Using revealed and stated preference data to estimate the scope and access benefits associated with cave diving

In a single-site travel cost model framework, revealed and stated preference data are jointly estimated to provide the first use-value estimate associated with recreational cave diving. Focusing on one of Florida's first magnitude springs, we estimate average per-person per-trip use values of approximately $155, generating annual cave diving use values in the region of $1075. Further, in an investigation of potential site quality changes, we find that divers are sensitive to scope effects with an additional cave system increasing annual per-person use values by approximately $100, while improved access yields an additional $50 in per-person annual consumer surplus. Finally, three additional model specifications are estimated and indicate that divers use different travel cost preferences when assessing their revealed and stated preference trip counts but a single preference structure to evaluate site quality changes.     

Augmenting travel cost models with contingent behavior data

This paper proposes contingent behavior survey questions as a valuable supplement to observed data in travel cost models of non-market demand for recreational resources. A set of observed and contingent behavior results for each survey respondent allows the researcher to control for individual heterogeneity by taking advantage of panel data methods when exploring the nature of respondent demands. The contingent scenarios also provide opportunities to (a) test for differences between observed and contingent preferences and/or (b) assess likely demands under conditionsbeyond the domain of observed variation in costs or resource attributes. Most importantly, contingent scenarios allow the researcher to imposeexogenously varying travel costs. Exogenous imposition of travel costs together with panel methods reduces the omitted variables bias that plagues observed-data travel cost models of recreational demand. Using a convenience sample of data for illustrative purposes, we show how to estimate the demand for recreational angling by combining observed and contingent behavior data. We begin with simple naive pooled Poisson models and progress to more theoretically appropriate fixed effects panel Poisson specifications.The authors are at the University of Nevada and UCLA, respectively. We gratefully acknowledge the comments of both Scott Shonkwiler and participants in the W133 meetings in Santa Fe, New Mexico and for research material provided by Wayne Gray. The data were provided by Rang Narayanan. Research assistance was provided by Jerry McGraw and Natalie Tucker. Research partially supported by the Nevada Experiment Station. Any errors or omissions remain the authors' responsibility.     

Measuring angling quality in count data models of recreational fishing

This paper develops a methodology for investigating different specifications of angling quality in recreational demand models. The methodology is used to compare three alternative specifications of the relationship between angling demand and site quality. The site quality alternatives include chemical concentrations, biological stress indices based on the chemicals, and catch per unit effort. The three alternatives are differentiated using a likelihood ratio non-nested testing procedure.     

Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles

According to intuition and theories of diffusion, consumer preferences develop along with technological change. However, most economic models designed for policy simulation unrealistically assume static preferences. To improve the behavioral realism of an energy–economy policy model, this study investigates the “neighbor effect,” where a new technology becomes more desirable as its adoption becomes more widespread in the market. We measure this effect as a change in aggregated willingness to pay under different levels of technology penetration. Focusing on hybrid-electric vehicles (HEVs), an online survey experiment collected stated preference (SP) data from 535 Canadian and 408 Californian vehicle owners under different hypothetical market conditions.Revealed preference (RP) data was collected from the same respondents by eliciting the year, make and model of recent vehicle purchases from regions with different degrees of HEV popularity: Canada with 0.17% new market share, and California with 3.0% new market share. We compare choice models estimated from RP data only with three joint SP–RP estimation techniques, each assigning a different weight to the influence of SP and RP data in coefficient estimates. Statistically, models allowing more RP influence outperform SP influenced models. However, results suggest that because the RP data in this study is afflicted by multicollinearity, techniques that allow more SP influence in the beta estimates while maintaining RP data for calibrating vehicle class constraints produce more realistic estimates of willingness to pay. Furthermore, SP influenced coefficient estimates also translate to more realistic behavioral parameters for CIMS, allowing more sensitivity to policy simulations.     

The value of health benefits from ambient air quality improvements in Central and Eastern Europe: An exercise in benefits transfer

This study is an initial effort to estimate one important category of benefits of environmental improvements in Central and Eastern Europe (CEE), those related to the effects of air pollution on human health. Our estimates are derived from data on ambient air quality in selected CEE locations, together with a model that links these ambient conditions to physical impacts on health and attaches economic values (in dollar terms) to these impacts. Given data limitations, our focus here is on three pollutants: particulates (PM), sulfur dioxide (SO₂), and lead (Pb). Our data set includes ambient concentrations for these pollutants in four CEE countries: Bulgaria, Hungary, Poland, and Ukraine.Given the ambient data, dose-response functions taken from the clinical and epidemiological literature in the U.S., Canada, and Western Europe are used to generate estimates of the change in physical effects. These effects then are given an economic value by applying two approaches for scaling unit valuation figures applicable to the U.S. A Monte Carlo model is constructed to propagate the uncertainties of the dose-response functions and unit values to obtain confidence intervals on the total benefits from pollutant reductions in each country. We examine scenarios where the CEE countries improve ambient conditions for the pollutants in question to meet European Community (EC) standards and then compare these scenarios to ones involving uniform percentage ambient reductions across locations in each country.     

Economic and quality of life burden of anemia on patients with CKD on dialysis: a systematic review

Abstract

Aims: The overall cost and health-related quality of life (HRQoL) associated with current treatments for chronic kidney disease (CKD)-related anemia are not well characterized. A systematic literature review (SLR) was conducted on the costs and HRQoL associated with current treatments for CKD-related anemia among dialysis-dependent (DD) patients.

Materials and methods: The authors searched the Cochrane Library, MEDLINE, EMBASE, NHS EED, and NHS HTA for English-language publications. Original studies published between January 1, 2000 and March 17, 2017 meeting the following criteria were included: adult population; study focus was CKD-related anemia; included results on patients receiving iron supplementation, red blood cell transfusion, or erythropoiesis stimulating agents (ESAs); reported results on HRQoL and/or costs. Studies which included patients with DD-CKD, did not directly compare different treatments, and had designs relevant to the objective were retained. HRQoL and cost outcomes, including healthcare resource utilization (HRU), were extracted and summarized in a narrative synthesis.

Results: A total of 1,625 publications were retrieved, 15 of which met all inclusion criteria. All identified studies included ESAs as a treatment of interest. Two randomized controlled trials reported that ESA treatment improves HRQoL relative to placebo. Across eight studies comparing HRQoL of patients achieving high vs low hemoglobin (Hb) targets, aiming for higher Hb targets with ESAs generally led to modest HRQoL improvements. Two studies reported that ESA-treated patients had lower costs and HRU compared to untreated patients. One study found that aiming for higher vs lower Hb targets led to reduced HRU, while two other reported that this led to a reduction in cost-effectiveness.

Limitations: Heterogeneity of study designs and outcomes; a meta-analysis could not be performed.

Conclusions: ESA-treated patients undergoing dialysis incurred lower costs, lower HRU, and had better HRQoL relative to ESA-untreated patients. However, treatment to higher Hb targets led to modest HRQoL improvements compared to lower Hb targets.