Abstract

The STochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model has become a widely employed methodological approach within social science research, largely used to understand the complex relationships between human social systems and the non-human environment. The general assumption of the model is that anthropogenic environmental impacts are a multiplicative function of population, affluence, and technology. While previous STIRPAT research has examined the impact of technology in terms of urbanization, estimating the specific effect of urban population, we argue that this measure is better understood as a proxy for modernization. As an alternative, we frame urbanization as a multidimensional driver of environmental change, and we operationalize the technology dimension through cross-national data on impervious surface area, or what we call ‘terrestrial technology’. To demonstrate the potential of this example for environmental sociology, we draw from political economy to show how operationalizing technology offers a stronger, more nuanced understanding of the socioeconomic drivers of environmental degradation. Analytically, we employ a spatial regression model that estimates the effect of terrestrial technology on total carbon emissions for 173 countries. Our results show that impervious surface area is positively related to total carbon output and thus should be considered an operational measure of technology in future STIRPAT analyses.

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