Scope Elasticity of Willingness to pay in Discrete Choice Experiments

Abstract

Sensitivity to scope in nonmarket valuation refers to the property that people are willing to pay more for a higher quality or quantity of a nonmarket public good. Establishing significant scope sensitivity has been an important check of validity and a point of contention for decades in stated preference research, primarily in contingent valuation. Recently, researchers have begun to differentiate between statistical and economic significance. This paper contributes to this line of research by studying the significance of scope effects in discrete choice experiments (DCEs) using the scope elasticity of willingness to pay concept. We first formalize scope elasticity in a DCE context and relate it to economic significance. Next, we review a selection of DCE studies from the environmental valuation literature and derive their implied scope elasticity estimates. We find that scope sensitivity analysis as validity diagnostics is uncommon in the DCE literature and many studies assume unitary elastic scope sensitivity by employing a restrictive functional form in estimation. When more flexible specifications are employed, the tendency is towards inelastic scope sensitivity. Then, we apply the scope elasticity concept to primary DCE data on people’s preferences for expanding the production of renewable energy in Norway. We find that the estimated scope elasticities vary between 0.13 and 0.58, depending on the attribute analyzed, model specification, geographic subsample, and the unit of measurement for a key attribute. While there is no strict and universally applicable benchmark for determining whether scope effects are economically significant, we deem these estimates to be of an adequate and plausible order of magnitude. Implications of the results for future DCE research are provided.

The Reliability of Delphi Surveys and Benefit Transfer to Predict Outcomes of Contingent Valuation Surveys

“…The assumption was pre-determined by the linear specification of the utility functions in Siikamaki et al (2019) to estimate WTP. However, recent research shows that when imposing more flexible utility specifications in analyzing CE data, scope elasticities can range from 0.13 to 0.58 (Dugstad et al, 2021). From our population CV results, the scope elasticity of WTP for the two preservation plans equals 0.46. x Correspondingly, in Scenario 1, we employ a scope elasticity of 0.46 for the Further, the simulated WTP version for Plan A and Plan B using a scope elasticity of 0.46 is NOK 1140 and NOK 577, respectively.…”

“…In our primary analysis (and in the simulated reference scenario), we assumed a scope elasticity of WTP of one for the North American BT exercise, meaning that when the quality or quantity of the environmental good increases by 1 percent, WTP will also increase proportionally (Amiran & Hagen, 2010;Whitehead, 2016;Kling & Phaneuf, 2018;Dugstad et al, 2021). The assumption was pre-determined by the linear specification of the utility functions in Siikamaki et al (2019) to estimate WTP.…”

Spatial Trade-Offs in National Land-Based Wind Power Production in Times of Biodiversity and Climate Crises

“…In our base case, we use an average, annual mean willingness to pay (WTP) to avoid one turbine of €23 per household taken from the only two local non-market valuation studies we are aware of from Norway. Both are choice experiment studies: one from a proposed WPP in the municipality of Sandnes on the west coast (García et al 2016, WTP estimate used in Grimsrud et al 2021) and one from a proposed WPP in the municipality of Aurskog-Høland in eastern Norway (Dugstad et al 2022). Because of well-known concerns related to hypothetical bias in choice experiment and other stated preference methods, we choose conservative estimates from these studies.…”

“…There is uncertainty regarding the local disamenity cost specification. Both theoretical and empirical studies generally show ambiguous results for distance decay effects, which determine boundaries for affected populations (e.g., Glenk et al 2020) and the scope effects (e.g., Dugstad et al 2021) of environmental impacts. This is also the case for wind power externalities, e.g., Wen et al (2018) and Mattmann et al (2016).…”

Altruist Talk May (also) Be Cheap: Revealed Versus Stated Altruism as a Predictor in Stated Preference Studies

“…Reciprocity promotes social norms, by encouraging hard-working colleagues or sanctioning free riders (Czajkowski et al 2017). 3 Sensitivity to scope in nonmarket valuation refers to the property that people are willing to pay more for a higher quality or quantity of a nonmarket public good (see e.g., Dugstad et al 2021). 4 Andreoni (1989) terms prosocial behaviour entirely motivated by the concern for others as pure altruism, prosocial behaviour entirely motivated from the warm glow of giving pure egoism, while prosocial behaviour motivated by both altruism and egoism, he terms impure altruism.…”