A substantial literature over the past thirty years has evaluated tradeoffs between money and fatality risks. These values in turn serve as estimates of the value of a statistical life. This article reviews more than 60 studies of mortality risk premiums from ten countries and approximately 40 studies that present estimates of injury risk premiums. This critical review examines a variety of econometric issues, the role of unionization in risk premiums, and the effects of age on the value of a statistical life. Our meta-analysis indicates an income elasticity of the value of a statistical life from about 0.5 to 0.6. The paper also presents a detailed discussion of policy applications of these value of a statistical life estimates and related issues, including risk-risk analysis.

the authors. Discussion papers are research materials circulated by their authors for purposes of information and discussion. They have not necessarily undergone formal peer review or editorial treatment. Experience with Market-Based Environmental Policy Instruments

This article reviews the economics literature on monitoring and enforcement of environmental policy. In the last few years there has been a rapid growth in both theoretical developments and empirical studies of monitoring and enforcement. Various factors have contributed to this growth, including (1) the growth of the law and economics literature and its interest in issues of law enforcement and penalties, (2) increased emphasis on enforcement by EPA and other regulatory agencies, and (3) the availability of data on firm compliance. The economics literature on environmental monitoring and enforcement has closely followed the related field of optimal penalties in the law and economics literature. The scope of the article includes both public and private mechanisms designed to compel firms (and individuals) to comply with environmental formal regulations and informal rules of conduct or social norms. For purposes of this paper, monitoring and enforcement includes monitoring and inspections by enforcement authorities as well as sanctions, remedial actions, and other mechanisms designed to punish and/or bring a firm into compliance. It also includes non-governmental actions such as citizen suits authorized by

Landscape ecology is a field that has grown from realizing that maintenance of ecological resources requires management at several spatial and temporal scales, including landscape-level ecosystems as whole units of study and management (Forman, 1995; Grumbine, 1994; Noss, 1983 and 1996). The subsequent need for characterizing landscape structure has led to a variety of measurements for assessing different aspects of spatial patterns; however, most of these measurements are known to depend on both the spatial extent of a specified landscape and the measurement grain. Therefore, measurements that incorporate a range of scales would be most informative. In response, this paper introduces a new method for obtaining a multi-resolution characterization of land cover fragmentation patterns within a fixed geographic extent. Our particular interest is in watersheddelineated extents. The method applies the concept of conditional entropy as one moves from larger “parent ” land cover pixels to smaller “child ” pixels that are heirarchically nested within the parent pixels. When applied over a range of resolutions, one obtains a “conditional entropy profile”. The conceptual and methodological development of conditional entropy profiles is presented, followed by current and future directions for evaluating and applying this methodology. 1

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What determines the relationship between pollution and growth? Are the forces that explain the behavior over time of these quantities potentially useful to understand more generally the relationship between policies and growth? In this paper, we make a first attempt to analyze the equilibrium behavior of two quantities—the level of pollution and the level of income—in a setting in which societies choose, via voting, how much to regulate pollution. Our major finding is that, consistent with the evidence, the relationship between pollution and growth need not be monotone and that the precise equilibrium nature of the relationship between the two variables depends on whether individuals vote over effluent charges or directly restrict the choice of technology. Moreover, our analysis of the pollution problem suggests that, more generally, endogenous policy choices should be taken seriously as potential sources of heterogeneity when studying cross country differences in economic performance.

Carbon capture and storage (CCS) technologies remove carbon dioxide from flue gases for storage in geologic formations or the ocean. We find that CCS is technically feasible and economically attractive within the range of carbon policies discussed domestically and internationally. Current costs are about $200 to $250 per ton of carbon, although costs are sensitive to fuel prices and other assumptions and could be reduced significantly through technical improvements. Near-term prospects favor CCS for certain industrial sources and electric power plants, with storage in depleted oil and gas reservoirs. Deep aquifers may provide an attractive longer-term storage option, whereas ocean storage poses greater technical and environmental uncertainty. Vast quantities of economically recoverable fossil fuels, sizable political obstacles to their abandonment, and inherent delay associated with developing alternative energy sources suggest that CCS should be seriously considered in the portfolio of options for addressing climate change, alongside energy efficiency and carbon-free energy. Key Words: carbon, capture, storage, sequestration, climate change, technology JEL Classification Numbers: Q30, Q40, O30 Contents 1.

The basic idea of traditional density estimation is to model the overall point density analytically as the sum of influence functions of the data points. However, traditional density estimation techniques only consider the location of a point. Supervised density estimation techniques, on the other hand, additionally consider a variable of interest that is associated with a point. Density in supervised density estimation is measured as the product of an influence function with the variable of interest. Based on this novel idea, a supervised density-based clustering named SCDE is introduced and discussed in detail. The SCDE algorithm forms clusters by associating data points with supervised density attractors which represent maxima and minima of a supervised density function. Results of experiments are presented that evaluate SCDE for hot spot discovery and co-location discovery in spatial datasets. Moreover, the benefits of the presented approach for generating thematic maps are briefly discussed.

...........................................................................................................................................iv 1. Introduction..................................................................................................................................1 2. A Model of Cost Heterogeneity and Policy Choice.....................................................................6 2.1 A Model of Heterogeneous Costs......................................................................................... 6 2.2 Alternative Policies for Emission Allocation....................................................................... 7 2.2.1 Cost of a Uniform Emission Rate Standard ............................................................... 7 2.2.2 Cost of a Uniform Percentage Reduction Standard ................................................... 9 2.2.3 Cost of a Market-Based Policy Instrument ................................................................ 9 2.3 The...

In 2002, methodological issues around time series analyses of air pollution and health attracted the attention of the scientific community, policy makers, the press, and the diverse stakeholders concerned with air pollution. As the Environmental Protection Agency (EPA) was finalizing its most recent review of epidemiological evidence on particulate matter air pollution (PM), statisticians and epidemiologists found that the S-Plus implementation of Generalized Additive Models (GAM) can overestimate effects of air pollution and understate statistical uncertainty in time series studies of air pollution and health. This discovery delayed the completion of the PM Criteria Document prepared as part of the review of the U.S. National Ambient Air Quality Standard (NAAQS), as the time-series findings were a critical component of the evidence. In addition, it raised concerns about the adequacy of current model formulations and their software implementations. In this paper we provide improvements in semi-parametric regression directly relevant to risk estimation in time series studies of air pollution. First, we introduce a closed form estimate of the asymptotically exact covariance matrix of the linear component of a GAM. To ease the implementation of these calculations, we develop the S package gam.exact, an extended version of gam.