scholarly journals Choosing not to choose: A meta-analysis of status quo effects in environmental valuations using choice experiments

2018 ◽  
Vol 18 (1) ◽  
pp. 79 ◽  
Author(s):  
Jesus Barreiro-Hurle ◽  
Maria Espinosa-Goded ◽  
Jose Miguel Martinez-Paz ◽  
Angel Perni

<p>Discrete choice experiments (DCE) normally include in their choice sets an option described as the status quo (i.e. no change to current situation; SQ). The literature has identified Status Quo Effect (SQE) as the systematic preference of the SQ over the alternatives that propose changes over and beyond what can be captured by the variation of attributes’ levels. In this paper, we conduct a meta-analysis of DCE applied in environmental policy to identify potential drivers of SQE. We find that accounting for heterogeneity in the econometric analysis, excluding protest responses and easing the choice’s cognitive burden reduce the presence of SQE.</p>

2019 ◽  
Vol 65 (02) ◽  
pp. 507-532
Author(s):  
WAN NORHIDAYAH W MOHAMAD ◽  
KEN WILLIS ◽  
NEIL POWE

An issue in environmental economics is how respondents make choices in discrete choice experiments (DCEs), and whether different strategies impact on the reliability of willingness-to-pay (WTP) results. Do individuals make choices with reference to their status quo (SQ) position, or can they make simulated market choices amongst only hypothetical scenarios? This study uses a split sample to test whether the inclusion or exclusion of the SQ on a choice card in DCEs affects the WTP estimates, based on visitors’ preferences for tourist facilities at Kenyir Lake, Malaysia. The results indicated little difference between both the samples in terms of goodness-of-fit, size and significance of the attribute coefficients, and WTP estimates for the Conditional Logit (CL) and Mixed Logit (MXL) models.


Nutrients ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 2677
Author(s):  
Anastasios Bastounis ◽  
John Buckell ◽  
Jamie Hartmann-Boyce ◽  
Brian Cook ◽  
Sarah King ◽  
...  

Food production is a major contributor to environmental damage. More environmentally sustainable foods could incur higher costs for consumers. In this review, we explore whether consumers are willing to pay (WTP) more for foods with environmental sustainability labels (‘ecolabels’). Six electronic databases were searched for experiments on consumers’ willingness to pay for ecolabelled food. Monetary values were converted to Purchasing Power Parity dollars and adjusted for country-specific inflation. Studies were meta-analysed and effect sizes with confidence intervals were calculated for the whole sample and for pre-specified subgroups defined as meat-dairy, seafood, and fruits-vegetables-nuts. Meta-regressions tested the role of label attributes and demographic characteristics on participants’ WTP. Forty-three discrete choice experiments (DCEs) with 41,777 participants were eligible for inclusion. Thirty-five DCEs (n = 35,725) had usable data for the meta-analysis. Participants were willing to pay a premium of 3.79 PPP$/kg (95%CI 2.7, 4.89, p ≤ 0.001) for ecolabelled foods. WTP was higher for organic labels compared to other labels. Women and people with lower levels of education expressed higher WTP. Ecolabels may increase consumers’ willingness to pay more for environmentally sustainable products and could be part of a strategy to encourage a transition to more sustainable diets.


2017 ◽  
Vol 38 (3) ◽  
pp. 306-318 ◽  
Author(s):  
Brendan Mulhern ◽  
Richard Norman ◽  
Koonal Shah ◽  
Nick Bansback ◽  
Louise Longworth ◽  
...  

2021 ◽  
Vol 70 (3) ◽  
pp. 192-207
Author(s):  
Insa Thiermann ◽  
Gunnar Breustedt ◽  
Uwe Latacz-Lohmann

Im vorliegenden Artikel wurde mithilfe eines Discrete-Choice-Experiments bestimmt, welche Faktoren die Entscheidung von Landwirten beeinflussen, an einem hypothetischen Förderprogramm zur Ansäuerung von Gülle bei der Feldausbringung teilzunehmen. Bei der Gülleansäuerung handelt es sich um ein in Dänemark verbreitetes Verfahren zur Minderung von Ammoniakemissionen. Die Merkmale aus den Choice-Sets bildeten die Eigenschaften des Verfahrens (Emissionsminderung), der Finanzierung (Erstattung der zusätzlichen Kosten) und der gesetzlichen Regelungen (mindestens anzurechnende Stickstoffmenge, Erlass von Auflagen der Düngeverordnung) ab. Die Auswertung der Befragung erfolgte durch ein Mixed-Logit-Modell und die Schätzung latenter Klassen. Insgesamt zeigte sich eine sehr hohe Bereitschaft an möglichen Förderprogrammen teilzunehmen und das Verfahren zu nutzen. Die Entscheidung für die Gülleansäuerung wurde positiv von der zu erwartenden Emissionsreduktion und der Erstattung der zusätzlichen Kosten beeinflusst. Auch das Angebot, Gülle nicht einarbeiten zu müssen, wirkte sich positiv auf die Teilnahmebereitschaft aus. Die Vorgabe, den zusätzlich enthaltenden Stickstoff in der Düngebedarfsberechnung anzusetzen, senkte die Bereitschaft der Teilnahme.


Author(s):  
Deborah J. Street ◽  
Rosalie Viney

Discrete choice experiments are a popular stated preference tool in health economics and have been used to address policy questions, establish consumer preferences for health and healthcare, and value health states, among other applications. They are particularly useful when revealed preference data are not available. Most commonly in choice experiments respondents are presented with a situation in which a choice must be made and with a a set of possible options. The options are described by a number of attributes, each of which takes a particular level for each option. The set of possible options is called a “choice set,” and a set of choice sets comprises the choice experiment. The attributes and levels are chosen by the analyst to allow modeling of the underlying preferences of respondents. Respondents are assumed to make utility-maximizing decisions, and the goal of the choice experiment is to estimate how the attribute levels affect the utility of the individual. Utility is assumed to have a systematic component (related to the attributes and levels) and a random component (which may relate to unobserved determinants of utility, individual characteristics or random variation in choices), and an assumption must be made about the distribution of the random component. The structure of the set of choice sets, from the universe of possible choice sets represented by the attributes and levels, that is shown to respondents determines which models can be fitted to the observed choice data and how accurately the effect of the attribute levels can be estimated. Important structural issues include the number of options in each choice set and whether or not options in the same choice set have common attribute levels. Two broad approaches to constructing the set of choice sets that make up a DCE exist—theoretical and algorithmic—and no consensus exists about which approach consistently delivers better designs, although simulation studies and in-field comparisons of designs constructed by both approaches exist.


2016 ◽  
Vol 37 (3) ◽  
pp. 285-297 ◽  
Author(s):  
Brendan Mulhern ◽  
Nick Bansback ◽  
Arne Risa Hole ◽  
Aki Tsuchiya

Background: Discrete choice experiments incorporating duration can be used to derive health state values for EQ-5D-5L. Yet, methodological issues relating to the duration attribute and the optimal way to select health states remain. The aims of this study were to: test increasing the number of duration levels and choice sets where duration varies (aim 1); compare designs with zero and non-zero prior values (aim 2); and investigate a novel, two-stage design to incorporate prior values (aim 3). Methods: Informed by zero and non-zero prior values, two efficient designs were developed, each consisting of 120 EQ-5D-5L health profile pairs with one of six duration levels (aims 1 and 2). Another 120 health state pairs were selected, with one of six duration levels allocated in a second stage based on existing estimated utility of the states (aim 3). An online sample of 2,002 members of the UK general population completed 10 choice sets each. Differences across the regression coefficients from the three designs were assessed. Results: The zero prior value design produced a model with coefficients that were generally logically ordered, but the non-zero prior value design resulted in a set of less ordered coefficients where some differed significantly. The two-stage design resulted in ordered and significant coefficients. The non-zero prior value design may include more “difficult” choice sets, based on the proportions choosing each profile. Conclusions: There is some indication of compromised “respondent efficiency”, suggesting that the use of non-zero prior values will not necessarily result in better overall precision. It is feasible to design discrete choice experiments in two stages by allocating duration values to EQ-5D-5L health state pairs based on estimates from prior studies.


2019 ◽  
Vol 39 (6) ◽  
pp. 681-692 ◽  
Author(s):  
Domino Determann ◽  
Dorte Gyrd-Hansen ◽  
G. Ardine de Wit ◽  
Esther W. de Bekker-Grob ◽  
Ewout W. Steyerberg ◽  
...  

Background. Discrete choice experiments (DCEs) are increasingly used in the health care context to inform on patient preferences for health care services. In order for such experiments to provide useful and policy-relevant information, it is vital that the design includes those options that the respondent faces in the real-life situation. Whether to include opt-out, neither, or status quo alternatives has, however, received little attention in the DCE literature. We aim to investigate whether the use of different unforced choice formats affects DCE results in different settings: 1) opt-out versus neither in a health care market where there is no status quo and 2) including status quo in addition to opt-out in a health care market with a status quo. Design. A DCE on Dutch citizens’ preferences for personal health records served as our case, and 3189 respondents were allocated to the different unforced choice formats. We used mixed logit error component models to estimate preferences. Results. We found that the use of different unforced choice formats affects marginal utilities and welfare estimates and hence the conclusions that will be drawn from the DCE to inform health care decision making. Conclusions. To avoid biased estimates, we recommend that researchers are hesitant to use the neither option and consider including a status quo in addition to opt-out in settings where a status quo exists.


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