Reinterpreting economic complexity in multiple dimensions

Önder Nomaler, Bart Verspagen
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Abstract

We build on the interpretation of the Economic Complexity method as Correspondence Analysis (CA), and propose that the Canonical form of CA (CCA), which originated in the ecology literature, can be used to calculate multi-dimensional economic complexity. The traditional (CA) way of calculating economic complexity includes no "external" information such as countries' development characteristics to facilitate interpretation of "complexity". This has led to a wide range of fairly ad hoc interpretations of economic complexity on the basis of ex-post correlation to a long list of other variables. By the ex-ante inclusion of a number of country variables in the construction of the complexity indicators, CCA enables better interpretation, also in the case of multi-dimensional indicators. The analysis is further facilitated by another element of the ecologists' toolbox, the so-called biplots, which are CCA-based graph embeddings that represent a lower-dimensional product-space in which products and countries are positioned together, in mutual correspondence to each other. We show that in this way, CCA provides a richer account of development in many of its aspects, especially economic growth.
从多个维度重新解读经济的复杂性
我们将经济复杂性方法解释为对应分析法(CA),并在此基础上提出,源于生态学文献的对应分析法的卡农形式(CCA)可用于计算多维经济复杂性。传统的(CA)经济复杂性计算方法不包括 "外部 "信息,如国家的发展特征,以方便对 "复杂性 "的解释。这就导致了对经济复杂性的一系列相当特别的解释,其依据是与一长串其他变量的事后相关性。通过在构建复杂性指标时事先纳入一些国家变量,共同国家评估可以更好地进行解释,在多维指标的情况下也是如此。生态学家工具箱中的另一个元素--所谓的双图(biplots)--进一步促进了分析的进行,双图是基于 CCA 的图嵌入,代表了一个低维度的产品空间,在这个空间中,产品和国家被定位在一起,相互对应。我们表明,通过这种方式,CCA 可以更丰富地描述发展的许多方面,尤其是经济增长。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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