Empirical Analysis of Hypothetical Bias in Stated-Preference Experiments

2017 ◽  
pp. 447-463
Author(s):  
Li Tang ◽  
Xia Luo
Keyword(s):  
Empirical Analysis ◽  
Stated Preference ◽  
Hypothetical Bias ◽  
Stated Preference Experiments

scholarly journals Can Calibration Reconcile Stated and Observed Preferences?

2005 ◽  
Vol 37 (1) ◽  
pp. 237-248 ◽  
Author(s):  
F. Bailey Norwood
Keyword(s):  
Public Good ◽  
Conjoint Analysis ◽  
Lower Bounds ◽  
Stated Preference ◽  
Hypothetical Bias ◽  
Upper And Lower Bounds ◽  
Stated Preference Experiments

Hypothetical bias is a pervasive problem in stated-preference experiments. Recent research has developed two empirically successful calibrations to remove hypothetical bias, though the calibrations have not been tested using the same data or in a conjoint analysis. This study compares the two calibrations in a conjoint analysis involving donations to a public good. Results find the calibrations are biased predictors of true donations but that calibrated and uncalibrated models together provide upper and lower bounds to true donations.

scholarly journals Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments

2014 ◽  
Vol 22 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Jens Hainmueller ◽  
Daniel J. Hopkins ◽  
Teppei Yamamoto
Keyword(s):  
Causal Inference ◽  
Conjoint Analysis ◽  
Stated Preference ◽  
Attitudes Toward Immigrants ◽  
Multiple Treatment ◽  
Stated Preference Experiments ◽  
Randomized Design ◽  
Survey Experiments ◽  
Voter Decision Making ◽  
Identification Analysis

Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show howconjoint analysis, an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and assess several causal hypotheses simultaneously. In conjoint analysis, respondents score a set of alternatives, where each has randomly varied attributes. Here, we undertake a formal identification analysis to integrate conjoint analysis with the potential outcomes framework for causal inference. We propose a new causal estimand and show that it can be nonparametrically identified and easily estimated from conjoint data using a fully randomized design. The analysis enables us to propose diagnostic checks for the identification assumptions. We then demonstrate the value of these techniques through empirical applications to voter decision making and attitudes toward immigrants.

scholarly journals Preprint: Mobility surveys beyond stated preference: Introducing MyTrips, an SP-off-RP survey tool, and results of two case studies

2021 ◽  
Author(s):  
Christian Rudloff ◽  
Markus Straub
Keyword(s):  
Case Studies ◽  
Latent Class ◽  
Stated Preference ◽  
Hypothetical Bias ◽  
Rural Setting ◽  
Daily Routine ◽  
Actual Behavior ◽  
Survey Tool ◽  
First Case

When introducing new mobility offers or measures to influence traffic, stated preference (SP) surveys are often used to assess their impact. In SP surveys respondents do not answer questions about their actual behavior but about hypothetical settings. Therefore, answers are often biased. To minimise this hypothetical bias, so-called stated preference-off-revealed preference (SP-off-RP)surveys were developed. They base SP questions on respondents’ revealedbehavior and place unknown scenarios in a familiar context. Until now this method was applied mostly to scenarios investigating the willingness to pay. The application to more complex mode or route choice problems, which require the calculation of routes, has not yet been done. In this paper, the MyTrips survey tool for the collection of SP-off-RP data based on respondents’ actual mobility behavior is presented. SP questions are based on alternatives to typical routes of respondents, which are calculated on the fly with an intermodal router. MyTrips includes a larger survey and collectsmobility diaries for one day representing respondents’ daily routine, calculates alternative routes and creates SP questions based on a Bayesian optimal design. Results from two case studies investigating behavior changes are presented. The first case study investigated the extension of a subway line in Vienna,Austria. The second case study focused on the introduction of micro transit vehicles in a rural setting, replacing infrequent bus services. Results of the two case studies show a difference in response behaviour between SP and RP settings and suggest a reduction of hypothetical bias. For the latter study a Latent Class SP-off-RP model was estimated. It shows that availability and accessibility of public transport are the main influence on the willingness to use it independent of other household characteristics.

scholarly journals Improving Drinking Water Quality in South Korea: A Choice Experiment with Hypothetical Bias Treatments

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2569
Author(s):  
Adelina Gschwandtner ◽  
Cheul Jang ◽  
Richard McManus
Keyword(s):  
South Korea ◽  
Choice Experiment ◽  
Latent Class ◽  
Cost Benefit Analysis ◽  
Stated Preference ◽  
Cost Benefit ◽  
Hypothetical Bias ◽  
Sensitivity Analyses ◽  
The Difference ◽  
Water Treatments

The objective of this present study is to use choice experiments and an extensive cost-benefit analysis (CBA) to investigate the feasibility of installing two advanced water treatments in Cheongju waterworks in South Korea. The study uses latent class attribute non-attendance models in a choice experiment setting in order to estimate the benefits of the two water treatments. Moreover, it explores strategies to mitigate potential hypothetical bias as this has been the strongest criticism brought to stated preference methods to date. Hypothetical bias is the difference between what people state in a survey they would be willing to pay and what they would actually pay in a real situation. The study employs cheap talk with a budget constraint reminder and honesty priming with the latter showing more evidence of reducing potential hypothetical bias. The lower bound of the median WTP (willingness to pay) for installing a new advanced water treatment system is approximately $2 US/month, similar to the average expenditures for bottled water per household in South Korea. These lower bounds were found using bootstrapping and simulations. The CBA shows that one of the two treatments, granular activated carbon is more robust to sensitivity analyses, making this the recommendation of the study.

Value of the Facilities and Attributes of New Heavy Rail and Bus Rapid Transit Projects in a Developing City: The Case of Lima, Peru

2003 ◽  
Vol 1835 (1) ◽  
pp. 50-58 ◽  
Author(s):  
Manuel J. Martínez ◽  
Javier Cornejo
Keyword(s):  
No Value ◽  
Stated Preference ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Stated Preference Experiments ◽  
Operational Design ◽  
Feeder Bus ◽  
Bus Service ◽  
Heavy Rail

Preferences of heavy rail (HR) system users are studied in relation to the system’s alignment and bus connections in the context of a developing city. Stated preferences techniques are applied to estimate the monetary value of a long set of attributes of a new mass transit service: HR connected to bus rapid transit (BRT). Attributes include time, fare, bicycle storage at stations, stairways, feeder bus integration, integration with BRT, type of bus service, bus itinerary, and quality of buses. The long set of attributes deserved three stated preference experiments grouped by time and fare, characteristics of HR, and characteristics of BRT. They were linked by the common attribute of the fare. Results of the values of the attributes are presented. The value of the preference for HR is reduced to 8% when a feeder bus is not offered and the HR route does not reach downtown. The value of a feeder bus using small vehicles is higher than the value of BRT even if BRT operates with new buses and express service to downtown. Bicycle storage or escalators have no value for the prospective passenger. After the response of users to the new services is analyzed, conclusions for the operational design of the system are presented.

Videos Improve Attention and Cheap Talk in Online Surveys

2021 ◽  
Vol 16 (2) ◽  
pp. 347-376
Author(s):  
Jerrod Penn ◽  
◽  
Wuyang Hu ◽  
Keyword(s):  
Willingness To Pay ◽  
Choice Experiment ◽  
Stated Preference ◽  
Cheap Talk ◽  
Hypothetical Bias ◽  
Control Group ◽  
Online Surveys ◽  
Participant Engagement ◽  
Reducing Potential

Cheap Talk (CT) is a mainstay technique among stated preference practitioners to reduce Hypothetical Bias (HB). The usefulness of CT may be questionable in online surveys due to the limited control researchers have on participant engagement. In the context of an online choice experiment on hotels, we compare a control group of respondents who receives a CT script as a traditional passage of text versus a group who must answer an attention-check question to verify their comprehension of the script as well as another group who receives the CT script as a video and then answer the attention-check question. We find that compared to the control group, simply offering the attention-check question reduced willingness to pay (WTP), and those who answer the attention-check question correctly behaved differently to those who did not. Overall, video CT script is shown to improve attention and be more effective in reducing potential HB than a text-based script.

scholarly journals Virtual Immersive Reality for Stated Preference Travel Behavior Experiments: A Case Study of Autonomous Vehicles on Urban Roads

2018 ◽  
Vol 2672 (50) ◽  
pp. 35-45 ◽  
Author(s):  
Bilal Farooq ◽  
Elisabetta Cherchi ◽  
Anae Sobhani
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Stated Preference ◽  
Urban Streets ◽  
Stated Preference Experiments ◽  
Visual Aid

Stated preference experiments have been criticized for lack of realism. This issue is particularly visible when the scenario does not have a well understood prior reference, as in the case of research into demand for autonomous vehicles. The paper presents Virtual Immersive Reality Environment (VIRE), which is capable of developing highly realistic, immersive, and interactive choice scenarios. We demonstrate the use of VIRE in researching pedestrian preferences related to autonomous vehicles and associated infrastructure changes on urban streets in Montréal, Canada. The results are compared with predominantly used approaches: text-only and visual aid. We show that VIRE results in respondents having better understanding of the scenario and it yields more consistent results.

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