• Energy Research

This paper investigates second-best issues in the regulation of external costs of energy use by heterogeneous firms. The efficiency of regulatory energy policies depends in general on the policy incentives given for both output reduction and input substitution. The resulting endogeneity of firms' supply functions appears to lead to complicated policy rules. In contrast to earlier efforts, the analysis considers an arbitrarily large number of non-identical price-taking firms in a joint market; a large variety of possible production functions, including varying levels of economies of scale and possibilities for input substitution; and elasticities of market demand which may vary from completely elastic to completely inelastic. Two second-best instruments are considered, namely output taxes and energy-efficiency standards, and are compared to the benchmark of first-best energy taxes. The underlying market factors determining the relative efficiency of these second-best instruments, when used optimally, are identified.

This paper studies urban sustainability from the perspective of externalities. We develop a general spatial equilibrium model of a monocentric city, in which two types of externalities occur. On the one hand, pollution in the industrial center leads to a spatially differentiated deterioration of the environmental quality in the residential area. On the other hand, the existence of the city is explained by agglomeration economies, represented as simple Marshallian external benefits in production. We investigate free-market versus first-best and second-best optimal spatial equilibria, and conclude that the pursuit of environmental goals may sometimes come at the expense of reduced agglomeration economies, but may actually sometimes also stimulate these economies. © 2002 Elsevier Science B.V. All rights reserved.

AbstractWe provide a theoretical framework to analyze how climate change influences the Ganges and how this influence affects pollution in the river caused by tanneries in Kanpur, India. We focus on two tanneries, and that are situated on the same bank of the Ganges in Kanpur. Both produce leather and leather production requires the use of noxious chemicals. Tannery is situated upstream from tannery Tannery leather production depends on labor use but tannery leather production depends on labor use, the chemical waste generated by tannery and the natural pollution absorbing capacity of the Ganges. In this setting, we perform four tasks. First, we construct a metric that measures the climate change induced mean reduction in the natural capacity of the Ganges to absorb pollution in the time interval Second, we use this metric and determine the equilibrium production of leather by both tanneries in the benchmark case in which there is no pollution. Third, we ascertain how the benchmark equilibrium is altered when tannery accounts for the negative externality foisted upon it by tannery Finally, we study the impact on leather production and on labor use when the two tanneries merge and then discuss the policy implications stemming from our research.

Automobile gasoline demand can be expressed as a multiplicative function of fuel efficiency, mileage per car and car ownership. This implies a linear relationship between the price elasticity of total fuel demand and the price elasticities of fuel efficiency, mileage per car and car ownership. In this meta-analytical study we aim to investigate and explain the variation in empirical estimates of the price elasticity of gasoline demand. A methodological novelty is that we use the linear relationship between the elasticities to develop a meta-analytical estimation approach based on a Seemingly Unrelated Regression (SUR) model with Cross Equation Restrictions. This approach enables us to combine observations of different elasticities and thus increase our sample size. Furthermore, it allows for a more detailed interpretation of our meta-regression results. The empirical results of the study demonstrate that the SUR approach leads to more precise results (i.e., lower standard errors) than a standard meta-analytical approach. We find that, with mean short run and long run price elasticities of - 0.34 and - 0.84, respectively, the demand for gasoline is not very price sensitive. Both in the short and the long run, the impact of a change in the gasoline price on demand is mainly driven by responses in fuel efficiency and mileage per car and to a slightly lesser degree by changes in car ownership. Furthermore, we find that study characteristics relating to the geographic area studied, the year of the study, the type of data used, the time horizon and the functional specification of the demand equation have a significant impact on the estimated value of the price elasticity of gasoline demand. © 2007 Elsevier B.V. All rights reserved.

Since the outbreak of the corona virus in the end of 2019, many worldwide attempts have been made to monitor and control the COVID-19 pandemic. A wealth of empirical data has been collected and used by national health authorities to understand and mitigate the spread and impacts of the corona virus. In various countries this serious health concern has led to the development of corona dashboards monitoring the COVID-19 evolution. The present study aims to design and test an extended corona dashboard, in which—beside up-to-date daily core data on infections, hospital and intensive care admissions, and numbers of deceased people—also the evolution of vaccinations in a country is mapped out. This dashboard system is next extended with time-dependent contextual information on lockdown and policy stringency measures, while disaggregate information on the geographic spread of the COVID-19 disease is provided by means of big data on contact intensity and mobility motives based on detailed Google Mobility data. Finally, this context-specific corona dashboard, named ‘Dutchboard’, is further extended towards the regional and local level so as to allow also for space-specific ‘health checks’ and assessments.

In our rapidly urbanizing world, the problem of rurality versus urbanization is becoming a source of concern. Rural tourism development may become a new important stimulus for promoting a sustainable transformation of the farmers’ livelihood. This calls for a smart specialization in rural tourism where the focus is on a balanced rural revitalization strategy. As part of the empirical research, this paper introduces a livelihood sustainability index. This index helps to construct a balanced system for the evaluation of livelihood sustainability achievements in rural tourism destinations. It is based on livelihood capital, livelihood strategy, and the interlinkage between livelihood and environment, in order to dynamically assess the livelihood sustainability of rural households. Taking Huangpi District of the Wuhan area in China as our applied case study, the livelihood sustainability index appears to show over the past years a significant rise, based on a comprehensive index method, an entropy method, and a coupling coordination model. Our findings show that the development of rural tourism has clearly promoted livelihood sustainability. This has inter alia resulted in the accumulation of livelihood capital, an asset of which both social and cultural capital have benefitted greatly; livelihood strategies have also improved, and therefore so have livelihood diversity and stability; and finally, the interlinkage and coordination degree between livelihood and the environment has also changed positively from a primary to intermediate balanced development. However, the livelihood sustainability index in the area concerned is still relatively low, and has not yet reached its possible optimal level. Hence, there is still much room for improvement. Various approaches can be proposed to achieve a more sustainable livelihood, such as enhancing livelihood capital; narrowing the economic gap between farmers by participating in professional tourism activity; establishing the mechanism of industrial integration and the development of rural eco-tourism; and coordinating a balanced development of livelihood and environmental quality.

The anticipated implications of international environmental policy strategies are critical for the success or failure of international negotiations on climate change policies. In this paper, we discuss the complex modeling issues related to the incorporation of international environmental policy measures in one of the popular applied general equilibrium models for international trade, the so-called GTAP model. Special attention is paid to an extended version of this model addressing environmental and energy problems, viz. the GTAP-E model. Various numerical results of simulation experiments with this model at a worldwide scale will be presented. In particular, we will address the question how to include the frequently discussed instruments of International Emission Trading, Joint Implementation and Clean Development Mechanisms in a computable general equilibrium model such as the GTAP-E model. © 2005 Elsevier B.V. All rights reserved.