Economic Complexity Unfolded: Interpretable Model for the Productive Structure of Economies

TL;DR

This paper introduces a probabilistic, interpretable Bayesian non-parametric model to uncover the hidden capabilities underlying a country's economic complexity, using trade data and a culinary metaphor for capability acquisition.

Contribution

It presents a novel Bayesian non-parametric framework with Indian Buffet Process priors for extracting and interpreting economic capabilities from trade data.

Findings

Provides a concise description of capabilities behind economic complexity.

Offers an interpretable model linking capabilities to export patterns.

Demonstrates the model's effectiveness with economic trade data.

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.