Economic Complexity and Human Development: Comparing Traditional and Slack Based Data Envelopment Analysis Models

Diogo Ferraz, H. F. Moralles, N. D. Costa, D. Rebelatto
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引用次数: 2

Abstract

Several studies argue that economic growth cannot well explain human development. The economic complexity approach is an alternative understanding of how economic sophistication can affect well-being. Moreover, there is increasing literature using traditional Data Envelopment Analysis (DEA) models to measure the transformation of wealth into human development. However, we did not find studies comparing more advanced models, such as Slack Based Models (SBM), and which considers the economic sophistication as an input to generate human development. To fill this gap, the aim of this article is to compare traditional and SBM-DEA models, measuring the countries' efficiency in converting economic complexity into human development. We analyzed 50 countries through Data Envelopment Analysis (DEA) in 2013, comparing Constant and Variable returns of scale traditional and Slack Based models. We also proposed the Composite Index of Human Development and Economic Complexity (CIHD-EC). Our findings show that the traditional variable return of scale model tends to overestimate efficient countries. It occurs especially in developed and rich economies. In contrast, the slack-based model provides a better understanding of the problem under analysis. Finally, our CIHD-EC shows that only Singapore is efficient to transform economic complexity into human development around the world.
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经济复杂性与人类发展:比较传统和基于Slack的数据包络分析模型
一些研究认为,经济增长不能很好地解释人类的发展。经济复杂性方法是对经济复杂性如何影响福祉的另一种理解。此外,越来越多的文献使用传统的数据包络分析(DEA)模型来衡量财富向人类发展的转化。然而,我们没有发现比较更先进的模型的研究,例如基于Slack的模型(SBM),该模型将经济复杂性视为产生人类发展的输入。为了填补这一空白,本文的目的是比较传统模型和SBM-DEA模型,衡量各国将经济复杂性转化为人类发展的效率。2013年,我们通过数据包络分析(DEA)对50个国家进行了分析,比较了规模传统模型和基于Slack模型的不变收益和可变收益。提出了人类发展与经济复杂性综合指数(CIHD-EC)。研究结果表明,传统的规模变量收益模型往往高估了效率国家。这种情况在发达国家和富裕国家尤为常见。相比之下,基于松弛的模型可以更好地理解所分析的问题。最后,我们的CIHD-EC表明,只有新加坡能够有效地将经济复杂性转化为人类发展。
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