Using survey-based choice experiments, we find that willingness to pay (WTP) for cap-and-trade programs depends upon their distributional impacts, including changes in the numbers of carbon-intensive versus green jobs and whether there will be additional regulations to limit non-global co-pollutant emissions from firms that buy permits. We estimate a model suitable for out-of-sample forecasting of WTP in other regions nationally, where systematic heterogeneity is captured by predicted county-level climate-change attitudes from the Yale Climate Map project.
We review a wide selection of published papers that rely on stated preference methods to reveal the tradeoffs that people are willing to make to protect either individual wild bird species, categories of species (guilds), or the habitats upon which these species rely. We focus on the features of these studies that make them more or less suitable for ‘benefits-function transfer,’ where the policy-related usefulness of the original research can be multiplied by transferring the estimated models to predict benefits associated with other types of wild birds in other regions.
Some outdoor recreation activities are regulated and require participants to have a permit or license (e.g., hunting and fishing). However, wildlife watching—and especially birdwatching—is a non-consumptive activity that requires no permit or license and thus leaves few formal data trails. Crowd-sourced data with associated volunteered geographic information, gathered by a variety of citizen/community science projects and social media platforms, can complement the information about non-consumptive activities provided by standard administrative datasets.
Several universities have implemented, and numerous others are considering, internal carbon fee or pricing programs intended to reduce greenhouse gas emissions, finance carbon reduction programs, signal sustainability and/or prepare for future mandatory carbon reductions. We employ survey-based choice experiments concerning potential internal carbon-pricing programs at a flagship public university.
A Heckman-type approach to sample selection correction is inappropriate for the conditional logit choice models used to analyze choice experiments. Logit model errors preclude reliance on the conventional assumption of potentially correlated bivariate normal errors. We propose and demonstrate a novel method of sample selection correction for multi-alternative conditional logit models that adapts mixed logit estimation methods.
Citizen/community science samples are self-selected, limiting their value for predicting population behavior. We field a general-population survey to elicit different levels of knowledge about (or engagement with) the eBird project and transfer a fitted sample-selection function, combining that function with eBird member attributes to correct a model of spatial consideration sets.
We revisit a 2003 general-population survey designed to determine people’s willingness to bear the costs of public policies to reduce illnesses and avoid premature deaths in their communities. We re-estimate earlier models, omitting all respondent-specific characteristics and adding new county-level data on a variety of contextual variables circa 2003. Then we transfer this model to the context of the 2020-21 COVID-19 pandemic, substituting 2020-era levels of the contextual variables.
Using choice experiments from an online survey, we quantify the effect of federal UI on the trade-offs that individuals are willing to make with respect to county-level pandemic policies. When respondents are asked to assume that federal UI will be zero, they tend to be averse to losses in average household income but favorably disposed toward increased unemployment. With positive federal UI payments, however, respondents become more willing to accept losses in average household income but view increased unemployment less favorably.
Studies of participant attention allocation in choice experimentshave found mixed evidence that participants employ attribute non-attendance (ANA) as a decision heuristic or as a part of a fully rational search strategy. Many studies find that correcting for ANA has considerable effects on willingness-to-pay (WTP) estimates, but the right method of correction depends on the reasons for ANA. We conduct an experiment that, coupled with results from a previous survey, give us a uniquely suitable dataset to explore the heuristic-vs.-rationality debate.
The survey instrument for this stated-preference choice experiment includes enough abundance information about individual species of regionally common backyard birds to permit the calculation of a variety of alternative biodiversity measures. The choice tasks in our choice experiment each specifically describe the consequences of the policy for five of the top 25 backyard bird species in the respondent’s region, as well as the average effects on all other common backyard species in the area.
Members of Cornell University’s eBird project report bird sitings at geo-coded destinations. With origin information, we can infer the value to this group of biodiversity in bird species by observing how much more in travel costs they are willing to incur to gain opportunities to see more diverse populations of birds.
We use monthly panel data on birth outcomes for more than 3000 U.S. counties, combined with the timing of heat waves during trimesters of gestation, to identify statistical relationships between prenatal exposure and adverse outcomes for the newborn or the mother.
Members of Cornell University’s eBird project report bird sitings at geo-coded destinations. With origin information, we can infer the value to this group of biodiversity in bird species by observing how much more in travel costs they are willing to incur to gain opportunities to see more diverse populations of birds.
In the Journal of the Association of Environmental and Resource Economics
A set of guidelines for SP studies that is more comprehensive than that of the original National Oceanic and Atmospheric Administration (NOAA) Blue Ribbon Panel on contingent valuation, is more germane to contemporary applications, and reflects the two decades of research since that time.
A failed 2010 ballot proposition sought an $18 per year increase in vehicle registration fees to provide revenue to support state parks. Using data aggregated to the census tract level, we examine factors that affected this effort to retreat somewhat from a `user pays’ approach to funding state parks.
Data from a tornado shelter (safe-room) rebate program in Arkansas from 2006 through 2010 permits us to examine the role of risk perceptions in stimulating homeowner investments in self-protection. The decision to self-protect depends upon both the recency and the proximity of tornado events, as well as on average education and income levels in the county in question. The pulse in self-protection investment after a tornado is relatively large, yet short-lived and relatively local, and there is some evidence that short-run supply constraints limit the expression of peak demand over time and across space.
In numerous regions around the globe, climate change can be expected to change the pattern of severe weather events. The nature of future changes in these patterns can be difficult to predict, but it is instructive to consider some of the potential consequences of extreme weather on household migration decisions based on past events. We examine bi-directional county-to-county migration flows in the U.S., treating various types of extreme weather events as random exogenous shocks to the affected communities and their economies.
We estimate a utility-theoretic choice model to quantify demand for publicly provided medical treatment policies. We find diminishing marginal utility for increased recoveries and avoided premature deaths. Willingness to pay for different types of treatment policies varies with who would benefit, with each respondent’s own characteristics, community ethnic fractionalization and immigrant composition, as well as the respondent’s expected private benefits from the policy, attitude toward government interventions and overall health care funding priorities.
Economic researchers often require monetized values of households’ willingness to pay for reductions in risks to human life and health. Compared to valuing reductions in the risk of death, there is a smaller literature on valuing reductions in morbidity risks. I compare the requirements for environmental benefit-cost analysis with the limitations of the standard approaches taken in cost-effectiveness analysis in health economics, and I highlight some areas that are ripe for further research.
In Journal of Environmental Economics and Management
A choice model based on utility in a sequence of prospective future health states permits us to generalize the concept of the value of statistical life (VSL). Our representative national survey asks individuals to choose between costly risk-reducing programs and the status quo in randomized stated choice scenarios. Our model allows for separate marginal utilities for discounted net income and avoided illness years, post-illness years, and lost life-years. Our estimates permit calculation of overall willingness to pay to reduce risks for a wide variety of different prospective illness profiles. These can be benchmarked against the standard VSL as a special case.
In a survey about health risk reductions, we also collect data about individual time preferences using a choice about payout options for hypothetical lottery winnings.We model individual discount rates as a function of age, other socio-demographic variables and variables to capture health expectations. For older subjects, undesirable current health behaviors are better predicted by their back-casted discount rates at age 21. Changing time preferences as people mature may lead to the development of health habits while they are young that are likely to be inconsistent with the preferences of their older future selves.
In The Political Economy of Environmental Justice H. Spencer Banzhaf (ed.)
We examine migration patterns around seven Superfund sites, from 1970 to 2000, including periods of remediation. There is little evidence of groups “coming to the nuisance” in these data. One possible reason is that households may have had different perceptions about the environmental hazards of the sites, and these perceptions may have changed over time in unpredictable ways. The sites may be perceived to be improving if they are remediated, or, alternatively, the sites may be permanently stigmatized.
The time-tradeoff (TTO) method typically describes some period of years in an adverse health state and asks respondents how many (fewer) years in “full health” they would accept to avoid the longer time period in the adverse health state. We use a large general-population choice experiment designed to permit estimation of willingness to pay (WTP) to reduce health risks with different time profiles. Here, however, we focus on the tradeoffs between discounted time in different health states, rather than tradeoffs between health states and net income.
Morbidity and quality-of-life considerations may be particularly important to the task of valuing non-fatal harm to wildlife in the wake of an environmental disaster. We argue that the other species morbidity-reduction component of WTP should be calculated net of any “outrage” component associated with the cause of the harm. This net WTP is likely to be correlated with the premium that people are willing to pay for chicken products from birds for which the quality-of-life has been enhanced by improved animal welfare measures.
Stated preference researchers know that a good’s placement among a sequence of goods in a set of valuation questions can have a substantial impact on people’s valuations of these different goods. However, the economic consequences of potential order effects stemming from other questions in a survey, prior to the valuation tasks, have received surprisingly little attention. We find that the order used in prior questions may change people’s opinions toward various attributes of the good to be valued, and thereby change WTP by a substantial amount.
Survey respondents may assume that the substantive alternative(s) in an SP choice set, in their own particular case, will be different from what the survey instrument describes. We demonstrate a strategy to control and correct for scenario adjustment in the estimation of willingness to pay for a non-market good, using data from follow-up questions, and ex post econometric controls, for each respondent’s subjective departures from the intended choice scenario.
We estimate large systematic differences, by type of illness, in individual willingness to pay (WTP) to reduce the risk of the major health threats. These include five types of cancers, chronic heart disease, heart attacks, respiratory disease, strokes, diabetes, Alzheimer’s disease and traffic accidents. Analyses that constrain values to be the same across all illnesses forgo valuable information for benefit-cost analyses of health, environmental and safety policies. The rank ordering of values for illness-specific risk reductions is correlated with spending patterns by government agencies.
Using a large stated preference survey conducted across the U.S. and Canada, we assess differences in individual willingness to pay (WTP) for health risk reductions between the two countries. WTP differs systematically with age, gender, education, and marital status, as well as a number of attitudinal and subjective health-perception variables. Age profiles for WTP are markedly different across the two countries. Canadians tend to display flatter age profiles, with peak WTP realized at older ages.
We show in a theoretical model that the benefit from additional attention to the marginal attribute within a choice set depends upon the expected utility loss from making a suboptimal choice if it is ignored. Guided by this analysis, we then develop an empirical method to measure an individual’s propensity to attend to attributes. As a proof of concept, we offer an empirical example of our method using a conjoint analysis of demand for programs to reduce health risks.
Information about preferences for treatment and prevention policies can help policy makers more effectively allocate public health resources. We estimate a random utility model of preferences for treatment and prevention policies and explore sources of systematic heterogeneity in preferences. Marginal utility associated with avoided deaths is about twice as high for prevention policies as for treatment policies, and there is significant heterogeneity with respect to disease type, the group targeted by the policy, and respondent characteristics.
We explore the relationship between willingness to pay (WTP) for climate change mitigation and distributional preferences, by which we mean individuals’ opinions about who should be responsible for climate change prevention and whether the share of climate change impacts borne by the poor is a cause for concern. WTP is higher when larger cost shares are borne by parties deemed to bear a greater responsibility for mitigation, and when respondents believe (and care) that the impacts of climate change may be borne disproportionately by the world’s poor.
Risk aversion and time preferences are important sources of heterogeneity in preferences for public policies with near-term costs and uncertain future benefits. Using stated preference data, we first jointly estimate individual-specific risk aversion and discount rate parameters then use these as individual “characteristics” in a separate model to explain preferences for climate change mitigation policies. The more risk-averse the individual, and/or the lower their discount rate, the higher is their willingness to pay.
The “value of a statistical life” (VSL) is shorthand for an important concept, but the term tends flummox people who are unfamiliar with it. The VSL actually measures people’s “willingness to swap alternative goods and services for a tiny reduction in the chance of sudden death.” The general public (and many politicians) would be less angry/alarmed/confused if we came up with a better shorthand. I also argue that economists’ continual pursuit of a single number for “the” VSL is misguided and can be misleading.
Demand by adults for programs which reduce their own health risks is influenced by (1) their parenthood status, (2) the numbers of children in different age brackets, (3) the ages of the adults themselves, (4) the latency period before they would fall ill, and (5) whether there will still be children in the household at that time. For younger adults, willingness to pay by parents is greater than for non-parents, and increases with each additional young child. For middle-aged adults, willingness to pay for corresponding risk reductions is lower when teenagers are present.
We use this unique opportunity to explore the determinants of subjective choice difficulty to assess how well the customary reduced-form proxies are likely to capture this behavioral aspect of subjects’ interactions with stated-choice tasks. Common measures do not fully explain subjective choice difficulty, which also depends on the interplay among objective attribute-space complexity, the similarity of alternatives in utility space, and cognitive resource constraints.
In Journal of Environmental Economics and Management
We estimate demand for environmental polices to improve health, using choice experiments concerning community-lvel illnesses and premature deaths avoided, policy duration, and the affected population size. Preferences for policy attributes vary systematically with the scenario design, with the source of risk and type of health threat, and with respondent characteristics. Omission of illness information biases upwards the value of avoided premature deaths, and individuals view avoided deaths and avoided illnesses as substitutes.
We develop a model that assesses the influence of choice set misspecification arising from the omission of perceived substitutes among real-world alternatives in the same class of goods. This problem may be present when individuals are allowed to select a “no purchase” option instead of being forced to choose from an explicit set of SP alternatives. A comparison of rival models suggests researchers who overlook the presence of perceived real alternatives related to an SP experiment can end up with noticeably biased welfare estimates.
We estimate a model to explain climate policy preferences as a function of the domestic and international distribution of policy costs as well as the climate change impacts that each respondent believes will occur under a policy of business-as-usual. WTP for climate change mitigation is greater when the domestic incidence of mitigation costs is borne mostly through higher energy taxes, and when costs are understood to be shared internationally with other groups of countries, rather than being borne mostly by a country group including the US.
We review the discussion at a workshop whose goal was to achieve a better integration among behavioral, economic, and statistical approaches to choice modeling. The workshop explored how current approaches to the specification, estimation, and application of choice models might be improved to better capture the diversity of processes that are postulated to explain how consumers make choices.
Our survey specifies explicit risks of (a) outright program failure and (b) program redundancy due to possible private sector substitutes. Our discounted expected utility model of choice accommodates both these objective risks and the possibility of subjective scenario adjustment or selective inattention by respondents. We then counterfactually simulate willingness-to-pay in the absence of these distortions.
We examine the sale prices of nearly 34,000 homes near sites in three metropolitan areas for up to a 30-year period. Our results are both surprising and inconsistent with most prior work. The principal result is that, when cleanup is delayed for 10, 15, and even up to 20 years, the discounted present value of the cleanup is mostly lost. A possible explanation for these property value losses is that the sites are stigmatized and the homes in the surrounding communities are shunned. The results suggest that expedited cleanup and minimizing the number of stigmatizing events would reduce these losses.
We assess whether samples of respondents drawn from large internet consumer panels are representative of the underlying population. We model the attrition/selection process for a major consumer panel maintained by Knowledge Networks, Inc (KN). Starting from KN’s over 525,000 random-digitdialed (RDD) panel-recruitment telephone contact attempts, and ending with a sample of respondents to an actual online survey, we span all junctures at which systematic selection could occur.
In hedonic property value models, economists typically assume that changing perceptions of environmental risk should be captured by changes in housing prices. For long-lived risks emanating from point sources, however, many other features of neighborhoods seem to change as well. Households relocate in response to changes in. perceived environmental quality. We consider spatial patterns in selected census variables over three decades in the vicinity of four Superfund sites. We find many examples of moving and staying behavior, inferred from changes in the relative concentrations of a wide range of socio-demographic groups in census tracts near the site versus farther away.
In Journal of Environmental Economics and Management
In environmental economics, hedonic property value (HPV) models have often employed distance from a localized environmental disamenity as a proxy for perceived risk. The magnitude of a distance effect on housing prices, however, may depend upon the direction in which it is being measured. We generalize conventional distance models to allow for continuously varying directional effects by converting from Cartesian to polar coordinates. A simple empirical example (for housing prices around Woburn, Massachusetts, between 1988 and 1996) illustrates how failure to allow for directional heterogeneity can obscure otherwise statistically significant distance effects in HPV.
Individuals’ demands for programs targeting a particular illness are higher when there is a history of that illness and when subjective risks are higher. A history of other illnesses and greater other-illness subjective risks decrease demand. These comorbidity effects operate through the marginal utilities of both (i) adverse health states and (ii) income.
We describe recent progress in several areas related to endogeneity, including choice set formation and attention to attributes, interactions among decision-makers, respondents’ strategic behavior in answering stated preference choices, models of multiple discrete/continuous choice, distributions of willingness-to-pay, and methods for handling traditionally endogenous explanatory variables.
We develop and test an empirical model of individuals’ intertemporal demands for programs to mitigate health risks over the remaining years of their lives. We find qualified support for the Erhlich (2000) life-cycle model, which predicts that individuals expect to derive increasing marginal utility from reducing health risks that come to bear later in their lives. However, we also find that as individuals age, there appears to be a systematic downward shift in their anticipated schedule of marginal utility for risk reduction at future ages. Our model improves upon earlier work by differentiating between the respondent’s current age and the future ages at which they would experience adverse health states.
Debate about the appropriate value for any single social discount rate for public projects stems in part from our lack of knowledge about how individual discount rates vary across people and across choice contexts. We estimate prototype utility-theoretic models concerning private tradeoffs involving money over time that reveal individual-specific discount rates. If researchers estimate aggregate willingness to pay for a public project as a function of heterogeneous individual discount rates, they can then counterfactually simulate of willingness to pay under lower social discount rates argued to be compatible with intergenerational equity.
Willingness-to-pay for climate change mitigation depends on people’s perceptions about just how bad things will get if nothing is done. Individual subjective distributions for future climate conditions are combined with stated choices over alternative climate policies to estimate individual option prices (the appropriate ex ante welfare measure in the face of uncertainty) for climate change mitigation. We find statistically significant sensitivity of estimated option prices to both expected future conditions and uncertainty about future conditions.
Willingness to support public programs for risk management often depends on individual subjective risk perceptions in the face of uncertain science. As part of a larger study concerning climate change, we explore individual updated subjective risks as a function of individual priors, the nature of external information, and individual attributes. We examine several rival hypotheses about how subjective risks change in the face of new information (Bayesian updating, alarmist learning, and ambiguity aversion). The source and nature of external information, as well as its collective ambiguity, can have varying effects across the population, in terms of both expectations and uncertainty.
In Journal of Environmental Economics and Management
Seven independent samples of survey respondents were asked to value the identical good. Elicitation methods include one actual purchase and six widely used hypothetical choice formats. Using a common underlying indirect utility function (and stochastic structure) allows data for different elicitation methods to be used independently, compared pair-wise (as in much of the earlier literature) or pooled across all samples in one unified model.
We suggest that “unobserved heterogeneity” is only one component of unobserved variability. Empirical research that suggests that random components are unlikely to be independent of systematic components, and random component variances are unlikely to be constant between or within individuals, time periods, locations, etc. We also review evidence that random components are functions of systematic components. We recommend caution in the use and interpretation of complex choice model specifications (in particular, random-parameter models).
In Valuing Recreation and the Environment Joseph A. Herriges and Catherine L. Kling (eds.)
The purpose of this chapter is to demonstrate the opportunities for, and utility of, explicit modeling of survey response/nomesponse. A good understanding of the relationship between survey response propensities and observable behavioral relationships within just the subsample of respondents can help inform researchers and policy makers about the likely nature of nomesponse biases.
We adapt the theoretical state-preference model to value nonmarket public goods under individual uncertainty about use, illustrating with an assessment of willingness-to-pay to prevent acid rain lake damage in the northeast United States. Individual usage uncertainty is modelled via probabilities of participation in trout fishing. We produce quantitative welfare measures, including individual fitted and simulated passive- and active-use values, individual expected consumer surplus, option price, option value, and complete individual willingness-to-pay loci.
In the Journal of Environmental Economics and Management
Respondent experience (i.e., a respondent’s information set) has long been suspected to influence contingent valuation estimates of environmental values. We assess the influence of experience by explicitly modeling the relationship between respondent experience and both fitted individual resource values and the conditional variance of these estimated values.
In the Journal of Agricultural and Resource Economics
A model of recreation demand is developed to determine the role of water levels in determining participation at and frequency of trips taken to various federal reservoirs and rivers in the Columbia River Basin. Contingent behavior data are required to break the near-perfect multicollinearities among water levels at some waters.
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. The contingent scenarios also provide opportunities to (a) test for differences between observed and contingent preferences and/or (b) assess likely demands under conditions beyond the domain of observed variation in costs or resource attributes.
In the Journal of Environmental Economics and Management
We generalize upon previous analyses of dichotomous-choice with follow-up data by relaxing the assumption that the identical unobserved resource value motivates both responses. While values implied by the first and second responses are highly correlated and may be drawn from the same distribution, they are definitely not identical. Furthermore, assuming that they are identical can severely distort the estimated valuation distribution.
Contingent valuation survey responses are combined with travel cost data on actual market behavior to estimate jointly both the parameters of the underlying utility function and its corresponding ordinary demand function. This is a prototypical empirical example of a new modeling strategy, variants of which should prove useful in many applications, especially where reliance on a single valuation method is undesirable.
In the Journal of the American Statistical Association
The luck of the draw in assigning the referendum thresholds on individual referendum contingent valuation questionnaires can produce a surprisingly wide variety of value estimates. We control for the behavioral biases that confound other comparison studies by using one sample of payment card CV data and simulating 200 samples of consistent referendum responses. Where referendum questions have produced different value estimates than other formats, elaborate explanations for the apparent discrepancies may not be necessary.
Most researchers working with referendum contingent valuation data have used ordinary logit models and have done without confidence intervals for their fitted willingness-to-pay (WTP) values derived using referendum contingent valuation data. We then how an alternative approach, censored logistic regression, makes it straightforward to produce confidence intervals (either for individual observations, at the means of the data, or for an arbitrarily forecasted set of explanatory variables).
Medium- to long-run price elasticities of demand for water are higher than short-run studies suggest. We examine data from the Los Angeles Department of Water and Power’s 1983 residential energy survey. Households’ decisions to install shower retrofit devices are influenced by the potential to save money on water heating bills. We attribute toilet retrofit decisions more to noneconomic factors which might be characterized as “general conservation mindedness.”
In the Journal of Environmental Economics and Management
Contingent valuation methods (CVM) have been shown to be potentially very useful for eliciting information about demands for non-market goods. We assess the sensitivity of “payment card” CVM results to the researcher’s choice of estimation method. Empirical payment card data are used in both (a) a naive ordinary least squares (OLS) procedure employing interval midpoints as proxies for the true dependent variable, and (b) an efficient maximum likelihood (ML) procedure which explicitly accommodates the intervals. Depending upon the design of the payment card, OLS can yield biased parameter estimates, misleading inferences regarding the effects of different variables on resource values, and biased estimates of the overall resource value.
In the Journal of Environmental Economics and Management
This paper challenges the W. M. Hanemann [Amer. J. Agr. Econom.66, 332–341 (1984)] and C. Sellar, J. P. Chavas, and J. R. Stoll [J. Environ. Econom. Management13, 382–390 (1986)] utilizations of logit models to estimate the value of non-market resources from “referendum” survey data. These data are more informative than conventional choice data. The “random utility” interpretation of logit models is therefore too restrictive. Bypassing the utility function entirely, it will be shown that parameters and standard errors for utility-theoretic inverse Hicksian demand functions can be extracted directly and much more simply. Estimated demand functions need not be limited to those corresponding to the linear-in-parameters utility difference specifications which can be handled by packaged logit programs.
Closed-ended contingent valuation surveys are used to assess demands in hypothetical markets and recently have been applied widely to the valuation of (non-market) environmental resources. This interviewing strategy holds considerable promise for more general market research applications. The authors describe a new maximum likelihood estimation technique for use with these special data. Unlike previously used methods, the estimated models are as easy to interpret as ordinary least squares regression results and the results can be approximated accurately by packaged probit estimation routines.
Closed-ended contingent valuation surveys can be very useful in the evaluation of non-market resources. Respondents merely state whether they would accept or reject a hypothetical threshold amount, either as payment for giving up access to the resource, or as a fee for its use. We develop a maximum likelihood procedure which exploits the variation in the threshold values to allow direct and separate point estimates of regression-like slope coefficients and error standard deviations (without truncation bias). Our illustration uses data from a survey of recreational fishermen to examine factors which influence individuals’ willingness-to-pay.
This paper examines medium-run adjustments to the existing housing stock, focusing on discrete energy conservation “retrofits” such as insulation and storm windows. Individual household data are employed in a two-level nested logit model to estimate a translog indirect utility function. Simulations reveal considerable sensitivity of the demand for retrofits to their own prices, to relative energy prices and to changes in real incomes.
(Using an arbitrary early date for sorting) Survey instrument example
One instance of the online survey involving choice experiments concerning public health risk reductions. This “treatment” survey employed choice tasks concerning public policies that would (1) treat children, adults and seniors (in different proportions) who have a specific type of illness. Policies also varied in terms of (2) how many people would get sick over a specified number of future years, (3) how many would recover fully without and with the policy, (4) how many deaths would occur with and without the policy, and (5) the cost per month to the respondent.
(Using an arbitrary early date for sorting) Survey instrument example
One instance of the online survey involving choice experiments concerning public health risk reductions. This “prevention” variant employed choice tasks concerning environmental policies that would reduce specific categories of pollutants that cause different specific types of illness. Policies varied in terms of the number of years they would remain in effect, how many people would get sick with and without the policy, how many would die with and without the policy, and the cost to the respondent.
(Using an arbitrary early date for sorting) Survey instrument example
One instance of the online survey involving choice experiments concerning private health risk reductions. The choice tasks in this survey invite respondents to choose between alternative health risk reduction programs, each described in terms of the particular illness, their future age at which the illness would begin, the prognosis, the percent risk reduction the program would deliver, and the cost per month of the program. Each illness was described as a future illness profile, to permit modeling of willingness to pay for avoided illness-years as well as avoided premature mortality.
(Using an arbitrary early date for sorting) Survey instrument example
One instance of the online survey involving choice experiments concerning pandemic policy in California, Oregon, and Washington State. Choice tasks concerned pandemic policies that would last different numbers of months and would reduce different total numbers of cases and deaths over that period. We also conveyed the differing strictness of pandemic rules for a set of ten different activities. Costs were expressed unconventionally. We included an average cost per month for people in the respondent’s county, and a cost in terms of an unemployment rate for the county.
(Using an arbitrary early date for sorting) Survey instrument example
One instance of the pencil-and-paper survey involving choice experiments concerning humanely raised meats. This project had its beginnings as senior thesis for Claire Tonry, in the University of Oregon’s Program in Environmental Studies. Each respondent is presented with six choice tasks concerning three types of grocery items (chicken breasts, top sirloin beef steak, and ground beef) from animals raised in different ways. In each case, the respondent (in their role as a consumer) is asked to choose between conventionally raised, free-range, and humanely raised animals.
(Using an arbitrary early date for sorting) Survey instrument example
One instance of the mail survey involving choice experiments concerning climate change programs. This mail survey was fielded weekly, for 50 weeks, with 200 surveys sent out each week, because we wished to have the option to explore whether current events (e.g., weather) had any distinguishable effects on climate policy preferences. Each survey contained just a single choice task between a specified climate change prevention program and business as usual.
(Using an arbitrary early date for sorting) Survey instrument example
One instance of the online survey involving choice experiments concerning carbon reduction programs in higher education. Our university wished to understand the willingness of its stakeholders to bear the higher costs of switching to green energy for the campus. The main features of alternative programs are the percent decrease in carbon emissions that would be achieved, and the cost per year to the respondent. But these programs also differ in their distributional consequences, i.e., how the costs of the program would be borne and how the revenue thus collected would be used.
(Using an arbitrary early date for sorting) Survey instrument example
One instance of the online survey involving choice experiments concerning cap-and-trade programs. We employ many more images than we have used in earlier surveys. The choice tasks in this survey concern cap-and-trade programs that will reduce carbon emissions by a specified percent at some number of dollars per month in household costs. However, the programs are differentiated in terms of their distributtional consequences in county-level labor markets, the percent of permits auctioned, and the uses for this auction revenue.
(Using an arbitrary early date for sorting) Survey instrument example
One instance of the online survey involving choice experiments concerning backyard birds. Species richness (the number of different species of birds) is the most common measure of avian biodiversity. However, species richness can be the same whether there is one member of each species, or thousands of members of each species. This survey includes choice tasks that describe how conservation measures could affect the abundance of individual species, making it possible to employ alternative measures of biodiversity.