Economics
New submissions
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New submissions for Thu, 16 May 24
- [1] arXiv:2405.09023 [pdf, other]
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Title: The Rise of Recommerce: Ownership and Sustainability with Overlapping GenerationsSubjects: General Economics (econ.GN)
The emergence of the branded recommerce channel - digitally enabled and branded marketplaces that facilitate purchasing pre-owned items directly from a manufacturer's e-commerce site - leads to new variants of classic IS and economic questions relating to secondary markets. Such branded recommerce is increasingly platform-enabled, creating opportunities for greater sustainability and stronger brand experience control but posing a greater risk of cannibalization of the sales of new items. We model the effects that the sales of pre-owned items have on market segmentation and product durability choices for a monopolist facing heterogeneous customers, contrasting outcomes when the trade of pre-owned goods takes place through a third-party marketplace with outcomes under branded recommerce. We show that the direct revenue benefits of branded recommerce are not their primary source of value to the monopolist, and rather, there are three indirect effects that alter profits and sustainability. Product durability increases, a seller finds it optimal to forgo marketplace fees altogether, and there are greater seller incentives to lower the quality uncertainty associated with pre-owned items. We establish these results for a simple two-period model as well as developing a new infinite horizon model with overlapping generations. Our paper sheds new insight into this emerging digital channel phenomenon, underscoring the importance of recommerce platforms in aligning seller profits with sustainability goals.
- [2] arXiv:2405.09087 [pdf, ps, other]
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Title: The Nature of Transaction Cost: Eliminating Misunderstandings and Reconstructing CognitionAuthors: Li MingqianSubjects: Theoretical Economics (econ.TH)
The connotation of transaction costs has never been definitively determined, and the independence of the concept has never been rigorously demonstrated. This paper delves into the thought systems of several prominent economists in the development of transaction cost economics, starting from first-hand materials. By combining multiple works of the authors, it reconstructs the true meanings and identifies endogeneity issues and logical inconsistencies. The conclusion of this paper is bold. Previous research has been largely filled with misinterpretations and misunderstandings, as people have focused solely on the wording of transaction cost definitions, neglecting the nature of transaction costs. The intention of transaction cost theory has been unwittingly assimilated into the objects it intends to criticize. After delineating the framework of "transaction costs-property rights-competition", this paper reconstructs the concept of transaction costs and the history of transaction cost concepts, providing a direct response to this theoretical puzzle that has plagued the academic community for nearly a century.
- [3] arXiv:2405.09161 [pdf, ps, other]
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Title: Exploring the Potential of Large Language Models for Automation in Technical Customer ServiceJournal-ref: Proceedings of the Spring Servitization Conference (SSC2024)Subjects: General Economics (econ.GN)
Purpose: The purpose of this study is to investigate the potential of Large Language Models (LLMs) in transforming technical customer service (TCS) through the automation of cognitive tasks. Design/Methodology/Approach: Using a prototyping approach, the research assesses the feasibility of automating cognitive tasks in TCS with LLMs, employing real-world technical incident data from a Swiss telecommunications operator. Findings: Lower-level cognitive tasks such as translation, summarization, and content generation can be effectively automated with LLMs like GPT-4, while higher-level tasks such as reasoning require more advanced technological approaches such as Retrieval-Augmented Generation (RAG) or finetuning ; furthermore, the study underscores the significance of data ecosystems in enabling more complex cognitive tasks by fostering data sharing among various actors involved. Originality/Value: This study contributes to the emerging theory on LLM potential and technical feasibility in service management, providing concrete insights for operators of TCS units and highlighting the need for further research to address limitations and validate the applicability of LLMs across different domains.
- [4] arXiv:2405.09500 [pdf, ps, other]
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Title: Identifying Heterogeneous Decision Rules From Choices When Menus Are UnobservedSubjects: Theoretical Economics (econ.TH); Econometrics (econ.EM); Statistics Theory (math.ST)
Given only aggregate choice data and limited information about how menus are distributed across the population, we describe what can be inferred robustly about the distribution of preferences (or more general decision rules). We strengthen and generalize existing results on such identification and provide an alternative analytical approach to study the problem. We show further that our model and results are applicable, after suitable reinterpretation, to other contexts. One application is to the robust identification of the distribution of updating rules given only the population distribution of beliefs and limited information about heterogeneous information sources.
- [5] arXiv:2405.09509 [pdf, other]
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Title: Double Robustness of Local Projections and Some Unpleasant VARithmeticSubjects: Econometrics (econ.EM)
We consider impulse response inference in a locally misspecified stationary vector autoregression (VAR) model. The conventional local projection (LP) confidence interval has correct coverage even when the misspecification is so large that it can be detected with probability approaching 1. This follows from a "double robustness" property analogous to that of modern estimators for partially linear regressions. In contrast, VAR confidence intervals dramatically undercover even for misspecification so small that it is difficult to detect statistically and cannot be ruled out based on economic theory. This is because of a "no free lunch" result for VARs: the worst-case bias and coverage distortion are small if, and only if, the variance is close to that of LP. While VAR coverage can be restored by using a bias-aware critical value or a large lag length, the resulting confidence interval tends to be at least as wide as the LP interval.
Cross-lists for Thu, 16 May 24
- [6] arXiv:2405.09360 (cross-list from cs.LG) [pdf, other]
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Title: The Unfairness of $\varepsilon$-FairnessSubjects: Machine Learning (cs.LG); Theoretical Economics (econ.TH); Mathematical Finance (q-fin.MF); Machine Learning (stat.ML)
Fairness in decision-making processes is often quantified using probabilistic metrics. However, these metrics may not fully capture the real-world consequences of unfairness. In this article, we adopt a utility-based approach to more accurately measure the real-world impacts of decision-making process. In particular, we show that if the concept of $\varepsilon$-fairness is employed, it can possibly lead to outcomes that are maximally unfair in the real-world context. Additionally, we address the common issue of unavailable data on false negatives by proposing a reduced setting that still captures essential fairness considerations. We illustrate our findings with two real-world examples: college admissions and credit risk assessment. Our analysis reveals that while traditional probability-based evaluations might suggest fairness, a utility-based approach uncovers the necessary actions to truly achieve equality. For instance, in the college admission case, we find that enhancing completion rates is crucial for ensuring fairness. Summarizing, this paper highlights the importance of considering the real-world context when evaluating fairness.
Replacements for Thu, 16 May 24
- [7] arXiv:2009.11689 (replaced) [pdf, ps, other]
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Title: A characterization of absorbing sets in coalition formation gamesSubjects: Theoretical Economics (econ.TH); Computer Science and Game Theory (cs.GT)
- [8] arXiv:2307.11127 (replaced) [pdf, other]
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Title: Asymptotically Unbiased Synthetic Control Methods by Distribution MatchingComments: This study was presented at the Workshop on Counterfactuals in Minds and Machines at the International Conference on Machine Learning in July 2023 and at the International Conference on Econometrics and Statistics in August 2023Subjects: Econometrics (econ.EM); Machine Learning (cs.LG); Methodology (stat.ME)
- [9] arXiv:2310.09105 (replaced) [pdf, other]
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Title: Estimating Individual Responses when Tomorrow MattersSubjects: Econometrics (econ.EM)
- [10] arXiv:2312.08174 (replaced) [pdf, other]
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Title: Double Machine Learning for Static Panel Models with Fixed EffectsSubjects: Econometrics (econ.EM); Machine Learning (cs.LG); Machine Learning (stat.ML)
- [11] arXiv:2402.01766 (replaced) [pdf, other]
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Title: LLM Voting: Human Choices and AI Collective Decision MakingComments: Submitted to AIES2024Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Machine Learning (cs.LG); General Economics (econ.GN)
- [12] arXiv:2403.11240 (replaced) [pdf, other]
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Title: Speed, Accuracy, and ComplexityAuthors: Duarte GonçalvesSubjects: Theoretical Economics (econ.TH)
- [13] arXiv:2404.16061 (replaced) [pdf, ps, other]
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Title: Dynamic Many Valued Logic Systems in Theoretical EconomicsAuthors: Daniel LuSubjects: Logic in Computer Science (cs.LO); Theoretical Economics (econ.TH)
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