The purpose of this paper is to gain empirical footing on the mechanisms that drive and mitigate global warming, which is a topic of growing significance to themes of social justice. Using components of the ecological footprint, we construct a measure of each nation’s relative contributions to carbon dioxide emissions after accounting for the amount sequestered by domestic forestlands. We refer to this measure as the “climate footprint,” and construct a structural equation model to test key theorizations in the environmental sociology literature. We add to this body of work by incorporating and empirically testing ecofeminist positions that the status of women is a cause and an effect of environmental conditions. Results suggest women and the environment are interconnected dimensions of exploitation, as ecological losses weaken women’s status in nations. We also find that nations with greater female representation in governing bodies have lower climate footprints, controlling for domestic (urbanization, production) and global (world-system integration) drivers. Conclusions point to the potential for gender equality and improving the status of women worldwide to curtail climate change. Other theoretical and empirical implications are treated, including the benefits of bringing women into theories of the environment and the utility of structural equation techniques for testing hypotheses that specify direct and indirect connections among relevant predictors and the outcome.
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Forest land calculations include demands on forest materials (e.g., food, fiber, fuelwood) as well as the forest area needed to absorb the carbon dioxide gases generated from the burning of fossil fuels.
These values are offered so readers may compare the climate footprint of countries. To ease interpretation of the analysis, these values were multiplied by negative one such that larger values on the outcome variable indicate the generation of carbon dioxide that accelerates global warming.
We note the internal debate across “essentialist” versus “social constructivist” strands of ecofeminist approaches (Buckingham, 2004; Warren, 1987). The former attributes the relationship between women and nature to biological origins (e.g., Daly, 1978); the latter traces the relationship to social and economic structures (e.g., Rocheleau, Thomas-Slayter, & Wangari, 1996). Although engaging this debate falls beyond the scope of this paper, we note that our presentation is more consonant with the social constructivist logic.
One anonymous reviewer referred us to the work of Ehrlich and Ehrlich (2013) that touts the potential for reducing footprints by extending full rights, education, and opportunities to women as a means to foster reductions in fertility.
To ease interpretation, we remind readers that higher values for climate footprints are indicative of unsustainable demands on nature.
To quote Bollen (1989:vi), “Structural equation models are not very helpful if you have little idea about the subject matter. To begin the fitting process, the analysts must draw upon their knowledge to construct a multiequation system that specifies the relations between all latent variables, disturbances, and indicators. Furthermore they must turn to substantive information when respecifying models and when evaluating the final model. Empirical results can reveal that initial ideas are in error or they can suggest ways to modify a model, but they are given meaning only within the context of a substantively informed model.” We have had the same experience of Bollen (1989:vi), who states, “I frequently have found that the beginning model does not adequately describe the data. Respecification is often necessary.”
Although longitudinal methods can be, and have been, applied to assess claims of causality, we are cautious of doing so in this particular context for a few reasons. First, emerging scholarship deeply cautions against the use of repeated measures designs, particularly in the context of quantitative macro-comparative research (see e.g., Babones, 2013). Second, the ecological footprint and biocapacity data from which we draw are subject to transformations based on the annual average productivity yields for each respective year. Thus, year-to-year fluctuations capture changes in consumption dynamics and resource stocks, in addition to spikes in productivity that result from technological advances, gains in efficiency, and ecosystem management differentials. In sum, comparing these data overtime is complicated in the extreme (see e.g., Haberl, Erb, & Krausmann, 2001; Kitzes et al., 2009). Finally, the relatively under-explored nature of the dynamics analyzed makes the SEM estimation a sensible first step.
In order to perform logarithmic transformation, a constant first had to be added to eliminate negative values. The constant is calculated as the absolute value of smallest number plus one. This preserves the distribution of the data while allowing for logging techniques to meet assumptions of normality.
Following Nugent and Shandra (2009), the year women received full voting rights is subtracted from 2004 to indicate the number of years that women have had full recognition. The five nations included in the analysis (United Arab Emirates, Oman, Qatar, Saudi Arabia, and Serbia) in which women have not yet received full voting rights are given a value of ‘0’ for this variable.
The POLITY2 score is used in the analysis, which removes special codes: “−66” (foreign occupation), “−77” (collapse of centralized authority), and “−88” (transitional government) and treats them as system missing, “0”, and prorated polity scores across transition periods, respectively. We refer readers to Marshall, Gurr, and Jaggers (2013) for full details on dataset construction.
In an alternative specification, we included squared terms of the modernization indicators to assess the plausibility of an Environmental Kuznet’s Curve (results available upon request). This modification produced unacceptable fit statistics and essentially uninterpretable results.
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See Table 2.
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McKinney, L.A., Fulkerson, G.M. Gender Equality and Climate Justice: A Cross-National Analysis. Soc Just Res 28, 293–317 (2015). https://doi.org/10.1007/s11211-015-0241-y