What Do Property Values Really Tell Us? A Hedonic Study of Underground Storage Tanks

http://le.uwpress.org/content/89/2/211

Abstract:

Hedonic property value models are widely used but are susceptible to potentially invalid conjectures based on the assumed measure of environmental quality. This paper focuses on an application where this is of particular concern: leaking underground storage tanks. I estimate a hedonic model using quasi-experimental and spatial econometric techniques. Similar to previous studies, I examine how house prices vary with distance to the disamenity. This approach yields little evidence that prices are adversely impacted. However, to better measure risks I utilize home-specific data on groundwater well tests and correspondence from regulators, and find an 11% depreciation when households are well informed.

 A horizontal cylindrical steel tank with a factory applied coating and galvanic anodes

http://en.wikipedia.org/wiki/Underground_storage_tank

by Dennis Guignet, Research Economist, U.S. Environmental Protection Agency, National Center for Environmental Economics

Land Economics http://le.uwpress.org/

Volume 89, Number 2; May 1, 2013; pages 211-22

A full 2012 version of this paper is available free of charge at http://tinyurl.com/aye9hnl

Valuation of Human Health: An Integrated Model of Willingness to Pay for Mortality and Morbidity Risk Reductions

http://yosemite.epa.gov/ee/epa/eed.nsf/WPNumber/2012-07

Abstract:

This paper develops and applies an integrated model of human mortality and morbidity valuation that is consistent with principles of welfare economics. The standard expected utility model of one person facing two health states (alive and dead) is extended to a setting in which two family members (a parent and a child) face three health states (healthy, sick, and dead). A key finding is that total health benefits of public programs equate to the sum of willingness to pay for reduced mortality risk plus a fraction of the willingness to pay for reduced morbidity risk. Implications of the integrated model are tested using two field data sets from the U.S. on skin cancer and leukemia risk reductions. Results obtained show how the integrated model can be used to increase the accuracy of health benefit estimation for benefit-cost analyses as well as for the design of public hazard reduction programs.

...

Willingness to pay values obtained from the constrained estimates are presented in Table 6. These estimates show that parents are willing to pay $70.06 annually for a 100% reduction in unconditional mortality risk from skin cancer for themselves and are willing to pay $105.44 annually for a 100% reduction in unconditional mortality risk from skin cancer for their children.

For leukemia, constrained estimates suggest that parents are willing to pay $811.29 to eliminate their children’s unconditional mortality risk. This estimate exceeds the corresponding estimates for skin cancer possibly because in the leukemia study, parents were asked for an immediate, one-time payment for vaccines that would be effective for life; whereas in the skin cancer study, parents were asked how much they would pay in the first year for sun lotions when a stream of annual purchases would be required to maintain effectiveness. Table 6 also indicates that parents are willing to pay $760.81 to eliminate leukemia likelihood risk for themselves and -$295.02 (estimate not significantly different from zero at conventional levels) to eliminate conditional mortality risk for this disease for themselves.

...

An “average” parent’s willingness to pay to reduce her children’s and her own unconditional mortality risk of skin cancer by 1 in 10,000 are $0.48 and $0.21, respectively. These point estimates suggest that parents are willing to pay more than twice as much to reduce unconditional mortality risk for their children than they are willing to pay to reduce their own risk.22 In light of the finding of perfect substitution between illness likelihood risk and conditional mortality risk, the value of reduced morbidity from skin cancer is zero. The “average” parent’s willingness to pay to reduce unconditional mortality risk from leukemia by 1 in 10,000 to their child is $4.28. In light of perfect substitution, the value of reduced morbidity risk for children implied by the estimates is equal to zero.

...

VSL estimates can be obtained by multiplying the estimates of willingness to pay to reduce unconditional mortality risk shown in Table 7 by 10,000. The skin cancer estimates, which pertain to one-year risk reductions, suggest VSL values of $4,800 for children and $2,100 for adults. The corresponding VSL values for leukemia, which pertain to permanent risk reductions, are $42,800 for children and $13,100 for adults.
Two factors may help to explain why these VSL values are much lower than those generally obtained in labor market studies (Viscusi and Aldy 2003). First, labor market estimates of VSL are interpreted as the marginal value of saving one life; whereas estimates presented here are interpreted as the average willingness to pay to save one life in the case where unconditional mortality risk is eliminated.24 Marginal willingness to pay for a unit of risk reduction would be expected to decline as successive increments in risk reduction are considered (see Section 2), thus the VSL obtained here is expected to be lower than the estimates of VSL obtained in other studies. Second, parents tended to overestimate illness likelihood risk and conditional mortality risk in both the skin cancer and leukemia data sets. A given value for willingness to pay to eliminate reduced unconditional mortality risk may therefore underestimate willingness to pay to reduce a unit of risk.

...

by Shelby Gerking 1, Mark Dickie 2 and Marcella Veronesi 3
1. Corresponding author, Department of Economics, University of Central Florida, P.O. 1400, Orlando, FL 32816-1400, United States and Department of Economics and Tilburg Sustainability Center, Tilburg University, P.O. Box 90153, 5000 LE Tilburg, the Netherlands. email: 56f100pu@gmail.com phone: 407-349-9093 fax: 407-823-3669
2. Department of Economics, University of Central Florida, P.O. 1400, Orlando, FL 32816-1400, United States email: mdickie@bus.ucf.edu.
3. ETH Zurich, Universitaetstrasse 22, 8092 Zurich, Switzerland email: marcella.veronesi@env.ethz.ch

U.S. Environmental Protection Agency National Center for Environmental Economics (NCEE) http://yosemite.epa.gov/ee/epa/eed.nsf/webpages/homepage

Working Paper 12-07; October, 2012

Keywords: willingness to pay, children, environmental hazards, health, integrated analysis, morbidity, mortality, value of a statistical life, cancer, stated preference 

The Price Premium for Organic Wines: Estimating a Hedonic Farm-gate Price Equation

http://ideas.repec.org/p/hhs/osloec/2013_007.html

http://www.sv.uio.no/econ/english/research/memorandum/pdf-files/2013/memo-07-2013.pdf

Abstract::

Organic wines are increasingly produced and appreciated. Since organic production is more costly, a crucial question is whether they benefit from a price premium. We estimate hedonic price functions for Piedmont organic and conventional wines. We use data on the production side in addition to variables of interest [to] consumers. Our results show that, along with characteristics of interest to consumers, some farm and producer characteristics not directly relevant for consumers do significantly affect wine prices. We find that organic wine tends to obtain higher prices than conventional wine. The price premium is not simply an addition to other price components, but organic quality modifies the impact of the other variables on price.

...

Delmas, Doctori-Blas and Shuster (2008) report that organic wine-growing costs in California are 10 to 15 percent higher than for conventional grapes.

 http://en.wikipedia.org/wiki/Italian_wine

...

Among [on-farm winemakers 1.3 percent] had some organic production (not necessarily wine) [which] mirrors the general percentage of organic farms in the region.

...

A DOC appellation(Denominazione di Origine Controllata – Controlled Designation of Origin)  relative to no appellation (table wines), raises the price by about 38 percent. The DOCG (Denominazione di Origine Controllata e Garantita -Controlled and Guaranteed Designation of Origin) classification raises the price by [an additional] 14 percent... The only variety with a significant positive premium is Nebbiolo. This is an expected result, since it is the grape variety from which the most prestigious wines are made (such as Barbaresco and Barolo). The price premium is as high as 71.5 percent.... The more specialized the producer is in producing wine (in terms of the share of total agricultural area devoted to grape production), the higher is the price of his wine. The price increase is close to 0.4 percent for each additional 1 percent of agricultural area devoted to wine-growing. This result can be interpreted both in terms of better quality (and hence, higher prices) of specialized farmers, and in better marketing skills of farmers [devoted] specifically to wine-growing.

...

Organic wine - all [else being] ... equal - obtains a higher price in the market.... Under the assumption of the unified model, i.e., that organic quality raises the price but does not change the impact of the other variables on wine price, we find ... the price premium, which did not seem to exist only considering average price data, is actually sizeable, 27 percent.

...

by Alessandro Corsi 1 and Steinar Strom 2

1. Università di Torino, Department of Economics; alessandro.corsi@unito.it

2. University of Oslo, Department of Oslo; steinar.strom@econ.uio.no

Length: 28 pages

Date of creation: 11 Mar 2013

University of Oslo, Department of Economics, http://www.oekonomi.uio.no/indexe.html P.O Box 1095 Blindern, N-0317 Oslo, Norway; Phone: 22 85 51 27; Fax: 22 85 50 35; Email: econdep@econ.uio.no;

Keywords: Organic wines; Hedonic price functions; Farming; Prices; Price variables;

The Impact of Brownfields on Residential Property Values in Cincinnati, Ohio: A Spatial Hedonic Approach

http://ideas.repec.org/p/hhs/huiwps/0085.html

Abstract:

This paper empirically assesses the impact brownfield sites have on market values of single-family residential properties. Using three different hedonic model specifications, namely Ordinary Least Squares, Spatial Autoregressive, and Spatial Error Model, this study shows that properties located less than 1,000 feet from a brownfield site experience a significant depreciation in property values. As expected, spatial dependence among real estate property values is present meaning that the two spatial hedonic model specifications are superior to the Ordinary Least Squares specification. The study contributes to the relevant real estate and urban economics literature by determining the negative impact brownfield sites have on the value of single-family residential properties in our study region in Cincinnati, by explicitly accounting for the phenomenon of spatial dependence in the dependent variable, and by addressing the declining influence of brownfield sites on property values in a nonlinear relationship.

...

Most of the variables in each of the three model specifications are statistically significant at the 99% level of confidence.... The interpretation of the spatial dependence in the Spatial Autoregressive (SAR) specification is a structural process, based on the assumption of omitted variables....  As such, the SAR approach does account to some extent for ... latent influences, such as noise and crime issues and other excluded variables. The total SAR impacts ... show that one additional bedroom adds 8.67% to the market value of a house, while a full bath and a half bath add 16.18% and 11.37% respectively. Having a central air conditioning system increases the property value by 35.72%, while a heating system adds 27.03% and a garage adds 12.86%.... An increase in the age of the house by one year causes a decrease in the property value by only 0.68%; a 1% increase of the population aged 25 or older holding a bachelor's degree or higher by ZIP code increases the property values by 1.37%. Also of note is that properties in very poor and unlivable condition are devalued by 81.12%.

http://www.dep.state.fl.us/mainpage/programs/brownfields.htm

The total estimated impact with respect to the distance of a property to its closest brownfield is -0.23076. ... Decreasing the maximum distance allowed to a brownfield site, i.e., from 1,000 to 0 feet ... translates into a maximum possible reduction in property value of or 19.96%. In other words, ... the largest change in property value is 19.96%. ...

The Spatial Error Model (SEM) addresses spatial dependence through spatially structured random effects in the disturbance process.... The SEM results indicate that one additional bedroom, full bath, and a half bath add 7.05%, 14.03%, and 10.35% respectively to property values. An increase in property value of estimated 28.28%, 31.98%, and 12.19% is associated with adding an air conditioner, a heating system, and a garage, while age and very poor condition reduce property values by 0.64% and 86.72%. Again, a 1% increase in the population with at least a college degree increases the property values by 1.35%.

With an estimated coefficient of -0.2536, brownfields have in the SEM specification a somewhat higher influence on residential property prices. Here, a maximum possible reduction in property value is calculated as 21.93%, related to reducing the distance to the closest brownfield site from 1,000 to 0 feet.
....
Reducing the distance from 500 to 0 feet under the SEM model results in a decrease of residential property values of 16.03%, while reducing the distances from 1,000 to 500 feet and from 500 to 100 feet results in property reductions of 5.90% and 11.43% respectively. The non-linear relationship implies that brownfield sites have a larger impact on prices of properties that are closer than of those that are further. More specifically, reducing the distance from 100 to 0 feet in the SEM specification results devaluates a property by 4.60%, while reducing the distance from 1,000 to 900 feet devalues a property by 0.76%.
...
Using the results from the Spatial Autoregressive (SAR) or the Spatial Error Model (SEM) specification respectively, the authors estimated that brownfield sites in the City of Cincinnati, Ohio devalue housing prices by as much as 19.96% to 21.93% for those properties that are adjacent to brownfield sites. For the average priced house of $94,595 in our sample that means a devaluation of $18,881 to $20,745.

...

by Oana Mihaescu 1 and Rainer vom Hofe 2

1. HUI Research oana.mihaescu@hui.se

2. University of Cincinnati

Date of creation: 24 Apr 2013

The Swedish Retail Institute (HUI), Regeringsgatan 60, 103 29 Stockholm, Sweden; Phone: +46 (0)8 762 72 80, Fax: +46 (0)8 679 76 06; http://www.hui.se/ email: info@hui.se

via Research Papers in Economics
www.REPEC.org

The Economics of Ecosystems and Biodiversity (TEEB) for Business Coalition Study Shows Multi Trillion Dollar Natural Capital Risk

http://tinyurl.com/d8t5uwa

The report, “Natural Capital at Risk – The Top 100 Externalities of Business”, estimates the global top 100 environmental externalities are costing the economy world-wide around $4.7 trillion a year in terms of the economic costs of greenhouse gas emissions, loss of natural resources, loss of nature-based services such as carbon storage by forests, climate change and air pollution-related health costs. This was released today from The TEEB for Business Coalition during the Business for the Environment summit in New Delhi.

Companies and their investors face both an opportunity and a significant problem. Consumer demand is set to grow significantly over the next few years with the increase in middle class consumers, especially in emerging markets. However, this is against a backdrop of increasing resource scarcity and the degradation of our natural ecosystems. One of the challenges will be to understand the value of the natural systems we rely on – commonly referred to as natural capital - and how these systems can be managed. The current business model creates significant environmental externalities. For example, water is not usually priced according to how scarce it is. The report, authored by Trucost, identifies financial risk from environmental externalities e.g. damages from climate change, pollution, land conversion and depletion of natural resources, across business sectors at a regional level. It demonstrates that high impact business sectors make an economic loss when the costs of environmental damage such as their natural resource use and pollution costs are accounted for.

http://oregonstate.edu/instruction/anth481/ectop/ecservices.html

However, businesses and investors can take account of natural capital impacts in decision making to manage risk and gain competitive advantage.

Headline findings are:

• The primary production (agriculture, forestry, fisheries, mining, oil and gas exploration, utilities) and primary processing (cement, steel, pulp and paper, petrochemicals) sectors analyzed are estimated to have externality costs totalling US$7.3 trillion, which equates to 13% of global economic output in 2009.
• The value of the Top 100 externalities is estimated at US$4.7 trillion or 65% of the total primary sector impacts identified.
• The majority of environmental externality costs are from greenhouse gas emissions (38%) followed by water use (25%); land use (24%); air pollution (7%), land and water pollution (5%) and waste (1%).

The highest impact sectors by region globally include:

• Coal-fired power in Eastern Asia and in Northern America rank 1 and 3, respectively estimated at US$ 453 billion per annum in Eastern Asia and US$ 317 billion in North America. These consist of
• the damage impacts of GHG emissions, and the health costs and other damage due to air pollution. In both instances, these social costs exceeded the production value of the sector.
• The other highest impact sectors are agriculture, in areas of water scarcity, and where the level of production and therefore land use is also high. Cattle ranching in South America, at an estimated US$ 354 billion ranks second. Wheat and rice production in Southern Asia rank fourth and fifth respectively.
• Iron, steel and ferroalloy manufacturing ranks 6 at US$225 billion. Cement manufacturing globally accounts for 6% of CO2 emissions, and Eastern Asia produces an estimated 55% of the world’s cement, so it is not surprising that it comes in at # 7.

During the past decade commodity prices erased a century-long decline in real terms, and risks are growing from over-exploitation of increasingly scarce, unpriced natural capital. Depletion of ecosystem goods and services, such as damages from climate change, pollution or land conversion, generate economic, social and environmental externalities. Growing business demand for natural capital, and falling supply due to environmental degradation and events such as drought, are contributing to natural resource constraints including water scarcity.

The report assessed more than 100 environmental impacts using the Trucost environmental model which condenses them into six eKPIs to cover the major categories of natural capital consumption: water use, greenhouse gas (GHG) emissions, waste, air pollution, water and land pollution, and land use. These eKPIs were then quantified by region across over 500 business sectors. The method used has limitations and is only designed to give a high-level indication of the priority sectors and regions where natural capital risk lies. Limitations in the method are outlined in the report to support ongoing development of this type of analysis.

The study ranks the top 100 impacts in each sector, broken down by region to provide a platform for companies and investors to assess exposure to unpriced natural capital, both directly and through supply chains and holdings. It also highlights sector-level variation in regional exposure to impacts to identify opportunities to enhance competitive advantage. Impacts across all six eKPIs were combined by region and sector to create a ranking of the top region-sectors globally.

Alastair MacGregor, Chief Operating Officer of Trucost, who conducted the study states, “Recent soft commodity price volatility due to drought, and its impacts on company profits, nation’s trade balances and inflation has underscored the dependency of investment returns on natural capital. This trend will accelerate in the future on a number of fronts .”

...

The report shows that the scale and variation in impacts provide opportunities for companies and their investors to differentiate themselves by optimizing their supply chains and investment strategies. Some recommendations for companies include implementing processes to measure and manage natural capital used; strengthening business models to mitigate exposure to global risks such as water scarcity, volatile energy and agricultural prices, rising GHG emissions and climate change impacts.

...

Commenting on the study Michael Izza, chief executive of ICAEW explains, “This study highlights that the disciplines of accountancy and economics need to evolve to recognise that the limiting factors to production and growth are no longer just labour, capital and technology. As our economies, populations and our consumption have grown exponentially relative to nature, which once seemed so abundant and limitless, we now have to face the fact that this is not so.”

Download the Natural Capital at Risk: The Top 100 Externalities for Business Report free of charge at http://www.teebforbusiness.org/how/natural-capital-risk.html

Strategically Placing Green Infrastructure: Cost-Effective Land Conservation in the Floodplain

http://www.rff.org/Documents/EST-green-infrastructure-report.pdf

Abstract:

Green infrastructure approaches have attracted increased attention from local governments as a way to lower flood risk and provide an array of other environmental services.  The peer-reviewed literature, however, offers few estimates of the economic impacts of such approaches at the watershed scale. Carolyn Kousky, Sheila M. Olmstead, Margaret A. Walls and Molly Macauley; all of Reesources for the Future estimate the avoided flood damages and the costs of preventing development of floodplain parcels in the East River Watershed of Wisconsin’s Lower Fox River Basin. Results suggest that the costs of preventing conversion of all projected floodplain development would exceed the flood damage mitigation benefits by a substantial margin. However, targeting of investments to high-benefit, low-cost parcels can reverse this equation, generating net benefits. The analysis demonstrates how any flood-prone community can use a geographic-information-based model to estimate the flood damage reduction benefits of green infrastructure, compare them to the costs, and target investments to design cost-effective nonstructural flood damage mitigation policies.

...

Estimates of the avoided flood damage from floodplain conservation...  include total building, content, and inventory loss; business interruption loss; the number of at least moderately damaged buildings; and the truckloads of debris generated. Estimating agricultural losses using Hazus would have required many assumptions, including the timing of floods during crop cycles, and changes in crop yields....

 

http://dnr.wi.gov/topic/greatlakes/greenbay.html

As expected, losses increase with flood event severity (all estimates are in 2010 dollars). The estimated building, content, and inventory loss for a 100-year flood event in the ERW is approximately $84 million (for residential properties, Hazus estimates an average of $132,600 of building and contents losses per damaged household). A 10-year flood generates losses about half this size, while a 200-year flood generates losses of $95million. These expected losses vary across the watershed, with depth of flooding and the density of affected structures. The Brown County Planning Department forecasts an additional 54,819 residents in the county by 2025, creating demand for about 21,000 acres of new residential development and 2,447 acres of commercial development. These forecasts, made available to the author in GIS so that they could identify the particular parcels expected to convert, are the basis for their future development scenario. We identify all parcels that were in natural areas or agriculture in the 2010 tax assessor maps, but are projected to be in some developed use by 2025 in Brown County’s forecasts. Table 2 summarizes the estimated flood damages for this future development scenario. Building losses increase, relative to 2010, by roughly $3−15 million, depending  on the event. For the 100-year flood, for example, building losses increase from $84 million to $96 million with the additional acres of development.

...
The 2010 AAL, the expected economic damage from flooding in any given year in the ERW with 2010 land use and development patterns, is $19.43 million. The AAL for the future (2025) scenario is $22.06 million. The difference, $2.63 million, is the increase in expected annual flood damages from the additional  development projected to occur by 2025. Correspondingly, this is an estimate of the annual benefits of avoided flood damages if the planned floodplain development does not occur.