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Building on cornerstone traditions in historical sociology, as well as work in environmental sociology and political-economic sociology, we theorize and investigate with moderation analysis how and why national militaries shape the effect of economic growth on carbon pollution. Militaries exert a substantial influence on the production and consumption patterns of economies, and the environmental demands required to support their evolving infrastructure. As far-reaching and distinct characteristics of contemporary militarization, we suggest that both the size and capital intensiveness of the world’s militaries enlarge the effect of economic growth on nations’ carbon emissions. In particular, we posit that each increases the extent to which the other amplifies the effect of economic growth on carbon pollution. To test our arguments, we estimate longitudinal models of emissions for 106 nations from 1990 to 2016. Across various model specifications, robustness checks, a range of sensitivity analyses, and counterfactual analysis, the findings consistently support our propositions. Beyond advancing the environment and economic growth literature in sociology, this study makes significant contributions to sociological research on climate change and the climate crisis, and it underscores the importance of considering the military in scholarship across the discipline.

Modeling asymmetric relationships is an emerging subject of interest among sociologists. York and Light advanced a method to estimate asymmetric models with panel data, which was further developed by Allison. However, little attention has been given to the large- N, large- T case, wherein autoregression, slope heterogeneity, and cross-sectional dependence are important issues to consider. The authors fill this gap by conducting Monte Carlo experiments comparing the bias and power of the fixed-effects estimator to a set of heterogeneous panel estimators. The authors find that dynamic misspecification can produce substantial biases in the coefficients. Furthermore, even when the dynamics are correctly specified, the fixed-effects estimator will produce inconsistent and unstable estimates of the long-run effects in the presence of slope heterogeneity. The authors demonstrate these findings by testing for directional asymmetry in the economic development–CO2 emissions relationship, a key question in macro sociology, using data for 66 countries from 1971 to 2015. The authors conclude with a set of methodological recommendations on modeling directional asymmetry.

Prior reviews have discussed the potential relationship between global economic integration and smoking prevalence, but for the most part, these non-empirical studies have only offered speculative observations. This cross-national study employs two-way fixed effects regression models and a three-way interaction to test whether integration into the global economy, measured as imports (% of GDP), affects male and female smoking prevalence across country income groups (developed vs. less developed nations) and time from 2000 to 2015. We observe that the effect of global economic integration on female smoking prevalence increased in magnitude over time in both income groups, but we see no such effect on male smoking prevalence. The effect does not differ by income group. We conclude by discussing the theoretical implications of our findings, along with policy recommendations.

This study tests whether greater political equality at the nation-state level moderates economic growth’s association with production-based and consumption-based CO2 emissions. Based on data for 10...

The demand-side perspective argues that the drug overdose epidemic is a consequence of changes in the economy that leave behind working-class people who lack a college education. In contrast, the supply-side perspective maintains that the epidemic is primarily due to changes in the licit and illicit drug environment, whereas a third, distinct perspective argues that income inequality is likely a key driver of the epidemic. To evaluate these competing perspectives, we use a two-level random intercept model and U.S. state-level data from 2006 to 2017. Contrary to the demand-side approach, we find that educational attainment is not associated with drug-related mortality. In support of the supply-side approach, we provide evidence indicating that opioid prescription rates are positively associated with drug-related mortality. We also find that income inequality is a key driver of the epidemic, particularly the lack of resources going to the bottom 20% of earners. We conclude by arguing that considerations of income inequality are an important way to link the arguments made by the demand-side and the supply-side perspectives.

Societies need to transition to renewable energy and eliminate fossil fuel use as soon as possible. However, policymakers have mostly neglected to consider that there is an array of possible energy transition pathways. Therefore, I offer a typology that envisions potential energy futures as falling along a two-dimensional model comprised of the structural organization of the social (political, economic, and civil) on one axis — on a spectrum of democratic versus monopolistic — and the scale of the energy system on the other — dichotomized as centralized versus decentralized. This typology suggests that there are four potential energy futures, which I term: (1) libertarian energy decentralism, (2) technocratic energy centralism, (3) democratic energy centralism, and (4) democratic energy decentralism. These four futures are not equal in terms of power, equity, and ecological impact. I argue that the democratization of the social is necessary to facilitate a “just transition,” but the scale of the energy system will also play a pivotal role in reinforcing and reproducing democratic and just social relations.

The macro-comparative decoupling literature has often sought to test the arguments made by the treadmill of production (TP) and ecological modernization (EM) theories. However, due to data limitations, these studies have been limited to analyzing the years after 1960. Given that both theories discuss historical processes operating before 1960, analyzing pre-1960 data is warranted to more comprehensively test the propositions made by both theories. We assess the long-term relationship between economic growth and CO2 emissions from 1870 to 2014 using a sample of global North nations. We use Prais-Winsten regression models with time interactions to assess whether, when, and how much CO2 emissions have decoupled from economic growth over time. We find that significant relative decoupling has occurred twice since 1870: during the last 30 years of the nineteenth century, the timing of which is contrary to what both the EM and TP theories might expect, and after 1970. We also observe that the relationship remained relatively stable from the turn of the twentieth century to approximately 1970, which aligns with the arguments made by the classical TP work. We conclude that shifts in the global organization of production have shaped the magnitude of the economic growth–CO2 emissions relationship and its changes over time, which has implications for climate mitigation policy.

This study contributes to interdisciplinary research on the social and environmental determinants of population health, with a focus on the interaction between working hours and fine particulate matter (PM2.5) concentration. The authors estimate longitudinal models of the relationship between US state-level average life expectancy and both average working hours and PM2.5 concentration for the 2005-2014 period. Results obtained from two-way fixed effects models indicate that average life expectancy is negatively associated with both average working hours and fine particulate matter concentration. Findings also indicate clear moderating relationships: the negative association between life expectancy and working hours is amplified as PM2.5 concentration increases, and the negative relationship between life expectancy and fine particulate matter concentration is amplified when average working hours increase. The results of this study underscore the need for additional research on the multiplicative impacts of socioeconomic factors and environmental factors in the modeling of population health.

This study investigates the possibly changing relationship between non-fossil fuel energy sources (biomass, geothermal, hydro, nuclear, solar, and wind) and CO2 emissions over the temporal period 2000 to 2013. The results from two-way fixed effects longitudinal models demonstrate that the carbon elasticities of these energy sources change over time but not symmetrically. Wind’s association with CO2 emissions became increasingly negative after the Great Recession (i.e., suppressed emissions at a greater rate). Nuclear’s association with CO2 resembled a distorted U-shaped curve over time. Biomass’ elasticity fluctuated between positive and negative values. Solar and geothermal’s elasticity remained fairly consistent over the course of the analysis, and hydro’s elasticity increased over time but remained negative throughout the study’s temporal period. The study provides several tentative explanations for these findings. Overall, the results suggest there are various processes at play that influence an energy source’s relation to CO2 emissions.

Ambient air pollution, in the form of fine particulate matter (PM2.5), poses serious population health risks. We estimate cross-national longitudinal models to test whether the negative relationship between life expectancy and PM2.5 concentration is larger in nations with higher levels of income inequality. The dependent variable is average life expectancy at birth, and the focal predictor variables include PM2.5 concentration, income inequality, and the two-way interaction between them. We also estimate the average marginal effects of PM2.5 concentration from low to high values of income inequality, and the predicted values of life expectancy from low to high values of PM2.5 concentration and income inequality. Results indicate that the negative relationship between life expectancy and PM2.5 concentration is larger in nations with higher levels of income inequality, and the reductions in predicted life expectancy are substantial when both PM2.5 concentration and income inequality are high. We suggest that the theoretical principles of Power, Proximity, and Physiology help explain our findings. This study underscores the importance in considering the multiplicative impacts of environmental conditions and socioeconomic factors in the modeling of population health.

While an extensive body of social science research focuses on the interrelationships among economic development, energy systems, and the environment, studies involving the analysis of historical time series data are limited outside the field of economics. Along with the typical statistical challenges that accompany longitudinal data, time series data are likely to experience time-variation and bidirectionality in their relationships with one another. We address these issues and illustrate the utility of semiparametric, time-varying vector autoregressive (VAR) models for analyzing socioecological relationships. We analyze data for the United States from 1870 to 2017, and show how the relationships between GDP per capita, trade openness, fossil fuel intensity, and GHG emissions per capita have changed over time. We conclude by suggesting potential avenues for future research that use these methods.

A central premise of development strategies is that nations use natural resources, such as fossil fuels, to raise population living standards and enhance well-being. However, research shows that the relationship among human well-being, resource use, and the associated emissions is complex and context specific. To better understand if natural resource use plays a historic role in generating human well-being in the United States, the authors conduct a time-series analysis of greenhouse gas emissions and average life expectancy from 1913 to 2017. The results show that increases in greenhouse gas emissions per capita have an instantaneous, negative effect on life expectancy. The authors also find evidence that income inequality has a long-run negative effect on life expectancy. Additional analyses provide mixed results regarding whether and how the effects of emissions on life expectancy are conditional on income inequality. These findings contradict the assumption that reductions in emissions necessitate trade-offs in human well-being in high-income contexts.

This study investigates the effect that Leadership in Energy and Environmental Design (LEED) had on academic performance using a difference-in-differences (DID) estimator using data from the years 2006&ndash, 2016. By obtaining data from the Ohio Department of Education and the Ohio Facilities Construction Commission, this investigation examines the effect that LEED design had on the Student Performance Index for schools that opened in the year 2012. Each LEED school was matched with a non-LEED school based on several criteria. The study determined that LEED did not have an impact on the Student Performance Index. Though we find no relationship, green schools do provide educational opportunities that standard buildings do not. We suggest that the state of Ohio should take advantage of potentially untapped opportunities in their green schools program that could enhance both social and ecological sustainability.