arXiv - ECON - General Economics最新文献

{"title":"Cognitive Hierarchy in Day-to-day Network Flow Dynamics","authors":"Minyu Shen, Feng Xiao, Weihua Gu, Hongbo Ye","doi":"arxiv-2409.11908","DOIUrl":"https://doi.org/arxiv-2409.11908","url":null,"abstract":"When making route decisions, travelers may engage in a certain degree of\u0000reasoning about what the others will do in the upcoming day, rendering\u0000yesterday's shortest routes less attractive. This phenomenon was manifested in\u0000a recent virtual experiment that mimicked travelers' repeated daily trip-making\u0000process. Unfortunately, prevailing day-to-day traffic dynamical models failed\u0000to faithfully reproduce the collected flow evolution data therein. To this end,\u0000we propose a day-to-day traffic behavior modeling framework based on the\u0000Cognitive Hierarchy theory, in which travelers with different levels of\u0000strategic-reasoning capabilities form their own beliefs about lower-step\u0000travelers' capabilities when choosing their routes. Two widely-studied\u0000day-to-day models, the Network Tatonnement Process dynamic and the Logit\u0000dynamic, are extended into the framework and studied as examples. Calibration\u0000of the virtual experiment is performed using the extended Network Tatonnement\u0000Process dynamic, which fits the experimental data reasonably well. We show that\u0000the two extended dynamics have multiple equilibria, one of which is the\u0000classical user equilibrium. While analyzing global stability is intractable due\u0000to the presence of multiple equilibria, local stabilities near equilibria are\u0000developed analytically and verified by numerical experiments. General insights\u0000on how key parameters affect the stability of user equilibria are unveiled.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"It depends: Varieties of defining growth dependence","authors":"Anja JanischewskiFaculty of Economics and Business Administration, Chemnitz University of Technology, Katharina BohnenbergerGerman Institute for Interdisciplinary Social Policy Research, University of Bremen, SOCIUM and Institute for Socio-Economics, University of Duisburg-Essen, Matthias KrankeFreiburg Institute for Advanced Studies, Tobias VogelDepartment for Philosophy, Politics and Economics, Faculty of Economy and Society, Witten/Herdecke University, Riwan DriouichInstitut de Ciència i Tecnologia Ambientals, Tobias FroeseChair for Corporate Sustainability, ESCP Business School, Stefanie GeroldInstitute of Philosophy and Social Science, Brandenburg University of Technology Cottbus-Senftenberg, Raphael KaufmannZOE Institute for Future-Fit Economies, Lorenz KeyßerInstitute of Geography and Sustainability, Faculty of Geosciences and Environment, University of Lausanne, Jannis NiethammerICLEI European Secretariat, Christopher OlkOtto Suhr Institute for Political Science, Freie Universität Berlin, Matthias SchmelzerNorbert-Elias-Center for Transformation Design and Research, University of Flensburg, Germany and Friedrich-Schiller-University Jena, Aslı YürükUrban Transformation and Global Change Laboratory, Steffen LangeCentre for Pluralist Economics, University of Siegen","doi":"arxiv-2409.12109","DOIUrl":"https://doi.org/arxiv-2409.12109","url":null,"abstract":"Many socio-economic systems require positive economic growth rates to\u0000function properly. Given uncertainty about future growth rates and increasing\u0000evidence that economic growth is a driver of social and environmental crises,\u0000these growth dependencies pose serious societal challenges. In recent years,\u0000more and more researchers have thus tried to identify growth-dependent systems\u0000and develop policies to reduce their growth dependence. However, the concept of\u0000'growth dependence' still lacks a consistent definition and operationalization,\u0000which impedes more systematic empirical and theoretical research. This article\u0000proposes a simple but powerful framework for defining and operationalizing the\u0000concept of 'growth dependence' across socio-economic systems. We provide a\u0000general definition consisting of four components that can be specified for\u0000different empirical cases: (1) the system under investigation, (2) the unit of\u0000measurement of growth, (3) the level of growth and (4) the relevant functions\u0000or properties of the system under investigation. According to our general\u0000definition, a socio-economic system is growth-dependent if it requires a\u0000long-term positive growth rate in terms of a unit of economic measurement to\u0000maintain all its functions or properties that are relevant within the chosen\u0000normative framework. To illustrate the usefulness of our scheme, we apply it to\u0000three areas at the heart of the existing literature on growth dependence:\u0000employment, social insurance systems and public finance. These case studies\u0000demonstrate that whether or not a system is growth-dependent hinges not only on\u0000the empirical properties of the system itself but also on the specification of\u0000the concept of growth dependence. Our framework enables coherent, robust and\u0000effective definitions and research questions, fostering comparability of\u0000findings across different cases and disciplines.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlocking NACE Classification Embeddings with OpenAI for Enhanced Analysis and Processing","authors":"Andrea Vidali, Nicola Jean, Giacomo Le Pera","doi":"arxiv-2409.11524","DOIUrl":"https://doi.org/arxiv-2409.11524","url":null,"abstract":"The Statistical Classification of Economic Activities in the European\u0000Community (NACE) is the standard classification system for the categorization\u0000of economic and industrial activities within the European Union. This paper\u0000proposes a novel approach to transform the NACE classification into\u0000low-dimensional embeddings, using state-of-the-art models and dimensionality\u0000reduction techniques. The primary challenge is the preservation of the\u0000hierarchical structure inherent within the original NACE classification while\u0000reducing the number of dimensions. To address this issue, we introduce custom\u0000metrics designed to quantify the retention of hierarchical relationships\u0000throughout the embedding and reduction processes. The evaluation of these\u0000metrics demonstrates the effectiveness of the proposed methodology in retaining\u0000the structural information essential for insightful analysis. This approach not\u0000only facilitates the visual exploration of economic activity relationships, but\u0000also increases the efficacy of downstream tasks, including clustering,\u0000classification, integration with other classifications, and others. Through\u0000experimental validation, the utility of our proposed framework in preserving\u0000hierarchical structures within the NACE classification is showcased, thereby\u0000providing a valuable tool for researchers and policymakers to understand and\u0000leverage any hierarchical data.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What Does ChatGPT Make of Historical Stock Returns? Extrapolation and Miscalibration in LLM Stock Return Forecasts","authors":"Shuaiyu Chen, T. Clifton Green, Huseyin Gulen, Dexin Zhou","doi":"arxiv-2409.11540","DOIUrl":"https://doi.org/arxiv-2409.11540","url":null,"abstract":"We examine how large language models (LLMs) interpret historical stock\u0000returns and compare their forecasts with estimates from a crowd-sourced\u0000platform for ranking stocks. While stock returns exhibit short-term reversals,\u0000LLM forecasts over-extrapolate, placing excessive weight on recent performance\u0000similar to humans. LLM forecasts appear optimistic relative to historical and\u0000future realized returns. When prompted for 80% confidence interval predictions,\u0000LLM responses are better calibrated than survey evidence but are pessimistic\u0000about outliers, leading to skewed forecast distributions. The findings suggest\u0000LLMs manifest common behavioral biases when forecasting expected returns but\u0000are better at gauging risks than humans.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How (Not) to Incentivize Sustainable Mobility? Lessons from a Swiss Mobility Competition","authors":"Silvio Sticher, Hannes Wallimann, Noah Balthasar","doi":"arxiv-2409.11142","DOIUrl":"https://doi.org/arxiv-2409.11142","url":null,"abstract":"We investigate the impact of a gamified experiment designed to promote\u0000sustainable mobility among students and staff members of a Swiss\u0000higher-education institution. Despite transportation being a major contributor\u0000to domestic CO2 emissions, achieving behavioral change remains challenging. In\u0000our two-month mobility competition, structured as a randomized controlled trial\u0000with a 3x3 factorial design, neither monetary incentives nor norm-based nudging\u0000significantly influences mobility behavior. Our (null) results suggest that\u0000there is no \"gamified quick fix\" for making mobility substantially more\u0000sustainable. Also, we provide some lessons learned on how not to incentivize\u0000sustainable mobility by addressing potential shortcomings of our mobility\u0000competition.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of Public Cash Transfer Programs on US Entrepreneurs' Financing Constraint","authors":"Liukun Wu","doi":"arxiv-2409.09955","DOIUrl":"https://doi.org/arxiv-2409.09955","url":null,"abstract":"In this paper, I conduct a policy exercise about how much the introduction of\u0000a cash transfer program as large as a Norwegian-sized lottery sector to the\u0000United States would affect startups. The key results are that public cash\u0000transfer programs (like lottery) do not increase much the number of new\u0000startups, but increase the size of startups, and only modestly increase\u0000aggregate productivity and output. The most important factor for entrepreneurs\u0000to start new businesses is their ability.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bitcoin Transaction Behavior Modeling Based on Balance Data","authors":"Yu Zhang, Claudio Tessone","doi":"arxiv-2409.10407","DOIUrl":"https://doi.org/arxiv-2409.10407","url":null,"abstract":"When analyzing Bitcoin users' balance distribution, we observed that it\u0000follows a log-normal pattern. Drawing parallels from the successful application\u0000of Gibrat's law of proportional growth in explaining city size and word\u0000frequency distributions, we tested whether the same principle could account for\u0000the log-normal distribution in Bitcoin balances. However, our calculations\u0000revealed that the exponent parameters in both the drift and variance terms\u0000deviate slightly from one. This suggests that Gibrat's proportional growth rule\u0000alone does not fully explain the log-normal distribution observed in Bitcoin\u0000users' balances. During our exploration, we discovered an intriguing\u0000phenomenon: Bitcoin users tend to fall into two distinct categories based on\u0000their behavior, which we refer to as ``poor\" and ``wealthy\" users. Poor users,\u0000who initially purchase only a small amount of Bitcoin, tend to buy more\u0000bitcoins first and then sell out all their holdings gradually over time. The\u0000certainty of selling all their coins is higher and higher with time. In\u0000contrast, wealthy users, who acquire a large amount of Bitcoin from the start,\u0000tend to sell off their holdings over time. The speed at which they sell their\u0000bitcoins is lower and lower over time and they will hold at least a small part\u0000of their initial holdings at last. Interestingly, the wealthier the user, the\u0000larger the proportion of their balance and the higher the certainty they tend\u0000to sell. This research provided an interesting perspective to explore bitcoin\u0000users' behaviors which may apply to other finance markets.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"101 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Market for Lemons? Strategic Directions for a Vigilant Application of Artificial Intelligence in Entrepreneurship Research","authors":"Martin Obschonka, Moren Levesque","doi":"arxiv-2409.08890","DOIUrl":"https://doi.org/arxiv-2409.08890","url":null,"abstract":"The rapid expansion of AI adoption (e.g., using machine learning, deep\u0000learning, or large language models as research methods) and the increasing\u0000availability of big data have the potential to bring about the most significant\u0000transformation in entrepreneurship scholarship the field has ever witnessed.\u0000This article makes a pressing meta-contribution by highlighting a significant\u0000risk of unproductive knowledge exchanges in entrepreneurship research amid the\u0000AI revolution. It offers strategies to mitigate this risk and provides guidance\u0000for future AI-based studies to enhance their collective impact and relevance.\u0000Drawing on Akerlof's renowned market-for-lemons concept, we identify the\u0000potential for significant knowledge asymmetries emerging from the field's\u0000evolution into its current landscape (e.g., complexities around construct\u0000validity, theory building, and research relevance). Such asymmetries are\u0000particularly deeply ingrained due to what we term the double-black-box puzzle,\u0000where the widely recognized black box nature of AI methods intersects with the\u0000black box nature of the entrepreneurship phenomenon driven by inherent\u0000uncertainty. As a result, these asymmetries could lead to an increase in\u0000suboptimal research products that go undetected, collectively creating a market\u0000for lemons that undermines the field's well-being, reputation, and impact.\u0000However, importantly, if these risks can be mitigated, the AI revolution could\u0000herald a new golden era for entrepreneurship research. We discuss the necessary\u0000actions to elevate the field to a higher level of AI resilience while\u0000steadfastly maintaining its foundational principles and core values.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"118 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic Link and Flow Prediction in Bank Transfer Networks","authors":"Shu Takahashi, Kento Yamamoto, Shumpei Kobayashi, Ryoma Kondo, Ryohei Hisano","doi":"arxiv-2409.08718","DOIUrl":"https://doi.org/arxiv-2409.08718","url":null,"abstract":"The prediction of both the existence and weight of network links at future\u0000time points is essential as complex networks evolve over time. Traditional\u0000methods, such as vector autoregression and factor models, have been applied to\u0000small, dense networks, but become computationally impractical for large-scale,\u0000sparse, and complex networks. Some machine learning models address dynamic link\u0000prediction, but few address the simultaneous prediction of both link presence\u0000and weight. Therefore, we introduce a novel model that dynamically predicts\u0000link presence and weight by dividing the task into two sub-tasks: predicting\u0000remittance ratios and forecasting the total remittance volume. We use a\u0000self-attention mechanism that combines temporal-topological neighborhood\u0000features to predict remittance ratios and use a separate model to forecast the\u0000total remittance volume. We achieve the final prediction by multiplying the\u0000outputs of these models. We validated our approach using two real-world\u0000datasets: a cryptocurrency network and bank transfer network.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Economic impacts of a drastic gas supply shock and short-term mitigation strategies","authors":"Anton Pichler, Jan Hurt, Tobias Reisch, Johannes Stangl, Stefan Thurner","doi":"arxiv-2409.07981","DOIUrl":"https://doi.org/arxiv-2409.07981","url":null,"abstract":"The Russian invasion of Ukraine on February 24, 2022 entailed the threat of a\u0000drastic and sudden reduction of natural gas supply to the European Union. This\u0000paper presents a techno-economic analysis of the consequences of a sudden gas\u0000supply shock to Austria, one of the most dependent countries on imports of\u0000Russian gas. Our analysis comprises (a) a detailed assessment of supply and\u0000demand side countermeasures to mitigate the immediate shortfall in Russian gas\u0000imports, (b) a mapping of the net reduction in gas supply to industrial sectors\u0000to quantify direct economic shocks and expected relative reductions in gross\u0000output and (c) the quantification of higher-order economic impacts through\u0000using a dynamic out-of-equilibrium input-output model. Our results show that\u0000potential economic consequences can range from relatively mild to highly\u0000severe, depending on the implementation and success of counteracting mitigation\u0000measures. We find that securing alternative gas imports, storage management,\u0000and incentivizing fuel switching represent the most important short-term policy\u0000levers to mitigate the adverse impacts of a sudden import stop.","PeriodicalId":501273,"journal":{"name":"arXiv - ECON - General Economics","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}