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A new class of tests of contagion is proposed identifying transmission channels of financial market crises through changes in higher order moments of the distribution of returns such as coskewness. Applying the framework to test for contagion in real estate and equity markets following the Hong Kong crisis in 1997-1998 and the U.S. subprime crisis in 2007 shows that the coskewness-based tests of contagion detect additional channels not identified by the correlation-based tests. Implications of contagion in pricing exchange options where there is a change in higher order comoments of returns on the underlying assets are also investigated.

The Australian Electricity Market Operator generates one-day ahead electricity demand forecasts for the National Electricity Market in Australia and updates these forecasts over time until the time of dispatch. Despite the fact that these forecasts play a crucial role in the decision-making process of market participants, little attention has been paid to their evaluation and interpretation. Using half-hourly data from 2011 to 2015 for New South Wales and Queensland, it is shown that the official half-hourly demand forecasts do not satisfy the econometric properties required of rational forecasts. Instead there is a relationship between forecasts and forecast horizon similar to a term structure model of interest rates. To study the term structure of demand forecasts, a factor analysis that uses a small set of latent factors to explain the common variation among multiple observables is implemented. A three-factor model is identified with the factors admitting interpretation as the level, slope and curvature of the term structure of forecasts. The validity of the model is reinforced by assessing the economic value of demand forecasts. It is demonstrated that simple adjustments to long-horizon electricity demand forecasts based on the three estimated factors can enhance the informational content of the official forecasts.

An empirical model of multiple asset classes across countries is formulated in a latent factor framework. A special feature of the model is that financial market linkages during periods of financial crises, including spillover and contagion effects, are formally specified. The model also captures a range of common factors including global shocks, country and market shocks, and idiosyncratic shocks. The framework is applied to modelling linkages between currency and equity markets during the East Asian financial crisis of 1997-98. The results provide strong evidence that cross-market links are important. Spillovers have a relatively larger effect on volatility than contagion, but both are statistically significant.

Although water supply diversification has been proposed as a solution to dwindling water reserves, the optimal mix of natural and manufactured sources of water remains largely unexplored. We develop a dynamic portfolio model of water supply that hedges against the supply risks from all potential water sources, by taking into account the size of water reserves, uncertainties of water flows as well as differences in supply costs. The optimal portfolio shares for an existing water supply system are derived and compared with the observed contributions to total water stock, revealing unexploited hedging opportunities between various naturally occurring water sources as well as a general over-reliance on manufactured water. The optimal solution implies that future supply augmentations should target natural sources of water ahead of manufactured water. It is estimated that the optimization of the water supply portfolio for a medium-sized city results in annual cost-savings of up to $463 million.

Threats posed by wild predators to livestock production have too often resulted in human–wildlife conflict, to the detriment of these keystone species and broader biodiversity conservation. Long‐standard practices of lethal control are increasingly seen as costly, controversial, and ineffective, however, with nonlethal alternatives ever more prominent. In addition to assessing these tools' ecological effectiveness, there remains a key role for the social sciences, particularly qualitative research, in identifying obstacles to and opportunities for the long‐term sustainability and scaling up of these coexistence interventions. The Wood River Wolf Project (WRWP), a collaboration among ranchers, environmental organizations, and government agencies in Blaine County, Idaho, has pursued coexistence between gray wolves and domestic sheep since 2008, demonstrating and developing nonlethal techniques and garnering regional and international attention as a model for collaborative coexistence. Yet the Project has also struggled with changing conditions and internal challenges. Investigation of this prominent effort—its history and practices as well as the broader socio‐political and economic context—highlights the challenges of adaptive governance in the face of reduced capacity and hostile legal‐political contexts, while providing important insights for practitioners and policymakers promoting wildlife coexistence in shared landscapes.

California has experienced increasing frequency and intensity of wildfire, with the five largest fires on record since 2018. Over the same period, licensed cannabis production has grown to a high-grossing industry, while remaining an important source of rural livelihood. Importantly, the geography of cannabis production overlaps with high fire hazard areas more than any other crop in the state. We developed and deployed a state-wide survey of licensed outdoor producers to determine direct and indirect impacts of wildfire, as well as how producers have responded to these threats. Quantitative and narrative data were subjected to statistical and thematic analyses, demonstrating key findings around fire-related losses, mitigation tools and techniques, and perceptions of risk. Producers experienced a range of impacts beyond direct burning, including reduced light (affecting grow rates), ash deposition (with impacts on product quality and saleability), and production disruptions. Producer responses to the threat of fire and smoke varied, in part affected by the costs of mitigation, yet some common strategies emerged. However, while most growers reported impacts from fire, these were often outweighed by concerns over other pressures on production and profitability. Our hope is that these findings around the experiences and concerns of California’s cannabis producers will inform future research directions and provide the first steps toward policy interventions to better address the challenges of living with wildfire.

A multivariate GARCH model of natural resources is specified to capture the effects of time varying portfolio risk. A special feature of the model is the inclusion of realized volatility for natural resource assets that are available at multiple frequencies as well as being sensitive to sudden changes in climatic conditions. Natural resource portfolios under climate change are simulated from bootstrapping schemes as well as being derived from global climate model projections. Both approaches are applied to a multiasset water portfolio model consisting of reservoir inflows, rainwater harvesting, and desalinated water. The empirical results show that while reservoirs remain the dominant water asset, adaptation to climate change involves increased contributions from rainwater harvesting and more frequent use of desalinated water. It is estimated that climate change increases annual water supply costs by between 7% and 44% over a 20-year forecast horizon.

California (USA) supports the largest legal cannabis market in the world, yet faces increasing risk from wildfire. While anecdotal evidence of impacts to cannabis crops has been documented during recent extreme fire seasons, the economic losses resulting from smoke exposure and other indirect effects (e.g., ash fall, mandatory evacuations, power outages) are not well understood. We conducted an online survey of licensed cannabis farms across the state, reporting wildfire impacts on cannabis crops from 2018 through 2021. We summarized regional variation in reported cannabis crop losses, fit a hierarchical multinomial model to assess the effects of proximity to fire and smoke exposure on crops, and trained a random forest model to make impact predictions for all state-licensed outdoor cannabis farms. We found that cannabis farms experienced wildfire-related crop losses across all cannabis growing regions in 2020, but that northern regions experienced particularly high crop loss across all four study years. We also found that exposure to wildfire smoke was a stronger predictor of reported impacts than proximity to wildfire. The output of our random forest model suggested substantial impacts for the cannabis industry in 2020, with predicted crop losses between 4.54% and 21.61% statewide, and between 9.09% and 42.83% in the northernmost counties. Estimated potential economic losses in 2020 and 2021 were as high as$1.44 billion and $ 970.04 million, respectively—losses which themselves exceed annual values of many of California’s other agricultural commodities. Together our results indicate substantial impacts of wildfire for the California cannabis industry as a whole. We suggest that more attention be given to strategies for mitigating cannabis crop losses from wildfires, especially in light of increasing fire occurrence and severity under climate change.

A factor analysis of long-term bond spreads is performed by decomposing international interest rate spreads into national and global factors. The factors are latent, and are assumed to have GARCH-type specifications as well as exhibiting serial dependence. An indirect estimator is used to compute estimates of the unknown parameters. The sampling performance of this estimator is investigated and compared with an alternative direct estimator based on the Kalman predictor. The factor model is applied to weekly data on long-bond spreads between five countries-Australia, Japan, Germany, Canada and the UK- and the USA over the period 1991 to 1999. The resulting factor decomposition is used to examine the international investor's optimal portfolio decision in a mean-variance framework.

The emerging field of convivial conservation (CC) draws on the tradition of political ecology (PE) to present a “radical” alternative to contemporary environmentalisms, speaking to the challenges of conservation in the Anthropocene as well as the global ascent of reactionary populism. Building on previous work arguing for the ongoing value of dialogue between PE and the American West, I here develop a conversation between CC and another radical intervention, the collaborative conservation of the West’s so-called “radical center” (RC). Using the nexus of wolf–livestock conflict and public lands grazing, I first trace a genealogical history of western environmental politics before turning to CC as critical corrective to the shortcomings of the RC. Scholarship on the commons and commoning provides an analytical bridge and political toolkit for linking the empirics of place with the aspirational aims of conviviality, and naming and navigating on-the-ground obstacles to collaborative conservation efforts in the region. This dialogue in turn highlights deeply rooted tensions of capitalist political economy and questions of non/belonging rooted in settler colonialism—necessary regional engagements for building from polarized antagonism toward an alternative environmental politics of coexistence and conviviality.