Crime,weather, and climate change

This paper estimates the impact of climate change on the prevalence of criminal activity in the United States. The analysis is based on a 30-year panel of monthly crime and weather data for 2997 US counties. I identify the effect of weather on monthly crime by using a semi-parametric bin estimator and controlling for state-by-month and county-by-year fixed effects. The results show that temperature has a strong positive effect on criminal behavior, with little evidence of lagged impacts. Between 2010 and 2099, climate change will cause an additional 22,000 murders, 180,000 cases of rape, 1.2 million aggravated assaults, 2.3 million simple assaults, 260,000 robberies, 1.3 million burglaries, 2.2 million cases of larceny, and 580,000 cases of vehicle theft in the United States.     

Environmental Constituent Interest, Green Electricity Policies, and Legislative Voting

Research in political economy has traditionally sought to disentangle the effects of legislative ideology and constituent interest in explaining policy decisions. Frequently, proxy variables are used to measure constituent interest. However, these measures do not adequately reflect true constituent interest, which is based upon the costs and benefits of the policies under consideration, incorporating the scope of the policies. Using Haiku, a detailed model of the US electricity sector, and TAF, an integrated assessment model of pollution pathways and valuation, I construct economic measures of constituent interest at the state level as well as for federal policy. I then use these measures to analyze state adoption of more stringent green electricity policies and congressional roll-call voting on federal environmental policy. Previous studies that use proxy measures of constituent interest typically find that the legislator ideology matters more, while my study shows that both ideology and constituent interest are significant factors.     

The higher price of cleaner fuels: Market power in the rail transport of fuel ethanol

This paper provides evidence of market power in the transportation of ethanol used in reformulated gasoline and alternative transportation fuels. I estimate a reduced form model for railroad route-level prices. My identification strategy instruments for railroad entry, controls for selection and explicitly models capacity constraints. A detailed understanding of this industry is important because U.S. environmental policies seek to substantially expand ethanol use. Evidence of market power may alter the types of policies pursued by lawmakers. I find that ethanol shipment prices are lower for more competitive routes. I also find evidence that railroads price discriminate based on environmental regulation at route destinations. Monopolist prices for shipments to carbon monoxide non-attainment areas are 3% higher than shipments to other destinations. This price premium falls sharply with increased competition. This suggests a perverse result where environmental regulation increases the price of a clean input.     

Modeling the influence of precipitation and nitrogen deposition on forest understory fuel connectivity in Sierra Nevada mixed-conifer forest

Climate change models for California's Sierra Nevada predict greater inter-annual variability in precipitation over the next 50 years. These increases in precipitation variability coupled with increases in nitrogen deposition from fossil fuel consumption are likely to result in increased productivity levels and significant increases in forest understory fuel loads. Higher understory plant biomass contributes to fuel connectivity and may increase future fire size and severity in the Sierra Nevada. The objective of this research was to develop and test a model to determine how changing precipitation and nitrogen deposition levels affect shrub and herb biomass production, and to determine how often prescribed fire would be needed to counter increasing fuel loads. Model outputs indicate that under an increasing precipitation scenario significant increases in shrub and herb biomass occur that can be counteracted by decreasing the fire return interval to 10 years. Under a scenario with greater inter-annual variability in precipitation and increased nitrogen deposition, implementing fire treatments at an interval equivalent to the historical range of 15–30 years maintains understory vegetation fuel loads at levels comparable to the control.     

Climate change, humidity, and mortality in the United States

This paper estimates the effects of humidity and temperature on mortality rates in the United States (c. 1973-2002) in order to provide an insight into the potential health impacts of climate change. I find that humidity, like temperature, is an important determinant of mortality. Coupled with Hadley CM3 climate-change predictions, I project that mortality rates are likely to change little on the aggregate for the United States. However, distributional impacts matter: mortality rates are likely to decline in cold and dry areas, but increase in hot and humid areas. Further, accounting for humidity has important implications for evaluating these distributional effects.     

Substitution between biofuels and fossil fuels: Is there a green paradox?

We show that (i) subsidies for renewable energy policies with the intention of encouraging substitution away from fossil fuels may accentuate climate change damages by hastening fossil fuel extraction, and that (ii) the opposite result holds under some specified conditions. We focus on the case of subsidies for renewable resources produced under increasing marginal costs, and assume that both the renewable resources and the fossil fuels are currently in use. Such subsidies have a direct effect and an indirect effect working in opposite directions. The direct effect is the reduction in demand for fossil fuels at any given price. The indirect effect is the reduction in the current equilibrium price for fossil fuels, which tends to increase the amount of fossil fuels demanded. Whether the sum of the two effects will actually result in an earlier or later date of exhaustion of the stock of fossil fuels depends on the curvature of the demand curve for energy and of the supply curve for the renewable substitute.     

Discounting,inequality and economic convergence

The aim of this paper is to examine the impact of inequalities and economic convergence on the efficient discount rate when international credit and risk-sharing markets are inefficient. We consider an economy in which initial consumption levels and growth expectations are heterogeneous. In the benchmark case in which relative inequalities are permanent and relative risk aversion is constant, inequalities do not affect the discount rate. We derive necessary and sufficient conditions under which permanent inequalities reduce the discount rate. We also show that the anticipation of economic convergence raises the efficient discount rate when relative prudence is larger than unity.     

Impacts of daily weather variability on simulations of the Canadian boreal forest

This study examines the importance of climate variability when simulating forest succession using a process-based model of stand development. The FORSKA-2V forest gap model, originally developed for forcing with monthly mean climate data, was modified to accept daily weather data. The model's performance was compared using different temporal resolutions of forcing along a bioclimatic transect crossing the boreal region of central Canada, including the aspen-parkland and forest-tundra ecotones. Forcing the model with daily weather data improved the simulation of key attributes of present-day forest along the transect, particularly at the ecotones, compared to forcing with monthly data or long term averages. The results support the hypothesis that climatic variability at daily time-scales is an important determinant of present-day boreal forest composition and productivity. To simulate boreal forest response to climatic change it will be necessary to create climatic scenarios that include plausible projections of future daily scale variability.     

Exploring the future of European crop production in a liberalised market, with specific consideration of climate change and the regional competitiveness

Long-term future development of European agriculture within the global market is highly uncertain, but can potentially have large impacts on the future of agricultural businesses, rural communities and amenities such as traditional landscapes and biodiversity. Despite great uncertainties it is of interest to explore the extent of these potential changes. This paper provides an explorative scenario of the European crop production in a liberalised world without European Union (EU) market interventions. The results do not form a prediction or a business as usual scenario, but rather a plausible and salient thought-experiment of a possible future based on the consistent integration of current conceptual and quantitative models.Future scenarios for climate, demography, technology and global demand for agricultural commodities are used to assess the competitiveness of European agriculture. Regional economic competitiveness is determined by combining indicators for the economic strength of farms in a region and population pressure on agricultural land, and subsequently used to determine where agricultural production is likely to sustain under the market liberalisation scenario. The method is illustrated for the 27 EU member state countries for three commodities: wheat, potato and milk (relying on grass).Results include maps of the dominant wheat, potato and milk producing regions across Europe as projected for 2050. They show that due to increased agricultural productivity, less agricultural land will be needed to supply the European demand for food and feed. In addition, production will concentrate in those regions which have a comparative advantage. This potentially leads to a strong polarisation between north-western Europe and southern Europe, which faces negative impacts of climate change and central and northern Europe where agricultural businesses lag in economic strength and farm size. A contrasting policy intervention scenario illustrates how differences in demand and productivity result in an expansion of the agricultural area, especially for the production of wheat.Although the complete liberalisation scenario may seem unlikely, and the underlying assumptions have great uncertainty, the results help identify and map market pressures on agricultural land use across regions in Europe. As such, it stimulates policy debate on the desired future for the European agricultural sector and the trade-offs between economic competitiveness under global market conditions and policy intervention. In addition, it provides a basis for the planning of alternative economic strategies for agriculturally less competitive regions.     

Would hotelling kill the electric car?

In this paper, we show that the potential for endogenous technological change in alternative energy sources may alter the behaviour of resource-owning firms. When technological progress in an alternative energy source can occur through learning-by-doing, resource owners face competing incentives to extract rents from the resource and to prevent expansion of the new technology. We show that in such a context, it is not necessarily the case that scarcity-driven higher traditional energy prices over time will induce alternative energy supply as resources are exhausted. Rather, we show that as we increase the learning potential in the substitute technology, lower equilibrium energy prices prevail and there may be increased resource extraction and greenhouse gas emissions. We show that the effectiveness and the incidence of emissions reduction policies may be altered by increased potential for technological change. Our results suggest that treating finite resource rents as endogenous consequences of both technological progress and policy changes will be important for the accurate assessment of climate change policy.     

Neural network modelling for the analysis of forcings/temperatures relationships at different scales in the climate system

A fully non-linear analysis of forcing influences on temperatures is performed in the climate system by means of neural network modelling. Two case studies are investigated, in order to establish the main factors that drove the temperature behaviour at both global and regional scales in the last 140 years. In particular, our neural network model shows the ability to catch non-linear relationships among these variables and to reconstruct temperature records with a high degree of accuracy. In this framework, we clearly show the need of including anthropogenic inputs for explaining the temperature behaviour at global scale and recognise the role of El Niño southern oscillation for catching the inter-annual variability of temperature data. Furthermore, we analyse the relative influence of global forcing and a regional circulation pattern in determining the winter temperatures in Central England, showing that the North Atlantic oscillation represents the driven element in this case study. Our modelling activity and results can be very useful for simple assessments of relationships in the complex climate system and for identifying the fundamental elements leading to a successful downscaling of atmosphere–ocean general circulation models.     

东江流域1959-2009年气候变化及其对径流的影响

依据东江流域21个气象站1959-2009年逐年平均降雨、蒸发、日照、湿度及气温等气象要素序列,选择常用的线性倾向估计及非参数M．K等趋势分析方法,分析了东江流域近50年来气温、降水、蒸发、日照及湿度等气象要素的变化趋势。选择降雨和蒸发两个气候要素两两组合,构成未来气候变动的36种假想情景,运用改进的SCS月模型模拟计算了顺天流域年径流量的变化幅度。结果表明：在过去的50年间,流域降雨量呈不显著增长,而气温则为显著上升,其他气候要素如蒸发、日照及湿度等均呈不同程度减少趋势;关联度分析表明降雨在所有气象要素中与径流的关联度为最大,说明了在东江流域降雨是径流量变化的主要驱动因子;未来流域降雨增加,蒸发减少的气候情景模式下,径流量会有所增加,反之亦然;由降雨变化引起的流域月径流量的增幅较由蒸发变化引起的相应流量的增幅变化大。     

Adjustment costs from environmental change

The paper is concerned with the case whereby the distribution of a firm's productivity shocks changes without the knowledge of the firm. Over time the firm learns about the nature and extent of the change in the distribution of the shock and adjusts, incurring adjustment costs in the process. The long-run loss in profits (±) due to the shift in the distribution we term the equilibrium response. The transitory loss in profits, incurred while the firm is learning about the distribution shift, is termed the adjustment cost. The theory is then applied to the problem of measuring adjustment costs in the face of imperfectly observed climate change in agriculture. The empirical part of the paper involves estimating a restricted profit function for agricultural land in a five-state region of the Midwest US as a function of prices, land characteristics, actual weather realizations and expected weather. We then simulate the effect of an unobserved climate shock, where learning about the climate shock is by observing the weather and updating prior knowledge using Bayes Rule. We find adjustment costs to climate change are 1.4% of annual land rents.     

An inventory of tree species in Europe—An essential data input for air pollution modelling

We present a detailed tree species inventory covering Europe, parts of Africa and parts of Asia. The inventory contains 39 groups of species that are important for biogenic VOCs or pollen emission calculations. For example: oak (Quercus), poplar (Populus), pines (Pinus), spruce (Picea), birch (Betula) and alder (Alnus). The inventory is based on national forest inventories and national statistics and gives tree species distribution in percentage within broadleaved as well as conifer forests. The inventory includes data from 799 regions and is redistributed into the 50 km × 50 km EMEP grid. The inventory is therefore prepared for easy implementation into atmospheric transport models by providing an extension to already applied land use data such as the Corine Land Cover (CLC2000) or Global Land Cover (GLC2000). The gridded version of the data set will be available on the webpage http://www.dmu.dk/International/Air/Models/Background/Trees/.     

Cost-effective environmental policy: implications of induced technological change

Cost-effective environmental policy generally requires that all emission sources are faced with the same tax. In this paper I discuss how the existence of induced technological change may alter this result, if at least some of the effect is external to the firm. Focusing on Learning by doing (LBD) effects in abatement activities, it is shown that emission sources with external learning effects should be faced with a higher tax than emission sources with only autonomous technological change. By using simple numerical simulations, it is further investigated to what degree a cost-effective climate policy differs from a free quota market, under various assumptions about learning effects, diffusion of technology and environmental targets. The results indicate that optimal taxes may be significantly higher in the industrial world than in the developing world. Moreover, the industrial world's share of global abatement may be much higher in a cost-effective solution than in a free quota market. The global cost savings of a fully flexible implementation of the Kyoto Protocol are further questioned, as potential spillover effects of technological growth in the industrial world are not internalised in the market.     

Evaluating and managing wildlife impacts of climate change under uncertainty

Wildlife managers face the daunting task of managing wildlife in light of uncertainty about the nature and extent of future climate change and variability and its potential adverse impacts on wildlife. A conceptual framework is developed for managing wildlife under such uncertainty. The framework uses fuzzy logic to test hypotheses about the extent of the wildlife impacts of past climate change and variability, and fuzzy multiple attribute evaluation to determine best compensatory management actions for adaptively managing the potential adverse impacts of future climate change and variability on wildlife. A compensatory management action is one that can offset some of the potential adverse impacts of climate change and variability on wildlife. Implementation of the proposed framework requires wildlife managers to: (1) select climate impact states, hypotheses about climate impact states, possible management actions for alleviating adverse wildlife impacts of climate change and variability, and future climate change scenarios; (2) choose biological attributes or indicators of species integrity; (3) adjust those attributes for changes in non-climatic variables; (4) define linguistic variables and associated triangular fuzzy numbers for rating both the acceptability of biological conditions under alternative management actions and the relative importance of biological attributes; (5) select minimum or maximum acceptable levels of the attributes and reliability levels for chance constraints on the biological attributes; and (6) define fuzzy sets on the extent of species integrity and biological conditions and select a fuzzy relation between species integrity and biological conditions. A constructed example is used to illustrate a hypothetical application of the framework by a wildlife management team. An overall best compensatory management action across all climate change scenarios is determined using the minimax regret criterion, which is appropriate when the management team cannot assign or is unwilling to assign probabilities to the future climate change scenarios. Application of the framework can be simplified and expedited by incorporating it in a web-based, interactive, decision support tool.