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on Discrete Choice Models |
| By: | Jason Sockin; Pawel Adrjan; Mária Balgová; Simon Jäger; Jonas Jessen |
| Abstract: | Discrete choice experiments are widely used to estimate workers' willingness to pay (WTP) for job amenities under the assumption that varying an attribute does not change workers' beliefs about other job attributes. We test this assumption by embedding an amenity with a known market price-a popular monthly public transport pass-in a large-scale discrete choice experiment with German workers. Many workers, including public transport users, overvalue the ticket by more than 100%, despite WTP for other attributes aligning with the literature. A complementary belief-elicitation experiment shows that advertising an amenity, such as the pass but also common amenities like work from home, causally shifts beliefs about unlisted attributes of the job. Posted wages similarly signal unlisted attributes so that wage variation, the money metric for WTP calculation, is itself contaminated by belief spillovers-such as higher pay signaling heightened stress. These spillovers imply that discrete choice estimates capture perceived bundles rather than isolated attributes, and distort current estimates of non-wage compensation and monopsony power. |
| Keywords: | Amenities, discrete choice, job postings |
| JEL: | J31 J32 J42 C83 C90 D83 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:crm:wpaper:26184 |
| By: | Reynaert, Mathias; Xu, Wenxuan; Zhao, Hanlin |
| Abstract: | Agents often make choices by forming expectations about attributes, but such expectations are usually unobserved by researchers. We develop two methods for estimating discrete choice models where agents use unobserved heterogeneous information sets to form expectations. Preferences are point-identified using a finite mixture approximation of the unobserved information structure or set-identified with partial information. Both methods apply to individual- and market-level data without imposing strong assumptions on how expectations are formed. We revisit two empirical applications that confirm the importance of accounting for unobserved information: firms’ revenue expectations when exporting and consumers’ fuel cost expectations when purchasing cars. |
| JEL: | C5 C8 D8 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19484 |
| By: | Tien Mai |
| Abstract: | Route and activity choice are connected levels of a common sequential mobility decision problem: activity choice determines what people do, where, and when, while route choice governs how they move between activities. This review develops a unified framework connecting transportation choice modeling with inverse reinforcement learning (IRL) and imitation learning (IL). Under explicit assumptions, recursive logit, logit dynamic discrete choice, and maximum-entropy IRL share a soft Bellman representation, while trajectory occupancies and network flows satisfy related conservation laws. However, utility, reward, policy, occupancy, constraints, and observation errors remain different estimands with different behavioral and counterfactual interpretations. We review constrained and inverse-constrained learning, occupancy-ratio and DICE methods, incomplete and mixed-quality demonstrations, graph and sequence learning, transfer, data fusion, multi-agent choice, and large language models. Our central message is that machine learning adds the greatest value when embedded within a behaviorally disciplined framework: exact transitions enforce feasibility, structured rewards preserve interpretable trade-offs, observation models address heterogeneous data sources, and network or equilibrium solvers produce coherent system outcomes. Such hybrid models can improve scalability and prediction without sacrificing behavioral identification or policy relevance. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.15339 |
| By: | Cash Looi; Ruben Loaiza-Maya; Didier Nibbering |
| Abstract: | Standard multinomial probit (MNP) models specify symmetric latent utility distributions, implying that choice probabilities respond symmetrically to positive and negative covariate shifts of the same magnitude. This restriction is often implausible in empirical choice settings and can lead to misleading elasticity and substitution predictions. We propose a skewed multinomial probit (SMNP) model that captures asymmetric choice responses by specifying a multivariate skew-normal distribution for the latent utilities. The model preserves the flexible substitution patterns of the MNP framework, introduces alternative-specific skewness parameters, and nests the standard MNP model when skewness is zero. Introducing skewness creates identification and computational challenges because the skewness parameters interact with the MNP scale normalization and disrupt the conditional Gaussian updating structure used in Bayesian MNP estimation. We address these challenges through a covariance reparameterization that enforces identification and positive definiteness by construction, interpretable priors on the identified parameter space, and a double data-augmentation scheme that yields a Metropolis-Hastings within Gibbs sampler. Numerical experiments and applications to consumer choice data show that SMNP recovers asymmetric choice responses, improves probabilistic prediction, and produces economically meaningful differences in price elasticities and substitution patterns. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.10336 |
| By: | Fleck, Lara (ROA, Maastricht University); Becker, Dominik (Federal Institute for Vocational Education and Training (BIBB)); Fregin, Marie-Christine (ROA, Maastricht University); de Grip, Andries (ROA, Maastricht University); Pfeifer, Harald (Federal Institute for Vocational Education and Training (BIBB)); Weis, Kathrin (Federal Institute for Vocational Education and Training (BIBB)) |
| Abstract: | With the advent of generative artificial intelligence, prompting skills are becoming increasingly relevant in the workplace. Using a discrete choice experiment (DCE), we asked decision-makers on hiring in German firms in all sectors of the economy are asked to choose between job applicants with different skills bundles. Applicant profiles vary in five attributes: prompting skills, occupation-specific skills gaps, social skills, gender and salary expectations. We find that prompting skills increase applicants’ hiring probability by 4 percent and employers are willing to pay 2 percent above the average salary of a skilled worker in their firm. This WTP is modest compared to the WTP for having matching occupation-specific skills or high social skills. However, in large firms as well as firms that have adopted or are planning to adopt AI, high prompting skills increase applicant’s hiring probability by 9 percent. Moreover, prompting skills have some leverage to balance out low to intermediate social skills. Yet, higher prompting skills do not compensate for occupation-specific skills gaps. Instead of such a compensatory effect, the demand for prompting skills seems to upgrade skills requirements in jobs. |
| Keywords: | prompting skills, generative AI, discrete choice experiment, willingness to pay, skills complementarities |
| JEL: | J23 J24 M51 O33 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18871 |
| By: | Marek Giergiczny (German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; University of Warsaw, Faculty of Economic Sciences); Jette Bredahl (University of Copenhagen, Department of Food and Resource Economics); Klaus Glenk (SRUC, Department of Rural Economy, Environment and Society); Jürgen Meyerhoff (Technische Universität Berlin, Institute for Landscape Architecture and Environmental Planning); Jens Abildtrup (Université de Lorraine, Université de Strasbourg, AgroParisTech, CNRS, INRAE, BETA); Fitalew Agimass Taye (Griffith University, Griffith Business School); Wiktor Budziński (University of Warsaw, Faculty of Economic Sciences); Mikołaj Czajkowski (University of Warsaw, Faculty of Economic Sciences); Borys Draus (Bureau for Forest Management and Geodesy); Michela Faccioli (University of Trento, School of International Studies and Department of Economics and Management); Tomasz Gajderowicz (University of Warsaw, Faculty of Economic Sciences); Michael Getzner (TU Wien, Institute of Spatial Planning); Tom X. Hackbarth (Vrije Universiteit Amsterdam); Piotr Janiec (University of Agriculture in Krakow); Thomas Lundhede (University of Copenhagen, Department of Food and Resource Economics); Marius Mayer (Munich University of Applied Sciences, Department of Tourism); Alistair McVittie (SRUC, Department of Rural Economy, Environment and Society); Rachel Oh (National University of Singapore, Department of Geography); Roland Olschewski (WSL Swiss Federal Research Institute, Economics and Social Sciences); Henrique M. Pereira (German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig); Martin Quaas (German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; Leipzig University); Jarosław Socha (University of Agriculture in Krakow); Niels Strange (University of Copenhagen, Department of Food and Resource Economics); Milan Ščasný (Charles University, Environment Centre; Charles University, Institute of Economic Studies, Faculty of Social Sciences); Sviataslau Valasiuk (University of Warsaw, Faculty of Economic Sciences); Adam Wasiak (Regional Directorate of State Forests in Radom); Néstor Fernández (German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig) |
| Abstract: | Forests across Europe are undergoing rapid transformation as biodiversity loss and climate change reshape priorities for forest management. Strategies that promote biodiverse and structurally complex forests are increasingly advocated to enhance ecological resilience, yet they are often assumed to conflict with societal preferences, potentially limiting public support for conservation and restoration. We examined whether forest characteristics associated with biodiversity conservation and climate adaptation are consistently valued by society across Europe. We combined a visual discrete choice experiment involving 11, 622 respondents from twelve European countries with a travel cost model to evaluate whether stated societal preferences were reflected in observed recreational behaviour. We then integrated harmonized preference estimates with continental forest inventory and remote-sensing data to map the spatial distribution of societal values associated with forest ecosystem condition. Across all countries, respondents consistently preferred forests characterized by taller canopies, greater tree-species richness, heterogeneous age structures, and more deadwood. These preferences closely aligned with observed visitation behaviour despite substantial differences in geography, accessibility, and recreational traditions. Spatial analyses further showed that forests with greater structural complexity consistently exhibited higher societal value. Our findings demonstrate that biodiversity-oriented forest management and societal values largely converge across Europe, suggesting that many interventions promoting ecological resilience can simultaneously strengthen public support for forest conservation and restoration, providing a stronger foundation for adaptive, multifunctional forest governance under global environmental change. |
| Keywords: | biodiversity conservation, forest management, structural complexity, forest recreation, ecosystem services, discrete choice experiment, travel cost method |
| JEL: | Q57 Q23 Q26 Q51 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:war:wpaper:2026-25 |
| By: | Teck Yong Tan |
| Abstract: | A monopolist sells a product line whose variants are horizontally differentiated from the buyers' perspective but ordered by production cost. Buyers privately know their ideal product, and willingness to pay may be correlated with horizontal need. The seller screens buyers through product mismatch, and what she must screen determines whether mismatch creates or reduces information rent. When buyers differ only in horizontal need, mismatch creates rent: the seller induces less mismatch, assigning served buyers products closer to their ideals than under the first best. When willingness to pay is correlated with horizontal need, mismatch instead reduces rent: the seller induces more mismatch, sells the basic product to buyers whose efficient products are advanced variants while excluding buyers better matched to it, and stronger horizontal differentiation can expand coverage and raise profit. Because mismatch is type-specific, optimal allocations are determined by individual rationality rather than by incentive compatibility alone. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.21765 |