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on Discrete Choice Models |
| By: | Anna Maria Boros (University of Warsaw, Faculty of Economic Sciences); Anna Małgorzata Bartczak (University of Warsaw, Faculty of Economic Sciences; University of Warsaw, Robert Zajonc Institute for Social Studies) |
| Abstract: | Perceived realism of the policy scenario presented in stated preference (SP) valuation depends on trust in the scientific soundness of the projected policy outcomes (epistemic credibility) and in policymakers' capability to deliver them (implementation credibility). Using a discrete choice experiment (DCE) with 1, 100 Polish urban residents, we examine how policy scenario credibility shapes preferences for air pollution mitigation reducing risks from chronic obstructive pulmonary disease (COPD). We contrast domain experts and artificial intelligence (AI) with no-source control as information sources on policy outcome projections. We find that epistemic and implementation credibility are strongly correlated; thus, we treat credibility as a single variable affecting preferences. Using a hybrid mixed logit (HMXL) model, we demonstrate that higher perceived credibility increases programme support, lowers cost sensitivity, and thus elevates willingness to pay (WTP) for the programme and morbidity risk reduction. We find no evidence that the information source influences preferences or scenario credibility. |
| Keywords: | air pollution, artificial intelligence, chronic obstructive pulmonary disease, credibility, discrete choice experiment, information source |
| JEL: | D91 Q51 Q53 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:war:wpaper:2026-33 |
| By: | Shakeeb Khan (Boston College); Tatiana Komarova (Faculty of Economics, University of Cambridge); Denis Nekipelov (Amazon) |
| Abstract: | Semiparametric discrete choice models are widely used in economics, yet discrete covariates create a fundamental tension as coefficients point identified under continuous regressors may become only partially identified. We show this generates serious estimation pathologies. Classical estimators, including the maximum score estimators of Manski (1975, 1985, 1987), may have population maximizers that are outer regions of the identified set (Komarova (2013)) and converge to a random set over deterministic regions partitioning that outer region. We introduce the Random Set Quantile (RSQ) estimator, establish consistency and local robustness, and apply it to the 2019 UK General Election. |
| Keywords: | Maximum score estimation, Partial identification, Identified set, Robustness, Random Set Quantile, Panel data discrete choice, Multinomial choice |
| JEL: | C14 C31 C25 |
| Date: | 2026–09–20 |
| URL: | https://d.repec.org/n?u=RePEc:boc:bocoec:1117 |
| By: | Gabriel Nova; Stephane Hess; Sander Van Cranenburgh |
| Abstract: | Discrete choice model specification is a time-consuming task in which modellers often specify and estimate multiple models while balancing goodness-of-fit, parsimony, and behavioural plausibility. We present Delphos, a multitask reinforcement learning framework that learns transferable specification strategies across transport choice datasets. Delphos frames model specification as a sequential decision-making problem in which it applies a sequence of modelling actions and receives feedback from an estimation environment based on model performance and convergence. To transfer modelling decisions across datasets with different sets of variables, Delphos represents utility specifications as sets of modelling terms using a DeepSet-Q architecture, allowing a shared specification policy to learn across multiple datasets. Trained on nine transport choice datasets, Delphos consistently outperforms independently trained single-task agents, indicating that sharing modelling experience improves learning efficiency and helps identify promising sequences of modelling decisions with fewer unsuccessful estimation attempts. When applied without further training to the unseen Swissmetro and Decisions datasets, the same agent identifies competitive specifications in less than 20 minutes on a standard CPU. It achieves a higher log-likelihood per observation than the VNS metaheuristic on Swissmetro and performance comparable to a published MNL specification developed by expert modellers on Decisions. These findings show that accumulating and reusing modelling experience enables Delphos to function as an intelligent assistant for discrete choice model specification. It reduces manual trial-and-error while allowing modellers to retain control over model diagnosis, refinement, and final selection. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.18441 |
| By: | Ali Moghaddasi Kelishomi (Loughborough University); Daniel Sgroi (University of Warwick) |
| Abstract: | Empirical comparisons of preferences often treat the dispersion parameter in a random utility model as noise around a correctly specified utility function. We show that this interpretation can fail: dispersion absorbs systematic behaviour that the fitted preference family cannot span. Using portfolio choices from four studies, we estimate disappointment-aversion random utility models and compare the dispersion parameter with revealed-preference diagnostics. A money-metric decomposition separates axiomatic inconsistency from the additional loss due to imposing DA-CRRA preferences. Both components in dependently predict dispersion, and model-relative misspecification remains strongly predictive among subjects who satisfy revealed-preference consistency. In our sharpest test, coefficients estimated on three studies predict dispersion in a held-out representative sample. A calibrated simulation illustrates the distinction. The dispersion parameter is therefore not a model-free measure of decision quality. It is jointly informative about choice inconsistency and preference-model fit, with implications for comparisons of recovered preferences and stochastic precision across people and environments |
| Keywords: | Revealed Preference, Random Utility Models, Model Misspecification, Structural Noise, Choice Consistency JEL codes: D81, D11, D12, C91 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1629 |
| By: | Mogge, Lukas; Roeckert, Julian; Rukundo, Emmanuel Nshakira; Krähnert, Kati |
| Abstract: | We study stated and realized demand for a new parametric insurance product against excessive rainfall among rice farmers in Vietnam's Mekong Delta, a region highly exposed to climate change. Using a household survey of 3, 000 rice-farming households, we elicit willingness to pay (WTP) using a multiple-bounded dichotomous choice approach. Stated demand is substantial: 33% of respondents report a WTP of at least half the market price, and 18% report a WTP equal to or higher than the market price. Stated demand is significantly higher among men, younger respondents, and respondents reporting better self-assessed product understanding. Yet when insurance agents offered the product at a subsidized price below respondents' stated WTP, no respondent purchased it. We discuss mechanisms that may explain this discrepancy between stated and realized demand, including limited incentive compatibility of the WTP elicitation mechanism, changes in valuations, and contextual barriers to insurance adoption. |
| Abstract: | Wir untersuchen die geäußerte und die tatsächliche Nachfrage nach einem neuen parametrischen Versicherungsprodukt gegen übermäßige Niederschläge bei reisanbauenden Haushalten im vietnamesischen Mekong-Delta - einer Region, die stark vom Klimawandel betroffen ist. Auf der Grundlage einer Befragung von 3.000 reisanbauenden Haushalten ermitteln wir die Zahlungsbereitschaft mittels eines "Multiple-Bounded Dichotomous Choice"-Verfahrens. Die geäußerte Nachfrage ist substanziell: 33 % der Befragten geben eine Zahlungsbereitschaft von mindestens der Hälfte des Marktpreises an, und 18 % nennen einen Betrag, der dem Marktpreis entspricht oder darüber liegt. Die geäußerte Nachfrage ist bei männlichen Befragten, jüngeren Befragten sowie Befragten, die ihr eigenes Produktverständnis höher einschätzen, signifikant höher. Als Versicherungsvertreter das Produkt jedoch zu einem subventionierten Preis anboten, der unter der angegebenen Zahlungsbereitschaft der Befragten lag, erwarb kein einziger Teilnehmer das Versicherungsprodukt. Wir erörtern Mechanismen, die diese Diskrepanz zwischen geäußerter und tatsächlicher Nachfrage erklären könnten, darunter die eingeschränkte Anreizkompatibilität des Verfahrens zur Ermittlung der Zahlungsbereitschaft, Veränderungen der Bewertung sowie kontextuelle Hindernisse für den Abschluss der Versicherung. |
| Keywords: | Agriculture, parametric weather insurance, Vietnam, willingness-to-pay |
| JEL: | G52 Q14 Q12 O12 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:rwirep:343540 |
| By: | Samuel D. Higbee |
| Abstract: | We show how to optimally design experiments when the resulting data will be used to choose a welfare-maximizing policy subject to constraints. A decision maker seeks to maximize Bayes expected welfare by choosing a policy whose effects depend on an unknown finite-dimensional parameter. The decision maker has access to a first wave of experimental data with a fixed design but may choose the design of a second wave that will be collected before choosing the policy. The resulting experimental design--policy choice problem is a very high-dimensional dynamic program that is generally intractable in finite samples. We propose a tractable approximation based on the limit experiment and show it is asymptotically optimal using a new asymptotic representation theorem for adaptive experiments with continuous treatments. We apply the method to a conditional cash transfer experiment and demonstrate the potential for large gains from tailoring the experiment to the policy choice. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.10971 |
| By: | Gangadharan, Lata; Gsottbauer, Elisabeth; Leslie, Gordon; Pretto, Madeline |
| Abstract: | Do households comprehend the nature of tail-risks inherent to real-time electricity pricing (RTP) plans? We develop a randomized and incentivized experiment calibrated to real-world price distributions and find that (a) probabilistic risk disclosure, beyond that offered in standard marketing materials, elicits greater demand for real-time pricing products relative to a low-risk fixed-price alternative, (b) products with tail-risk protection might not be highly sought, and (c) the experience of a RTP bill shock drives choice away from RTP. Personal experience receiving a tail price plays a greater role in risk comprehension and moving subsequent choices toward less risky plans than receipt of an additional ex-ante probabilistic risk disclosure. We discuss the implications these findings may have for regulators with a consumer protection mandate. |
| Keywords: | consumer protection;dynamic pricing;experimental economics;information provision;retail electricity markets;risk perception;tail-risk |
| JEL: | C91 D18 D81 L94 Q41 |
| Date: | 2026–09–30 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:140854 |
| By: | Hild, Paul Ergün; Hilweg-Waldeck, Michael |
| Abstract: | Career choice, earnings, and other key economic outcomes have been linked to gender differences in willingness to compete. This paper examines how gender stereotypes shape these differences. We conduct a meta-study of prior work and demonstrate that the wide variation in gender competition gaps can be explained by stereotypes: Men enter competitions more in traditionally male-stereotyped domains, whereas in female-stereotyped domains, the gap is smaller or even reversed. Importantly, these differences are not explained by gender gaps in performance. To explore mechanisms, we collect belief data in an elicitation experiment. We find that stereotyped beliefs about gender performance differences explain more than half of the variation in competition gaps in the literature. Next, we experimentally manipulate stereotypes through framing and informational cues about others beliefs. Although these interventions significantly shift beliefs, the effects do not translate into changes in competitive behavior. Our findings highlight the importance of stereotypes in shaping gender gaps in competitiveness while suggesting that shifting beliefs alone is unlikely to close these gaps without deeper or longer-term interventions. |
| Keywords: | Gender, Competitiveness, Stereotypes, Beliefs, Experiment |
| JEL: | D91 J16 C90 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:zewdip:343565 |
| By: | Zhentong Lu; Myung Hwan Seo; Youngki Shin; Qichen Zhang |
| Abstract: | We develop a stochastic nested fixed point (SNFP) estimator for random coefficients logit demand models that updates model parameters using stochastic gradients and performs demand inversion one market at a time. Relative to the conventional nested fixed point (NFP) estimator, SNFP substantially reduces memory requirements and computational cost, making estimation feasible in very large datasets. We establish the large-$T$ (number of markets) asymptotic properties of the estimator under regularity conditions. We also characterize the effect of sharing one block of simulation draws across markets and show how to correct for it. Monte Carlo simulations show that the SNFP estimator achieves statistical accuracy comparable to the NFP estimator, and in our benchmark a single online pass estimates a model with 100 million markets in about 5.5 hours. An empirical application using scanner data further demonstrates the practical advantages of SNFP for large-scale demand estimation. |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.23998 |
| By: | Felix J Bierbrauer (Université de Cologne); Pierre C Boyer (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique); Andreas Peichl (LMU - Ludwig Maximilian University [Munich] = Ludwig Maximilians Universität München); Paul Vanborre (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | How much defense spending should we provide, and how should we finance it? How much political support among citizens for defense spending should we expect? These are pressing questions to address as defense spending is set to go up substantively in the coming years with the goal of achieving self-sufficiency and EU sovereignty. National defense is the textbook example of a pure public good. We review insights from the theory of pure public goods to identify challenges for an efficient provision and financing of national defense. Key insights are: (i) The citizens' willingness to pay taxes for national defense depends on the design of distributive policies (ii) Pareto efficiency requires responsiveness to the preferences of citizens who pay for public goods via the tax system, (iii) An increase of national defense spending may go hand-in-hand with additional redistribution and (iv) uncertainty about the citizens' willingness to pay for increased defense spending implies uncertainty about the political feasibility of reform packages. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:hal:ipppap:halshs-05543774 |
| By: | Ali Moghaddasi Kelishomi (Loughborough University); Daniel Sgroi (University of Warwick); Andis Sofianos (Durham University) |
| Abstract: | How does rationality shape cooperation in strategic settings? We study this question in a laboratory experiment that links individual rationality, measured by consistency with the generalized axiom of revealed preference, to behaviour in an indefinitely repeated Prisoner’s Dilemma. Participants are grouped by pre-measured rationality before interacting repeatedly. We find that higher rationality substantially increases cooperation and payoffs. This effect operates through a novel mechanism: more rational individuals make fewer implementation errors when executing their intended strategies, thereby sustaining cooperative outcomes. By contrast, higher cognitive ability also promotes cooperation and higher payoffs, but through a distinct channel—reducing strategic errors in responding optimally to others’ actions. Our results provide the first experimental evidence linking rationality to cooperation via decision-making errors, and clarify the distinct roles of rationality and intelligence in shaping strategic behaviour. Together, the findings offer a unified account of how cognitive constraints affect cooperation in repeated games |
| Keywords: | Repeated Prisoners Dilemma, Cooperation, Rationality, Intelligence, Learning, Strategy Errors JEL codes: C73, C91, C92, D83 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1630 |
| By: | Mira Frick; Ryota Iijima; Yuhta Ishii; Nicholas Wu |
| Abstract: | Consider an auction with buyers whose values depend on an underlying state (e.g., market fundamentals). How does the auction format shape the information that buyers' bids reveal about the state? We recast auctions as statistical experiments and compare different auction formats in terms of the (Lehmann) informativeness of the induced experiments. Our main finding is that among a large class of auctions (e.g., $k$th-price, all-pay), the first-price auction is the most informative. As a result, this auction guarantees the highest payoffs to a decision-maker who uses the information revealed by buyers' bids in a monotone decision problem (e.g., a prediction problem or the choice of a reserve price in a future auction). |
| Date: | 2026–09 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2609.21168 |