Coastal SEES Collaborative Research: Non-Market Value Meta-Data on Willingness to Pay for Coastal Marsh Habitat Change

These data represent a meta-dataset of observations on per household economic value - represented by per household willingness-to-pay (WTP) - for improvements in coastal marsh habitat, drawn from stated-preference studies in the research literature. The metadata allow estimation of benefit transfer functions via meta-regression modeling. Within these econometric functions, the dependent variable is a comparable estimate of economic value (e.g., WTP) drawn from extant primary valuation studies. Independent variables represent observable factors hypothesized to explain variation in this value measure across observations. These functions can be used to produce out-of-sample predictions of WTP for coastal marsh habitat improvements at sites for which no primary valuation studies have been conducted. They can also be used to understand the factors associated with systematic variations in marsh habitat values across different sites and studies. These data are described in Vedogbeton, H. and R.J. Johnston. 2020. Commodity Consistent Meta-Analysis of Wetland Values: An Illustration for Coastal Marsh Habitat. Environmental and Resource Economics 75(4), 835-865, and allow replication of the results presented therein. The metadata are extracted from primary studies that estimate total (use and nonuse) per household WTP for changes in the quantity or quality of coastal marsh wildlife habitats or their services, in US and Canada. These studies were identified via a systematic review of the literature. The metadata combine information provided by these primary non-market valuation studies with publicly available external data extracted from sources such as the US Census, US National Historical GIS (https://www.nhgis.org/), and US Fish and Wildlife Service National Wetlands Inventory (https://www.fws.gov/wetlands/Data/Mapper.html). Studies included in the metadata are restricted to those that estimate total per household WTP for coastal wetland habitat changes using generally accepted stated preference methods, report theoretically comparable and quantifiable measures of economic value, and provide sufficient information to enable inclusion in the metadata. The data are further restricted to observations from studies conducted in the US or Canada, and published between 1990 and 2016, inclusive. The resulting metadata include 141 total observations of WTP per household from 23 studies published from 1990 to 2016, with all values adjusted to 2016 USD. These 141 habitat-value observations are identified by the variable changsize = 0 within the data. Because the meta-analysis is restricted to WTP in the positive domain, two negative-WTP observations were subsequently dropped, leading to the 139 habitat-value observations reported in Vedogbeton and Johnston (2020). An additional 18 metadata observations are drawn from similar primary stated preference studies that estimate total WTP for changes in coastal marsh area (or size), where these area increases provide habitat combined with other wetland services such as flood control, water filtration, aesthetics, recreation, and habitat. These additional observations are used for the habitat-and-area value models in the paper, and are identified by the variable changsize = 1 within the data. The combined data include 159 total observations (141 habitat-value and 18 habitat-and-area value observations). The metadata compile variables characterizing (1) the scope [magnitude] of the valued habitat change and the spatial scale of the wetland area affected by the change, (2) the type of habitat, marsh and uses affected, (3) regions sampled by the primary study, and (4) original study methodology used to measure the value(s), sample size from these studies, and year. The categorical variable "code" identifies how each of these observations are used within the data analysis of Vedogbeton and Johnston (2020). The attached pdf file, "Stata Code_Marsh Meta", provides illustrative Stata (v16) code used to generate some of the primary model results in this article, using the data. Note that some variable labels in the Stata code differ slightly from those used in the published paper. This project was supported by National Science Foundation grant 1427105.