EARLY EVIDENCE ON RECREATIONAL MARIJUANA LEGALIZATION AND TRAFFIC FATALITIES

Over the last few years, marijuana has become legally available for recreational use to roughly a quarter of Americans. Policy makers have long expressed concerns about the substantial external costs of alcohol, and similar costs could come with the liberalization of marijuana policy. Indeed, the fraction of fatal accidents in which at least one driver tested positive for tetrahydrocannabinol has increased nationwide by an average of 10% from 2013 to 2016. For Colorado and Washington, both of which legalized marijuana in 2014, these increases were 92% and 28%, respectively. However, identifying a causal effect is difficult due to the presence of significant confounding factors. We test for a causal effect of marijuana legalization on traffic fatalities in Colorado and Washington with a synthetic control approach using records on fatal traffic accidents from 2000 to 2016. We find the synthetic control groups saw similar changes in marijuana-related, alcohol-related, and overall traffic fatality rates despite not legalizing recreational marijuana. (JEL K42, I12, I18)     

Research on Marital Satisfaction and Stability in the 2010s: Challenging Conventional Wisdom

Although getting married is no longer a requirement for social acceptance, most people do marry in their lifetimes, and couples across the socioeconomic spectrum wish their marriages to be satisfying and long lasting. This review evaluates the past decade of research on the determinants of satisfaction and stability in marriage, concluding that the scholarship of the past 10 years has undermined three assumptions that were formerly accepted as conventional wisdom. First, research exploiting methods such as latent class growth analyses reveal that, for most couples, marital satisfaction does not decline over time but in fact remains relatively stable for long periods. Second, contrary to predictions of behavioral models of marriage, negative communication between spouses can be difficult to change, does not necessarily lead to more satisfying relationships when it is changed, and does not always predict distress in the first place. Third, dyadic processes that are reliably adaptive for middle-class and more affluent couples may operate differently in lower income couples, suggesting that influential models of marriage may not generalize to couples living in diverse environments. Thus, the accumulated research of the past 10 years indicates that the tasks of understanding and promoting marital satisfaction and stability are more complex than we appreciated at the start of the decade, raising important questions that beg to be answered in the years ahead.     

“Big Brother’s Bigger Brother”: The Visual Politics of (Counter) Surveillance in Baltimore

In 2016, without the knowledge of its citizens, Baltimore City Police deployed a military aerial surveillance technology called Wide Area Motion Imagery (WAMI), which can track the movements of every person in public view over the entire city. Though the trial of the “spy plane,” as the program was dubbed, quickly ended in scandal, organizers from Baltimore’s low-income minority neighborhoods successfully rebooted the program in 2020, this time framing WAMI partly as a tool of “sousveillance” (watching “from below”) that can track the movements of police officers. The paper shows how organizers “rebranded” WAMI around two conceptions of sousveillance—“citizen-centered” and “state-centered”—creating an unlikely coalition of supporters from both pro- and anti-policing sides of the criminal justice reform debate. But while the renewed program has vowed to be a “Big Brother” to the state, it will continue to be used for traditional surveillance, raising troubling questions about privacy. The article sheds light on the politics of watching and being watched in the era of technology-driven criminal justice reform.     

Conditional covariance penalties for mixed models

The prediction error for mixed models can have a conditional or a marginal perspective depending on the research focus. We introduce a novel conditional version of the optimism theorem for mixed models linking the conditional prediction error to covariance penalties for mixed models. Different possibilities for estimating these conditional covariance penalties are introduced. These are bootstrap methods, cross-validation, and a direct approach called Steinian. The behavior of the different estimation techniques is assessed in a simulation study for the binomial-, the t-, and the gamma distribution and for different kinds of prediction error. Furthermore, the impact of the estimation techniques on the prediction error is discussed based on an application to undernutrition in Zambia.     

Risk–risk governance in a low-carbon future: Exploring institutional,technological, and behavioral tradeoffs in climate geoengineering pathways

Deliberations are underway to utilize increasingly radical technological options to help address climate change and stabilize the climatic system. Collectively, these options are often referred to as “climate geoengineering.” Deployment of such options, however, can create wicked tradeoffs in governance and require adaptive forms of risk management. In this study, we utilize a large and novel set of qualitative expert interview data to more deeply and systematically explore the types of risk–risk tradeoffs that may emerge from the use of 20 different climate geoengineering options, 10 that focus on carbon dioxide or greenhouse gas removal, and 10 that focus on solar radiation management and reflecting sunlight. We specifically consider: What risks does the deployment of these options entail? What types of tradeoffs may emerge through their deployment? We apply a framework that clusters risk–risk tradeoffs into institutional and governance, technological and environmental, and behavioral and temporal dimensions. In doing so, we offer a more complete inventory of risk–risk tradeoffs than those currently available within the respective risk-assessment, energy-systems, and climate-change literatures, and we also point the way toward future research gaps concerning policy, deployment, and risk management.     

Competitive and Cooperative Positioning in Supply Chain Logistics Relationships*

Cooperative logistics relationships require the sharing of information, which must be enabled by the integration of disparate information systems across partners. In this article, we theorize business‐to‐business logistics relationships should be managed using cooperative and competitive postures. Based on data from 91 dyadic relationships using interorganizational information technology (IT), we find that performance gains accrue when parties share strategic information and customize IT; mutual trust enables IT customization and strategic‐information flows and equitable relationship‐specific investments positively impact IT customization, mutual trust, and performance. Among other scholarly and practical implications discussed, partners should compete on resources for IT customization and cooperate to share strategic information. Managers tend to think of relationships with firms as polar opposites and view them as entirely cooperative or entirely competitive. Our results support active balancing and understanding of both competitive and cooperative stances. Such an approach enables conditions for participation symmetry that yields greater performance gains.     

A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.