Since Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) of 1980, which is known as Superfund, public have concerned about hazardous waste land in terms of their health and environmental risks associated with. As a result, The Environmental Protection Agency (EPA) tried to identify most waste sited all over the nation and test their magnitude of contaminations by Hazardous Ranking System (HRS). The EPA placed most substantial dangerous sites on its National Priorities List (NPL) and started remedial cleanups at these sites. Over the 30 years after the first cleanup process, the benefits of Superfund cleanups is not explicitly calculated contrary to the costs of Superfund remediation which is easy to estimate. This
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Thus, most tangible empirical method to figure out the benefits of Superfund cleanup program is tracing fluctuation in housing market near hazardous sites. People try to avoid waste land due to health and environmental risk, so demand of residential properties goes down and housing price also drops. When hazardous waste sites become cleanup, people perceive their health risks will be reduced and are willing to live near the sites. This will cause increasing in supply of housing and population and result in higher value of local housing market. This growing amount of housing price can be interpreted as the benefits from Superfund cleanup program. On the contrary, the costs of Superfund program is over $40 million on average for each cleanup. Therefore, we would like to compare the benefits by increasing housing values contiguous hazardous sites to cost of each cleanup to investigate the economic outcomes for this …show more content…
Also they employ a regression discontinuity (RD) design to investigate sites close to cutoff HRS scores by assuming unobservables are similar or change smoothly near threshold point. GG focus on median housing price at the census tract level to analyze the effect of Superfund cleanups. However, most affected houses by cleanups are located near hazardous sites. They are cheaper than other area farther from the sites and poorer households reside there. Thus, if the site is deleted from NPL, these houses attain more appreciation rather than farther communities. GMT point out this problem and they examine lower deciles of tract-level housing value distribution and smaller radius to the hazardous site than GG’s method to capture localized benefits. GMT’s results from strict RD sample within the 3km buffer show that cleanup process to deletion increases housing values by 17.4% at 10th percentile of price distribution comparing to pre-proposal stage. Additionally, housing price raises 20.0% at 40th percentile, 15.4% at the median, and 11.4% at 60th percentile. The similar results are derived from RD sample. Nonetheless, these appreciation cannot guarantee to exceed the costs of cleanup process because their calculation covers only some part of census tract size. We need to know entire benefits for communities near hazardous sites, so their work seizes
Thus, most tangible empirical method to figure out the benefits of Superfund cleanup program is tracing fluctuation in housing market near hazardous sites. People try to avoid waste land due to health and environmental risk, so demand of residential properties goes down and housing price also drops. When hazardous waste sites become cleanup, people perceive their health risks will be reduced and are willing to live near the sites. This will cause increasing in supply of housing and population and result in higher value of local housing market. This growing amount of housing price can be interpreted as the benefits from Superfund cleanup program. On the contrary, the costs of Superfund program is over $40 million on average for each cleanup. Therefore, we would like to compare the benefits by increasing housing values contiguous hazardous sites to cost of each cleanup to investigate the economic outcomes for this …show more content…
Also they employ a regression discontinuity (RD) design to investigate sites close to cutoff HRS scores by assuming unobservables are similar or change smoothly near threshold point. GG focus on median housing price at the census tract level to analyze the effect of Superfund cleanups. However, most affected houses by cleanups are located near hazardous sites. They are cheaper than other area farther from the sites and poorer households reside there. Thus, if the site is deleted from NPL, these houses attain more appreciation rather than farther communities. GMT point out this problem and they examine lower deciles of tract-level housing value distribution and smaller radius to the hazardous site than GG’s method to capture localized benefits. GMT’s results from strict RD sample within the 3km buffer show that cleanup process to deletion increases housing values by 17.4% at 10th percentile of price distribution comparing to pre-proposal stage. Additionally, housing price raises 20.0% at 40th percentile, 15.4% at the median, and 11.4% at 60th percentile. The similar results are derived from RD sample. Nonetheless, these appreciation cannot guarantee to exceed the costs of cleanup process because their calculation covers only some part of census tract size. We need to know entire benefits for communities near hazardous sites, so their work seizes