Abstract
Obesity has become a global health crisis, affecting people of all ages, regions, and socio-economic backgrounds. While individual behaviour and genetic factors contribute to obesity, the role of economic complexity in the evolution of obesity rates has not yet been empirically studied. Using a large panel of 110 countries over the period 1976–2015, this article estimates the linear and non-linear links between obesity and economic complexity. According to baseline results, an improvement in economic complexity will lead to an increase in obesity up to a certain threshold. Beyond this turning point, any further increase in economic complexity will significantly contribute to obesity reduction. The issue of simultaneity is tackled using the two-stage instrumental variable method. Our findings support the Obesity Kuznets Curve (OKC) pattern, which suggests that economic progress and obesity have an inverted U-shaped relationship. Our results suggest that greater embeddedness of knowledge in the products produced and exported by a country increases the likelihood of obesity in society, at least up to a threshold. From these results, some important policy implications are discussed.
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Source: Authors’ construction from WHO data
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Source: Authors’ construction
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Source: Authors’ construction
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Data availability
Data will be made availabe upon reasonable request from the authors.
Notes
Thus, we have eight non-overlap** five-year intervals: 1976–1980; 1981–1985; 1986–1990; 1991–1995; 1996–2000; 2001–2005; 2006–2010 and 2011–2015.
Suleman Dawood School of Business, LUMS, Pakistan.
We limit ourselves to adopting a broad definition of regions according to the World Bank classification.
Chiappini et al. [30] take a similar approach in the FDI-health relationship by assuming that a specific country's level of inward FDI in a given year is highly dependent on the level of inward FDI of its neighbours, especially from the previous period. Similarly, in order to mitigate endogeneity problems in the political stability-equality relationship, Vu [108] uses the level of political instability of neighboring countries as an instrumental variable for a country's own political instability.
There are empirical approaches to identifying robust determinants of obesity, such as the Extreme Bounds Analysis (EBA) proposed by Sala-I-Martin [94]. EBA is a relatively neutral procedure by which variables can be selected for an empirical model when the theoretical determinants of a phenomenon are ambiguous or conflicting. While this approach is interesting and robust, we assume that the determinants highlighted in this article are regularly cited in recent literature as drivers of obesity. Moreover, given that it is impossible to control for all observable and unobservable drivers of obesity, we limit ourselves to applying the procedure proposed by Oster [83], which is more recent. This robust approach has also been implemented by more recent studies in health economics (see Vu [107],Mohanty and Saxena [85],Ahsan and Thakur [3]).
See https://news.un.org/en/story/2022/03/1113312. Accessed November 18, 2022.
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We are very grateful to the journal editor and the three anonymous reviewers for their constructive comments and helpful suggestions. Our gratitude also goes to Eric Tamno for his constructive suggestions. All other errors are our own.
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This study was funded by LUMS Research Grant (OVH122-SDB-Ummad).
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Djeunankan, R., Tadadjeu, S., Njangang, H. et al. The hidden cost of sophistication: economic complexity and obesity. Eur J Health Econ (2024). https://doi.org/10.1007/s10198-024-01699-7
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DOI: https://doi.org/10.1007/s10198-024-01699-7