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<p>The general objective in this article is to determine the effect of soft power on vulnerability to climate change. In other words, the effects of soft power on the capacity to adapt to climate change. Using a sample of 107 countries of cross-section data, the study adopts a triple empirical strategy; firstly, controlling heterogeneity problems using the OLS approach absorbing several fixed effect levels. Secondly, based on an evaluation of potential selection bias due to unobservable elements (Oster in J Bus Econ Stat 37: 2 187–204, 2019), the model is controlled by adding variables of various origins (geographic, historical-institutional, etc.). Third, the empirical strategy adopts a two-step instrumental variables approach to resolve plausible sources of endogeneity (Baum An introduction to modern econometrics using stata, Stata Press, College Station, 2006). At the end of the analyses, the results illustrate a negative effect of soft power on vulnerability to climate change; in other words, an improvement in the level of soft power reduces vulnerability to climate change through the level of social adaptation. More specifically, this effect is pronounced in the MENA region. The results remain robust when applying alternative approaches to controlling endogeneity, such as the Lewbel approach (J Bus Econ Stat 30:(1) 67–80, 2012), Conley et al. (Rev Econ Stat 94(1):260–272, 2012) and Kiviet (J Econom 218(2): 294–316, 2020).</p>

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From Attraction to Adaptation: How Soft Power Reduces Climate Vulnerability

  • 期刊论文

  • 发表日期：

    2026年2月9日

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  • Dieudonné Mignamissi,
  • Eric Xaverie Possi Tebeng

摘要

The general objective in this article is to determine the effect of soft power on vulnerability to climate change. In other words, the effects of soft power on the capacity to adapt to climate change. Using a sample of 107 countries of cross-section data, the study adopts a triple empirical strategy; firstly, controlling heterogeneity problems using the OLS approach absorbing several fixed effect levels. Secondly, based on an evaluation of potential selection bias due to unobservable elements (Oster in J Bus Econ Stat 37: 2 187–204, 2019), the model is controlled by adding variables of various origins (geographic, historical-institutional, etc.). Third, the empirical strategy adopts a two-step instrumental variables approach to resolve plausible sources of endogeneity (Baum An introduction to modern econometrics using stata, Stata Press, College Station, 2006). At the end of the analyses, the results illustrate a negative effect of soft power on vulnerability to climate change; in other words, an improvement in the level of soft power reduces vulnerability to climate change through the level of social adaptation. More specifically, this effect is pronounced in the MENA region. The results remain robust when applying alternative approaches to controlling endogeneity, such as the Lewbel approach (J Bus Econ Stat 30:(1) 67–80, 2012), Conley et al. (Rev Econ Stat 94(1):260–272, 2012) and Kiviet (J Econom 218(2): 294–316, 2020).