Inferring comparative advantage via entropy maximization

Abstract

We revise the procedure proposed by Balassa to infer comparative advantage, which is a standard tool, in Economics, to analyze specialization (of countries, regions, etc.). Balassa's approach compares the export of a product for each country with what would be expected from a benchmark based on the total volumes of countries and products flows. Based on results in the literature, we show that the implementation of Balassa's idea generates a bias: the prescription of the maximum likelihood used to calculate the parameters of the benchmark model conflicts with the model's definition. Moreover, Balassa's approach does not implement any statistical validation. Hence, we propose an alternative procedure to overcome such a limitation, based upon the framework of entropy maximisation and implementing a proper test of hypothesis: the `key products' of a country are, now, the ones whose production is significantly larger than expected, under a null-model constraining the same amount of information employed by Balassa's approach. What we found is that countries diversification is always observed, regardless of the strictness of the validation procedure. Besides, the ranking of countries' fitness is only partially affected by the details of the validation scheme employed for the analysis while large differences are found to affect the rankings of products Complexities. The routine for implementing the entropy-based filtering procedures employed here is freely available through the official Python Package Index PyPI.

References in corpus (14)

• The Building Blocks of Economic Complexity
• The statistical mechanics of networks
• The Statistical Physics of Real-World Networks
• Nestedness in complex networks: Observation, emergence, and implications
• Maximum likelihood: extracting unbiased information from complex networks
• Inferring monopartite projections of bipartite networks: an entropy-based approach
• Enhanced reconstruction of weighted networks from strengths and degrees
• Economic Development and Inequality: a complex system analysis
• Unfolding the innovation system for the development of countries: co-evolution of Science, Technology and Production
• On the convergence of the Fitness-Complexity Algorithm
• Fast and scalable likelihood maximization for Exponential Random Graph Models with local constraints
• A new and stable estimation method of country economic fitness and product complexity
• A faster horse on a safer trail: generalized inference for the efficient reconstruction of weighted networks
• Grand canonical validation of the bipartite International Trade Network

Cited by in corpus (2)

• Pattern detection in bipartite networks: a review of terminology, applications and methods
• Maximum entropy modeling of Optimal Transport: the sub-optimality regime and the transition from dense to sparse networks