater than the value added by a citizen of the lowest HQI country to their respective economy (which happens to be the Democratic Republic of the Congo).

Raising the number of a country’s scientific papers to a power of (1 + its economic growth rate) is a mathematical trick that models both of these scenarios:

1. Scientific output growth that continues at the rate of the country’s past 12-year economic growth rate for the next 11 years.
2. Scientific output growth that starts off at the country’s average past 12-year economic growth, and then slows down by 6.95% every year over the next 30 years.

The assumption here is that a country’s scientific output will continue growing at the rate of the country’s economic growth over its past 12 years. This may seem a strange assumption, since a country’s future growth cannot be assumed to follow at the same rate as its past growth.

In fact, the correct assumption is that its economic growth will be quite lower. But what we are modeling here is not economic growth, it is growth in scientific output, whose future growth follows along the lines of a country’s past economic growth.

An example will make this clear. South Korea’s GDP grew from $771 billion USD in 2004 to $1.14 trillion in 2015 (all in 2000 dollars), a growth of about 48%. During the same period, its scientific output rose from 31182 papers in 2004 to 69469 papers in 2015, a growth of 122%, more than double its economic growth.

The growth in South Korea’s scientific output from 2004 to 2015 is actually similar to its GDP growth from 1989 to 2003 ($332 billion to $735 billion, a growth of 122%).

In short, scientific output is a lagging indicator of a country’s development, due to the amount of past investment necessary for its growth. No matter how much a country invests into increasing its scientific output, the tangible fruits of said investment will be over a decade in the future. The exception being countries like Saudi Arabia who rapidly increased their scientific output by importing foreign scientists.

India’s scientific output grew from 33031 papers in 2004 to 113144 papers in 2015, a growth of 242%. During the same period, its inflation-adjusted GDP grew from $0.971 trillion to $2.03 trillion, a growth of 109%. The growth in its scientific output was more than double the growth in its economic output.

Its growth, in fact, was similar to its GDP growth from 1981 to 2003. The reason for its slow economic growth over this period may have been its low-effectiveness gene-culture (low IQ, etc.), and its low urbanization rate accompanied by its vast size, that meant it took far longer than South Korea to build the infrastructure and institutions necessary to support effective scientific research.

This phenomenon of scientific growth growing far faster than economic growth can be seen throughout the world. Needless to say, a more rigorous study of the relationship between scientific output and past economic growth can be done. But we can take it as a general rule that past economic growth predicts future scientific output growth.

China’s Coming Supremacy

Raising China’s 2015 scientific paper count of 416409 to a power of 1.105 (1 + its annual economic output growth over 2004-2015) results in 1620204, or 1.62 million. What this means is that once China reaches close to its full economic potential (perhaps after 2030), it will be producing about 1.62 million scientific papers every year. Compare this to the 567000 scientific papers published by the United States in 2015, which, according to the same HQI calculation, will grow to 606000 during the same period. In other words, in the next 20 or more years, China’s scientific output will be 2.67 times as large as that of the United States.

While this may sound controversial to someone who has been wooed by the nascent racism of neocons, globalists and central bank usurer economists in their propagandizing the idea that the US can somehow maintain a permanent technological edge over China, that despite China’s enormous growth and a scientific output that is closely approaching that of the United States, that there is something wrong with the Chinese that will forever keep them as second-class citizens on the world stage, to someone who understands the history of Japan and South Korea’s growth, and who understands the realities of the gene-culture, this conclusion of China’s approaching supremacy is merely stating the obvious.

Using the HQI for Comparative Study of Gene-Cultures and National Potentials

Below is a list of the world’s highest HQI nations (the full list is at the end), for the reader’s viewing pleasure, and to help you follow along the rest of the essay.

Rank	Country	2015 Citable Scientific Documents	2015 Population	Average Real Annual Economic Growth (2004-2015) [12-Year Min-Max Method]	HQI	Predicted Scientific Output at Near-Full Potential (2035 and After)
1	Singapore	17,976	5,618,866	7.32	4823	36,824
2	Switzerland	39,358	8,238,610	1.01	3910	43,774
3	Australia	82,567	23,923,101	2.99	3561	115,764
4	Iceland	1,365	336,728	2.41	3549	1,624
5	Norway	18,228	5,142,842	1.17	2925	20,445
6	Qatar	2,766	2,350,549	14.88	2815	8,991
7	Denmark	23,081	5,661,723	-0.65	2812	21,633
8	Sweden	35,039	9,693,883	0.41	2775	36,556
9	Monaco	129	38,320	1.64	2683	140
10	Luxembourg	1,692	543,261	1.51	2564	1,893
11	Israel	18,040	7,919,528	3.71	2410	25,938
12	New Zealand	13,052	4,596,396	1.25	2352	14,693
13	Netherlands	51,434	16,844,195	-0.03	2238	51,239

While the Qatari population have a higher IQ, and are more liberal, than most other Arab populations (perhaps with the exception of Lebanese Christians), their high HQI is strongly a result of their importation of foreign scientists on the one hand, and their fast growing oil revenue on the other, the latter funding the former.

Germanic nations have the highest HQI in the world. Switzerland and Iceland, with their relatively low immigration rates, show the high productivity of Germanic genes and cultures. Australia, Denmark, Norway, Sweden, New Zealand and the Netherlands, with their Germanic roots, follow along the same lines.

The table shows how the HQI can be used to compare the genetic-cultural quality of any two countries. Iceland’s HQI of 3548, divided by the 2238 HQI of the Netherlands, results in a 58% advantage for the Icelandic people. Icelandic people are 58% more capable and productive than Netherlanders, and if the two countries had the same population, Iceland would be 58% more powerful militarily, technologically and economically.

Israel’s high HQI is influenced by its high economic growth, a large portion of which comes from its cozy relationship with the United States (US intelligence agencies, for example, are reliant on many Israeli technology companies). It’s highly unlikely that its population is more capable than that of the Netherlands or New Zealand. This shows that the HQI is not immune to aberrations, similar to all other methods, as reality is full of aberrations caused by disasters, sanctions, wars and political changes.

But regarding Israel, the HQI shows one very important result: Israel is already close to its full scientific potential. Over the next 30 years or so, its scientific output can grow from 18040 papers to 21631. No great improvement can be expected from Israel, and given its precarious political situation, even this much growth may not be possible, though stranger things have happened.

Changes in HQI Reflect Fundamental Genetic-Cultural Changes in a Nation

Far more interesting than a country’s economic growth is HQI growth. The HQI itself is a measure of growth potential, HQI growth means growth in the growth potential. When a nation climbs toward a peak in achievement, economic growth refers to this climb. HQI growth refers to an increase in the height of the peak, a removal of constraints that prevent a nation from reaching the heights reached by other nations.

China’s 2015 HQI was 6.4% lower than its 2010 HQI. This means that between 2010 and 2015, there were some forces in effect that reduced China’s genetic-cultural fitness, or economic fitness, so that while it continued to grow fast, its predicted near-full potential decreased. This was mostly caused by a large drop in the number of scientific papers published by China in 2015. I have contacted SCImago to find out whether this change was due to changes in their paper counting methodologies or whether it was due to a real drop in China’s output. If it was a real drop, maybe it was due to China’s best and brightest aging and retiring, or due to growing practice of usury creating a Western European-style of stagnation faster than expected, or due to some unknown dysgenic effect.

From 2010 to 2015, Ethiopia’s HQI increased by 173%. This is a very, very good sign. It means that there are genetic-cultural changes that are improving the nation’s future potential, or that there are bottlenecks that are being overcome. Not only is the nation climbing toward the peak, the peak itself is growing. Perhaps it is due to improvements in nutrition and health care, or beneficial cultural changes, or both. The actual beneficial change is probably smaller.

Poland has been Europe’s favorite backwater since at least Adam Smith’s time. What does the HQI tell us about what is going on in there? From 2010 to 2015, Poland’s HQI increased by 21.9%. There are forces at work in Poland that are increasing its population’s genetic-cultural fitness, so that whatever we believed Poland’s maximum growth potential to have been in 2010, in 2015 that maximum growth potential was 21.9% higher.

The HQI of the United States decreased by 12.3% from 2010 to 2015. This means that there are forces at work reducing the genetic-cultural fitness of America’s average citizen. One simple explanation could be the increase in immigration from lower HQI nations, who increase the population of the US without significantly increasing its economic and scientific output. Keeping population constant, the HQI still decreased by 8.9%, therefore immigration might be only causing a 3.4 percentage points of this dysgenesis.

Germany’s HQI increased by 0.2% from 2010 to 2015, meaning that no interesting structural change happened. These numbers are from before the recent migrant crisis, whose presence is sure to bring down Germany’s HQI.

Japan’s HQI fell 15.7% from 2010 to 2015. Not only is the nation coming down the peak (through its negative economic growth), the nation’s peak is also decaying.

Russia’s HQI increased by 31.1% from 2010 to 2015. Even though its economic growth was low (0.36%), its scientific output greatly increased during this period, from 38878 papers to 55500. Russia’s seeming low GDP growth is largely due to economic warfare from Wall Street. Its scientific growth shows its true economic fitness.

Why Scientific Output is Important

The HQI uses scientific output as the most important indicator of a nation’s genetic-cultural fitness. There are many good reasons for this, the two most important being:

1. Producing science requires that a nation be prosperous enough to afford having a class of society who dedicate most of their time to research. And that prosperity can only come from high genetic-cultural fitness for most countries, excepting a few oil states that can afford to import scientists.
2. Producing science requires very high intellectual capacity and drive for accomplishment (perhaps most importantly IQ and testosterone). If a nation’s population is incapable of producing science, they will be equally incapable of producing high-tech military equipment and industrial innovation, necessary for a nation to increase its power.

A nation’s scientific output is a very good indicator of its fitness. If a nation’s economy is growing fast, by raising the scientific output to the power of its real economic growth, the HQI gives the nation a fair chance at proving itself. China’s scientific output per capita is quite low compared to that of the United States. But its real economic growth is much higher. We can safely assume that China’s per capita scientific output is going to grow at a rate similar to its past economic growth.

The Bottleneck Effect in the Growth of Scientific Output

India’s example shows that there might be a bottleneck effect in the growth of scientific output in large and highly undeveloped nations. As mentioned, India’s scientific output grew by 242% from 2004 to 2015, similar to its economic growth from 1981 to 2003. 12 years of scientific output growth were equal to 23 years of past economic growth. While in the case of South Korea, its 2004 to 2015 scientific growth was roughly similar to its economic growth of the 12 years preceding that.

India may have already overcome the bottleneck. Indonesia, Bangladesh, Pakistan, Nigeria, the Philippines and Vietnam probably haven’t yet, and this probably partly accounts for their low HQI’s.

For a large, undeveloped and already low-HQI nation (low IQ, bad law enforcement, etc.), building the prosperity and infrastructure necessary for doing science takes far longer than it takes a smaller and higher HQI nation. Decades of education, infrastructure building and perhaps most importantly, urbanization, are needed before a country’s scientific output momentum gets going.

List of 203 Sovereign States by Human Potential

Below is a table of 203 sovereign states sorted by HQI, from highest HQI to lowest. Note that the HQI number shows the genetic-cultural quality of each individual citizen within that nation, not the nation’s power. While each additional Singaporean citizen adds a value of 4822 to the economy of Singapore, each additional US citizen adds a value of 1372. Since the genetic-cultural quality of Singaporeans is so much higher than the genetic-cultural quality of US citizens, what the HQI shows is that if Singapore had the same number of citizens as the United States, it would 3.5 times as powerful as the United States, as each individual citizen adds so much more to its power and productivity. Singapore’s real superiority is probably lower, as it is mostly its fast economic growth, aided by its geo-political situation, that’s contributing to its high HQI.

The HQI for certain nations, such as Indonesia and North Korea, are clearly inaccurate due to their exclusion from the world’s scientific community. The HQI of Indonesia and many former Central Asian Soviet states should increase considerably as they start to adopt Western scientific practices.

Please see below the table for the fine print regarding the numbers.

Rank	Country	2015 Citable Scientific Documents	2015 Population	Average Real Annual Economic Growth (2004-2015) [12-Year Min-Max Method]	HQI
1	Singapore	17,976	5,618,866	7.32	4823
2	Switzerland	39,358	8,238,610	1.01	3910
3	Australia	82,567	23,923,101	2.99	3561
4	Iceland	1,365	336,728	2.41	3549
5	Norway	18,228	5,142,842	1.17	2925
6	Qatar	2,766	2,350,549	14.88	2815
7	Denmark	23,081	5,661,723	-0.65	2812
8	Sweden	35,039	9,693,883	0.41	2775
9	Monaco	129	38,320	1.64	2683
10	Luxembourg	1,692	543,261	1.51	2564
11	Israel	18,040	7,919,528	3.71	2410
12	New Zealand	13,052	4,596,396	1.25	2352
13	Netherlands	51,434	16,844,195	-0.03	2238
14	Belgium	29,180	11,183,411	0.68	2058
15	Finland	17,551	5,460,592	-1.55	2034
16	Hong Kong	14,710	7,313,557	3.12	1997
17	Liechtenstein	102	37,461	-0.40	1967
18	Ireland	11,370	4,726,856	1.09	1959
19	Canada	89,312	35,871,283	0.13	1859
20	Austria	21,818	8,557,761	-0.09	1859
21	Slovenia	5,428	2,079,085	-0.43	1851
22	United Kingdom	169,483	63,843,856	-0.60	1818
23	Taiwan	34,011	23,381,038	4.53	1717
24	South Korea	73,433	49,750,234	3.61	1627
25	Greenland	125	57,275	0.05	1610
26	Czech Republic	20,759	10,777,060	1.02	1569
27	United States	567,007	325,127,634	0.51	1372
28	Portugal	21,159	10,610,014	-0.77	1359
29	Macao	819	584,420	3.20	1278
30	Spain	79,209	47,199,069	0.30	1277
31	Estonia	2,620	1,280,227	-2.23	1264
32	Germany	149,773	82,562,004	-0.77	1218
33	France	103,733	64,982,894	-0.08	1165
34	Grenada	140	106,694	3.33	1138
35	Poland	37,285	38,221,584	4.23	1120
36	Cyprus	1,789	1,164,695	-0.51	1088
37	Slovakia	6,271	5,457,889	2.67	1068
38	Malta	559	431,239	0.75	1000
39	Italy	95,836	61,142,221	-1.74	945
40	Greece	16,616	11,125,833	-1.67	934
41	Saint Kitts and Nevis	62	55,376	1.83	889
42	Croatia	5,533	4,255,374	-1.12	869
43	China	416,409	1,401,586,609	10.55	856
44	Saudi Arabia	17,529	29,897,741	5.90	768
45	Malaysia	23,414	30,651,176	2.95	756
46	Brunei Darussalam	366	428,539	1.03	668
47	Serbia	6,540	9,424,030	2.97	663
48	Hungary	9,478	9,911,396	-0.81	653
49	Lithuania	2,973	2,998,969	-1.86	629
50	Iran	39,727	79,476,308	5.02	626
51	Japan	109,305	126,818,019	-0.41	605
52	New Caledonia	171	263,147	3.75	580
53	San Marino	22	31,802	3.26	563
54	Seychelles	59	93,754	3.79	540
55	Chile	10,347	17,924,062	2.50	535
56	Latvia	1,503	2,031,361	-1.23	498
57	Tunisia	6,228	11,235,248	2.17	493
58	Bermuda	43	65,578	0.13	485
59	Palau	14	21,291	-0.22	481
60	Turkey	39,275	76,690,509	2.27	479
61	Romania	13,053	21,579,201	0.70	475
62	Lebanon	2,076	5,053,624	5.60	464
63	Montenegro	316	621,556	2.50	432
64	Dominica	37	72,680	2.90	416
65	Bulgaria	3,441	7,112,641	1.73	410
66	United Arab Emirates	3,858	9,577,128	2.30	358
67	Uruguay	1,208	3,429,997	4.39	354
68	Macedonia	814	2,109,251	3.01	347
69	Barbados	128	287,482	0.83	341
70	Russian Federation	57,881	142,098,141	0.36	312
71	Jordan	2,313	7,689,760	5.45	338
72	Oman	1,461	4,157,783	3.56	335
73	Brazil	61,122	203,657,210	3.70	332
74	French Polynesia	122	282,764	0.11	319
75	Kuwait	1,327	3,583,399	1.84	311
76	Iraq	1,793	35,766,702	27.77	295
77	South Africa	17,409	53,491,333	2.03	292
78	Argentina	11,815	42,154,914	2.17	253
79	Bahrain	344	1,359,726	5.20	252
80	Georgia	1,067	4,304,540	4.28	246
81	Armenia	953	2,989,467	-0.14	232
82	Andorra	24	80,950	-0.26	216
83	Fiji	231	892,727	1.95	212
84	Trinidad and Tobago	285	1,346,697	5.03	207
85	Egypt	14,800	84,705,681	4.49	198
86	Cuba	1,760	11,248,783	6.76	191
87	Bosnia and Herzegovina	756	3,819,684	2.95	177
88	Thailand	11,632	67,400,746	3.39	174
89	Guam	36	169,885	3.00	174
90	Colombia	7,500	49,529,208	4.28	163
91	Belarus	1,554	9,259,666	3.78	163
92	India	123,206	1,282,390,303	7.08	162
93	Azerbaijan	676	9,612,580	17.29	160
94	Botswana	410	2,056,370	1.11	157
95	Panama	485	3,987,866	8.46	151
96	Tuvalu	2	9,916	2.01	150
97	Mauritius	208	1,253,581	3.57	148
98	Kazakhstan	2,062	16,770,447	5.95	142
99	Libya	352	6,317,080	21.21	142
100	Costa Rica	720	5,001,657	3.88	137
101	Cayman Islands	11	59,967	-0.20	134
102	Morocco	4,079	33,955,157	5.00	134
103	Ukraine	8,868	44,646,131	-1.35	129
104	Algeria	5,171	40,633,464	3.75	129
105	Puerto Rico	660	3,680,058	-0.79	125
106	Namibia	286	2,392,370	6.15	125
107	Albania	406	3,196,981	4.32	121
108	Bhutan	82	776,461	10.04	121
109	Mongolia	298	2,923,050	8.01	118
110	Vanuatu	34	263,888	4.84	112
111	Palestine (West Bank & Gaza)	475	4,548,815	6.18	112
112	Mexico	18,417	125,235,587	0.21	110
113	Marshall Islands	7	52,993	0.88	99
114	Nigeria	5,112	183,523,432	18.20	97
115	Ecuador	1,418	16,225,691	4.25	88
116	Bahamas	46	387,549	-0.39	86
117	Federated States of Micronesia	12	104,460	-0.51	83
118	Moldova	348	3,436,828	1.71	82
119	Antigua and Barbuda	10	91,822	0.67	81
120	Ghana	1,531	26,984,328	8.97	81
121	Aruba	12	103,889	-2.26	80
122	Gabon	174	1,751,199	1.72	80
123	Jamaica	305	2,813,276	-0.77	76
124	Congo	388	4,671,142	3.59	76
125	Belize	32	347,598	2.69	74
126	Swaziland	106	1,285,519	2.38	68
127	Sri Lanka	1,255	21,611,842	6.27	67
128	Pakistan	10,962	188,144,040	4.64	66
129	Cape Verde	35	508,315	6.95	65
130	Solomon Islands	43	584,482	4.10	63
131	Gambia	157	1,970,081	1.36	63
132	Peru	1,813	31,161,167	5.10	63
133	Suriname	38	548,456	5.38	62
134	Venezuela	1,473	31,292,702	7.55	60
135	Maldives	22	357,981	7.57	57
136	Viet Nam	4,092	93,386,630	6.40	55
137	Samoa	13	193,228	0.76	50
138	Kenya	2,215	46,748,617	4.32	49
139	Tonga	7	106,379	-0.20	48
140	Saint Lucia	11	184,937	3.25	47
141	Cameroon	1,116	23,393,129	4.09	47
142	Senegal	691	14,967,446	4.22	45
143	Uganda	1,270	40,141,262	7.03	38
144	Laos	226	7,019,652	7.81	36
145	Benin	409	10,879,828	4.30	36
146	Kiribati	5	105,555	1.51	36
147	Guyana	34	807,611	2.53	34
148	Nepal	922	28,440,629	4.73	33
149	Malawi	519	17,308,685	5.75	32
150	Zambia	432	15,519,604	6.76	31
151	Burkina Faso	508	17,914,625	5.81	30
152	Indonesia	6,280	255,708,785	5.49	29
153	Ethiopia	1,691	98,942,102	11.11	29
154	Tanzania	1,261	52,290,796	6.56	28
155	Saint Vincent and the Grenadines	4	109,374	2.15	28
156	Bolivia	290	11,024,522	5.08	26
157	Rwanda	278	12,428,005	7.92	26
158	Paraguay	182	7,032,942	5.04	25
159	Kyrgyzstan	142	5,707,529	5.23	24
160	Syrian Arab Republic	502	22,264,996	5.07	23
161	Equatorial Guinea	17	799,372	12.91	23
162	Zimbabwe	552	15,046,102	-2.88	23
163	Bangladesh	3,011	160,411,249	6.06	22
164	Cambodia	317	15,677,059	6.67	22
165	Philippines	2,091	101,802,706	4.39	21
166	Papua New Guinea	156	7,631,819	6.48	21
167	Togo	156	7,170,797	3.56	19
168	Lesotho	43	2,120,116	5.09	18
169	Uzbekistan	426	29,709,932	8.46	18
170	Sierra Leone	112	6,318,575	6.20	17
171	Guinea-Bissau	37	1,787,793	3.77	17
172	Timor-Leste	23	1,172,668	4.25	16
173	Niger	169	19,268,380	18.20	16
174	Côte d’Ivoire	386	21,295,284	3.16	16
175	El Salvador	135	6,426,002	0.39	16
176	Sudan	597	39,613,217	4.66	15
177	Guatemala	243	16,255,094	3.42	13
178	Mali	239	16,258,587	3.18	13
179	Mozambique	299	27,121,827	8.06	13
180	Nicaragua	100	6,256,510	1.74	13
181	Tajikistan	107	8,610,384	7.05	13
182	Liberia	63	4,503,439	4.92	13
183	Djibouti	13	899,658	4.59	12
184	Yemen	297	25,535,086	4.38	11
185	Dominican Republic	116	10,652,135	5.81	11
186	Madagascar	278	24,235,390	1.56	9
187	Honduras	92	8,423,917	2.07	9
188	Mauritania	35	4,080,224	8.92	9
189	Comoros	8	770,058	1.95	8
190	Haïti	112	10,603,731	0.01	8
191	Sao Tome and Principe	2	202,781	6.19	8
192	Central African Republic	41	4,803,082	3.45	7
193	Guinea	106	12,347,766	2.35	7
194	Angola	83	22,819,926	12.50	5
195	Myanmar	181	54,164,262	10.42	4
196	Chad	38	13,605,625	16.86	4
197	Eritrea	29	6,737,634	3.86	4
198	Burundi	42	10,812,619	1.42	3
199	Afghanistan	74	32,006,788	11.27	3
200	North Korea	52	25,155,326	1.85	2
201	Turkmenistan	9	5,373,487	9.85	2
202	Democratic Republic of the Congo	75	71,246,355	5.92	1

The economic growth rate data comes from my essay The 12-Year Min-Max Average. Please see this essay for technical details on how the numbers were calculated.

Only “citable” scientific documents are counted, citable documents are generally higher in quality and more important than non-citable ones. However, citable and no-citable documents tend to rise and fall together, so that including non-citable documents shouldn’t have a significant effect on the HQI numbers.

Population data comes the United Nations and the World Bank. Scientific output data from SCIMago. Economic growth data from the World Bank and Trading Economics.

* A country’s GDP growth rate could be said to somewhat take into account its population growth, since when all other things are equal, growth in population results in economic growth. However, this will only apply to a stagnant economy whose only increase or decrease is a result of population change rather than