This study aims to demonstrate, through an econometric and Machine Learning approach, the health expenditure-economic growth nexus in China over the period 1980-2017. Describing the situation of the Chinese health system through the economic literature, we apply different econometric tests. The Toda and Yamamoto approach is crucial in our analysis: It highlights the existence of a bidirectional causal flow, running from health expenditure renew to GDP per capita and vice versa. This scenario respects the economic growth theory and hypothesis. Finally, in order to validate our results, as required by scientific models, we chose to test the econometric results obtained through a D2C algorithm in Machine Learning. At present, there is no evidence of other studies using this kind of approach in order to explain the health expenditure-economic growth nexus in China over this period.
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