Do Landfills Always Depress Nearby Property Values?

All available hedonic pricing estimates of the impact of landfills on nearby property values are assembled, including original estimates for three landfills in Pennsylvania. A meta-analysis shows landfills that accept high volumes of waste (500 tons per day or more) decrease adjacent residential property values by 13.7%, on average. This impact diminishes with distance at a gradient of 5.9% per mile. Lower-volume landfills decrease adjacent property values by 2.7%, on average, with a gradient of 1.3% per mile. While essentially all high-volume landfills negatively impact nearby property values, 20-26% of low-volume landfills do not impact nearby property values.

Spatial Econometric Approaches to Estimating Hedonic Property Value Models

The inclusion of spatial correlation of house price in hedonic pricing model may produce better marginal implicit price estimate(s) of the environmental variable(s) of interest. Most applications where a spatial econometric model is applied to the estimation of a hedonic property value model have used either a spatial lag model or a spatial autoregressive (SAR) error model. Incorrect spatial specification may produce even worse estimate outcome than OLS. Three issues regarding the specification of a spatial hedonic pricing model are considered. First, we question the "convention" of row-standardizing the spatial weights matrix. Second, we argue that the spatial error component (SEC) model is more theoretically intuitive and appealing for modeling house price. Third, we explore whether the choice of spatial model is important, empirically, using a large house sale dataset that includes measures of proximity to landfills. With one exception, estimated marginal implicit prices are fairly robust across all models.row-standardization, spatial econometrics, SEC model, SAR error model, spatial lag model, hedonic pricing, landfill, house price, Public Economics,

The Impact of Agricultural Conservation Easement on House Prices: A New Hedonic Price Model That Incorporates Spatial Autocorrelation and Spatial Heterogeneity

Research Methods/ Statistical Methods,

Benefit Transfer – The Quick, the Dirty, and the Ugly?

Environmental Economics and Policy,

Using Frontier Models to Mitigate Omitted Variable Bias in Hedonic Pricing Models: A Case Study for Air Quality in Bogotá, Colombia

Hedonic pricing models use property value differentials to value changes in environmental quality. If unmeasured quality attributes of residential properties are correlated with an environmental quality measure of interest, conventional methods for estimating implicit prices will be biased. Because many unmeasured quality measures tend to be asymmetrically distributed across properties, it may be possible to mitigate this bias by estimating a heteroskedastic frontier regression model. This approach is demonstrated for a hedonic price function that values air quality in Bogotá, Colombia.hedonic pricing model, omitted variables, air quality, frontier model

MODELING ECONOMIC GROWTH WITH UNPREDICTABLE SHOCKS: A STATE-LEVEL APPLICATION FOR 1960-90

A Barro-type economic growth model is estimated for the 50 states in the U.S. using data for three decades beginning in 1960. Frontier estimation techniques are used to test for the presence of state-specific shocks to economic growth that are independent of the usual, normally-distributed random errors. We find that large, positive shocks to growth occur during the period 1960-90. Our results indicate that the error term structure assumed each other OLS may not be appropriate for modeling economic growth.Economic growth, Frontier estimation, Shocks, U.S. states, Community/Rural/Urban Development,

OPTIMAL MANAGEMENT OF A FOREST/WILDLIFE SYSTEM WITH BILATERAL EXTERNALITIES

Browsing by large ungulate wildlife species damages valuable trees, but increases the productivity of the wildlife stock. The optimal management of trees and wildlife involves a tradeoff between these two impacts, as well as correct timing of tree harvests from each forest stand. For a model of moose and pine in Norway, it is found that harvest of adjacent forest stands should be adjusted over time to bring the stands into synch. Doing so maximizes the moose productivity boost that occurs immediately following harvest of mature trees, and protects the young trees from overbrowsing by spreading out the browsing pressure among more young trees. This result is, however, sensitive to the specification of the relationship between forage availability and moose productivity.Resource /Energy Economics and Policy,

MEASURING CONSUMER BENEFITS OF FOOD SAFETY RISK REDUCTIONS

Microbial pathogens and pesticide residues in food pose a financial burden to society which can be reduced by incurring costs to reduce these food safety risks. We explore three valuation techniques that place a monetary value on food safety risk reductions, and we present a case study for each: a contingent valuation survey on pesticide residues, an experimental auction market for a chicken sandwich with reduced risk of Salmonella, and a cost-of-illness analysis for seven foodborne pathogens. Estimates from these techniques can be used in cost/benefit analyses for policies that reduce food safety risks.Contingent valuation, Cost of illness, Experimental auction market, Food safety, Risk reduction, Salmonella, Food Consumption/Nutrition/Food Safety,

DESIGNING WETLAND CONSERVATION STRATEGIES UNDER CLIMATE CHANGE

A methodology for evaluating public wetlands conservation investments that considers climate change is developed and applied to Virginia's Elizabeth River watershed. A revised cellular automaton (CA) model is applied to project future land use change. Discrete stochastic sequential programming (DSSP) is used to model a parcel-based discrete-time decision process.Environmental Economics and Policy,