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

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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.

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Authors and Affiliations

  1. Faculty of Business, Multimedia University, Melaka, Malaysia

    Sakiru Adebola Solarin

  2. Department of Economics, Faculty of Political Sciences, Ankara Yildirim Beyazit University, Ankara, Turkey

    Muhammed Sehid Gorus & Onder Ozgur

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  1. Sakiru Adebola Solarin
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  2. Muhammed Sehid Gorus
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  3. Onder Ozgur
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by MSG and OO. The first draft of the manuscript was written by SAS and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Sakiru Adebola Solarin.

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Solarin, S.A., Gorus, M.S. & Ozgur, O. Modelling the economic effect of inbound birth tourism: a random forest algorithm approach. Qual Quant (2024). https://doi.org/10.1007/s11135-024-01852-7

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