Julius Alexander McGee

Understanding the Jevons paradox

There is considerable debate about the connections between efficiency and levels of resource consumption, particularly about the Jevons paradox and the rebound effect. To help clarify a variety of misunderstandings, we distinguish between the empirical claim that efficiency is often associated with rising resource consumption and the causal claim that efficiency leads to greater resource use. We show that at a variety of levels, a positive correlation between efficiency and resource consumption is common, suggesting that there is something to be explained. We then present various reasons that may explain these associations, some of which do not suggest a direct causal link between efficiency and consumption, but rather a connection through other mediating factors, and some of which do suggest a causal connection. We note that political economic theories propose that the effect of efficiency on consumption levels is not necessarily immediate and direct, but rather due to how it affects developmental pathways. We present an empirical analysis, using panel data on nations, which shows that more efficient nations tend to have higher rates of growth in electricity and overall energy consumption and carbon dioxide emissions, consistent with what political economic theories suggest.

Does Renewable Energy Development Decouple Economic Growth from CO2 Emissions

We assess how renewable electricity production interacts with GDP per capita to influence CO2 emissions per capita, analyzing cross-national data from 1960 to 2012. We find an interaction effect between the quantity of renewables and GDP per capita, where, counterintuitively, economic growth is more closely tied to emissions in nations with a large share of their electricity from renewable sources and growth of renewable electricity has a smaller suppressive effect on emissions in more affluent nations. Additional analyses suggest that this relationship emerges because renewable energy sources tend to suppress nuclear energy in affluent nations, thereby unintentionally perpetuating reliance on fossil fuels.

The impacts of technology: a re-evaluation of the STIRPAT model

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.

Urban density and the metabolic reach of metropolitan areas: A panel analysis of per capita transportation emissions at the county-level.

We engage a tension in the urban environment literature that positions cities as both drivers of environmental destruction and loci of environmental protection. We argue that the traditional binary view of cities as either harmful or beneficial is too simplistic; we advance a more nuanced understanding of cities to study their internal and external metabolic effects in terms of carbon emissions from on-road transportation at the county-level across the continental United States between 2002 and 2007. First, utilizing satellite imagery from the National Land Cover Database, we create a novel measure of population density by quantifying the number of people per square mile of impervious surface area. Second, we develop a measure of metropolitan adjacency from the rural classifications datasets published by the USDA. In spatial regression models, we find that while higher density reduces emissions, counties that are geographically isolated from metropolitan areas actually have lower per capita emissions, all else equal. We elaborate on the conceptual, methodological, and practical implications of our study in the conclusion.

How do Slums Change the Relationship between Urbanization and the Carbon Intensity of Well-Being?

This study examines how the relationship between urbanization (measured as the percentage of total population living in urban areas) and the carbon intensity of well-being (CIWB) (measured as a ratio of carbon dioxide emissions and life expectancy) in most nations from 1960–2013 varies based on the economic context and whereabouts of a substantial portion of a nation’s urban population. To accomplish this, we use the United Nations’ (UN) definition of slum households to identify developing countries that have substantial slum populations, and estimate a Prais-Winsten regression model with panel-corrected standard errors (PCSE), allowing for disturbances that are heteroskedastic and contemporaneously correlated across panels. Our findings indicate that the rate of increase in CIWB for countries without substantial slum populations begins to slow down at higher levels of urbanization, however, the association between urbanization and CIWB is much smaller in countries with substantial slum populations. Overall, while urbanization is associated with increases in CIWB, the relationship between urban development and CIWB is vastly different in developed nations without slums than in under-developed nations with slums.

Divergent Pathways on the Road to Sustainability: A Multilevel Model of the Effects of Geopolitical Power on the Relationship between Economic Growth and Environmental Quality:

The authors examine the effect of a country’s placement in the world system in 1960 on its ability to use wealth to mitigate environmental impacts. They use random-coefficients models to examine if countries belonging to core, semiperiphery, and periphery categories are able to use growth in gross domestic product (GDP) per capita to reduce CO2 emissions per capita. The findings indicate that core nations have an attenuated relationship between GDP per capita and carbon dioxide emissions per capita at higher levels of economic activity. However, nations in the semiperiphery have a relationship between GDP per capita and CO2 per capita that approximates the curve of a U. Furthermore, the authors highlight the ability of random-coefficients models to examine which levels of analysis variation in the dependent variable is most associated with. They find that the majority of variation in CO2 emissions is correlated with time-invariant variables, not with time-variant predictors, such as GDP.