Abstract
Economic complexity reflects the amount of knowledge that is embedded in the productive structure of an economy. It resides on the premise of hidden capabilities—fundamental endowments underlying the productive structure. In general, measuring the capabilities behind economic complexity directly is difficult, and indirect measures have been suggested which exploit the fact that the presence of the capabilities is expressed in a country’s mix of products. We complement these studies by introducing a probabilistic framework which leverages Bayesian non-parametric techniques to extract the dominant features behind the comparative advantage in exported products. Based on economic evidence and trade data, we place a restricted Indian Buffet Process on the distribution of countries’ capability endowment, appealing to a culinary metaphor to model the process of capability acquisition. The approach comes with a unique level of interpretability, as it produces a concise and economically plausible description of the instantiated capabilities.
Highlights
According to Lall [1, 2], each country has to find its own path towards development, focusing on its learning system in order to add capabilities to the ones it already owns
This line of reasoning, which Lall calls the “capabilities approach”, has been further developed in the seminal works of Hidalgo and Hausmann [3,4,5,6,7,8,9], as well as in [10,11,12]. These fundamental endowments describing the productive structure of an economy are at the roots of the economic complexity theory, which leverages tools from network science and econometrics to reflect the amount of knowledge that is embedded in the productive structure of an economy
Economic data suggests different capability distribution across countries, e.g., developed countries should in general exhibit a higher number of capabilities. This is different to the standard Indian Buffet Process (IBP) which implicitly assumes the same distribution Poisson(α) for the number of capabilities per country. We address this limitation via the Restricted IBP (R-IBP) formulation from [42]
Summary
According to Lall [1, 2], each country has to find its own path towards development, focusing on its learning system in order to add capabilities to the ones it already owns. With the intention to further reflect the ideas underlying the arguments of a capability driven economic competitiveness, the authors in [14, 15] propose a nonlinear relationship between the complexity of products and the fitness of countries. Both approaches have been shown to be economicallygrounded and to be effective in ranking countries and products by their importance in the network [16]. Besides highlighting the relationship between a country’s productive structure and its economic growth, economic complexity essentially introduces non-monetary and nonincome-based measures which uncover the countries’ hidden potential for development and growth. It sheds new light on the ongoing debate in the scientific community about the role of GDP as a measure for “economic success” [18, 19]
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