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on Discrete Choice Models |
| By: | Lee, Yunkyung |
| Keywords: | Marketing |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:360861 |
| By: | Hadziomerspahic, Amila; Kolstoe, Sonja H.; Dundas, Steven J. |
| Abstract: | Nonmarket valuation surveys are designed to ask the who, what, when, where and why for a population of interest to understand preferences for environmental goods. Recent declines in survey response rates and high costs associated with traditional survey modes (e.g., mail), along with recent advances in online sampling have led to increased use of non probability sample frames. This raises an important question for stated preference surveys about potential differences in willingness to pay (WTP) based on data collected by probability versus nonprobability samples. We develop a layered, sequential approach to test whether data processing and adjustments to estimation strategies can lead to similar welfare distributions for nonmarket attributes. Using a survey on the protection of safe recreation hours at ocean beaches, we find that our proposed process decreases the variance of marginal WTP for the non-probability sample and produces WTP distributions that overlap with the probability sample for our key attribute of interest. |
| Keywords: | Environmental Economics and Policy, Research Methods/ Statistical Methods |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:nceewp:388974 |
| By: | De Marchi, Elisa |
| Keywords: | Institutional and Behavioral Economics |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:360713 |
| By: | Nam, Hosung; Landry, Craig E. |
| Keywords: | Environmental Economics and Policy |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:360800 |
| By: | Fabien Giauque; Mehdi Farsi |
| Abstract: | Dynamic social norms have been recognized as a promising approach to promote energy sufficiency. By highlighting trends and future shifts rather than current states, dynamic norms allow for a better focus on emerging norms that are not widely adopted. While existing studies predominantly examine behavioral outcomes, the underlying processes and trade-offs remain to be explored. This paper uses a discrete choice experiment (DCE) combined with a randomized controlled trial to study electricity saving preferences under various dynamic norms. An emphasis is placed on the rationale for the norm changes. The results show that dynamic norms framed in terms of growing concerns about energy supply security positively affect electricity saving goal, whereas those framed around climate change do not. The heterogeneity analyses suggest that dynamic norms shape behavior through two complementary mechanisms: they generate new preferences while simultaneously reinforcing existing ones. The concluding analysis identifies four distinct groups that vary systematically in their preferences for electricity sufficiency. |
| Keywords: | Electricity saving; Dynamic Norms; Energy supply security; Climate change; Discrete choice experiment; Latent Class Model; Mixed Logit Model; Value-Belief-Norm Theory |
| JEL: | D12 D91 Q48 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:irn:wpaper:25-09 |
| By: | Dipankar Das |
| Abstract: | This paper presents the Sequential Rationality Hypothesis, which argues that consumers are better able to make utility-maximizing decisions when products appear in sequential pairwise comparisons rather than in simultaneous multi-option displays. Although this involves higher cognitive costs than the all-at-once format, the current digital market, with its diverse products listed by review ratings, pricing, and paid products, often creates inconsistent choices. The present work shows that preparing the list sequentially supports more rational choice, as the consumer tries to minimize cognitive costs and may otherwise make an irrational decision. If the decision remains the same on both offers, then that is a consistent preference. The platform uses this approach by reducing cognitive costs while still providing the list in an all-at-once format rather than sequentially. To show how sequential exposure reduces cognitive overload and prevents context-dependent errors, we develop a bounded attention model and extend the monotonic attention rule of the random attention model to theorize the sequential rational hypothesis. Using a theoretical design with common consumer goods, we test these hypotheses. This theoretical model helps policymakers in digital market laws, behavioral economics, marketing, and digital platform design consider how choice architectures may improve consumer choices and encourage rational decision-making. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.15332 |
| By: | Rapha\"el Langevin |
| Abstract: | Finite mixture models are widely used in econometric analyses to capture unobserved heterogeneity. This paper shows that maximum likelihood estimation of finite mixtures of parametric densities can suffer from substantial finite-sample bias in all parameters under mild regularity conditions. The bias arises from the influence of outliers in component densities with unbounded or large support and increases with the degree of overlap among mixture components. I show that maximizing the classification-mixture likelihood function, equipped with a consistent classifier, yields parameter estimates that are less biased than those obtained by standard maximum likelihood estimation (MLE). I then derive the asymptotic distribution of the resulting estimator and provide conditions under which oracle efficiency is achieved. Monte Carlo simulations show that conventional mixture MLE exhibits pronounced finite-sample bias, which diminishes as the sample size or the statistical distance between component densities tends to infinity. The simulations further show that the proposed estimation strategy generally outperforms standard MLE in finite samples in terms of both bias and mean squared errors under relatively weak assumptions. An empirical application to latent group panel structures using health administrative data shows that the proposed approach reduces out-of-sample prediction error by approximately 17.6% relative to the best results obtained from standard MLE procedures. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.20197 |
| By: | Zhang, Qi; Etienne, Xiaoli |
| Keywords: | Marketing |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:360860 |
| By: | Xin Liu; Luciano de Castro; Antonio F. Galvao |
| Abstract: | This paper suggests methods for estimation of the $\tau$-quantile, $\tau\in(0, 1)$, as a parameter along with the other finite-dimensional parameters identified by general conditional quantile restrictions. We employ a generalized method of moments framework allowing for non-linearities and dependent data, where moment functions are smoothed to aid both computation and tractability. Consistency and asymptotic normality of the estimators are established under weak assumptions. Simulations illustrate the finite-sample properties of the methods. An empirical application using a quantile intertemporal consumption model with multiple assets estimates the risk attitude, which is captured by $\tau$, together with the elasticity of intertemporal substitution. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.20853 |
| By: | Peter J. Hammond |
| Abstract: | In normative models a decision-maker is usually assumed to be Bayesian rational, and so to maximize subjective expected utility, within a complete and correctly specified decision model. Following the discussion in Hammond (2007) of Schumpeter's (1911, 1934) concept of entrepreneurship, as well as Shackle's (1953) concept of potential surprise, we consider enlivened decision trees whose growth over time cannot be accurately modelled in full detail. An enlivened decision tree involves more severe limitations than a mis-specified model, unforeseen contingencies, or unawareness, all of which are typically modelled with reference to a universal state space large enough to encompass any decision model that an agent may consider. We consider a motivating example based on Homer's classic tale of Odysseus and the Sirens. Though our novel framework transcends standard notions of risk or uncertainty, for finite decision trees that may be truncated because of bounded rationality, an extended and refined form of Bayesian rationality is still possible, with real-valued subjective evaluations instead of consequences attached to terminal nodes where truncations occur. Moreover, these subjective evaluations underlie, for example, the kind of Monte Carlo tree search algorithm used by recent chess-playing software packages. They may also help rationalize the contentious precautionary principle. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.06405 |
| By: | Collin Raymond; Yangwei Song |
| Abstract: | We extend well-known comparative results under expected utility to models of non-expected utility by providing novel conditions on local utility functions. We illustrate how our results parallel, and are distinct from, existing results for monotone comparative statics under expected utility, as well as risk preferences for non-expected utility. Our conditions generalize existing results for specific preferences (including expected utility) and allow us to verify monotone comparative statics for novel environments and preferences. We apply our results to portfolio choice problems where preferences or wealth might change, as well as precautionary savings. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.10664 |