For many Global South countries, domestic demand for cultural goods cannot sustain the livelihoods of cultural workers. Expanding exports is therefore essential, yet access to Global North markets remains constrained by persistent trade barriers. This article examines the determinants of cultural goods imports from the Global South, with a focus on Chile as a representative case. Using a dataset of Chilean cultural exports from 2005 to 2015, the study combines a Logit binary choice model with a Random Forests algorithm to identify and rank the most influential predictors of import likelihood. The Logit analysis shows that shorter distances, shared language, cultural proximity, political stability, and preferential trade agreements increase the probability of trade, while partial scope agreements reduce it. Machine learning results reinforce the importance of strong macroeconomic performance, higher capital stock, and robust institutions, alongside comprehensive trade frameworks, especially economic integration agreements, free trade agreements, and preferential trade agreements. Cultural affinity, proxied by a common language, also emerges as a consistent positive factor. By integrating econometric and predictive modelling, this research isolates the key variables shaping cultural trade and translates them into strategic guidance for policymakers. The findings point to actionable pathways for Global South exporters to diversify markets, strengthen trade partnerships, and improve the economic resilience of their creative sectors.
Matías Alberto Muñoz Hernández (Wed,) studied this question.