Vegetarian Utopias: Visions of dietary patterns in future societies and support for social change

The current study draws on the collective futures framework to examine how visions of future societies where most people consume plant-based, vegetarian or vegan diets are related to current support for social change towards plant-based diets. Participants were 506 university students in Aotearoa New Zealand invited to imagine a society in 2050 where most individuals consume a plant-based, vegetarian, or vegan diet. A thematic analysis was conducted on responses to an open-ended item asking how these future societies would be different to today. Participants reported a variety of potential positive and negative outcomes for individuals and wider society. Subsequent analyses of attitudes scales investigated the relationships between the collective dimensions of plant-based future societies and support for policies to promote plant-based diets. For a vegetarian future, the strongest predictor of current support for social change was the expectation that widespread vegetarianism would reduce societal dysfunction. For a vegan future, the strongest predictor of support for social change was an expectation of increased warmth in a vegan society. Implications for theory and advocacy are discussed.     

Lessons from the recent economic crisis: the Australian household stimulus package

This paper provides an impact evaluation analysis of the 2009 Australian Household Stimulus Package, which was composed by three main cash payments: the Back to School Bonus, the Single Income Family Bonus and the Tax Bonus for Working Australians. Using panel data from the 2008 and 2009 HILDA surveys, the results show that these cash payments reduced the risk of poverty and stimulated consumption expenditure. Nonetheless, only the Back to School Bonus and the Single Income Family Bonus were really important in achieving these goals, while the Tax Bonus for Working Australians did not contribute to stimulate consumption and failed to reduce the risk of poverty. Thus, the analysis confirms the crucial role of governments to protect the most vulnerable groups avoiding a dramatic deterioration of social outcomes and favoring a fast economic recovery when interventions are timely and well-targeted.     

Impact of commuting by workers on household dietary diversity in rural India

Drawing insights from the literature on transformation of rural non-farm employment, pathways from agriculture to nutrition, and linkages between migration and nutritional status of household, we seek to understand differences in dietary diversity across three mutually exclusive types of rural Indian households: where all members work in rural areas, at least one member commutes to urban areas, at least one member has no fixed place of work. Our analysis is based on a nationally representative data set from India for the year 2009–10 and we use propensity score matching methods. We find that as compared to households with no commuters, households with rural–urban commuters have higher dietary diversity; whereas households with no fixed place workers have lower dietary diversity. We also find differences in dietary diversity across households which differ by their primary source of income.     

A HPC based cloud model for real-time energy optimisation

Recent research has emphasised that an increasing number of enterprises need computation environments for executing HPC (High Performance Computing) applications. Rather than paying the cost of ownership and possess physical, fixed capacity clusters, enterprises can reserve or rent resources for undertaking the required tasks. With the emergence of new computation paradigms such as cloud computing it has become possible to solve a wider range of problems due to their capability to handle and process massive amounts of data. On the other hand, given the pressing regulatory requirement to reduce the carbon footprint of our built environment, significant researching efforts have been recently directed towards simulation-based building energy optimisation with the overall objective of reducing energy consumption. Energy optimisation in buildings represents a class of problems that requires significant computation resources and generally is a time consuming process especially when undertaken with building simulation software, such as EnergyPlus. In this paper we present how a HPC based cloud model can be efficiently used for running and deploying EnergyPlus simulation-based optimisation in order to fulfil a number of objectives related to energy consumption. We describe and evaluate the establishment of such an application-based environment, and consider a cost perspective to determine the efficiency over several cases we explore. This study identifies the following contributions: (i) a comprehensive examination of issues relevant to the HPC community, including performance, cost, user perspectives and range of user activities, (ii) a comparison of two different execution environments such as HTCondor and CometCloud and determine their effectiveness in supporting simulation-based optimisation and (iii) a detailed performance analysis to locate the limiting factors of these execution environments.     

How much can we trust China’s investment statistics?

Abstract

Building upon recent research into the underestimation of China’s official final consumption expenditure, this paper investigates the quality of China’s investment data. We strictly follow the official method to estimate the annual gross fixed capital formation (GFCF) expenditure from 2004 to 2012, and the resulting figures are significantly different from the official statistics. This implies that the ‘total investment in fixed assets’ data, which are the primary source for the estimation of GFCF, grossly exaggerate actual investments, and that the official GFCF figures are not, strictly speaking, independently estimated, as they are purported to be. We deduce that the official gross capital formation figure is more or less a residual item obtained by subtracting final consumption and net exports from the official GDP figure that is calculated based on the production-cum-income approach. As a result, the underestimation of China’s consumption expenditure automatically translates into overestimation of investment expenditure. We conclude that China’s official consumption and investment statistics cannot be trusted as the basis for policy discussions and academic research.     

Adaptive responses to landscape changes from onshore wind energy development in the Republic of Ireland

Covering 26 years of Irish onshore wind energy development, this article tracks patterns in landscape changes from wind farm construction and identifies adaptive responses in public policy and by stakeholder groups. Wind farms face well-documented challenges with social acceptance due to landscape changes; however, little research has examined interactions between landscape change and social adaptations over the long-term. This article systematically reviews 20 policy documents, undertakes spatio-temporal linear modeling of 212 wind farms using 9 landscape change metrics, and analyzes 5 stakeholder group interviews on adaptive responses to landscape changes. Upward trends occur in turbine height, impact accumulation, placement in agricultural landscapes, construction delays, and new farms built per year. Downward trends occur in the number of turbines per farm, visual disruption of protected areas, and placement in wetlands. Key patterns in stakeholder groups’ adaptations include conflicting interpretations of landscape amenities and evolution, and expanded community outreach, networking, and public participation after exposure to infrastructure. Stakeholders adapt to existing infrastructure separately from adapting strategies to respond to new wind farms. Overall, a mutual relationship emerges wherein landscape changes from wind farms respond to policies and stakeholder activities, while policies and stakeholder groups adapt to the physical realities of landscape change.     

An empirical investigation of water consumption forecasting methods

Many regions on earth face daily limitations in the quantity and quality of the water resources available. As a result, it is necessary to implement reliable methodologies for water consumption forecasting that will enable the better management and planning of water resources. This research analyses, for the first time, a large database containing data from 2 million water meters in 274 unique postal codes, in one of the most densely populated areas of Europe, which faces issues of droughts and overconsumption in the hot summer months. Using the R programming language, we built and tested three alternative forecasting methodologies, employing univariate forecasting techniques including a machine-learning algorithm, with very promising results.     

Non-stationary additive utility and time consistency

Within a continuous time life cycle model of consumption and savings, I study the properties of the most general class of additive intertemporal utility functionals. They are not necessarily stationary, and do not necessarily multiplicatively separate a discount factor from “per-period utility”. I prove rigorously that time consistency holds if and only if the per-period felicity function is multiplicatively separable in $t$, the date of decision and in $s$, the date of consumption, or equivalently, if the Fisherian instantaneous subjective discount rate does not depend on $t$. The model allows to explain “anomalies in intertemporal choice” even when the agents are time consistent and various empirical regularities. On the other hand, the model allows to characterize mathematically the “effective consumption profile” of naive, time-inconsistent agents.     

Environmental policies,national culture,and stock price crash risk: Evidence from renewable energy firms

This study investigates the impact of country‐level environmental performance and national culture on the stock price crash risk of renewable energy firms. Employing a large sample of 626 renewable energy firms across 31 countries, we find a significant nonlinear relationship between country‐level environmental performance and crash risk. National culture dimensions are found to strongly predict the crash risk of renewable energy firms, particularly after the global financial crisis. On the contrary, national culture dimensions and environmental policies are observed to not exert any significance in explaining the crash risk of fossil fuel firms. Our results are robust with respect to alternative measures of stock price crash risk and the endogeneity of national culture dimensions. Overall, the findings of this paper contribute to the environmental economics literature by providing new evidence regarding the role of societal and environmental factors in explaining the stock price crash risk of energy firms.