Modelling the economic effect of inbound birth tourism: a random forest algorithm approach

Sakiru Adebola Solarin (), Muhammed Sehid Gorus and Önder Özgür ()
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Sakiru Adebola Solarin: Multimedia University

Quality & Quantity: International Journal of Methodology, 2024, vol. 58, issue 5, No 10, 4223-4240

Abstract: Abstract Due to the tourism sector being one of the main drivers of economic growth in several countries, many studies have been conducted on the economic impact of the tourism sector. However, the economic effect of the different tourism activities, especially birth tourism has not been sufficiently explored in the existing literature. Using different proxies that capture the development of birth tourism, we examine the economic effect of birth tourism on economic growth in New Zealand for the period, 1980–2019. Novel machine-learning techniques including random forest algorithm and partial dependence plots have been used to estimate the relationship between the variables in a framework, which also include capital stock and financial development. The empirical findings of this study show that there is a non-linear relationship between per capita income and birth tourism-related variables in New Zealand. These results offer fresh insights to policymakers on the importance of birth tourism.

Keywords: Birth tourism; Economic growth; Tourism-led hypothesis; Machine learning; Random forest algorithm; New Zealand (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11135-024-01852-7

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