Economic Complexity, Capability
Hidalgo
The Atlas of Economic Complexity - PDF
The amount of knowledge that is required to make a product can vary enormously from one good to the next. Most modern products require more knowledge than what a single person can hold. [..] Accumulating productive knowledge is difficult. For the most part, it is not available in books or on the Internet. It is embedded in brains and human networks. It is tacit and hard to transmit and acquire. It comes from years of experience more than from years of schooling. Productive knowledge, therefore, cannot be learned easily like a song or a poem. It requires structural changes. Just like learning a language requires changes in the structure of the brain, developing a new industry requires changes in the patterns of interaction inside an organization or society.[..]
The Atlas of Economic Complexity attempts to measure the amount of productive knowledge that each country holds. Our measure of productive knowledge can account for the enormous income differences between the nations of the world and has the capacity to predict the rate at which countries will grow. In fact, it is much more predictive than other well-known development indicators, such as those that attempt to measure competitiveness, governance and education.
Consider the case of Singapore and Pakistan. The population of Pakistan is 34 times larger than that of Singapore. At market prices their GDPs are similar since Singapore is 38 times richer than Pakistan in per capita terms. Under the classification we use in this Atlas, they both export a similar number of different products, about 133.
How can products tell us about the conspicuous differences in the level of development that exist between these two countries? Pakistan exports products that are on average exported by 28 other countries (placing Pakistan in the 60 th percentile of countries in terms of the average ubiquity of their products), while Singapore exports products that are exported on average by 17 other countries (1 st percentile). Moreover, the products that Singapore exports are exported by highly diversified countries, while those that Pakistan exports are exported by poorly diversified countries. Our mathematical approach exploits these second, third and higher order differences to create measures that approximate the amount of productive knowledge held in each of these countries"
The Building Blocks of Economic Complexity - PDF
For Adam Smith, wealth was related to the division of labor. As people and firms specialize in different activities, economic efficiency increases, suggesting that development is associated with an increase in the number of individual activities and with the complexity that emerges from the interactions between them. Here we develop a view of economic growth and development that gives a central role to the complexity of a country’s economy by interpreting trade data as a bipartite network in which countries are connected to the products they export, and show that it is possible to quantify the complexity of a country’s economy by characterizing the structure of this network. Furthermore, we show that the measures of complexity we derive are correlated with a country’s level of income, and that deviations from this relationship are predictive of future growth. This suggests that countries tend to converge to the level of income dictated by the complexity of their productive structures, indicating that development efforts should focus on generating the conditions that would allow complexity to emerge in order to generate sustained growth and prosperity...
Now, if all countries are connected to each other through a global market for inputs and outputs so that they can exploit a division of labor at the global scale, why have differences in Gross Domestic Product (GDP) per capita exploded over the past two centuries? One possible answer is that some of the individual activities that arise from the division of labor described above cannot be imported, such as property rights, regulation, infrastructure, specific labor skills, etc., and so countries need to have them locally available in order to produce. Hence, the productivity of a country resides in the diversity of its available non-tradable capabilities, and therefore, cross-country differences in income can be explained by differences in economic complexity, as measured by the diversity of capabilities present in a country and their interactions...
We can create indirect measures of the capabilities available in a country by thinking of each one of these capabilities as a building block or Lego piece. In this analogy, a product is equivalent to a Lego model, and a country is equivalent to a bucket of Legos. Countries will be able to make products for which they have all the necessary capabilities, just like a child is able to produce a Lego model if the child’s bucket contains all the necessary Lego pieces. Using this analogy, the question of economic complexity is equivalent to asking whether we can infer properties such as the diversity and exclusivity of the Lego pieces inside a child’s bucket by looking only at the models that a group of children, each with a different bucket of Legos, can make. Here we show that this is possible if we interpret data connecting countries to the products they export as a bipartite network and assume that this network is the result of a larger, tripartite network, connecting countries to the capabilities they have and products to the capabilities they require (Fig 1a). Hence, connections between countries and products signal the availability of capabilities in a country just like the creation of a model by a child signals the availability of a specific set of Lego pieces.
Countries differ markedly in the diversification of their exports. Products differ in the number of countries that export them, which we define as their ubiquity. We document a new stylized fact in the global pattern of exports: there is a systematic relationship between the diversification of a country’s exports and the ubiquity of its products. We argue that this fact is not implied by current theories of international trade and show that it is not a trivial consequence of the heterogeneity in the level of diversification of countries or of the heterogeneity in the ubiquity of products. We account for this stylized fact by constructing a simple model that assumes that each product requires a potentially large number of non-tradable inputs, which we call capabilities, and that a country can only make the products for which it has all the requisite capabilities. Products differ in the number and specific nature of the capabilities they require, as countries differ in the number/nature of capabilities they have.
Products that require more capabilities will be accessible to fewer countries (i.e., will be less ubiquitous), while countries that have more capabilities will have what is required to make more products (i.e., will be more diversified). Our model implies that the return to the accumulation of new capabilities increases exponentially with the number of capabilities already available in a country. Moreover, we find that the convexity of the increase in diversification associated with the accumulation of a new capability increases when either the total number of capabilities that exist in the world increases or the average complexity of products, defined as the number of capabilities products require, increases.
This convexity defines what we term as a quiescence trap, or a trap of economic stasis: countries with few capabilities will have negligible or no return to the accumulation of more capabilities, while at the same time countries with many capabilities will experience large returns - in terms of increased diversification - to the accumulation of additional capabilities. We calibrate the model to three different sets of empirical data and show that the derived functional forms reproduce the empirically observed distributions of product ubiquity, the relationship between the diversification of countries and the average ubiquity of the products they export, and the distribution of the probability that two products are co-exported. This calibration suggests that the global economy is composed of a relatively large number of capabilities – between 23 and 80, depending on the level of disaggregation of the data – and that products require on average a relatively large fraction of these capabilities in order to be produced. The conclusion of this calibration is that the world exists in a regime where the quiescence trap is strong.
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