Flood Risk Management: Exploring the Impacts of the Community Rating System Program on Poverty and Income Inequality.

Flooding remains a major problem for the United States, causing numerous deaths and damaging countless properties. To reduce the impact of flooding on communities, the U.S. government established the Community Rating System (CRS) in 1990 to reduce flood damages by incentivizing communities to engage in flood risk management initiatives that surpass those required by the National Flood Insurance Program. In return, communities enjoy discounted flood insurance premiums. Despite the fact that the CRS raises concerns about the potential for unevenly distributed impacts across different income groups, no study has examined the equity implications of the CRS. This study thus investigates the possibility of unintended consequences of the CRS by answering the question: What is the effect of the CRS on poverty and income inequality? Understanding the impacts of the CRS on poverty and income inequality is useful in fully assessing the unintended consequences of the CRS. The study estimates four fixed-effects regression models using a panel data set of neighborhood-level observations from 1970 to 2010. The results indicate that median incomes are lower in CRS communities, but rise in floodplains. Also, the CRS attracts poor residents, but relocates them away from floodplains. Additionally, the CRS attracts top earners, including in floodplains. Finally, the CRS encourages income inequality, but discourages income inequality in floodplains. A better understanding of these unintended consequences of the CRS on poverty and income inequality can help to improve the design and performance of the CRS and, ultimately, increase community resilience to flood disasters.

Performance or marketing benefits? The case of LEED certification.

Green building adoption is driven by both performance-based benefits and marketing based benefits. Performance based benefits are those that improve performance or lower operating costs of the building or of building users. Marketing benefits stem from the consumer response to green certification. This study illustrates the relative importance of the marketing based benefits that accrue to Leadership in Energy and Environmental Design (LEED) buildings due to green signaling mechanisms, specifically related to the certification itself are identified. Of course, all participants in the LEED certification scheme seek marketing benefits. But even among LEED participants, the interest in green signaling is pronounced. The green signaling mechanism that occurs at the certification thresholds shifts building patterns from just below to just above the threshold level, and motivates builders to cluster buildings just above each threshold. Results are consistent across subsamples, though nonprofit organizations appear to build greener buildings and engage in more green signaling than for-profit entities. Using nonparametric regression discontinuity, signaling across different building types is observed. Marketing benefits due to LEED certification drives organizations to build "greener" buildings by upgrading buildings at the thresholds to reach certification levels.

Estimated validity and reliability of on-board diagnostics for older vehicles: comparison with remote sensing observations.

Based on requirements under the Clean Air Act Amendments of 1990, most state vehicle inspection and maintenance (I/M) programs have, since 2002, replaced the tailpipe emission testing with the on-board diagnostic (OBD) II testing for 1996 model and newer vehicles. This test relies on the OBD II system to give the pass or fail result, depending on certain conditions that might cause the vehicle to emit pollution 1.5 times higher than the regulated standard. The OBD II system is a computer and sensors installed in the vehicle to monitor the emission control units and signal if there is any malfunction. As a vehicle ages, its engine, pollution control units, and OBD II system deteriorate. Because the OBD II system's durability directly influences the test outcome, it is important to examine the fleetwide trend in the OBD II test results in comparison with an alternative measure of identifying high emitting vehicles. This study investigates whether the validity and reliability of the OBD II test is related to the age of the OBD II system installed in the fleet. Using Atlanta's I/M testing records and remote sensing device (RSD) data collected during 2002-2005, this research establishes the convergent validity and interobserver reliability criteria for the OBD II test based on on-road emissions measured by RSDs. The study results show that older vehicles exhibit significantly lower RSD-OBD II outcome agreement than newer vehicles. This suggests that the validity and reliability of the OBD II test may decline in the older vehicle fleets. Explanations and possible confounding factors for these findings are discussed.

Superfund, hedonics, and the scales of environmental justice.

Environmental justice (EJ) is prominent in environmental policy, yet EJ research is plagued by debates over methodological procedures. A well-established economic approach, the hedonic price method, can offer guidance on one contentious aspect of EJ research: the choice of the spatial unit of analysis. Environmental managers charged with preventing or remedying inequities grapple with these framing problems. This article reviews the theoretical and empirical literature on unit choice in EJ, as well as research employing hedonic pricing to assess the spatial extent of hazardous waste site impacts. The insights from hedonics are demonstrated in a series of EJ analyses for a national inventory of Superfund sites. First, as evidence of injustice exhibits substantial sensitivity to the choice of spatial unit, hedonics suggests some units conform better to Superfund impacts than others. Second, hedonic estimates for a particular site can inform the design of appropriate tests of environmental inequity for that site. Implications for policymakers and practitioners of EJ analyses are discussed.