In this paper we examine the education and occupation mismatch for Hispanics in the US using a novel objective continuous mismatch index and explore the role of immigrants' social networks on this mismatch. We explore whether having a larger social network helps Hispanics in finding jobs that better match with their skill and education levels or whether living in areas with larger concentration of Hispanics leads to more competition for the same jobs in the labor market. Given that the legal status of immigrants influence how the social networks are leveraged and their impact on labor market outcomes, we focus on the citizenship status for Hispanics. The quality of match between Hispanic's college degree major and occupation is measured using one of the continuous indices proposed in Rios-Avila and Saavedra-Caballero (2019) and calculated using pooled data for all college graduates in the US from 2010 to 2017. The Hispanic networks measures are constructed as the share of Hispanic population who are 25 years or older with respect to the total population of the same age and the second measure only includes Hispanics with at least a bachelor's degree using the weighted pooled data from 2010 to 2015. We find that networks have a positive impact on the job-match quality, but mostly for Hispanic citizens and this effect is stronger when the networks constitutes of at least a college degree. This shows that Hispanic citizens living in higher concentration of Hispanic college graduates are better able to leverage their networks or their networks are better able to match them with jobs closer to their field of specialization and skill set.
{"title":"Education-Occupation Mismatch and Social Networks for Hispanics in the US: Role of Citizenship","authors":"Kusum Mundra, Fernando Rios Avila","doi":"10.2139/ssrn.3542644","DOIUrl":"https://doi.org/10.2139/ssrn.3542644","url":null,"abstract":"In this paper we examine the education and occupation mismatch for Hispanics in the US using a novel objective continuous mismatch index and explore the role of immigrants' social networks on this mismatch. We explore whether having a larger social network helps Hispanics in finding jobs that better match with their skill and education levels or whether living in areas with larger concentration of Hispanics leads to more competition for the same jobs in the labor market. Given that the legal status of immigrants influence how the social networks are leveraged and their impact on labor market outcomes, we focus on the citizenship status for Hispanics. The quality of match between Hispanic's college degree major and occupation is measured using one of the continuous indices proposed in Rios-Avila and Saavedra-Caballero (2019) and calculated using pooled data for all college graduates in the US from 2010 to 2017. The Hispanic networks measures are constructed as the share of Hispanic population who are 25 years or older with respect to the total population of the same age and the second measure only includes Hispanics with at least a bachelor's degree using the weighted pooled data from 2010 to 2015. We find that networks have a positive impact on the job-match quality, but mostly for Hispanic citizens and this effect is stronger when the networks constitutes of at least a college degree. This shows that Hispanic citizens living in higher concentration of Hispanic college graduates are better able to leverage their networks or their networks are better able to match them with jobs closer to their field of specialization and skill set.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122881066","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}
Econometricians are increasingly working with high-dimensional networks and their dynamics. Econometricians, however, are often confronted with unforeseen changes in network dynamics. In this paper, we develop a method and the corresponding algorithm for monitoring changes in dynamic networks. We characterize two types of changes, edge-initiated and node-initiated, to feature the complexity of networks. The proposed approach accounts for three potential challenges in the analysis of networks. First, networks are high-dimensional objects causing the standard statistical tools to suffer from the curse of dimensionality. Second, any potential changes in social networks are likely driven by a few nodes or edges in the network. Third, in many dynamic network applications such as monitoring network connectedness or its centrality, it will be more practically applicable to detect the change in an online fashion than the offline version. The proposed detection method at each time point projects the entire network onto a low-dimensional vector by taking the sparsity into account, then sequentially detects the change by comparing consecutive estimates of the optimal projection direction. As long as the change is sizeable and persistent, the projected vectors will converge to the optimal one, leading to a jump in the sine angle distance between them. A change is therefore declared. Strong theoretical guarantees on both the false alarm rate and detection delays are derived in a sub-Gaussian setting, even under spatial and temporal dependence in the data stream. Numerical studies and an application to the social media messages network support the effectiveness of our method.
{"title":"Monitoring Network Changes in Social Media","authors":"C. Chen, Yarema Okhrin, Tengyao Wang","doi":"10.2139/ssrn.3941331","DOIUrl":"https://doi.org/10.2139/ssrn.3941331","url":null,"abstract":"Econometricians are increasingly working with high-dimensional networks and their dynamics. Econometricians, however, are often confronted with unforeseen changes in network dynamics. In this paper, we develop a method and the corresponding algorithm for monitoring changes in dynamic networks. We characterize two types of changes, edge-initiated and node-initiated, to feature the complexity of networks. The proposed approach accounts for three potential challenges in the analysis of networks. First, networks are high-dimensional objects causing the standard statistical tools to suffer from the curse of dimensionality. Second, any potential changes in social networks are likely driven by a few nodes or edges in the network. Third, in many dynamic network applications such as monitoring network connectedness or its centrality, it will be more practically applicable to detect the change in an online fashion than the offline version. The proposed detection method at each time point projects the entire network onto a low-dimensional vector by taking the sparsity into account, then sequentially detects the change by comparing consecutive estimates of the optimal projection direction. As long as the change is sizeable and persistent, the projected vectors will converge to the optimal one, leading to a jump in the sine angle distance between them. A change is therefore declared. Strong theoretical guarantees on both the false alarm rate and detection delays are derived in a sub-Gaussian setting, even under spatial and temporal dependence in the data stream. Numerical studies and an application to the social media messages network support the effectiveness of our method.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123882008","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 study an e-commerce platform’s incentives to delist IP-infringing products and the effects of introducing a liability regime that induces the platform to increase its screening intensity. We identify conditions under which platform liability is socially desirable (respectively, undesirable) by analyzing its intended and unintended effects on the innovation incentives of brand owners. We show that making the platform liable for the presence of IP-infringing products can lead to a reduction (instead of an increase) in brand owners’ innovation if the platform responds to more screening by raising its commission rate. We then consider various extensions that allow us to identify additional forces that strengthen (respectively, weaken) the social desirability of liability. We conclude by presenting some implications for policymakers.
{"title":"Platform Liability and Innovation","authors":"Doh-Shin Jeon, Yassine Lefouili, Leonardo Madio","doi":"10.2139/ssrn.3945132","DOIUrl":"https://doi.org/10.2139/ssrn.3945132","url":null,"abstract":"We study an e-commerce platform’s incentives to delist IP-infringing products and the effects of introducing a liability regime that induces the platform to increase its screening intensity. We identify conditions under which platform liability is socially desirable (respectively, undesirable) by analyzing its intended and unintended effects on the innovation incentives of brand owners. We show that making the platform liable for the presence of IP-infringing products can lead to a reduction (instead of an increase) in brand owners’ innovation if the platform responds to more screening by raising its commission rate. We then consider various extensions that allow us to identify additional forces that strengthen (respectively, weaken) the social desirability of liability. We conclude by presenting some implications for policymakers.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131455521","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}
John Wihbey, Garrett Morrow, Myojung Chung, Mike W. Peacey
Social media companies have increasingly been using labeling strategies to identify, highlight, and mark content that may be problematic in some way but not sufficiently violating to justify removing it. Such labeling strategies, which are now being used by most major social platforms, present a host of new challenges and questions. This report, based on a national survey conducted in the U.S. in summer 2021 (N = 1,464), provides new insights into public preferences around social media company policy and interventions in the media environment. It is often assumed that there are highly polarized views about content moderation. However, we find relatively strong, bipartisan support for the basic strategy and general goals of labeling.
{"title":"The Bipartisan Case for Labeling as a Content Moderation Method: Findings from a National Survey","authors":"John Wihbey, Garrett Morrow, Myojung Chung, Mike W. Peacey","doi":"10.2139/ssrn.3923905","DOIUrl":"https://doi.org/10.2139/ssrn.3923905","url":null,"abstract":"Social media companies have increasingly been using labeling strategies to identify, highlight, and mark content that may be problematic in some way but not sufficiently violating to justify removing it. Such labeling strategies, which are now being used by most major social platforms, present a host of new challenges and questions. This report, based on a national survey conducted in the U.S. in summer 2021 (N = 1,464), provides new insights into public preferences around social media company policy and interventions in the media environment. It is often assumed that there are highly polarized views about content moderation. However, we find relatively strong, bipartisan support for the basic strategy and general goals of labeling.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134263535","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}
Jens Dick‐Nielsen, Thomas K. Poulsen, Obaidur Rehman
We show that uninformed corporate bond index trackers pay lower transaction costs when they request immediacy from dealers with central network positions. This centrality discount supports recent network models in which core dealers have a comparative advantage in carrying inventory. We show that core dealers provide more immediacy and revert deviations from their desired inventory faster. When dealers trade with other dealers, we find a centrality premium consistent with core dealers exploiting their comparative advantage to extract more surplus when bargaining with peripheral dealers. We rule out alternative explanations based on adverse selection and customer clienteles.
{"title":"Dealer Networks and the Cost of Immediacy","authors":"Jens Dick‐Nielsen, Thomas K. Poulsen, Obaidur Rehman","doi":"10.2139/ssrn.3752881","DOIUrl":"https://doi.org/10.2139/ssrn.3752881","url":null,"abstract":"We show that uninformed corporate bond index trackers pay lower transaction costs when they request immediacy from dealers with central network positions. This centrality discount supports recent network models in which core dealers have a comparative advantage in carrying inventory. We show that core dealers provide more immediacy and revert deviations from their desired inventory faster. When dealers trade with other dealers, we find a centrality premium consistent with core dealers exploiting their comparative advantage to extract more surplus when bargaining with peripheral dealers. We rule out alternative explanations based on adverse selection and customer clienteles.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114946842","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}
Financial technology (FinTech) companies are increasingly important to the financial system. We investigate the effect of peer-to-peer (P2P) lending on traditional banks by examining whether and how P2P lending activity in a state affects loan loss provisions among that state’s commercial banks. When borrowers take out loans from both a bank and a P2P lending platform, they become more leveraged. Banks may signal their anticipation of bad loans due to overleveraged borrowers by increasing their expected future loan losses. Using a large sample of US single-state banks from 2010 to 2018, we find that banks in states with a higher P2P lending volume report higher loan loss provisions. This positive relation is stronger for banks with greater exposure to the consumer loan market and for those with consumer borrowers who are more leveraged. Our findings show that bank managers use loan loss provisions to signal expected credit losses in response to P2P lending. We also find that P2P lending is associated with higher future loan charge-offs, which validates the signaling channel. Overall, our study offers new insight into the interaction between FinTech firms and traditional financial institutions.
{"title":"Loan Loss Signaling Among Banks Competing with FinTech Firms: Evidence from Peer-to-Peer Lending","authors":"Jeffrey Ng, T. Rusticus, Janus Jian Zhang","doi":"10.2139/ssrn.3622854","DOIUrl":"https://doi.org/10.2139/ssrn.3622854","url":null,"abstract":"Financial technology (FinTech) companies are increasingly important to the financial system. We investigate the effect of peer-to-peer (P2P) lending on traditional banks by examining whether and how P2P lending activity in a state affects loan loss provisions among that state’s commercial banks. When borrowers take out loans from both a bank and a P2P lending platform, they become more leveraged. Banks may signal their anticipation of bad loans due to overleveraged borrowers by increasing their expected future loan losses. Using a large sample of US single-state banks from 2010 to 2018, we find that banks in states with a higher P2P lending volume report higher loan loss provisions. This positive relation is stronger for banks with greater exposure to the consumer loan market and for those with consumer borrowers who are more leveraged. Our findings show that bank managers use loan loss provisions to signal expected credit losses in response to P2P lending. We also find that P2P lending is associated with higher future loan charge-offs, which validates the signaling channel. Overall, our study offers new insight into the interaction between FinTech firms and traditional financial institutions.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123307693","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}
Impact on consumer shopping behavior ramped up despite the fluctuations in the pandemic and lockdown in the past year due to of the social media. Because the advent of social media has changed the globe and the whole way it operates, putting the society and its peoples closer together even as a means of boosting customer assets through powerful communication during this challenging period. The purpose of this study is to define the characteristics of social media marketing factors and to examine the impact of those perceived factors upon customer purchasing decisions, given the immense concern in using social media marketing among fashion brands during the period of covid-19 pandemic. This research primarily fixated on five variables in social media, such as entertainment, interactions, trendiness, customization and word of mouth effect on the consumer purchasing decisions. A deductive methodology was taken, and 100 questionnaires, via the Google online form, were circulated to gather data. For data interpretation using SPSS, descriptive and inferential statistics were used such as mean value, standard deviation and correlation and regression analysis. The study of the data shows that social media-marketing factors like entertainment, communications, trends, customizing and word of mouth influence customer buying decisions, and that these factors have a positive relation with consumer purchase decisions. These results also revealed that women and individuals aged twenty-five to thirty-four years of age are more inclined to buy fashion-related products during this pandemic situation and suggested to develop marketing tools targeted at this particular category. Further, the results of this study will help fashion companies more specifically forecast the purchasing habits of their customers and control their investments and marketing efforts in this challenging period.
{"title":"Do Social Media Impact Consumer Buying Decisions in the Fashion Industry during the COVID-19 Pandemic?","authors":"S. Suraweera, Wgjm Jayathilake","doi":"10.31033/ijemr.11.4.27","DOIUrl":"https://doi.org/10.31033/ijemr.11.4.27","url":null,"abstract":"Impact on consumer shopping behavior ramped up despite the fluctuations in the pandemic and lockdown in the past year due to of the social media. Because the advent of social media has changed the globe and the whole way it operates, putting the society and its peoples closer together even as a means of boosting customer assets through powerful communication during this challenging period. The purpose of this study is to define the characteristics of social media marketing factors and to examine the impact of those perceived factors upon customer purchasing decisions, given the immense concern in using social media marketing among fashion brands during the period of covid-19 pandemic. This research primarily fixated on five variables in social media, such as entertainment, interactions, trendiness, customization and word of mouth effect on the consumer purchasing decisions. A deductive methodology was taken, and 100 questionnaires, via the Google online form, were circulated to gather data. For data interpretation using SPSS, descriptive and inferential statistics were used such as mean value, standard deviation and correlation and regression analysis. The study of the data shows that social media-marketing factors like entertainment, communications, trends, customizing and word of mouth influence customer buying decisions, and that these factors have a positive relation with consumer purchase decisions. These results also revealed that women and individuals aged twenty-five to thirty-four years of age are more inclined to buy fashion-related products during this pandemic situation and suggested to develop marketing tools targeted at this particular category. Further, the results of this study will help fashion companies more specifically forecast the purchasing habits of their customers and control their investments and marketing efforts in this challenging period.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131745493","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}
Social networks are integral to the performance of collaborative work, but research on network change has shed little light on the tactics firms use to deliberately stimulate collaborative network ties among their employees. In this paper, we empirically examine one such tactic, corporate offsites, as opportunity shocks for intra-organizational networking. We find that attending an offsite leads participants to significantly increase the number of new network ties that they initiate. But surprisingly, people who do not attend the offsite similarly increase their network outreach, consistent with deliberate compensatory behavior on the part of non-attendees. However, attendees also receive more incoming requests from new collaborators following offsites, a benefit that does not accrue to non-attendees. These results are consistent with a conceptualization of opportunities as affecting network change in two distinct ways: through the changes the individual makes in her own network, which are subject to individual agency, and through the decisions made by others, which also shape the focal individual’s network, but which fall outside of the focal individual’s agency. Integrating the traditional egocentric perspective with an altercentric perspective moves us closer to understanding both an individual’s agency to shape her evolving network and the limits on that agency.
{"title":"On Agency and its Limits: The Asymmetric Effects of Offsites on Network Tie Formation","authors":"Madeline King Kneeland, Adam M. Kleinbaum","doi":"10.2139/ssrn.3520640","DOIUrl":"https://doi.org/10.2139/ssrn.3520640","url":null,"abstract":"Social networks are integral to the performance of collaborative work, but research on network change has shed little light on the tactics firms use to deliberately stimulate collaborative network ties among their employees. In this paper, we empirically examine one such tactic, corporate offsites, as opportunity shocks for intra-organizational networking. We find that attending an offsite leads participants to significantly increase the number of new network ties that they initiate. But surprisingly, people who do not attend the offsite similarly increase their network outreach, consistent with deliberate compensatory behavior on the part of non-attendees. However, attendees also receive more incoming requests from new collaborators following offsites, a benefit that does not accrue to non-attendees. These results are consistent with a conceptualization of opportunities as affecting network change in two distinct ways: through the changes the individual makes in her own network, which are subject to individual agency, and through the decisions made by others, which also shape the focal individual’s network, but which fall outside of the focal individual’s agency. Integrating the traditional egocentric perspective with an altercentric perspective moves us closer to understanding both an individual’s agency to shape her evolving network and the limits on that agency.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125494441","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}
In this paper, we consider the concept of a 1-tier national monetary system based on a digital sovereign currency issued by a central bank. In contrast to the approach, based on a centralized technical infrastructure, used in most, if not all, CBDC projects, we suggest to use a decentralized infrastructure. Such an infrastructure can be thought of as a peer-to-peer network consisting of nodes, which are equipotent participants and are equally privileged, each providing a complete set of services required to maintain digital wallets and process transactions with digital currency. Also, unlike most of CBDC projects, two possible formats of digital titles of property are considered: digital accounts with continuously modifiable amount and token-like digital coins with a fixed non-modifiable amount. The suggested model of currency system involves built-in payment mechanisms enabling one to carry out, both online and offline, transfers of digital currency with immediate finality and irrevocability. In this paper, we present an overview of the suggested model of currency system.
{"title":"Sovereign Digital Currency System with Decentralized Infrastructure","authors":"K. Summanen","doi":"10.2139/ssrn.3902129","DOIUrl":"https://doi.org/10.2139/ssrn.3902129","url":null,"abstract":"In this paper, we consider the concept of a 1-tier national monetary system based on a digital sovereign currency issued by a central bank. In contrast to the approach, based on a centralized technical infrastructure, used in most, if not all, CBDC projects, we suggest to use a decentralized infrastructure. Such an infrastructure can be thought of as a peer-to-peer network consisting of nodes, which are equipotent participants and are equally privileged, each providing a complete set of services required to maintain digital wallets and process transactions with digital currency. Also, unlike most of CBDC projects, two possible formats of digital titles of property are considered: digital accounts with continuously modifiable amount and token-like digital coins with a fixed non-modifiable amount. The suggested model of currency system involves built-in payment mechanisms enabling one to carry out, both online and offline, transfers of digital currency with immediate finality and irrevocability. In this paper, we present an overview of the suggested model of currency system.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115899327","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 paper evaluates the effect of energy trade networks on the price volatility of coal, oil, natural gas, and electricity. This research conducts a longitudinal analysis using a time series of static coal trade networks to generate a dynamic trade network. It uses the component causality index as a leading indicator of the price volatility of the energy market. This research finds out that the component causality index, based on degree centrality, anticipates or moves together with coal volatility and, to a lesser degree, with natural gas and electricity volatility for the period 1998–2014. The proposed index could be integrated into a risk management system for investors and regulators. The broad impact of this research lies in the understanding of mechanisms of the instability and risk of the energy sector as a result of a complex interaction of the network of producers and traders.
{"title":"Volatility and Risk in the Energy Market: A Trade Network Approach","authors":"Germán G. Creamer, T. Ben-Zvi","doi":"10.3390/su131810199","DOIUrl":"https://doi.org/10.3390/su131810199","url":null,"abstract":"This paper evaluates the effect of energy trade networks on the price volatility of coal, oil, natural gas, and electricity. This research conducts a longitudinal analysis using a time series of static coal trade networks to generate a dynamic trade network. It uses the component causality index as a leading indicator of the price volatility of the energy market. This research finds out that the component causality index, based on degree centrality, anticipates or moves together with coal volatility and, to a lesser degree, with natural gas and electricity volatility for the period 1998–2014. The proposed index could be integrated into a risk management system for investors and regulators. The broad impact of this research lies in the understanding of mechanisms of the instability and risk of the energy sector as a result of a complex interaction of the network of producers and traders.","PeriodicalId":319022,"journal":{"name":"Economics of Networks eJournal","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125152976","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}
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