|
on Discrete Choice Models |
| By: | Stefano Carattini; Fabian Dvorak; Ivana Logar; Begum Ozdemir-Oluk |
| Abstract: | Corporate social responsibility and the private provision of (global) public goods are of key interest to economists and policymakers. Over the last few years, many more private companies made their operations carbon neutral. It is an empirical question how consumers value carbon-neutral and low-carbon products, which we address as follows. First, we provide a meta-analysis of the literature. We analyze consumers’ demand for carbon-neutral and low-carbon products, based on an overall sample of 29, 666 participants. The focus is on average willingness to pay for carbon reductions as well as on the characteristics of the underlying literature, which is mainly based on stated preferences and controlled environments. Second, we leverage information on prices and product characteristics from one of the largest online marketplaces, Amazon’s. Using a hedonic approach, we infer from revealed preferences on consumers’ valuation of carbon- neutral products. The staggered process of carbon-neutral certification leads to a series of quasi-natural experiments, which we use for identification purposes. We find that the literature suggests a positive willingness to pay for carbon reductions that exceeds most estimates of the social cost of carbon. However, this finding is not supported by the hedonic analyses, where we do not find evidence that consumers value carbon neutrality. |
| Keywords: | corporate social responsibility, pro-social behavior, stated and revealed preferences, meta-analysis, hedonic analysis, carbon-neutral labels |
| JEL: | D12 D22 H41 Q51 Q54 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12232 |
| By: | Carmelo Rodríguez à lvarez (Instituto Complutense de Análisis Económico (ICAE), Universidad Complutense de Madrid (Spain)) |
| Abstract: | We consider strategy-proof social choice correspondences (SCCs) –mappings from preference profiles to sets of alternatives– when individuals are endowed with single-peaked preferences over alternatives. We interpret the selected sets of alternatives as the basis for lotteries that determine the final social choice, and consider that agents’ preferences over sets are consistent with Expected Utility Theory and Bayesian updating from an initial probability assessment over the full set of alternatives. We exploit the relation between SCCs and probabilistic decision schemes –mappings from preference profiles to lotteries over alternatives–, to characterize the family of SCCs that satisfy strategy-proofness and unanimity for arbitrary initial probability assessments. We extend the analysis to multi-dimensional convex spaces of alternatives under the uniform initial probability assessment. |
| Keywords: | Strategy-Proofness; Single-Peaked Preferences; Social Choice Correspondences. |
| JEL: | C71 D71 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ucm:doicae:2506 |
| By: | Jana Freundt; Holger Herz |
| Abstract: | We establish the existence of intrinsic preferences for choice autonomy, defined as a preference for own choice in the absence of any instrumental value of choice, in large general population samples in nine countries using a novel preference elicitation tool. We find that such preferences are widespread, but also reveal stark differences across countries. Within countries, individuals who place a higher value on self-reliance and personal identity exhibit stronger intrinsic preferences for choice autonomy. In our small cross-country sample, we find suggestive evidence that differences are correlated with power distance, but not with measures of individualism, and that differences are predictive of managerial decentralization across countries. |
| Keywords: | autonomy, individualism, preferences, culture |
| JEL: | D01 D9 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12238 |
| By: | Kevin Zielnicki; Guy Aridor; Aur\'elien Bibaut; Allen Tran; Winston Chou; Nathan Kallus |
| Abstract: | Personalized recommendation systems shape much of user choice online, yet their targeted nature makes separating out the value of recommendation and the underlying goods challenging. We build a discrete choice model that embeds recommendation-induced utility, low-rank heterogeneity, and flexible state dependence and apply the model to viewership data at Netflix. We exploit idiosyncratic variation introduced by the recommendation algorithm to identify and separately value these components as well as to recover model-free diversion ratios that we can use to validate our structural model. We use the model to evaluate counterfactuals that quantify the incremental engagement generated by personalized recommendations. First, we show that replacing the current recommender system with a matrix factorization or popularity-based algorithm would lead to 4% and 12% reduction in engagement, respectively, and decreased consumption diversity. Second, most of the consumption increase from recommendations comes from effective targeting, not mechanical exposure, with the largest gains for mid-popularity goods (as opposed to broadly appealing or very niche goods). |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.07280 |
| By: | Kevin Zielnicki; Guy Aridor; Aurelien Bibaut; Allen Tran; Winston Chou; Nathan Kallus |
| Abstract: | Personalized recommendation systems shape much of user choice online, yet their targeted nature makes separating out the value of recommendation and the underlying goods challenging. We build a discrete choice model that embeds recommendation-induced utility, low-rank heterogeneity, and flexible state dependence and apply the model to viewership data at Netflix. We exploit idiosyncratic variation introduced by the recommendation algorithm to identify and separately value these components as well as to recover model-free diversion ratios that we can use to validate our structural model. We use the model to evaluate counterfactuals that quantify the incremental engagement generated by personalized recommendations. First, we show that replacing the current recommender system with a matrix factorization or popularity-based algorithm would lead to 4% and 12% reduction in engagement, respectively, and decreased consumption diversity. Second, most of the consumption increase from recommendations comes from effective targeting, not mechanical exposure, with the largest gains for mid-popularity goods (as opposed to broadly appealing or very niche goods). |
| Keywords: | personalization, recommender systems, streaming platforms |
| JEL: | L82 C25 D83 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12257 |
| By: | Agnieszka Zalejska-Jonsson; Sara Wilkinson |
| Abstract: | Urbanization has significantly altered land use, reducing natural habitats and exacerbating environmental issues such as increased temperatures, altered water cycles, and poor air quality. The study investigates whether and how buyers perceive greenery in housing developments, the impact of green infrastructure on consumer interest, and the potential financial benefits of investing in sustainable residential designs. The study builds upon research in consumer behavior, urban planning, and real estate economics to explore property buyers’ preferences. The study employed an experimental design embedded within a survey to test the effect of green infrastructure on buyers’ interest. Five courtyard designs with varying levels of greenery were developed in collaboration with landscape architects. These were visualized using 3D modeling techniques and virtual reality tools, allowing participants to explore different courtyard layouts. Respondents were randomly assigned one of the five courtyard scenarios and asked to evaluate its attractiveness and their interest in purchasing an apartment in the development. Data was collected from 922 participants in Sweden and 614 in Australia using structured online surveys. The analysis utilized structural equation modeling (SEM) to assess relationships between courtyard greenery, attractiveness, and purchasing interest. The study concludes that green infrastructure plays a significant role in shaping buyers' perceptions of residential developments. Findings indicate that greener courtyards enhance property attractiveness, social engagement, and environmental benefits, leading to increased willingness to pay. Additionally, study reflects how cultural and environmental contexts shape buyers’ perceptions of green spaces, compering results obtained in Sweden and Australia. The study’s experimental approach provides a novel methodology for evaluating the economic and psychological effects of greenery in residential developments |
| Keywords: | buyers perception; Green Infrastructure; housing; sustainable cities |
| JEL: | R3 |
| Date: | 2025–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:arz:wpaper:eres2025_230 |
| By: | Bruno Felipe de Oliveira; Alessandro V. M. Oliveira |
| Abstract: | This paper aims to discuss the impacts of low-cost airlines on the air transport market and, in particular, to present the most recent findings from the specialized literature in this field. To this end, several papers published on the topic since 2015 were selected and analyzed. Based on this analysis, the main subjects addressed in the studies were categorized into five groups: (i) impacts of low-cost airlines on competing carriers; (ii) impacts on airports; (iii) general effects on air transport demand; (iv) effects on passengers' choice processes; and (v) broader effects on geographical regions. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.00932 |
| By: | Yiqi Liu |
| Abstract: | Popular empirical strategies for policy evaluation in the panel data literature -- including difference-in-differences (DID), synthetic control (SC) methods, and their variants -- rely on key identifying assumptions that can be expressed through a specific choice of weights $\omega$ relating pre-treatment trends to the counterfactual outcome. While each choice of $\omega$ may be defensible in empirical contexts that motivate a particular method, it relies on fundamentally untestable and often fragile assumptions. I develop an identification framework that allows for all weights satisfying a Synthetic Parallel Trends assumption: the treated unit's trend is parallel to a weighted combination of control units' trends for a general class of weights. The framework nests these existing methods as special cases and is by construction robust to violations of their respective assumptions. I construct a valid confidence set for the identified set of the treatment effect, which admits a linear programming representation with estimated coefficients and nuisance parameters that are profiled out. In simulations where the assumptions underlying DID or SC-based methods are violated, the proposed confidence set remains robust and attains nominal coverage, while existing methods suffer severe undercoverage. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.05870 |
| By: | Ali Mehrabani (Department of Economics, University of Kansas, Lawrence, KS 66045); Shahnaz Parsaeian (Department of Economics, University of Kansas, Lawrence, KS 66045) |
| Abstract: | This paper provides a framework for joint shrinkage estimation and identification of latent group structures in panel data models with interactive fixed effects and large number of explanatory variables. The latent structure of the model allows individuals to be classified into a number of groups where the number of groups and/or each individual’s group identity are unknown. A doubly penalized principal component estimation procedure using a pairwise fusion penalty and an adaptive LASSO (least absolute shrinkage and selection operator) penalty is introduced to detect the latent group structure and select the relevant regressors. To implement the proposed approach, an alternating direction method of multipliers algorithm has been developed. The proposed method is further illustrated by simulation studies and an empirical application of economic growth across various countries which demonstrate the good performance of the method. |
| Keywords: | ADMM algorithm, high dimensionality, interactive fixed effects, pairwise adaptive group fused LASSO, parameter heterogeneity, principal component analysis. |
| JEL: | C33 C38 C51 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:kan:wpaper:202516 |
| By: | Ewa Cukrowska-Torzewska (Interdisciplinary Centre for Labour Market and Family Dynamics (LabFam), Faculty of Economic Sciences, University of Warsaw); Anna Matysiak (Interdisciplinary Centre for Labour Market and Family Dynamics (LabFam), Faculty of Economic Sciences, University of Warsaw); Agnieszka Kasperska (Interdisciplinary Centre for Labour Market and Family Dynamics (LabFam), Faculty of Economic Sciences, University of Warsaw); Gayle Kaufman (Davidson College) |
| Abstract: | This study provides causal evidence on the hiring and pay penalties associated with taking parental leave of varying lengths. We investigate how deviations from prevailing social norms, in the form of non-standard leave-taking behavior by mothers and fathers, affect their employment outcomes. We also compare the parental leave penalties with those linked to unemployment to disentangle the determinants of these penalties and to identify the mechanisms through which they operate. To this end, we conducted a discrete choice experiment with 997 managers, who evaluated hypothetical job candidates differing in the length of employment interruptions due to parental leave. Using a conditional logit model, we find that both mothers and fathers face disadvantages in hiring and remuneration when taking longer parental leave. Notably, fathers are penalized for taking any parental leave, though the penalties are more severe for longer leave. These poorer employability prospects stem from managers perceiving such fathers as less available for work. Meanwhile, mothers receive hiring and pay bonuses for taking shorter leaves, stemming from employer perceptions of such mothers as more available, competent, and motivated. |
| Keywords: | Energy parental leave, family policies, employment, wages, gender norms, ideal worker norms |
| JEL: | J13 J16 J22 J31 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:war:wpaper:2025-27 |
| By: | Julia Baarck; Mathias Dolls; Lisa Windsteiger |
| Abstract: | This study investigates how information about intergenerational and intragenerational inequality shapes fairness views and policy preferences. Using a large-scale randomized survey experiment with 4, 900 respondents in Germany, we test how exposure to information on wealth and age disparities affects (i) perceptions of distributive and intergenerational fairness, and (ii) support for redistributive and future-oriented policies. We find that respondents generally underestimate existing inequalities. Moreover, providing accurate information about the extent of age and wealth disparities has little impact on left-leaning and centrist individuals but elicits a backlash among right-leaning respondents: the information increases their perceived fairness of the status quo and lowers their support for redistributive and future-oriented measures. We attribute these counterintuitive responses to skepticism about the credibility and neutrality of the provided information. Overall, the findings highlight the limits of informational interventions and the potential for factual communication to backfire in politically polarized contexts. |
| Keywords: | fairness views, inequality, policy preferences, survey experiment |
| JEL: | D63 D72 J48 D83 D91 H23 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12234 |
| By: | Felipe Valencia-Clavijo |
| Abstract: | Large language models (LLMs) are increasingly examined as both behavioral subjects and decision systems, yet it remains unclear whether observed cognitive biases reflect surface imitation or deeper probability shifts. Anchoring bias, a classic human judgment bias, offers a critical test case. While prior work shows LLMs exhibit anchoring, most evidence relies on surface-level outputs, leaving internal mechanisms and attributional contributions unexplored. This paper advances the study of anchoring in LLMs through three contributions: (1) a log-probability-based behavioral analysis showing that anchors shift entire output distributions, with controls for training-data contamination; (2) exact Shapley-value attribution over structured prompt fields to quantify anchor influence on model log-probabilities; and (3) a unified Anchoring Bias Sensitivity Score integrating behavioral and attributional evidence across six open-source models. Results reveal robust anchoring effects in Gemma-2B, Phi-2, and Llama-2-7B, with attribution signaling that the anchors influence reweighting. Smaller models such as GPT-2, Falcon-RW-1B, and GPT-Neo-125M show variability, suggesting scale may modulate sensitivity. Attributional effects, however, vary across prompt designs, underscoring fragility in treating LLMs as human substitutes. The findings demonstrate that anchoring bias in LLMs is robust, measurable, and interpretable, while highlighting risks in applied domains. More broadly, the framework bridges behavioral science, LLM safety, and interpretability, offering a reproducible path for evaluating other cognitive biases in LLMs. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.05766 |
| By: | Arrora. Falak (University of Warwick) |
| Abstract: | How does the presence of fake news affect incentives to acquire legitimate information? I study a model of costly information acquisition where either an honest or a fake sender communicates with a receiver through a platform. The honest sender sends a true but noisy signal, whereas the fake sender sends a false and uninformative signal. The platform can verify the signal’s authenticity; however, it faces a tradeoff. Fake news, although harmful for the receiver, makes her more skeptical and increases the honest sender’s incentives for acquiring more precise information. The platform commits to a policy that indicates the screening probability and a disclosure rule. My central finding is that the screening policy that maximizes the receiver’s welfare often requires tolerating fake news, even when such screening is costless. Moreover, not informing the receiver even when a message has been screened and found to be true is sometimes better than full transparency because it keeps the receiver skeptical.These findings suggest that complete moderation and fact-checking of content may inadvertently leave the receiver worse off. |
| Keywords: | Information acquisition ; communication game ; fake news ; platforms ; fact-checking JEL Codes: C72 ; D82 ; D83 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:wrk:warwec:1586 |
| By: | Susanne Schennach; Vincent Starck |
| Abstract: | We propose a novel optimal transport-based version of the Generalized Method of Moment (GMM). Instead of handling overidentification by reweighting the data to satisfy the moment conditions (as in Generalized Empirical Likelihood methods), this method proceeds by allowing for errors in the variables of the least mean-square magnitude necessary to simultaneously satisfy all moment conditions. This approach, based on the notions of optimal transport and Wasserstein metric, aims to address the problem of assigning a logical interpretation to GMM results even when overidentification tests reject the null, a situation that cannot always be avoided in applications. We illustrate the method by revisiting Duranton, Morrow and Turner's (2014) study of the relationship between a city's exports and the extent of its transportation infrastructure. Our results corroborate theirs under weaker assumptions and provide insight into the error structure of the variables. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.05712 |
| By: | Davide Luparello |
| Abstract: | Contract workers constitute half of employment in India’s automotive industry but earn substantially less than permanent workers. Using data from the Annual Survey of Industries (2002-2019), I develop an estimator of labor supply and demand schedules to explain this wage premium. The model features nested CES production with distinct worker types, discrete choice supply functions with worker type-specific wage sensitivity and differentiated market conduct—Nash-Bertrand competition for contract workers versus plant-level union bargaining for permanent workers. I find that the wage premium stems entirely from permanent workers’ higher productivity rather than differential monopsony power or unionization advantages. |
| Keywords: | Markdowns, Markups, Productivity, India |
| JEL: | L11 L13 L62 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:baf:cbafwp:cbafwp25258 |