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on Discrete Choice Models |
By: | Ellen Sterk (RWTH Aachen University) |
Abstract: | The construction industry claims a vast quantity of natural resources and is responsible for more than half of the waste generated in Germany. R-concrete contains recycled aggregates and is a resource efficient alternative to primary concrete. A central stakeholder whose preferences may significantly influence the use of R-concrete is the construction client. Despite their central role in this respect, little is known about clients. This study contributes to the understanding of the clients’ demand decision. It determines the willingness to pay (WTP) for recycled aggregates and it examines which factors influence clients’ propensity to choose R-concrete. Additionally, the study identifies barriers and drivers for the demand for R-concrete. Throughout these questions, differences between client groups are considered. In addition to item-based questions on potential barriers and drivers, a discrete choice experiment is applied to estimate the clients’ WTP for a certain share of recycled aggregates in concrete. Positive and significant WTP estimates were found for all client groups. Overall, clients are willing to pay 0.26 € for every percentage point increase of added recycled aggregates. Private individuals’ WTP is lowest, while organizations are willing to pay most. However, even organizations’ WTP does not equal the price premium currently seen. The main barriers for demanding R-concrete are based on a lack of information. Therefore, in order to foster the use of R-concrete, instruments that rely on information provision are recommended. Moreover, the significant differences in client groups should be considered in designing these instruments. |
Date: | 2023 |
URL: | http://d.repec.org/n?u=RePEc:mar:magkse:202311&r=dcm |
By: | Costa-Font, Joan; Harrison, S.; Rudisill, C.; Salmasi, L. |
Abstract: | SARS-CoV-2 vaccines give rise to positive externalities on population health, society and the economy in addition to protecting the health of vaccinated individuals. Hence, the social value of such a vaccine exceeds its market value. This paper estimates the willingness to pay (WTP) for a hypothetical SARS-CoV-2 vaccine (or shadow prices), in four countries, namely the United States (US), the United Kingdom (UK), Spain and Italy, during the rst wave of the pandemic when COVID-19 vaccines were in development but not yet approved. WTP estimates are elicited using a payment card method to avoid `yea saying' biases, and we study the effect of protest responses, sample selection bias, as well as the influence of trust in government and risk exposure when estimating the WTP. Our estimates suggest evidence of an average value of a hypothetical vaccine of 100-200 US dollars once adjusted by purchasing power parity (PPP). Estimates are robust to several checks. |
Keywords: | social value; willingness to pay; vaccine value; vaccine attitudes; payment card; sample selection; protest responses; positive externalities; COVID-19 Research Initiative; Office of the Vice President for Research; University of South Carolina; Wiley deal |
JEL: | H23 H42 I18 |
Date: | 2023–05–07 |
URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:118625&r=dcm |
By: | Ali Goli; Amandeep Singh |
Abstract: | Language has a strong influence on our perceptions of time and rewards. This raises the question of whether large language models, when asked in different languages, show different preferences for rewards over time and if their choices are similar to those of humans. In this study, we analyze the responses of GPT-3.5 (hereafter referred to as GPT) to prompts in multiple languages, exploring preferences between smaller, sooner rewards and larger, later rewards. Our results show that GPT displays greater patience when prompted in languages with weak future tense references (FTR), such as German and Mandarin, compared to languages with strong FTR, like English and French. These findings are consistent with existing literature and suggest a correlation between GPT's choices and the preferences of speakers of these languages. However, further analysis reveals that the preference for earlier or later rewards does not systematically change with reward gaps, indicating a lexicographic preference for earlier payments. While GPT may capture intriguing variations across languages, our findings indicate that the choices made by these models do not correspond to those of human decision-makers. |
Date: | 2023–05 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:2305.02531&r=dcm |
By: | Serge Blondel (GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement); Ngoc Thao NOET (GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement) |
Keywords: | public good (PG) game, Incentives, Hypothetical or real payment |
Date: | 2023–04–19 |
URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-04075049&r=dcm |
By: | Lars P. Feld; Ekkehard A. Köhler |
Abstract: | James Buchanan would have celebrated his 100th birthday in 2019. This serves as an inspiration to look at the future of public choice and the question of how much normativity public choice can bear. In our analysis we draw parallels between public choice and German ordoliberalism (and its source in the Freiburg School of Economics). We argue that the reception of ordoliberalism exemplifies easy-to-grasp pitfalls that should be taken seriously. We anchor the future agenda of public choice in a solid individualist perspective. Similar to ordoliberalism, public choice will have to clarify its relation to normative economics. The effects of rules and institutions and their working properties should be thoroughly analyzed empirically. The role of ideas is important for the normative foundation of both public choice/ constitutional economics and ordoliberalism, and is rooted in normative individualism. It provides a benchmark by which rules and institutions can be judged as favorable. |
Keywords: | public choice, methodology, James Buchanan, normativity, individualism |
JEL: | B13 B26 B31 D78 E61 E63 |
Date: | 2023 |
URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10382&r=dcm |
By: | Minoru Kitahara; Yasunori Okumura |
Abstract: | We consider a school choice matching model where the priorities for schools are represented by binary relations that may not be weak order. We focus on the (total order) extensions of the binary relations. We introduce a class of algorithms to derive one of the extensions of a binary relation and characterize them by using the class. We show that if the binary relations are the partial orders, then for each stable matching for the profile of the binary relations, there is an extension for which it is also stable. Moreover, if there are multiple stable matchings for the profile of the binary relations that are ranked by Pareto dominance, there is an extension for which all of those matchings are stable. We provide several applications of these results. |
Date: | 2023–04 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:2305.00641&r=dcm |
By: | Gutierrez-Lythgoe, Antonio |
Abstract: | Research in the field of Artificial Intelligence has made considerable progress in recent years, demonstrating its effectiveness in predicting and classifying discrete decisions. However, these advances have been relatively underutilized in economic research due to the lack of links with economic theories that explain the decision-making process of agents. In this paper, we propose a microeconomic framework for decision trees, a machine learning technique, to establish a more solid connection with economic theory and encourage its application in the field of discrete choice. To do so, we rely on data from the 2019 EU-SILC for Spain. Through comparison with a conventional multinomial logit model, we demonstrate the usefulness of this economic perspective for studying the sociodemographic factors associated with self-employment in Spain. The results suggest that incorporating economic foundations can significantly improve the accuracy of predictions and the ability to draw individual sociodemographic profiles for self-employment. |
Keywords: | Artificial Intelligence; Machine Learning; Microeconomics; Self-employment; multinomial logit |
JEL: | C45 C53 J24 J62 L26 |
Date: | 2023–05 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:117275&r=dcm |