Abstract
The crux of sustainability concerns hinges on humanity’s overshoot of our global carrying capacity, which we currently exceed by about 50 %. Overshoot of the earth’s natural resource bases militates against our current and future prospects for sustainability. Despite the theoretical and practical impetus to examine these dynamics, there is a dearth of empirical sociological research that analyzes overshoot. The paper fills this gap by offering a structural equation model of each nation’s relative contributions to overshoot. The model tests key theorizations in the environmental sociology, development, and global political-economy literatures, and adds to them by theorizing and empirically testing ecofeminist positions that the status of women affects and is affected by environmental conditions. Findings support ecofeminist interpretations that resource degradation yields adverse impacts on women and that their representation in government bodes well for the environment. The theoretical, empirical, and policy-based conclusions and implications are treated, as well as future areas of research.
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Notes
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.
The author notes the differences in “essentialist” versus “social constructivist” strands of ecofeminist approaches (Buckingham 2004; Warren 1987). The former articulates the relationship between women and nature as having biological origins, mostly relating to women as child bearers (e.g., Daly 1978). The latter emphasizes the influence of social and economic structures on women’s position in society (e.g., Rocheleau et al. 1996). Although important, engaging in this debate falls outside the parameters of the present effort, though the theoretical and empirical presentation is most consonant with social constructivist logic.
Rwanda and Mozambique are classified as “low-income” according to the World Bank (2013), and average 49 and 35 % female representation in parliament, respectively, from 2004 to 2006.
The author notes that women’s political representation is one (quantifiable) facet of women’s political status that is included in the model based on general theoretical tenets, empirical precedence, and data availability. Although imprecise in its uniformity with the universe of ecofeminist positions presented above, the measure likely captures corresponding dimensions of the status of women, including those that go beyond political realms.
What Sachs and Warner refer to as “natural resource abundance” is empirically measured by the ratio of natural resource exports to GDP (Sachs and Warner 1995, 2001), although this indicator has little to do with resource abundance. In fact, they candidly reject calculating “natural resources per capita so that GDP is not in the denominator,” by stating, “this is not a good solution because we want to measure the importance of natural resources in the economy, not just per capita.” (Sachs and Warner 2001:830). This is precisely the issue, what Sachs and Warner are more accurately measuring is resource dependency (or the degree to which domestic production and trade centers on primary sector commodities)—not resource abundance.
These relationships are specified in accordance with theoretically derived, causal hypotheses. Specifically, the model is time-ordered such that exogenous variables (circa years prior to 2000) precede mitigating variables (circa 2005), and all independent variables predate the outcome, taken for the year 2007. This specification facilitates, to some degree, inferring causality from a cross-sectional design.
These values are offered so that the reader may compare overshoot across countries. To ease interpretation of the results, after undergoing log transformations, the data were multiplied by the value, negative one, such that the larger values on the outcome variable indicate greater contributions to the overshoot of global carrying capacity.
Ecological footprint and biocapacity data are given in the same metric and subject to identical methods to control for productivity differentials across land use types and nations, making comparisons possible. See Ewing et al. (2010) for elaboration.
Per capita values are used for measures of the ecological footprint and biocapacity in the analysis.
Other features of national footprint accounting methods also lead to conservative estimates of overshoot, such as failing to consider what might be termed a “water footprint,” the inability to account for pollutants for which the biosphere is unable to reabsorb, and the exclusion of greenhouse gas emissions other than carbon dioxide. Readers are referred to Kitzes et al. (2007, 2009) for full discussion of the strengths and weaknesses of the current accounting approach and proposed revisions, as well as elaboration of the rationale guiding the accounting framework (see also Wackernagel and Rees 1996).
This time period is chosen based on the generally accepted view that “time lags of several decades” (Wackernagel et al 2004: 271) exist between changes to ecology and social impacts. % change in biocapacity was derived by dividing the biocapacity in 1971 by the change in biocapacity from 1971 to 2001: (T2 − T1)/T1. This value was then multiplied by negative one (*−1) to ease interpretation of results such that larger values indicate greater losses.
One anonymous reviewer inquired about the lack of a pathway from democracy to women’s representation. The model presented was re-estimated to include this relationship, which was positive but not statistically significant. This is not too surprising given similar findings of other recent efforts (see e.g., Paxton et al. 2006). The inclusion of the insignificant pathway worsened model fit and subverts the technical goal of separating the effects of democracy from those of women’s representation; thus, those results are not presented but the author will share them with any reader who requests them.
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. Readers are referred to Marshall et al. (2013) for full details on construction of the dataset.
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Acknowledgments
Thanks to Katherine Johnson for helpful conversations in the course of developing the manuscript and Theda Skocpol for her encouragement and enthusiasm surrounding the paper's findings. The author acknowledges the thoughtful suggestions of two anonymous reviewers and the editors.
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Appendix: Rank of the overshoot of nations (positive numbers represent surplus)
Appendix: Rank of the overshoot of nations (positive numbers represent surplus)
United Arab Emirates | −9.9 |
Qatar | −8 |
Belgium | −6.7 |
Kuwait | −5.9 |
Singapore | −5.3 |
Netherlands | −5.2 |
South Korea | −4.6 |
Israel | −4.5 |
Macedonia | −4.3 |
Saudi Arabia | −4.3 |
Japan | −4.1 |
USA | −4.1 |
Italy | −3.9 |
Greece | −3.8 |
Spain | −3.8 |
Switzerland | −3.8 |
Mauritius | −3.7 |
UK | −3.6 |
Denmark | −3.4 |
Portugal | −3.2 |
Germany | −3.2 |
Nepal | −3.1 |
Czech Republic | −3 |
Oman | −2.9 |
Ireland | −2.8 |
Libya | −2.7 |
Slovenia | −2.7 |
Lebanon | −2.5 |
Malaysia | −2.3 |
Gambia | −2.3 |
Poland | −2.2 |
Austria | −2 |
France | −2 |
Bulgaria | −2 |
Iran | −1.9 |
Jordan | −1.9 |
Jamaica | −1.5 |
Mexico | −1.5 |
Trinidad & Tobago | −1.5 |
Turkey | −1.4 |
Slovakia | −1.4 |
El Salvador | −1.3 |
China | −1.2 |
Croatia | −1.2 |
Cuba | −1.2 |
Serbia | −1.2 |
Thailand | −1.2 |
South Africa | −1.2 |
Armenia | −1.1 |
Bosnia & Herzegovina | −1.1 |
Egypt | −1.1 |
Azerbaijan | −1.1 |
Ukraine | −1.1 |
Algeria | −1 |
Dominican Republic | −1 |
Iraq | −1 |
Albania | −1 |
Tunisia | −0.9 |
Costa Rica | −0.8 |
Syrian Arab Republic | −0.8 |
Sri Lanka | −0.8 |
Uzbekistan | −0.8 |
Hungary | −0.8 |
Romania | −0.7 |
North Korea | −0.7 |
Philippines | −0.7 |
Guatemala | −0.7 |
Moldova | −0.7 |
Uganda | −0.7 |
Turkmenistan | −0.7 |
Georgia | −0.6 |
Ghana | −0.6 |
Morocco | −0.6 |
Kenya | −0.5 |
Belarus | −0.5 |
Kazakhstan | −0.5 |
Swaziland | −0.5 |
Viet Nam | −0.5 |
Ethiopia | −0.4 |
Burundi | −0.4 |
India | −0.4 |
Pakistan | −0.4 |
Rwanda | −0.4 |
Tajikistan | −0.4 |
Togo | −0.4 |
Haiti | −0.4 |
Benin | −0.4 |
Zimbabwe | −0.4 |
Lesotho | −0.3 |
Yemen | −0.3 |
Lithuania | −0.3 |
Nigeria | −0.3 |
Bangladesh | −0.2 |
Tanzania | −0.2 |
Niger | −0.2 |
Venezuela | −0.1 |
Afghanistan | −0.1 |
Cambodia | −0.1 |
Honduras | −0.1 |
Norway | −0.1 |
Burkina Faso | 0 |
Malawi | 0 |
Somalia | 0 |
Senegal | 0.1 |
Sierra Leone | 0.1 |
Kyrgyzstan | 0.1 |
Indonesia | 0.2 |
Myanmar | 0.2 |
Panama | 0.2 |
Laos | 0.3 |
Ecuador | 0.4 |
Chile | 0.6 |
Mali | 0.6 |
Côte d’Ivoire | 0.7 |
Sudan | 0.7 |
Eritrea | 0.7 |
Cameroon | 0.9 |
Botswana | 1.1 |
Estonia | 1.1 |
Guinea | 1.1 |
Mozambique | 1.1 |
Nicaragua | 1.2 |
Liberia | 1.2 |
Russia | 1.3 |
Madagascar | 1.3 |
Zambia | 1.4 |
Latvia | 1.5 |
Chad | 1.5 |
Papua New Guinea | 1.7 |
Congo (Dem Rep) | 2 |
Angola | 2 |
Colombia | 2.1 |
Guinea-Bissau | 2.2 |
Peru | 2.4 |
Mauritania | 2.9 |
Sweden | 3.8 |
Uruguay | 4.8 |
Argentina | 4.9 |
Namibia | 5.4 |
New Zealand | 5.9 |
Brazil | 6.1 |
Finland | 6.3 |
Central African Republic | 7.1 |
Australia | 7.9 |
Canada | 7.9 |
Paraguay | 8 |
Mongolia | 9.6 |
Congo | 12.3 |
Bolivia | 16.2 |
Gabon | 27.9 |
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McKinney, L. Gender, democracy, development, and overshoot: a cross-national analysis. Popul Environ 36, 193–218 (2014). https://doi.org/10.1007/s11111-014-0217-0
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DOI: https://doi.org/10.1007/s11111-014-0217-0