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Productivity in Physical and Chemical Science Prediction
知识和财富自古以来被认为是相关[1]-[4]。拿破仑曾经说过:“没有伟大的数学”,不能成为一个伟大的国家。然而,这种关系是如何在现代世界仍然是一个敏感的政治问题[5],[8]。毫无疑问,科学技术研究影响经济发展[9]-[10],例如,科学发展与《国富论》密切相关[11]。科学发展被证明与一个社会的宽容和开放度的相关的,也反映了事实的态度支持科学相关估值经验,是基于现代科学进步的基础[12]-[13]。这个统计分析把科学生产力与经济发展联系起来,发现增加经济发展先于科学发展,这表明科学的作用：允许持续长期的经济发展,但不是触发经济发展。
最近伊达尔戈登对一个争论做出了重要的贡献，他提出了一个新颖的经济复杂性指数(ECI)来解释知识嵌入在社会产生的财富值。在他看来，现代社会能够积累大量的生产知识因为人们互相传播着各种知识。但为了充分利用这些知识，这些知识就必须通过组织和市场整合在一起。因此,在国家和全球层面上，个人专业化产生多样性。我们最繁荣的现代社会是明智的,而不是因为他们的公民个人很聪明,而是由于这些社会保持专门技术的多样性,也是因为它们能够重组创建一个更多种多样的好产品。
Knowledge and wealth have been recognized to be related since ancient times [1]–[4]. Napoleon used to say that “there cannot be a great nation without great mathematics”. Yet how this relationship works in the modern world is still a sensitive political issue [5]–[8]. There is no doubt that scientific and technological research affects economic development [9]–[10], for example. Scientific development and the wealth of nations are closely linked [11]. Scientific development was shown to correlate with tolerance and openness of a society, reflecting the fact that attitudes favoring science are related to valuation of empirical facts over personal convictions, which lay at the base of modern scientific progress [12]–[13]. This statistical analysis correlating scientific productivity with economic development, found that increases in economic development preceded that of scientific development, suggesting that the role of science was rather allowing sustained long term economic development but not triggering its.
A significant recent contribution to the debate was made by Hidalgo et al [14]–[16] who proposed a novel Economic Complexity Index (ECI) to account for knowledge embedded in society that produces wealth. In their words ,Modern societies can amass large amounts of productive knowledge because they distribute bits and pieces of it among its many members. But to make use of it, this knowledge has to be put back together through organizations and markets. Thus, individual specialization begets diversity at the national and global level. Our most prosperous modern societies are wiser, not because their citizens are individually brilliant, but because these societies hold a diversity of knowhow and because they are able to recombine it to create a larger variety of smarter and better products.” This ECI reflects the composition of a country's productive output and its structures that emerge to hold and combine knowledge [16]
These results open new questions. Do certain areas of science promote economic development more than others? Are more applied sciences better in advancing economic development than more general basic sciences?
In order to answer these questions we first assessed the closeness of the various widely used indices for knowledge and socio-economic development to the classical index of national wealth such as Gross Domestic Product per capita (GDPc) . This was done using a Joining Tree Cluster Analysis from the sofware Statistica 7, comparing the weighted pair-group average using euclidean distance and computing a matrix from this distances . The tree was then drawn from the data in the matrix.
Then we compared the relative publication effort made by each country regarding research in different areas of knowledge, with its present and future national wealth. Data of the number of publication by area for each country for the years starting 1998 came from the database of Scopus compiled by SCImago [17], whereas data for 1982 and 1992 was compiled manually by us from the Web of Science. We calculated the relative research effort of each scientific subject area as the percentage of the total number of publications of that country published in journals of that area in a year. For example, the number of publications in mathematical journals of that country, divided by the total number of publications in all subject areas of that country, multiplied by 100, served as the estimate of relative research effort in mathematics for that country. This number was used to calculate the “Revealed Comparative Advantages” (RCA) of the scientific publication effort, adapted from the economic literature [18]. RCA is a ratio of two shares. The numerator is the share of a country's publications in a given discipline or area of science in its total number of publications. The denominator is the share of the world's number of publications in that same discipline in the total world's publications.
In order to avoid statistical pitfalls due to non-linearity in our data, we used only nonparametric statistics for the analysis of the relationship between RCA and economic growth. Only countries with more than 100 publications in 1982, or 200 in 1996, and which had their GDPc data for the required years in the World Bank database, were taken into account.
Economic wealth was estimated using the Gross National Product per capita (GDPc) as calculated by the World Bank (GDP per capita based on purchasing power parity at constant 2005 US $). Percentage growth in wealth was estimated by calculating the perceptual increase of GDPc during a given period of time.
Countries with over 100 publications in 1998 recorded by Scopus and with GDPc data provided by the World Bank were used for the present analysis. Only 101 countries fulfilled these criteria.
Scientific productivity is a much better predictor of economic wealth and Human Development of a nation than other variables tracked by a number of commonly used indices proposed worldwide. Figure 1 show that the number of publications per capita of a country (Publication) is the index closest the GDP per capita and to the Human Development Index (HDI) of the country. “Publication” correlates much stronger with the wealth per capita of a nation than any of the other indices tested.
Rich countries with high GDPc publish relatively more in certain scientific disciplines, whereas poor countries with low GDPc publish relatively more in other disciplines (Table 1). The table shows the correlations between RCA or the relative research effort in each discipline assed by the publication record of the year 2010 of each country, with its GDPc of the same year. The table shows that richer countries publish more and therefore probably invest more research effort in neurosciences, computer sciences and psychology than poorer ones; whereas poorer countries publish more research in agriculture and multidisciplinary sciences.
Correlations between the RCA of the publication effort of scientific disciplines during 2000 with economic growth in the following years, estimated as percent increase in GDPc during the periods 2000–2005 (Table 2) shows a different result. Here relative research efforts in physics and chemistry were the best predictors for future economic growth, and efforts in medicine and psychology the best predictors for poor future economic growth. A part, but certainly not all, of the correlation between relative productivity in physical and chemical science and future economic growth could be explained by an additional correlation with development of technological knowledge. The Economic Complexity Index, as calculated in by Hausmann et al [16], mirrors some but not all of the patterns of correlation between RCS in scientific publications and GDPc growth in the following 5 years. For example, RCA in physics and material sciences was positively correlated to both, the economic complexity index achieved 8 years later and the economic growth achieved 5 years later. RCA in chemistry, however, did not correlated significantly with economic complexity but did correlate positively with economic growth. RCA in computer science, health, biochemistry and neuroscience, for example, correlated with future economic complexity but not with economic growth.
The pattern observed for the year 2000 was not exceptional. In Table 4 we show that in different historic moments, a highly significant correlation between high RCA in science and fast economic growth in the following year can be demonstrated. RCA of physics, chemistry and material science were good predictors for future economic growth in all years except 2005. RCA of these disciplines in the year 2005 did not correlated with economic growth in the following 5 years. This lack of correlation can be explained by the global financial crisis during the last 3 years of that period which wiped out economic growth worldwide.
This pattern emerges also if a different database, such as The Web of Science, and much older data is used. For 1982 (data for 64 countries), of the 247 areas used by the Web of Science at that time to classify the journals, very few produced statistically significant (p<0.01) positive correlations between the subsequent GDPc growth in the following years and the RCA of publications in a given area. These were: Asian Studies (spearman correlation = 0.54), Physics, Fluids & Plasmas (0.51), Engineering, Manufacturing (0.42) Andrology (0.39), Social Work (0.37), Engineering, Industrial (0.34), Physics, Particles & Fields (0.34). For 1987 (data for 70 countries) not a single of these 247 areas correlated with the subsequent GDPc growth. For 1992 (data for 88 countries) only Computer Science, Theory & Methods (0.31), Economics (0.30) and Engineering, Manufacturing (0.28) correlated significantly with the subsequent 5 year GDPc growth. That is, despite the fact that the Web of Science in the decades of 1980 and 1990 compiled information about publications, based on a very reduced and selective set of journals, coming from a small group of countries, their data shows a now familiar trend: Countries with high relative investment in physics and engineering are more likely to show higher economic growth in future years.
It is tempting to postulate a direct causal relation between economic growth and the development of certain scientific areas, or vice-versa. This direct causal relationship, however, does not exist as shown in Table 5. Here we perform a temporal relation analysis inspired by Granger [19] but for data from 1996 to 2005 where the quality of the databases is comparable.
We have to remark that the present study excluded countries with low scientific productivity, which include all poor countries. Previous studies [12] showed that the correlation between science and wealth of a country appears only after a threshold of economic development has been reached and that a rapid increase in scientific productivity was normally observed after a previous increase in economic development. On the other hand, the relative effort to support academic activity in rich countries seems to be close to the maximum tolerated by society. Rich countries have completed their scientific and industrial revolution in the past and focus now on other aspects of the wellbeing of their citizens, as they have to manage low economic growth. This would explain the low correlations found between scientific publications and future economic growth in rich countries. Therefore, the present conclusions are valid only for middle income countries.
Jeffry Sachs [11] recommended health, energy, agriculture, climate and ecology as the areas of science where investments were most likely to promote economic growth. None of them came out as positively correlated here. On the contrary, countries that knowingly or unknowingly complied with Sachs's recommendations achieved very poor economic growth. It is investment in hard sciences and basic sciences, such as physics and chemistry that correlate strongest with economic growth. Material sciences are normally considered to be part of physics although Scopus computes the publication in this area separately.
Our results show that the correlations between basic natural science and economic development is not due to direct causal chains. This is in agreement with more recent empirical explorations in economics [21] that revealed an intricate network of reciprocal relationships between knowledge, services, environment and finance. Here we propose that scientific development works in an analogous way, affecting multiple aspects of the economy and in turn being affected by many of these aspects producing positive feedback cycles. Hirschman [22] postulated the high development theory, as the view that development is a virtuous circle driven by external economies – that is, that modernization breeds modernization. Some countries, according to this view, remain underdeveloped because they have failed to get this virtuous circle going, and thus remain stuck in a low level trap. Our data would support the proposition that investing in basic scientific research seem to be the best way a middle income country can foment fast economic growth, triggering Hirschman's virtuous cycle. This proposition is also used by Lin [25] to solve the Needham Puzzle: Why the Industrial Revolution did not originate in China. The scientific revolution needs a profound conceptual revolution which is achieved by the development of basic natural sciences [13].
As for the future, the ranking of RCA in 2010 showed that the countries with an RCA value in Physics above 2.0 were Armenia, Ukraine, Moldova, Uzbekistan, Russia, Belarus, Bulgaria, Kazakhstan and Georgia. Most of them are among the fastest growing economies in 2012. Regrettably, no country from Africa or Latin America is on this list, although Mexico and Puerto Rico, the champions in RCA values in Physics in Latin American, are the only ones with values above 1.0.
References
1. Bacon F (1620) Novum Organum Scientiarum. In The Novum organon, or a true guide to the interpretation of nature, trans. G. W. Kitchin. Oxford: Oxford University Press, 1855.
2. Condorcet MJA (1794) Sketch for a historical picture of the progress of the human mind: tenth epoch. Daedalus 133 (3) 65–82. doi: 10.1162/0011526041504588
View Article PubMed/NCBI Google Scholar http://www.ukassignment.org/ygzydx/
3. Spencer H (1875) Progress: Its law and cause. In: Illustrations of universal progress: A series of discussions. pp. 1–60. New York, NY, US: D Appleton & Company, xxv, 451 pp.
4. Marshall A (1890) Principles of Economics. Amazon Kindle edition
View Article PubMed/NCBI Google Scholar
5. Nelson RR (1959) The Simple Economics of Basic Scientific Research. Journal of political Economy 67: 297–306. doi: 10.1086/258177
View Article PubMed/NCBI Google Scholar
6. Salter AJ, Martin BR (2001) The economic benefits of publicly funded basic research: A critical review. Research Policy 30: 509–532. doi: 10.1016/s0048-7333(00)00091-3
View Article PubMed/NCBI Google Scholar
7. King DA (2004) The scientific impact of nations. Nature 430: 311–316. doi: 10.1038/430311a
View Article PubMed/NCBI Google Scholar
8. Royal Society (2011) Knowledge, Networks and Nations: Global Scientific Collaboration in the 21st Century. RS Policy document 03/11. London, UK:
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