Publication

Publication

1. Causal inference, high-frequency data, and the recreational value of water quality (with Andrew Earle)    *Status: Conditionally Accepted at Journal of the Association of Environmental and Resource Economists

      Keywords: recreation demand | panel causal inference | revealed preferences | beach closure | welfare measurement | non-market valuation

Emerging datasets capture rich temporal variation in recreation behavior, but recre- ation demand analyses have traditionally used variation across sites, rather than across time, to value environmental amenities. We introduce a model and estimation proce- dure designed to exploit panel variation in recreation demand analyses by embedding panel data causal inference techniques within a travel cost random utility model. To demonstrate the method, we use “structural synthetic controls” to value the welfare losses caused by water-quality-induced beach closures in southeast Michigan. Losses tend to be larger on weekends and hotter days, and our results suggest that a stigma effect reduces visitation even after the beach reopens. Our method is particularly use- ful for valuing the recreational impacts of resource shocks, like harmful algal blooms or wildfires, and it can be applied broadly given the increasing availability of high- frequency recreation data.

2.  Getting off the ladder: Disentangling water quality indices to enhance the valuation of divergent ecosystem services. with Frank Lupi, Joseph A. Herriges, and R. Jan Stevenson.

Proceedings of the National Academy of Science, 120(18), e2120261120, April 2023. 

Keywords: water quality indices | stated preferences | willingness to pay

Many water quality valuation studies and Federal cost–benefit analyses build from pioneering work using a “water quality ladder” or a single water quality index (WQI) to characterize both current conditions and effects of policies. When policies lead to contrasting changes in valued ecosystem services like recreational fishing and swimming, analyses using a single ladder or index might obscure important underlying service trade-offs. We test for this effect using alternative approaches that separate water quality indices and value changes in distinct ecosystem services stemming from policies with small to moderate changes in water quality. The indices we test relate to nutrient loadings in Michigan’s rivers, lakes, and Great Lakes. Our split-sample experiment compares economic values for treatments with two versus three quality metrics. The key distinction is that the two-index survey, like many existing studies, aggregates subindices for water contact (for swimming and boating) and fish biomass scores (for fishing) into a single WQI, whereas the three-index survey separately utilizes both. We find that changes in our index reflecting changes in fecal bacteria and water clarity are valued differently from changes in our recreational fishing index. Aggregating changes in these two distinct recreational services using a single WQI yields consistently lower benefit estimates across a range of underlying changes in our experiment. In valuation scenarios with small changes in overall water quality, the WQI-based benefit estimates can differ substantially from benefits measured by decomposing the index and valuing the disparate subindices, differences which might change balance of benefits and costs in regulatory evaluations. 

3. Comparing water quality valuation across probability and non-probability samples.  with Kaitlynn Sandstrom-Mistry, Frank Lupi, and Joseph A. Herriges.

Applied Economic Perspectives and Policy, 45(2): 744–761, May 2023.

Keywords: address based sampling | contingent valuation |  MTurk | Qualtrics | stated preferences

We compare water quality valuation results from a probability sample and two opt-in non-probability samples, MTurk and Qualtrics. The samples differ in some key demographics, but measured attitudes are strikingly similar. For valuation models, most parameters were significantly different across samples, yet many of the marginal willingness to pay were similar across samples. Notably, for non-marginal changes there were some differences by samples: MTurk values were always significantly greater than the probability sample, as were Qualtrics values for changes up to about a 20% improvement. Overall, the evidence is mixed, with some key differences but many similarities across samples. 

4. Testing the robustness of a structural model for discerning use and non-use values of ecosystem services. with Frank Lupi.

Agricultural and Resource Economics Review, 52(2), 406-421, August 2023. 

Keywords: ecosystem services | Monte Carlo simulation | nonmarket valuation | structural estimation | combined revealed and stated preferences

A theoretically consistent structural model facilitates definition and measurement of use and non-use benefits of ecosystem services. Unlike many previous approaches that utilize multiple stated choice situations, we apply this conceptual framework to a travel cost random utility model and a consequential single referendum contingent valuation research design for simultaneously estimating use and non-use willingness to pay for environmental quality improvement. We employ Monte Carlo generated data to evaluate properties of key parameters and examine the robustness of this method of measuring use and non-use values associated with quality change. The simulation study confirms that this new method, combined with simulated revealed and stated preference data can generally, but not always, be applied to successfully identify use and non-use values of various ecosystems while consistency is ensured. 

• ARER Outstanding Article of 2023, Northeastern Agricultural and Resource Economics Association