According to Nurkse, Myrdal, Rosestein-Rodan, Hirschman, Myrdal, Prebisch and Furtado, productive activities are different in terms of their potential to generate growth and development. Activities with high increasing returns, high incidence of technological change and innovations and high synergies and linkages arising from labor division strongly induce Economic Development (Reinert 2009 ,p.9).
These are activities where imperfect competition rules, with all its typical features (learning curves, fast technical progress, high R&D spending, economies of scale and scope, high industrial concentration, entry barriers, product differentiation, etc…). This group of high value-added activities are usually opposed to low value-added activities typical of poor and middle income countries and its perfect competition market structure (Low R&D content, low technological innovation, perfect information, absence of learning curves , etc…) ( Reinert and Katel 2010 , pg 7 ).
For the classics of development economics, increases in productivity come from climbing the technological ladder, moving from low-quality activities to high-quality activities, through technological sophistication of the economy (Bresser-pereira 2014, pg103). In order to achieve this goal, the construction of a complex and diverse industrial system, subject to increasing returns to scale, synergies and linkages between activities is fundamental (Reinert 2010 Pg.3). The specialization in agriculture and mining does not allow for this type of technological change. How could we empirically measure these propositions from classical development economists? Ideally one could study the market structures (perfect versus imperfect competition) of products as revealed in world trade data. From the classification of these structures, one could correlate the product and market structures found with levels of per capita incomes. If the propositions of the classics of development are correct, we should find countries with high per capita income specializing in imperfect competition markets and poor countries specializing in perfectly competitive markets in tradable goods production; something, in fact, easy to see with a quick superficial analysis of current trade patterns, but difficult to “prove” in a more robust way.
Despite all the evidence from economic history of several successful stories that followed the recommendations of the classics (Southeast Asia, Japan, United States, etc.) and also of failures, such as Latin America and the Caribbean, one could argue that “hard science type” empirical evidence is still lacking to help reinforce the point of the structuralists. That´s where the Atlas of Economic Complexity (Hausmann, Hildalgo et al 2011) fits in: as an empirical breakthrough, able to give huge support to the propositions of the classical economists who saw productive sophistication as the way for economic development.
How can we measure productive sophistication?
Hausmann, Hildalgo et al developed an extraordinary simple and useful way to measure “economic complexity” or productive sophistication in a joint venture of MIT Media Lab and Harvard Kennedy School(http://atlas.media.mit.edu/). Based on countries’ exports they are able to measure indirectly the technological sophistication of economic structures. The methodology applied to several countries in the last 5 decades resulted in an impressive data base for more than 750 hundred products (SITC) in 140 countries for the the last 50 years. The two basic concepts to measure if a country is complex are the diversity and ubiquity of its export products. If an economy is able to export non ubiquitous and rare goods there is evidence that its economic structure is sophisticated. Of course there is problem here of relative scarcity in special natural resources as in diamonds and precious stones for example.
Non ubiquitous goods should therefore be further divided into those that have technological complexity (thus are scarce: planes, machines, etc) and those that are rare in nature (precious stones). To control the goods for this type of natural scarcity, the authors came up with a very ingenious ideia: to use export diversification of countries that export this same scarce good as a control for scarcity due to complexity. For example, if a country exports some very rare goods and the countries that export this same good has a diversified structure of exports, this is indication that the good is rare because of technological requirements, in other words, it is a complex good (airplanes). If other countries that export this same rare good are not able to do anything else, this is indication that the good is non ubiquitous but not complex, for example diamonds. By comparing this ubiquity and diversity of exports of countries in several years, the authors are able to build a formal index of “economic complexity” that is entirely based on relations found inside this huge network of relations; there are no consideration, whatsoever, on the “content” or “quality” of the goods.
For example, Botswana and Sierra Leone produce and export something very rare, thus non ubiquitous: diamonds. On the other hand they have a very limited and non diversified export structure. They produce non ubiquitous goods without complexity. At the extreme opposite one can find Japan, USA and Germany producing medical image processing equipment, something also very non ubiquitous; but when one looks at the export structure of these 3 countries one finds an extremely diversified export structure, a clear indication of “economic complexity”. In other words, non ubiquity with diversity means complexity. The other way around also works: a country that has a very diversified export structure but with ubiquitous goods (fish, mining, garmets) is not considered very “complex”. This country probably produces what everyone else is able to produce. Diversity without non ubiquity means lack of complexity.
Following this kind of reasoning the authors are able to classify countries according to their economic complexity (ECI) and find impressive correlations between their index and levels of per capita income; Japan, USA, UK, Sweden and Germany are always in the top ten in the last ten years of calculations. If we treat economic development as economic sophistication, following the classics, it is easy to see what this indicator does through a very ingenious methodology based on such simple concepts as ubiquity and diversity. The results achieved by the atlas in terms of complexity of products also point to something very in line with ideais from the classics of development: rich countries tend to “specialize” in imperfect competition markets whereas poor and middle income countries tend to “specialize” in perfect competition markets; something that paul Krugman has already discussed in his papers on trade patterns and imperfect competition.
Proximity, connectedness and “communities” of products
Another important attribute of goods in the atlas is “proximity”. Two products are close together if several countries are able to export this pair, in other words if their probability of being co-exported is high. For example, several countries export grapes, others export wines, but some countries export grapes and wine, so there is ground to say that there is “proximity” between grapes and wines. Of course this is a very intuitive example but the same exercise with other products yields interesting results; medicine and x-ray machines are close products according to the atlas. These “proximity” measures carry relevant information about capabilities involved in producing these goods around the globe and form, according to the authors, “connections” between products and clusters or “communities” of products; a community is defined depending on the relative distance between goods. In general highly “connected” products are complex whereas products with few connections are not complex. For example: crude oil has very few connections or no complexity at all, on the other extreme, machines are very connected and complex. “Communities” of complex goods carry products typical of imperfect competiton market structures, the opposite apply to non complex products. The 34 communities found by the authors are shown below.
Changes in productivity
From this perspective the productivity dynamics of an economy depends on its sectorial configuration. It is not then the case to only educate more or even train more workers; productivity becomes a matter of encouraging and developing the correct sectors. The pattern of productive specialization of an economy is key to understanding the productivity-enhancing process. Being productive means mastering advanced production technology and creating local capacity and skills in the right sectors. Producing cashew nuts or computer chips, cars or shoes, bananas or computers makes a difference. That is, the process of increasing productivity in an economy is non-neutral in terms of sectorial composition (agriculture, services and industry and GDP subsectors) and depends on the type of product that a country is capable of producing. The productivity of the economy does not depend only on individuals, it is something systemic. Workers employed in technologically sophisticated sectors will be productive due to the sector’s inherent characteristics and not the workers.
International comparisons show that the major differences in productivity between countries are precisely in the tradable goods sector, especially in manufacturing jobs, away from the so-called non sophisticated services. It is quite intuitive to understand that the productivity of a waiter, a driver, an airplane pilot or a store seller is practically the same in Europe, USA, Asia and Brazil. Even in the construction business, with the aid of more sophisticated machines, productivity among workers in different countries is not very different. The higher productivity of the rich countries then occurs in sectors other than those, especially sophisticated services and industry. Productivity is largely a sector-specific phenomenon. Rich countries are the ones able to grow their sectors of complex tradable goods and sophisticated services (US, Japan, Germany, Nordic, Southeast Asia, etc.) (Balassa, 1964).
1. Rainer Kattel & Erik S. Reinert, 2010. “Modernizing Russia: Round III. Russia and the other BRIC countries: forging ahead, catching up or falling behind?,” The Other Canon Foundation and Tallinn University of Technology Working Papers in Technology Governance and Economic Dynamics 32, TUT Ragnar Nurkse School of Innovation and Governance.
2. Erik S. Reinert, 2010. “Developmentalism,” The Other Canon Foundation and Tallinn University of Technology Working Papers in Technology Governance and Economic Dynamics 34, TUT Ragnar Nurkse School of Innovation and Governance.
3. Rainer Kattel & Jan A. Kregel & Erik S. Reinert, 2009. “The Relevance of Ragnar Nurkse and Classical Development Economics,” The Other Canon Foundation and Tallinn University of Technology Working Papers in Technology Governance and Economic Dynamics 21, TUT Ragnar Nurkse School of Innovation and Governance.
4. Bresser-Pereira, L.C., 2014, A Construção Política do Brasil, editora 34, São Paulo, Brazil
5. C. A. Hidalgo, B. Klinger, A.-L. Barabási, and R. Hausmann, “The Product Space Conditions the Development of Nations”, Science 27 July 2007: 317 (5837), 482-487. DOI:10.1126/science.1144581
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