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on Discrete Choice Models |
| By: | Yu Hao; Hiroyuki Kasahara |
| Abstract: | This paper extends the work of Arcidiacono and Miller (2011, 2019) by introducing a novel characterization of finite dependence within dynamic discrete choice models, demonstrating that numerous models display 2-period finite dependence. We recast finite dependence as a problem of sequentially searching for weights and introduce a computationally efficient method for determining these weights by utilizing the Kronecker product structure embedded in state transitions. With the estimated weights, we develop a computationally attractive Conditional Choice Probability estimator with 2-period finite dependence. The computational efficacy of our proposed estimator is demonstrated through Monte Carlo simulations. |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2405.12467&r= |
| By: | Fedor Sandomirskiy; Philip Ushchev |
| Abstract: | We revisit a classical question of how individual consumer preferences and incomes shape aggregate behavior. We develop a method that applies to populations with homothetic preferences and reduces the hard problem of aggregation to simply computing a weighted average in the space of logarithmic expenditure functions. We apply the method to identify aggregation-invariant preference domains, characterize aggregate preferences from common domains like linear or Leontief, and describe indecomposable preferences that do not correspond to the aggregate behavior of any non-trivial population. Applications include robust welfare analysis, information design, discrete choice models, pseudo-market mechanisms, and preference identification. |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2405.06108&r= |
| By: | Gildas Appéré (UA - Université d'Angers); Damien Dussaux (OCDE - Organisation de Coopération et de Développement Economiques = Organisation for Economic Co-operation and Development); Alan Krupnick (RESOURCES FOR THE FUTURE WASHINGTON DC USA - Partenaires IRSTEA - IRSTEA - Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture); Muriel Travers (Nantes Univ - Nantes Université) |
| Abstract: | Asthma is a non-communicable and non-curable lung disease that affects 10% of children and 4% of adults worldwide and is associated with an array of environmental contaminants and chemicals. This article offers values suitable for use in cost–benefit analyses of the willingness to pay (WTP) for reduced severity of asthma in adults and children and in reduced probability of getting asthma for these two population groups, all in the context of reducing chemical exposures. To this end, an online survey was administered between November 2021 and May 2022 to 12 727 respondents from seven countries of the Organisation for Economic Co-operation and Development (OECD). This article applies two stated preference methods for eliciting WTP: the contingent valuation method for reduced asthma severity and choice experiments for reduced probability of getting asthma of various severities. The context for such elicitations was a set of household products that contain fewer hazardous chemicals than what is currently available in supermarkets but are more expensive. The study finds that the WTP for reducing asthma severity in adults by one step, e.g. from "moderate plus" to "moderate", isUSD2022 529 per year on average. The parental WTP for reducing asthma severity in their children is USD2022 PPP 948 per year and is on average 1.8 times higher than their WTP for themselves. The mean value of a statistical case (VSC) of adult asthma which would be applied to predictions of new cases of asthma avoided by a regulation equals USD2022 280 000, while the mean VSC of childhood asthma equals USD2022 430 000. |
| Keywords: | Asthma, Health risk, Economic valuation, Stated preferences, Value of a statistical case |
| Date: | 2024–04–26 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-04436960&r= |
| By: | Dazhuo Wei |
| Abstract: | In this paper, I introduce a random attention span model (RAS) which uses stopping time to identify decision-makers' behavior under limited attention. Unlike many limited attention models, the RAS identifies preferences using time variation without any need for menu variation. In addition, the RAS allows the consideration set to be correlated with the preference. I also use the revealed preference theory that provides testable implications for observable choice probabilities. Then, I test the model and estimate the preference distribution using data from M-Turk experiments on choice behaviors that involve lotteries; there is general alignment with the distribution results from logit attention model. |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2405.11578&r= |
| By: | Pham, Hien |
| Abstract: | A monopolistic seller jointly designs allocation rules and (new) information about a pay-off relevant state to a buyer with private types. When the new information flips the ranking of willingness to pay across types, a screening menu of prices and threshold disclosures is optimal. Conversely, when its impact is marginal, bunching via a single posted price and threshold disclosure is (approximately) optimal. While information design expands the scope for random mechanisms to outperform their deterministic counterparts, its presence leads to an equivalence result regarding sequential versus. static screening. |
| Keywords: | mechanism design, information design, sequential screening, random mechanisms, bunching. |
| JEL: | D42 D82 D86 L15 |
| Date: | 2023–04–30 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:120989&r= |
| By: | Patrick Carlin; Shyam Raman; Kosali I. Simon; Ryan Sullivan; Coady Wing |
| Abstract: | This paper presents the results from a hypothetical set of questions related to mask-wearing behavior and opinions that were asked of a nationally representative sample of over 4, 000 participants in early 2022. Mask mandates were hotly debated in public discourse, and though much research exists on benefits of masks, there has been no research thus far on the distribution of perceived costs of compliance. As is common in economic research that aims to assess the value to society of non-market activities, we use survey valuation methods and ask how much participants would be willing to pay to be exempted from rules of mandatory community masking. The survey asks specifically about a 3 month exemption. We find that the majority of respondents (56%) are not willing to pay to be exempted from mandatory masking. However, the average person was willing to pay $525, and a small segment of the population (0.9%) stated they were willing to pay over $5, 000 to be exempted from the mandate. Younger respondents stated higher willingness to pay to avoid the mandate than older respondents. Combining our results with standard measures of the value of a statistical life, we estimate that a 3 month masking order was perceived as cost effective through willingness-to-pay questions only if at least 13, 333 lives were saved by the policy. |
| JEL: | H0 I0 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32349&r= |
| By: | Pranjal Rawat |
| Abstract: | In some markets, the visual appearance of a product matters a lot. This paper investigates consumer transactions from a major fashion retailer, focusing on consumer aesthetics. Pretrained multimodal models convert images and text descriptions into high-dimensional embeddings. The value of these embeddings is verified both empirically and by their ability to segment the product space. A discrete choice model is used to decompose the distinct drivers of consumer choice: price, visual aesthetics, descriptive details, and seasonal variations. Consumers are allowed to differ in their preferences over these factors, both through observed variation in demographics and allowing for unobserved types. Estimation and inference employ automatic differentiation and GPUs, making it scalable and portable. The model reveals significant differences in price sensitivity and aesthetic preferences across consumers. The model is validated by its ability to predict the relative success of new designs and purchase patterns. |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2405.10498&r= |
| By: | Wolter, Stefan C. (University of Bern); Zöllner, Thea (University of Bern) |
| Abstract: | Despite numerous measures intended to enhance gender equality, gender-specific study and career choices remain a persistent concern for policymakers and academics globally. We contribute to the literature on gendered career choices by focusing on explicitly stated parental preferences for their children’s occupations, using a large-scale randomized survey experiment with adults (N=5940) in Switzerland. The focus on parents (and hypothetical parents) is motivated by the observation that adolescents consistently mention their parents as the single most important factor influencing their career choices. The surveyed adults are presented with a realistic choice situation, in which their hypothetical daughter or son has been proposed two different training occupations. The pair of occupations presented to the adults is drawn from a random sample of 105 pairs of occupations, and the respondents are not informed about the gender distribution of the two occupations. Results show that adults are gender-neutral when advising a daughter but have a pronounced preference for male-dominated occupations when advising sons. Preferences are almost identical for parents and non-parents and across age cohorts of adults. |
| Keywords: | gender, occupational choice, career advice, vocational education |
| JEL: | J24 J16 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp16955&r= |
| By: | Radu Tanase; Ren\'e Algesheimer; Manuel S. Mariani |
| Abstract: | Addressing global challenges -- from public health to climate change -- often involves stimulating the large-scale adoption of new products or behaviors. Research traditions that focus on individual decision making suggest that achieving this objective requires better identifying the drivers of individual adoption choices. On the other hand, computational approaches rooted in complexity science focus on maximizing the propagation of a given product or behavior throughout social networks of interconnected adopters. The integration of these two perspectives -- although advocated by several research communities -- has remained elusive so far. Here we show how achieving this integration could inform seeding policies to facilitate the large-scale adoption of a given behavior or product. Drawing on complex contagion and discrete choice theories, we propose a method to estimate individual-level thresholds to adoption, and validate its predictive power in two choice experiments. By integrating the estimated thresholds into computational simulations, we show that state-of-the-art seeding methods for social influence maximization might be suboptimal if they neglect individual-level behavioral drivers, which can be corrected through the proposed experimental method. |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2405.13224&r= |
| By: | James G. MacKinnon (Queen's University); Morten Ørregaard Nielsen (Aarhus University); Matthew D. Webb (Carleton University) |
| Abstract: | We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but also the most computationally demanding, involves jackknifing at the cluster level. We also propose a linearized version of the cluster-jackknife variance matrix estimator as well as linearized versions of the wild cluster bootstrap. The linearizations are based on empirical scores and are computationally efficient. Throughout we use the logit model as a leading example. We also discuss a new Stata software package called logitjack which implements these procedures. Simulation results strongly favor the new methods, and two empirical examples suggest that it can be important to use them in practice. |
| Keywords: | logit model, logistic regression, clustered data, grouped data, cluster-robust variance estimator, CRVE, cluster jackknife, robust inference, wild cluster bootstrap, linearization |
| JEL: | C12 C15 C21 C23 |
| Date: | 2024–05 |
| URL: | https://d.repec.org/n?u=RePEc:qed:wpaper:1515&r= |
| By: | Rainald Borck (University of Potsdam, CESifo, CEPA); Peter Mulder (Netherlands Organization for Applied Scientific Research (TNO), Utrecht University) |
| Abstract: | We study the effect of energy and transport policies on pollution in two developing country cities. We use a quantitative equilibrium model with choice of housing, energy use, residential location, transport mode, and energy technology. Pollution comes from commuting and residential energy use. The model parameters are calibrated to replicate key variables for two developing country cities, Maputo, Mozambique, and Yogyakarta, Indonesia. In the counterfactual simulations, we study how various transport and energy policies affect equilibrium pollution. Policies may be induce rebound effects from increasing residential energy use or switching to high emission modes or locations. In general, these rebound effects tend to be largest for subsidies to public transport or modern residential energy technology. |
| Keywords: | pollution, energy policy, discrete choice, developing country cities |
| JEL: | Q53 Q54 R48 |
| Date: | 2024–05 |
| URL: | https://d.repec.org/n?u=RePEc:pot:cepadp:78&r= |
| By: | Yutaro Akita |
| Abstract: | This document presents a simple proof of Dekel (1986)'s representation theorem for betweenness preferences. The proof is based on the separation theorem. |
| Date: | 2024–05 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2405.11371&r= |
| By: | Sandro Ambuehl; Heidi C. Thysen |
| Abstract: | Good decision-making requires understanding the causal impact of our actions. Often, we only have access to correlational data that could stem from multiple causal mechanisms with divergent implications for choice. Our experiments comprehensively characterize choice when subjects face conflicting causal interpretations of such data. Behavior primarily reflects three types: following interpretations that make attractive promises, choosing cautiously, and assessing the fit of interpretations to the data. We characterize properties of interpretations that obscure bad fit to subjects. Preferences for more complex models are more common than those reflecting Occam’s razor. Implications extend to the Causal Narratives and Model Persuasion literatures. |
| JEL: | C91 D01 D83 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_11103&r= |
| By: | Okuyama, Suzuka |
| Abstract: | Existing studies on Behaviour-based price discrimination (BBPD) typically show that firms offer discounts to encourage consumers located middle of the line segment to switch in a duopoly model. However, in practice, some firms offer both this discount and a discount to encourage consumers with lower preferences for the product itself to buy at the same time. I introduce heterogeneity of consumer willingness to pay and relax the assumption that the market is fully covered. Then, there are three purchase histories: bought from a firm, bought from another firm, and bought nothing. I assume that the two firms offer three different prices according to the purchase histories under BBPD. In the second period, firms offer discounts not only for rival customers but also for customers who bought nothing. On the other hand, firms offer higher prices for consumers who purchase the same goods over two periods in the second period than in the first period. This paper shows that BBPD does not lower all prices in the second period and does not increase consumer surplus. |
| Keywords: | Behavior-based price discrimination, Hotelling model. |
| JEL: | D43 L13 |
| Date: | 2024–03–16 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:120949&r= |
| By: | Julius Schäper; Rainer Winkelmann |
| Abstract: | The paper introduces two estimators for the linear random effects panel data model with known heteroskedasticity. Examples where heteroskedasticity can be treated as given include panel regressions with averaged data, meta regressions and the linear probability model. While one estimator builds on the additive random effects assumption, the other, which is simpler to implement in standard software, assumes that the random effect is multiplied by the heteroskedastic standard deviation. Simulation results show that substantial efficiency gains can be realized with either of the two estimators, that they are robust against deviations from the assumed specification, and that the confidence interval coverage equals the nominal level if clustered standard errors are used. Efficiency gains are also evident in an illustrative meta-regression application estimating the effect of study design features on loss aversion coefficients. |
| Keywords: | Generalized least squares, linear probability model, meta regression |
| JEL: | C23 |
| Date: | 2024–05 |
| URL: | https://d.repec.org/n?u=RePEc:zur:econwp:445&r= |