ABSTRACT
Recent rapid growth of shale gas exploration in the state of Colorado (CO) and elsewhere in the United States has caused considerable public concern over potential environmental costs to local communities, proximal to the location of energy development. In Weld County, CO, shale gas exploration has grown substantially since 2013. Both population and new construction of houses also increased significantly after 2012. Combined, this increased the potential for negative externalities. The objective of the analysis is to apply the hedonic pricing method, using single-family residential data from October 2014 to March 2017 and a temporal-spatial identification strategy, to estimate the environmental cost of shale gas exploration on nearby house prices in Weld County, CO. However, results from spatial econometric models provide no evidence of significant environmental impacts on housing values. Our policy discussion explores a possible Coasian bargaining solution as the source for this case of a missing negative externality. The energy and housing markets appear to be internalising externalities, where side payments from energy developers to homeowners are enough to compensate for any environmental impacts to housing.
Acknowledgments
We thank Dennis Ahlstrand, Colorado Oil & Gas Conservation Commission for answering questions concerning GIS data, Courtney Anaya, Weld County Assessor's Office for help on housing data, and Ric Wise, Ashlie Koehn from the U.S. Bureau of Labor Statistics for detailed answers to our questions about oil and gas employment data.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. Different from other states, Colorado does not charge a permit fee for an application. This provides an incentive for operators to keep a number of permits to drill and wait until the oil price to rise or sell to another operator who is ready to drill. That is why some wells go through several re-fillings before they get drilled or they never get drilled.
2. After wells spud, they are eliminated from the permit data-set. The only way to match spud date and permit approval date for the same well is to look at each individual scout card, one well at a time.
3. Maximum likelihood estimation with spatial lag or spatial error models is often carried out (Anselin Citation1988). This approach requires calculation of an spatial weighting matrix, which is not feasible in the context of large number of varying properties transacted over time. In such cases, an instrumental variable method may be preferred.
4. These three alternative functional forms for the models have no substantial difference in estimated results. Full results are available upon request from the lead author.
5. This possibility is higher for Colorado compared to those states with permit application fees.
6. In Weld County, surface property rights can be severed from subsurface mineral rights. It is possible that individual property owners do not have claims to either bonus or lease payments underground. Results represent an average effect across properties, whose owners own mineral rights and not.