This paper studies a variable proportion portfolio insurance (VPPI) strategy. The objective is to determine the risk multiplier by maximizing the extended Omega ratio of the investor's cushion, using a binary stochastic benchmark. When the stock index declines, investors aim to maintain the minimum guarantee. Conversely, when the stock index rises, investors seek to track some excess returns. The optimization problem involves the combination of a non-concave objective function with a stochastic benchmark, which is effectively solved based on the stochastic version of concavification technique. We derive semi-analytical solutions for the optimal risk multiplier, and the value functions are categorized into three distinct cases. Intriguingly, the classification criteria are determined by the relationship between the optimal risky multiplier in Zieling et al. (2014 and the value of 1. Simulation results confirm the effectiveness of the VPPI strategy when applied to real market data calibrations.
{"title":"Optimal VPPI strategy under Omega ratio with stochastic benchmark","authors":"Guohui Guan, Lin He, Zongxia Liang, Litian Zhang","doi":"arxiv-2403.13388","DOIUrl":"https://doi.org/arxiv-2403.13388","url":null,"abstract":"This paper studies a variable proportion portfolio insurance (VPPI) strategy.\u0000The objective is to determine the risk multiplier by maximizing the extended\u0000Omega ratio of the investor's cushion, using a binary stochastic benchmark.\u0000When the stock index declines, investors aim to maintain the minimum guarantee.\u0000Conversely, when the stock index rises, investors seek to track some excess\u0000returns. The optimization problem involves the combination of a non-concave\u0000objective function with a stochastic benchmark, which is effectively solved\u0000based on the stochastic version of concavification technique. We derive\u0000semi-analytical solutions for the optimal risk multiplier, and the value\u0000functions are categorized into three distinct cases. Intriguingly, the\u0000classification criteria are determined by the relationship between the optimal\u0000risky multiplier in Zieling et al. (2014 and the value of 1. Simulation results\u0000confirm the effectiveness of the VPPI strategy when applied to real market data\u0000calibrations.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140199718","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}
Generative AI technologies such as ChatGPT, Gemini, and MidJourney have made remarkable progress in recent years. Recent literature has documented ChatGPT's positive impact on productivity in areas where it has strong expertise, attributable to extensive training datasets, such as the English language and Python/SQL programming. However, there is still limited literature regarding ChatGPT's performance in areas where its capabilities could still be further enhanced. This paper aims to fill this gap. We conducted an experiment in which economics students were asked to perform writing analysis tasks in a non-English language (specifically, Thai) and math & data analysis tasks using a less frequently used programming package (specifically, Stata). The findings suggest that, on average, participants performed better using ChatGPT in terms of scores and time taken to complete the tasks. However, a detailed examination reveals that 34% of participants saw no improvement in writing analysis tasks, and 42% did not improve in math & data analysis tasks when employing ChatGPT. Further investigation indicated that higher-ability students, as proxied by their econometrics grades, were the ones who performed worse in writing analysis tasks when using ChatGPT. We also found evidence that students with better digital skills performed better with ChatGPT. This research provides insights on the impact of generative AI. Thus, stakeholders can make informed decisions to implement appropriate policy frameworks or redesign educational systems. It also highlights the critical role of human skills in addressing and complementing the limitations of technology.
{"title":"Experimenting with Generative AI: Does ChatGPT Really Increase Everyone's Productivity?","authors":"Voraprapa Nakavachara, Tanapong Potipiti, Thanee Chaiwat","doi":"arxiv-2403.01770","DOIUrl":"https://doi.org/arxiv-2403.01770","url":null,"abstract":"Generative AI technologies such as ChatGPT, Gemini, and MidJourney have made\u0000remarkable progress in recent years. Recent literature has documented ChatGPT's\u0000positive impact on productivity in areas where it has strong expertise,\u0000attributable to extensive training datasets, such as the English language and\u0000Python/SQL programming. However, there is still limited literature regarding\u0000ChatGPT's performance in areas where its capabilities could still be further\u0000enhanced. This paper aims to fill this gap. We conducted an experiment in which\u0000economics students were asked to perform writing analysis tasks in a\u0000non-English language (specifically, Thai) and math & data analysis tasks using\u0000a less frequently used programming package (specifically, Stata). The findings\u0000suggest that, on average, participants performed better using ChatGPT in terms\u0000of scores and time taken to complete the tasks. However, a detailed examination\u0000reveals that 34% of participants saw no improvement in writing analysis tasks,\u0000and 42% did not improve in math & data analysis tasks when employing ChatGPT.\u0000Further investigation indicated that higher-ability students, as proxied by\u0000their econometrics grades, were the ones who performed worse in writing\u0000analysis tasks when using ChatGPT. We also found evidence that students with\u0000better digital skills performed better with ChatGPT. This research provides\u0000insights on the impact of generative AI. Thus, stakeholders can make informed\u0000decisions to implement appropriate policy frameworks or redesign educational\u0000systems. It also highlights the critical role of human skills in addressing and\u0000complementing the limitations of technology.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140036201","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}
We analyse the individual productivity effects of Italy's ban on ChatGPT, a generative pretrained transformer chatbot. We compile data on the daily coding output quantity and quality of over 36,000 GitHub users in Italy and other European countries and combine these data with the sudden announcement of the ban in a difference-in-differences framework. Among the affected users in Italy, we find a short-term increase in output quantity and quality for less experienced users and a decrease in productivity on more routine tasks for experienced users.
{"title":"The Heterogeneous Productivity Effects of Generative AI","authors":"David Kreitmeir, Paul A. Raschky","doi":"arxiv-2403.01964","DOIUrl":"https://doi.org/arxiv-2403.01964","url":null,"abstract":"We analyse the individual productivity effects of Italy's ban on ChatGPT, a\u0000generative pretrained transformer chatbot. We compile data on the daily coding\u0000output quantity and quality of over 36,000 GitHub users in Italy and other\u0000European countries and combine these data with the sudden announcement of the\u0000ban in a difference-in-differences framework. Among the affected users in\u0000Italy, we find a short-term increase in output quantity and quality for less\u0000experienced users and a decrease in productivity on more routine tasks for\u0000experienced users.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140036200","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}
Agricultural products play a critical role in human development. With economic globalization and the financialization of agricultural products continuing to advance, the interconnections between different agricultural futures have become closer. We utilize a TVP-VAR-DY model combined with the quantile method to measure the risk spillover between 11 agricultural futures on the futures exchanges of US and China from July 9,2014, to December 31,2022. This study yielded several significant findings. Firstly, CBOT corn, soybean, and wheat were identified as the primary risk transmitters, with DCE corn and soybean as the main risk receivers. Secondly, sudden events or increased eco- nomic uncertainty can increase the overall risk spillovers. Thirdly, there is an aggregation of risk spillovers amongst agricultural futures based on the dynamic directional spillover results. Lastly, the central agricultural futures under the conditional mean are CBOT corn and soybean, while CZCE hard wheat and long-grained rice are the two risk spillover centers in extreme cases, as per the results of the spillover network and minimum spanning tree. Based on these results, decision-makers are advised to safeguard against the price risk of agricultural futures under sudden economic events, and investors can utilize the results to construct a superior investment portfolio by taking different agricultural product futures as risk-leading indicators according to various situations.
{"title":"Uncovering the Sino-US dynamic risk spillovers effects: Evidence from agricultural futures markets","authors":"Han-Yu Zhu, Peng-Fei Dai, Wei-Xing Zhou","doi":"arxiv-2403.01745","DOIUrl":"https://doi.org/arxiv-2403.01745","url":null,"abstract":"Agricultural products play a critical role in human development. With\u0000economic globalization and the financialization of agricultural products\u0000continuing to advance, the interconnections between different agricultural\u0000futures have become closer. We utilize a TVP-VAR-DY model combined with the\u0000quantile method to measure the risk spillover between 11 agricultural futures\u0000on the futures exchanges of US and China from July 9,2014, to December 31,2022.\u0000This study yielded several significant findings. Firstly, CBOT corn, soybean,\u0000and wheat were identified as the primary risk transmitters, with DCE corn and\u0000soybean as the main risk receivers. Secondly, sudden events or increased eco-\u0000nomic uncertainty can increase the overall risk spillovers. Thirdly, there is\u0000an aggregation of risk spillovers amongst agricultural futures based on the\u0000dynamic directional spillover results. Lastly, the central agricultural futures\u0000under the conditional mean are CBOT corn and soybean, while CZCE hard wheat and\u0000long-grained rice are the two risk spillover centers in extreme cases, as per\u0000the results of the spillover network and minimum spanning tree. Based on these\u0000results, decision-makers are advised to safeguard against the price risk of\u0000agricultural futures under sudden economic events, and investors can utilize\u0000the results to construct a superior investment portfolio by taking different\u0000agricultural product futures as risk-leading indicators according to various\u0000situations.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140036098","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}
Joon Suk Huh, Ellen Vitercik, Kirthevasan Kandasamy
We study a sequential profit-maximization problem, optimizing for both price and ancillary variables like marketing expenditures. Specifically, we aim to maximize profit over an arbitrary sequence of multiple demand curves, each dependent on a distinct ancillary variable, but sharing the same price. A prototypical example is targeted marketing, where a firm (seller) wishes to sell a product over multiple markets. The firm may invest different marketing expenditures for different markets to optimize customer acquisition, but must maintain the same price across all markets. Moreover, markets may have heterogeneous demand curves, each responding to prices and marketing expenditures differently. The firm's objective is to maximize its gross profit, the total revenue minus marketing costs. Our results are near-optimal algorithms for this class of problems in an adversarial bandit setting, where demand curves are arbitrary non-adaptive sequences, and the firm observes only noisy evaluations of chosen points on the demand curves. We prove a regret upper bound of $widetilde{mathcal{O}}big(nT^{3/4}big)$ and a lower bound of $Omegabig((nT)^{3/4}big)$ for monotonic demand curves, and a regret bound of $widetilde{Theta}big(nT^{2/3}big)$ for demands curves that are monotonic in price and concave in the ancillary variables.
{"title":"Bandit Profit-maximization for Targeted Marketing","authors":"Joon Suk Huh, Ellen Vitercik, Kirthevasan Kandasamy","doi":"arxiv-2403.01361","DOIUrl":"https://doi.org/arxiv-2403.01361","url":null,"abstract":"We study a sequential profit-maximization problem, optimizing for both price\u0000and ancillary variables like marketing expenditures. Specifically, we aim to\u0000maximize profit over an arbitrary sequence of multiple demand curves, each\u0000dependent on a distinct ancillary variable, but sharing the same price. A\u0000prototypical example is targeted marketing, where a firm (seller) wishes to\u0000sell a product over multiple markets. The firm may invest different marketing\u0000expenditures for different markets to optimize customer acquisition, but must\u0000maintain the same price across all markets. Moreover, markets may have\u0000heterogeneous demand curves, each responding to prices and marketing\u0000expenditures differently. The firm's objective is to maximize its gross profit,\u0000the total revenue minus marketing costs. Our results are near-optimal algorithms for this class of problems in an\u0000adversarial bandit setting, where demand curves are arbitrary non-adaptive\u0000sequences, and the firm observes only noisy evaluations of chosen points on the\u0000demand curves. We prove a regret upper bound of\u0000$widetilde{mathcal{O}}big(nT^{3/4}big)$ and a lower bound of\u0000$Omegabig((nT)^{3/4}big)$ for monotonic demand curves, and a regret bound of\u0000$widetilde{Theta}big(nT^{2/3}big)$ for demands curves that are monotonic in\u0000price and concave in the ancillary variables.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140036198","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}
This article presents an analysis of China's economic evolution amidst demographic changes from 1990 to 2050, offering valuable insights for academia and policymakers. It uniquely intertwines various economic theories with empirical data, examining the impact of an aging population, urbanization, and family dynamics on labor, demand, and productivity. The study's novelty lies in its integration of Classical, Neoclassical, and Endogenous Growth theories, alongside models like Barro and Sala-i-Martin, to contextualize China's economic trajectory. It provides a forward-looking perspective, utilizing econometric methods to predict future trends, and suggests practical policy implications. This comprehensive approach sheds light on managing demographic transitions in a global context, making it a significant contribution to the field of demographic economics.
{"title":"Managing Demographic Transitions: A Comprehensive Analysis of China's Path to Economic Sustainability","authors":"Yuxin Hu","doi":"arxiv-2312.11806","DOIUrl":"https://doi.org/arxiv-2312.11806","url":null,"abstract":"This article presents an analysis of China's economic evolution amidst\u0000demographic changes from 1990 to 2050, offering valuable insights for academia\u0000and policymakers. It uniquely intertwines various economic theories with\u0000empirical data, examining the impact of an aging population, urbanization, and\u0000family dynamics on labor, demand, and productivity. The study's novelty lies in\u0000its integration of Classical, Neoclassical, and Endogenous Growth theories,\u0000alongside models like Barro and Sala-i-Martin, to contextualize China's\u0000economic trajectory. It provides a forward-looking perspective, utilizing\u0000econometric methods to predict future trends, and suggests practical policy\u0000implications. This comprehensive approach sheds light on managing demographic\u0000transitions in a global context, making it a significant contribution to the\u0000field of demographic economics.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138817815","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}
For emerging professions, such as jobs in the field of Artificial Intelligence (AI) or sustainability (green), labour supply does not meet industry demand. In this scenario of labour shortages, our work aims to understand whether employers have started focusing on individual skills rather than on formal qualifications in their recruiting. By analysing a large time series dataset of around one million online job vacancies between 2019 and 2022 from the UK and drawing on diverse literature on technological change and labour market signalling, we provide evidence that employers have started so-called "skill-based hiring" for AI and green roles, as more flexible hiring practices allow them to increase the available talent pool. In our observation period the demand for AI roles grew twice as much as average labour demand. At the same time, the mention of university education for AI roles declined by 23%, while AI roles advertise five times as many skills as job postings on average. Our regression analysis also shows that university degrees no longer show an educational premium for AI roles, while for green positions the educational premium persists. In contrast, AI skills have a wage premium of 16%, similar to having a PhD (17%). Our work recommends making use of alternative skill building formats such as apprenticeships, on-the-job training, MOOCs, vocational education and training, micro-certificates, and online bootcamps to use human capital to its full potential and to tackle talent shortages.
{"title":"Skills or Degree? The Rise of Skill-Based Hiring for AI and Green Jobs","authors":"Eugenia Gonzalez Ehlinger, Fabian Stephany","doi":"arxiv-2312.11942","DOIUrl":"https://doi.org/arxiv-2312.11942","url":null,"abstract":"For emerging professions, such as jobs in the field of Artificial\u0000Intelligence (AI) or sustainability (green), labour supply does not meet\u0000industry demand. In this scenario of labour shortages, our work aims to\u0000understand whether employers have started focusing on individual skills rather\u0000than on formal qualifications in their recruiting. By analysing a large time\u0000series dataset of around one million online job vacancies between 2019 and 2022\u0000from the UK and drawing on diverse literature on technological change and\u0000labour market signalling, we provide evidence that employers have started\u0000so-called \"skill-based hiring\" for AI and green roles, as more flexible hiring\u0000practices allow them to increase the available talent pool. In our observation\u0000period the demand for AI roles grew twice as much as average labour demand. At\u0000the same time, the mention of university education for AI roles declined by\u000023%, while AI roles advertise five times as many skills as job postings on\u0000average. Our regression analysis also shows that university degrees no longer\u0000show an educational premium for AI roles, while for green positions the\u0000educational premium persists. In contrast, AI skills have a wage premium of\u000016%, similar to having a PhD (17%). Our work recommends making use of\u0000alternative skill building formats such as apprenticeships, on-the-job\u0000training, MOOCs, vocational education and training, micro-certificates, and\u0000online bootcamps to use human capital to its full potential and to tackle\u0000talent shortages.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138817817","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}
The least-cost diet problem introduces students to optimization and linear programming, using the health consequences of food choice. We provide a graphical example, Excel workbook and Word template using actual data on item prices, food composition and nutrient requirements for a brief exercise in which students guess at and then solve for nutrient adequacy at lowest cost, before comparing modeled diets to actual consumption which has varying degrees of nutrient adequacy. The graphical example is a 'three sisters' diet of corn, beans and squash, and the full multidimensional model is compared to current food consumption in Ethiopia. This updated Stigler diet shows how cost minimization relates to utility maximization, and links to ongoing research and policy debates about the affordability of healthy diets worldwide.
最低成本饮食问题利用食物选择对健康的影响，向学生介绍了优化和线性编程。我们提供了一个图形示例、Excel 工作簿和 Word 模板，使用项目价格、食物成分和营养素需求的实际数据进行简短练习，让学生猜测并求解最低成本下的营养素充足率，然后将模型膳食与不同营养素充足率的实际消费进行比较。图形示例是由玉米、豆类和南瓜组成的 "三姐妹 "膳食，而完整的多维模型则与埃塞俄比亚目前的食物消费进行比较。这种最新的斯蒂格勒饮食法显示了成本最小化与效用最大化之间的关系，并与当前关于全球健康饮食可负担性的研究和政策辩论相联系。
{"title":"Least-cost diets to teach optimization and consumer behavior, with applications to health equity, poverty measurement and international development","authors":"Jessica K. Wallingford, William A. Masters","doi":"arxiv-2312.11767","DOIUrl":"https://doi.org/arxiv-2312.11767","url":null,"abstract":"The least-cost diet problem introduces students to optimization and linear\u0000programming, using the health consequences of food choice. We provide a\u0000graphical example, Excel workbook and Word template using actual data on item\u0000prices, food composition and nutrient requirements for a brief exercise in\u0000which students guess at and then solve for nutrient adequacy at lowest cost,\u0000before comparing modeled diets to actual consumption which has varying degrees\u0000of nutrient adequacy. The graphical example is a 'three sisters' diet of corn,\u0000beans and squash, and the full multidimensional model is compared to current\u0000food consumption in Ethiopia. This updated Stigler diet shows how cost\u0000minimization relates to utility maximization, and links to ongoing research and\u0000policy debates about the affordability of healthy diets worldwide.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138817826","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}
Wadim Strielkowski, Larisa Gorina, Elena Korneeva, Olga Kovaleva
This paper explores the role of energy-saving technologies and energy efficiency in the post-COVID era. The pandemic meant major rethinking of the entrenched patterns in energy saving and efficiency. It also provided opportunities for reevaluating energy consumption for households and industries. In addition, it highlighted the importance of employing digital tools and technologies in energy networks and smart grids (e.g. Internet of Energy (IoE), peer-to-peer (P2P) prosumer networks, or the AI-powered autonomous power systems (APS)). In addition, the pandemic added novel legal aspects to the energy efficiency and energy saving and enhanced inter-national collaborations and partnerships. The paper highlights the importance of energy efficiency measures and examines various technologies that can contribute to a sustainable and resilient energy future. Using the bibliometric network analysis of 12960 publications indexed in Web of Science databases, it demonstrates the potential benefits and challenges associated with implementing energy-saving technologies and autonomic power systems in a post-COVID world. Our findings emphasize the need for robust policies, technological advancements, and public engagement to foster energy efficiency and mitigate the environmental impacts of energy consumption.
{"title":"Energy-saving technologies and energy efficiency in the post-pandemic world","authors":"Wadim Strielkowski, Larisa Gorina, Elena Korneeva, Olga Kovaleva","doi":"arxiv-2312.11711","DOIUrl":"https://doi.org/arxiv-2312.11711","url":null,"abstract":"This paper explores the role of energy-saving technologies and energy\u0000efficiency in the post-COVID era. The pandemic meant major rethinking of the\u0000entrenched patterns in energy saving and efficiency. It also provided\u0000opportunities for reevaluating energy consumption for households and\u0000industries. In addition, it highlighted the importance of employing digital\u0000tools and technologies in energy networks and smart grids (e.g. Internet of\u0000Energy (IoE), peer-to-peer (P2P) prosumer networks, or the AI-powered\u0000autonomous power systems (APS)). In addition, the pandemic added novel legal\u0000aspects to the energy efficiency and energy saving and enhanced inter-national\u0000collaborations and partnerships. The paper highlights the importance of energy\u0000efficiency measures and examines various technologies that can contribute to a\u0000sustainable and resilient energy future. Using the bibliometric network\u0000analysis of 12960 publications indexed in Web of Science databases, it\u0000demonstrates the potential benefits and challenges associated with implementing\u0000energy-saving technologies and autonomic power systems in a post-COVID world.\u0000Our findings emphasize the need for robust policies, technological\u0000advancements, and public engagement to foster energy efficiency and mitigate\u0000the environmental impacts of energy consumption.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138817707","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}
Gordon Rausser, Galina Chebotareva, Wadim Strielkowski, Lubos Smutka
This paper explores the critical question of the sustainability of Russian solar energy initiatives in the absence of governmental financial support. The study aims to determine if Russian energy companies can maintain operations in the solar energy sector without relying on direct state subsidies. Methodologically, the analysis utilizes established investment metrics such as Net Present Value (NPV), Internal Rate of Return (IRR), and Discounted Payback Period (DPP), tailored to reflect the unique technical and economic aspects of Russian solar energy facilities and to evaluate the influence of sector-specific risks on project efficiency, using a rating approach. We examined eleven solar energy projects under ten different scenarios to understand the dynamics of direct state support, exploring variations in support cessation, reductions in financial assistance, and the projects' resilience to external risk factors. Our multi-criteria scenario assessment indicates that, under the prevailing market conditions, the Russian solar energy sector is not yet equipped to operate efficiently without ongoing state financial subsidies. Interestingly, our findings also suggest that the solar energy sector in Russia has a greater potential to reduce its dependence on state support compared to the wind energy sector. Based on these insights, we propose energy policy recommendations aimed at gradually minimizing direct government funding in the Russian renewable energy market. This strategy is designed to foster self-sufficiency and growth in the solar energy sector.
{"title":"Would Russian solar energy projects be feasible independent of state subsidies?","authors":"Gordon Rausser, Galina Chebotareva, Wadim Strielkowski, Lubos Smutka","doi":"arxiv-2312.07240","DOIUrl":"https://doi.org/arxiv-2312.07240","url":null,"abstract":"This paper explores the critical question of the sustainability of Russian\u0000solar energy initiatives in the absence of governmental financial support. The\u0000study aims to determine if Russian energy companies can maintain operations in\u0000the solar energy sector without relying on direct state subsidies.\u0000Methodologically, the analysis utilizes established investment metrics such as\u0000Net Present Value (NPV), Internal Rate of Return (IRR), and Discounted Payback\u0000Period (DPP), tailored to reflect the unique technical and economic aspects of\u0000Russian solar energy facilities and to evaluate the influence of\u0000sector-specific risks on project efficiency, using a rating approach. We\u0000examined eleven solar energy projects under ten different scenarios to\u0000understand the dynamics of direct state support, exploring variations in\u0000support cessation, reductions in financial assistance, and the projects'\u0000resilience to external risk factors. Our multi-criteria scenario assessment\u0000indicates that, under the prevailing market conditions, the Russian solar\u0000energy sector is not yet equipped to operate efficiently without ongoing state\u0000financial subsidies. Interestingly, our findings also suggest that the solar\u0000energy sector in Russia has a greater potential to reduce its dependence on\u0000state support compared to the wind energy sector. Based on these insights, we\u0000propose energy policy recommendations aimed at gradually minimizing direct\u0000government funding in the Russian renewable energy market. This strategy is\u0000designed to foster self-sufficiency and growth in the solar energy sector.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138629916","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：