  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.
