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on Discrete Choice Models |
| By: | Blackman, Allen; Dissanayake, Sahan; Martinez Cruz, Adan; Corral, Leonardo; Schling, Maja |
| Abstract: | We conduct a discrete choice experiment with leaders of a random sample of 164 Peruvian indigenous communities (ICs) - to our knowledge, the first use of rigorous stated preference methods to analyze land titling. We find that: (i) on average, IC leaders are willing to pay US$35, 000-45, 000 for a title, roughly twice the per community administrative cost of titling; (ii) WTP is positively correlated with the value of IC land and the risk of land grabbing; and (iii) leaders prefer titling processes that involve indigenous representatives and titles that encompass land with cultural value. |
| Keywords: | discrete choice experiment;Indigenous Community;land rights;mixed multinomiallogit |
| JEL: | O13 Q15 C93 |
| Date: | 2022–12 |
| URL: | http://d.repec.org/n?u=RePEc:idb:brikps:12633&r=dcm |
| By: | Andrew Chesher; Adam Rosen; Yuanqi Zhang |
| Abstract: | Many structural econometric models include latent variables on whose probability distributions one may wish to place minimal restrictions. Leading examples in panel data models are individual-specific variables sometimes treated as “fixed effects” and, in dynamic models, initial conditions. This paper presents a generally applicable method for characterizing sharp identified sets when models place no restrictions on the probability distribution of certain latent variables and no restrictions on their covariation with other variables. Endogenous explanatory variables can be easily accommodated. Examples of application to some static and dynamic binary, ordered and multiple discrete choice panel data models are presented. |
| Date: | 2023–10–11 |
| URL: | http://d.repec.org/n?u=RePEc:azt:cemmap:20/23&r=dcm |
| By: | Benjamin Enke; Cassidy Shubatt |
| Abstract: | We develop interpretable, quantitative indices of the objective and subjective complexity of lottery choice problems that can be computed for any standard dataset. These indices capture the predicted error rate in identifying the lottery with the highest expected value, where the predictions are computed as convex combinations of choice set features. The most important complexity feature in the indices is a measure of the excess dissimilarity of the cumulative distribution functions of the lotteries in the set. Using our complexity indices, we study behavioral responses to complexity out-of-sample across one million decisions in 11, 000 unique experimental choice problems. Complexity makes choices substantially noisier, which can generate systematic biases in revealed preference measures such as spurious risk aversion. These effects are very large, to the degree that complexity explains a larger fraction of estimated choice errors than proximity to indifference. Accounting for complexity in structural estimations improves model fit substantially. |
| Keywords: | complexity, choice under risk, cognitive uncertainty, experiments |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10644&r=dcm |
| By: | Andrea La Nauze; Erica Myers |
| Abstract: | We use an experiment to test whether consumers optimally acquire information on energy costs in appliance markets where, like many contexts, consumers are poorly informed and make mistakes despite freely-available information. We find consumers acquire information suboptimally; there is little correlation between the revealed utility gain from improved decision making due to information and willingness to pay for information. We compare two behavioral interventions to address consumer mistakes: a conventional subsidy for energy-efficient products and a non-traditional subsidy paying consumers to view information on energy costs. We show that paying for attention can target welfare improvements more effectively. |
| JEL: | D12 D83 D91 Q41 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31742&r=dcm |
| By: | Benjamin Enke; Cassidy Shubatt |
| Abstract: | We develop interpretable, quantitative indices of the objective and subjective complexity of lottery choice problems that can be computed for any standard dataset. These indices capture the predicted error rate in identifying the lottery with the highest expected value, where the predictions are computed as convex combinations of choice set features. The most important complexity feature in the indices is a measure of the excess dissimilarity of the cumulative distribution functions of the lotteries in the set. Using our complexity indices, we study behavioral responses to complexity out-of-sample across one million decisions in 11, 000 unique experimental choice problems. Complexity makes choices substantially noisier, which can generate systematic biases in revealed preference measures such as spurious risk aversion. These effects are very large, to the degree that complexity explains a larger fraction of estimated choice errors than proximity to indifference. Accounting for complexity in structural estimations improves model fit substantially. |
| JEL: | D03 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31677&r=dcm |
| By: | Domínguez, Patricio; Scartascini, Carlos |
| Abstract: | Crime levels are a perennial development problem in Latin America and a renewed concern in the United States. At the same time, trust in the police has been falling, and questions abound about citizens' willingness to support government efforts to fight crime. We conduct a survey experiment to elicit willingness to contribute toward reducing crime across five Latin American countries and the United States. We compare homicide, robbery, and theft estimates and find a higher willingness to contribute for more severe crimes and for higher crime reductions. In addition, we examine the role of information on the willingness to contribute by conducting two experiments. First, we show that exposing respondents to crime-related news increases their willingness to pay by 5 percent. Furthermore, while we document a 7 percent gap in willingness to pay for crime reduction between people who under- and over-estimate the murder rate, we find that this gap can be wholly eliminated by informing them about the actual level of crime. On average, our estimates suggest that households are willing to contribute around $140 per year for a 20 percent reduction in homicide. This individual-level predisposition would translate into additional investment in public security efforts of up to 0.5 percent of GDP. |
| Keywords: | willingness to pay;Cost of crime;Latin America;United States |
| JEL: | K42 H53 H27 |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:idb:brikps:12488&r=dcm |
| By: | Gergely Hajdu (Department of Economics, Vienna University of Economics and Business); Balázs Krusper (Lidl Stiftung & Co. KG) |
| Abstract: | Consumers are constantly exposed to new information that compels them to update their beliefs about products, thereby influencing future buying and selling decisions. This process does not simply stop with a product choice. We study how choosing a product affects learning about products in the choice set after the choice has been made. We design an experiment, where we have control over the objective ranking of the options in the choice set. Specifically, participants learn about the fundamental quality of financial investments by observing price changes in multiple rounds. Participants either choose some of the investments themselves (Choice condition) or have some of the investments assigned to them (Allocation condition). We find that learning is stickier after making a choice: participants respond less to price changes in the Choice condition than in the Allocation condition. This result holds for both own and non-owned investments and for both good news and bad news. The effect is unlikely to be driven by attention: we find no difference between the conditions in the amount of attention paid to the investments. We estimate a structural model and show that learning aligns closely with the Bayesian benchmark after exogenous product allocation, while it is too sticky after making a choice. Our model characterizes sticky learning in a tractable way that is easily portable, making it simple to analyze its consequences in other contexts. |
| Keywords: | biased beliefs, attention, sticky learning, choice effect |
| JEL: | D9 D12 G4 |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwwuw:wuwp349&r=dcm |
| By: | Díaz Escobar, Ana María; Salas Bahamón, Luz Magdalena; Piras, Claudia; Suaya, Agustina |
| Abstract: | This study tests four "light touch" interventions in the language used in job posts of male- dominated occupations to attract female workers using a discrete choice experiment. This experiment had more than 5000 participants from five Latin American countries. We test two possible mechanisms: the gender-stereotypes related to job skills and the use of inclusive language. We find that language matters, and men and women value information and inclusive language in job advertisements. However, women are more sensitive in this regard. We test the effect of simply aggregating irrelevant, but additional words to the job ad, and find that when the inclusive language in the ad is subtle, the effect of having more words is very important. But it decreases when the language signals a strong preference for an inclusive work environment. These findings highlight the importance of language and the type of information presented in job advertisements in attracting a gender-balanced workforce. |
| Keywords: | Language interventions;access to employment;labor discrimination;jobads;Occupational Segregation |
| JEL: | J16 J24 J63 C91 M54 |
| Date: | 2023–04 |
| URL: | http://d.repec.org/n?u=RePEc:idb:brikps:12819&r=dcm |
| By: | Gajendra Liyanaarachchi (University of Portsmouth); Giampaolo Viglia (University of Portsmouth); Fidan Kurtaliqi (Audencia Business School) |
| Abstract: | Purpose This study aims to investigate the implications, risks and challenges of data privacy due to the use of immersive technology in the hospitality industry. Design/methodology/approach The authors adopt a mixed-method approach. Study 1 is a focus group. The authors then provide external and ecological validity with a field experiment conducted with 139 hotel clients at a three-star continental European hotel. Findings Collecting biometric data results in unbalanced privacy compared to biographic data, as it diminishes individuals' control over their data and grants organizations absolute power. This unbalanced privacy directly influences consumers' willingness to disclose information, affecting their choice of hotels and access to services. Practical implications Hotels should redesign their strategies to accommodate heightened privacy risks with biometric data. This can be obtained by introducing systems that foster customer confidence in data usage and facilitate customers' willingness to disclose biometrics through immersive technology or biographic data. Originality/value This study introduces unbalanced privacy as a unique state due to sharing biometric data. The authors propose a novel doctrine, the uncontrollable privacy paradox, which is a shift from the privacy paradox. The uncontrollable privacy paradox addresses the unbalanced privacy envisaged through consumer powerlessness in data management. This research addresses the literature gap on the privacy paradox by offering a broader perspective, including business, industry and mixed reality considerations. |
| Date: | 2023–09–26 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-04219606&r=dcm |