I collect data on subjects' information acquisition during real and hypothetical risky choices using process-tracing software called Mouselab. I also measure subjects' cognitive ability using the cognitive reflective test (CRT). On average, measured risk preferences are not significantly different across real and hypothetical settings. However, cognitive ability is inversely related to risk aversion when choices are hypothetical, but it is unrelated when the choices are real. This interaction between cognitive ability and hypothetical setting is consistent with the notion that some individuals, specifically higher-ability individuals, treat hypothetical choices as "puzzles" and may help explain why some studies find that subjects indicate that they are more tolerant of risk when they make hypothetical choices than when they make real choices. On average, subjects demonstrate a similar degree of consistency across settings, and there are also no significant differences across settings in the amount of time subjects take to make a choice, the amount of information they acquire, or how they distribute their attention. I also find evidence to suggest that subjects acquire information in a manner consistent with the implicit calculation of expected utility. Specifically, individuals do not merely make choices "as if" they are integrating probabilities and outcomes, it appears that they actually are. Moreover, as they progress through a series of choices in a commonly used risk preference elicitation method, their information acquisition becomes progressively more consistent with integration models. Finally, on average, individuals appear to acquire information in real and hypothetical settings in similar ways.

In a controlled lab experiment, we investigate hypothetical biases in the value of time by comparing stated preference (SP) and revealed preference (RP) values attached to unexpected waiting times. The SP and RP choice sets are identical in terms of design with the only difference being that the RP choices have real consequences in terms of unexpected waiting times and monetary incentives. We find a substantial hypothetical bias with the average SP value of time being only 71% of the corresponding RP value. The bias is mainly driven by participants who have scheduling constraints during the time of the unexpected wait. Scheduling constraints are taken into account to a much lesser extent in the SP setting than in the RP setting, presumably because only in the latter, the consequences of ignoring them are costly. We find evidence that this effect is stronger for persons with relatively low cognitive ability.

Experimental willingness to pay (WTP) studies can be classified as hypothetical or non-hypothetical. In a hypothetical study, such as conjoint analysis, a subject does not need to make a real economic commitment. In contrast, in a non-hypothetical task such as in experimental auctions, a subject may need to actually buy the product. Subjects in hypothetical studies tend to overstate their true WTP. Consequently, researchers need to correct hypothetical values to obtain reliable WTP estimates. Recently, incentive-aligned and cheap talk approaches have been proposed as ways to correct for hypothetical bias. In a hypothetical task, a cheap talk script explicitly reminds the subject about the hypothetical nature of the task and its expected consequences. In an incentive-aligned task (non-hypothetical), subjects are randomly selected to physically buy the product. The objective of our study is to assess and compare the reduction of hypothetical bias in consumers’ willingness to pay for novel products by applying a generic, short, and neutral cheap talk script in a retail setting. To accomplish this objective, we employ non-hypothetical, hypothetical, and hypothetical with cheap talk treatments in our experimental design. We conducted our experimental retail study using conjoint analysis and open-ended elicitation mechanisms, utilizing Becker DeGroot Marshak (BDM) mechanism for the incentive-aligned treatments. Consistently in both elicitation mechanisms, using seemingly unrelated and random-effect Tobit techniques, we find that our cheap talk script is effective in eliminating the hypothetical bias. As expected, the hypothetical WTP values are significantly higher than the non-hypothetical values but the hypothetical values with cheap talk are not significantly different from incentive-aligned or non-hypothetical estimates. In addition, we find that open-ended estimates are significantly higher than conjoint analysis estimates and that emotions and familiarity can have significant impacts on WTP estimates.

Experimental willingness to pay (WTP) studies can be classified as hypothetical or non-hypothetical. In a hypothetical study, such as conjoint analysis, a subject does not need to make a real economic commitment. In contrast, in a non-hypothetical task such as in experimental auctions, a subject may need to actually buy the product. Subjects in hypothetical studies tend to overstate their true WTP. Consequently, researchers need to correct hypothetical values to obtain reliable WTP estimates. Recently, incentive-aligned and cheap talk approaches have been proposed as ways to correct for hypothetical bias. In a hypothetical task, a cheap talk script explicitly reminds the subject about the hypothetical nature of the task and its expected consequences. In an incentive-aligned task (non-hypothetical), subjects are randomly selected to physically buy the product. The objective of our study is to assess and compare the reduction of hypothetical bias in consumers’ willingness to pay for novel products by applying a generic, short, and neutral cheap talk script in a retail setting. To accomplish this objective, we employ non-hypothetical, hypothetical, and hypothetical with cheap talk treatments in our experimental design. We conducted our experimental retail study using conjoint analysis and open-ended elicitation mechanisms, utilizing Becker DeGroot Marshak (BDM) mechanism for the incentive-aligned treatments. Consistently in both elicitation mechanisms, using seemingly unrelated and random-effect Tobit techniques, we find that our cheap talk script is effective in eliminating the hypothetical bias. As expected, the hypothetical WTP values are significantly higher than the non-hypothetical values but the hypothetical values with cheap talk are not significantly different from incentive-aligned or non-hypothetical estimates. In addition, we find that open-ended estimates are significantly higher than conjoint analysis estimates and that emotions and familiarity can have significant impacts on WTP estimates.

Contingent Valuation (CV) methods are a primary tool in environmental economics to ascertain non-use or other values not observable through existing market mechanisms. Because common CV approaches typically rely on hypothetical answers from surveys in order to generate welfare estimates, these are often labelled stated preferences. Results from stated preference methods often diverge from those obtained when actual preference or behavior are involved. This divergence is commonly known as Hypothetical Bias (HB). This dissertation addresses HB as it applies to environmental applications. To begin, a meta-analysis using a sample of studies many times larger than previous works was performed. Its results identify which study protocols exacerbate HB, and which may mitigate it. Furthermore, the meta-analysis establishes the efficacy of some popular techniques to mitigate HB. The second essay focuses on understanding and addressing two important topics to environmental economics, distance decay and charismatic species conservation. These effects have not been investigated with respect to HB. We implement a field survey of monarch and viceroy butterfly conservation, creating survey treatment conditions involving both real payment and hypothetical scenarios in order to establish the extent of HB. The key finding is that while HB is present for both butterflies, HB in distance decay exists for monarchs. There is also additional HB for monarchs compared to viceroys, which we attribute to the former’s charisma. The final endeavor studies the usefulness of consequentiality, a relatively new tactic to reduce HB. Consequentiality is the degree to which respondents believe their answers may affect policy outcomes. Relying on the monarch field survey, we find that using a technique known as ex ante consequentiality may exacerbate HB. Another approach known as ex post consequentiality is more effective at reducing the extent of HB in the data. Lastly, some elements of the studies’ results showcase that HB is not always present and can also explain some of the mixed results found on the efficacy of HB mitigating methods reported in previous studies.

Economists are still searching for methods to reduce/eliminate Hypothetical Bias (HB). Different methods have been previously applied some with success and others without. In this study, we aimed to further test the cognitive dissonance approach (CD) through a learning design method to estimate the WTP for five beef attributes: Non-quality, Kentucky Proud, Appalachian, Grass Fed and a mix of 25% Non-quality and 75% Kentucky Proud, using a one and one half bounded model. To test the CD, 881 participants from the University of Kentucky, were randomly assigned to a real/hypothetical market for a battery recycling project at first and afterwards to a hypothetical market for beef. For the battery recycling, participants were asked to donate $1, $2 or $3. For the beef market, participants were randomly assigned to a $4 or $6 for the non-quality attribute patty. Participants assigned to a $4 were afterwards randomly assigned to a $4.5, $5, $5.5 or $6 and the ones assigned to a $6 were afterwards assigned to a $6.5, $7, $7.5 and $8 for the other attribute patties. From this study, we found that the learning design was effective in reducing the cognitive dissonance or conflicts between what consumers say and their actions.

Hypothetical bias continues to be a challenge for practitioners of the contingent valuation method (CVM). This study compared the effect of three hypothetical bias mitigation techniques in a CVM survey focused on estimating maximum willingness to pay for a beach conditions monitoring service among U.S. Gulf Coast beachgoers. Beach conditions information is known to affect beach patronage but no valuation study has yet estimated its value. The two techniques tested are: budget and substitutes cheap talk treatments and certainty follow-up. We presented a theoretically consistent model of budget-constrained utility maximization which accounts for the respondents’ subjective probability of a good beach trip with and without the beach conditions information. Interval regression was used to estimate respondents WTP for beach conditions monitoring service. Both mitigation treatments were unable to mitigate HB. The mean WTP was $3.39 and the net benefit for the program was between $188,531,063 and $391,474,452.

In the modern industrialized society, a long commuting time is becoming more and more common. However, commuting results in a number of different costs, for example, external costs such as congestion and pollution as well as internal costs such as individual time consumption. On the other hand, increased commuting opportunities offer welfare gains, for example via larger local labor markets. The length of the commute that is acceptable to the workers is determined by the workers' preferences and the compensation opportunities in the labor market. In this thesis the value of travel time or commuting time changes, has been empirically analyzed in four self-contained essays. First, a large set of register data on the Swedish labor market is used to analyze the commuting time changes that follow residential relocations and job relocations. The average commuting time is longer after relocation than before, regardless of the type of relocation. The commuting time change after relocation is found to differ substantially with socio-economic characteristics and these effects also depend on where the distribution of commuting time changes is evaluated. The same data set is used in the second essay to estimate the value of commuting time (VOCT). Here, VOCT is estimated as the trade-off between wage and commuting time, based on the effects wage and commuting time have on the probability of changing jobs. The estimated VOCT is found to be relatively large, in fact about 1.8 times the net wage rate. In the third essay, the VOCT is estimated on a different type of data, namely data from a stated preference survey. Spouses of two-earner households are asked to individually make trade-offs between commuting time and wage. The subjects are making choices both with regard to their own commuting time and wage only, as well as when both their own commuting time and wage and their spouse's commuting time and wage are simultaneously changed. The results show relatively high VOCT compared to other studies. Also, there is a tendency for both spouses to value the commuting time of the wife highest. Finally, the presence of hypothetical bias in a value of time experiment without scheduling constraints is tested. The results show a positive but not significant hypothetical bias. By taking preference certainty into account, positive hypothetical bias is found for the non-certain subjects.