In most countries, men are the principal asylum applicants, while women are admitted through family-reunification procedures. Family reunification implies that women’s residence permits are contingent on remaining married to their husbands. Using a staggered Difference-in-Differences (DID) Design, I document that granting asylum to family-reunified women improves their economic integration, increases the probability of divorce and decreases their risk of being victims of violence. I find significant impacts on victimization and economic integration regardless of whether the woman remains married or not. I propose that the results can be explained by a reduction in uncertainty about residency and an increase in female bargaining power when the women are granted an autonomous asylum status. JEL-Codes: J120, J150, J610, K370.
{"title":"Does Granting Refugee Status to Family-Reunified Women Improve Their Integration?","authors":"Linea Hasager","doi":"10.2139/ssrn.4692418","DOIUrl":"https://doi.org/10.2139/ssrn.4692418","url":null,"abstract":"In most countries, men are the principal asylum applicants, while women are admitted through family-reunification procedures. Family reunification implies that women’s residence permits are contingent on remaining married to their husbands. Using a staggered Difference-in-Differences (DID) Design, I document that granting asylum to family-reunified women improves their economic integration, increases the probability of divorce and decreases their risk of being victims of violence. I find significant impacts on victimization and economic integration regardless of whether the woman remains married or not. I propose that the results can be explained by a reduction in uncertainty about residency and an increase in female bargaining power when the women are granted an autonomous asylum status. JEL-Codes: J120, J150, J610, K370.","PeriodicalId":507782,"journal":{"name":"SSRN Electronic Journal","volume":"53 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141231399","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}
Racism has become more covert in post-civil rights America. Yet, measures to combat it are hindered by inadequate general knowledge on what “colorblind” race talk says and does and what makes it effective. We deepen understanding of covert racism by investigating one type of discourse – racial code words, which are (1) indirect signifiers of racial or ethnic groups that contain (2) at least one positive or negative value judgment and (3) contextually implied or salient meanings. Through a thematic analysis of 734 racial code words from 97 scholarly texts, we develop an interpretive framework that explains their tropes, linguistic mechanisms and unique roles in perpetuating racism, drawing from race, linguistic and cultural studies. Racial code words promote tropes of White people’s respectability and privilege and Racial/Ethnic Minorities’ pathology and inferiority in efficient, adaptable, plausibly deniable and almost always racially stratifying ways, often through euphemism, metonymy and othering. They construct a “colorblind” discursivity and propel both “epistemic racism” (racism in knowledge) and systemic racism (racism in action). We further strengthen applications of Critical Race Theory in sociolegal studies of race by presenting a “racial meaning decoding tool” to assist legal and societal measures to detect coded racism.
{"title":"Deconstructing Racial Code Words","authors":"Deirdre Pfeiffer, Xiaoqian Hu","doi":"10.2139/ssrn.4801114","DOIUrl":"https://doi.org/10.2139/ssrn.4801114","url":null,"abstract":"Racism has become more covert in post-civil rights America. Yet, measures to combat it are hindered by inadequate general knowledge on what “colorblind” race talk says and does and what makes it effective. We deepen understanding of covert racism by investigating one type of discourse – racial code words, which are (1) indirect signifiers of racial or ethnic groups that contain (2) at least one positive or negative value judgment and (3) contextually implied or salient meanings. Through a thematic analysis of 734 racial code words from 97 scholarly texts, we develop an interpretive framework that explains their tropes, linguistic mechanisms and unique roles in perpetuating racism, drawing from race, linguistic and cultural studies. Racial code words promote tropes of White people’s respectability and privilege and Racial/Ethnic Minorities’ pathology and inferiority in efficient, adaptable, plausibly deniable and almost always racially stratifying ways, often through euphemism, metonymy and othering. They construct a “colorblind” discursivity and propel both “epistemic racism” (racism in knowledge) and systemic racism (racism in action). We further strengthen applications of Critical Race Theory in sociolegal studies of race by presenting a “racial meaning decoding tool” to assist legal and societal measures to detect coded racism.","PeriodicalId":507782,"journal":{"name":"SSRN Electronic Journal","volume":"30 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141274322","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 research paper delves into the transformative possibilities of Artificial Intelligence (AI) within corporate finance, specifically focusing on its role in improving efficiency and decision-making processes. Through the utilization of machine learning, natural language processing (NLP), and robotic process automation (RPA), AI introduces innovative methods for enhancing corporate governance and sustainability practices. In the contemporary business landscape, corporations encounter mounting pressure to streamline operations while simultaneously addressing concerns regarding environmental, social, and governance (ESG) issues. Conventional finance methodologies often struggle to efficiently handle large volumes of data and extract actionable insights promptly. However, AI presents a shift in paradigm by enabling automated data analysis, recognizing patterns, and conducting predictive modeling, thus enabling finance professionals to make data-informed decisions swiftly and accurately. Machine learning algorithms play a pivotal role in detecting patterns and correlations within financial data, facilitating proactive risk management and strategic planning. Additionally, NLP technologies facilitate the extraction of valuable insights from unstructured data sources like regulatory filings, news articles, and social media, thereby enabling informed decision-making in corporate governance and sustainability endeavors. Moreover, RPA simplifies repetitive tasks and workflows, thereby reducing operational expenses and freeing up human resources for more strategic pursuits. Through the automation of routine processes such as data entry, reconciliation, and reporting, RPA enhances operational efficiency and ensures adherence to regulatory standards. Through the adoption of AI technologies, corporations can unlock novel avenues for innovation, optimize resource allocation, and promote sustainable growth within today's dynamic business milieu.
{"title":"Artificial Intelligence-Driven Corporate Finance: Enhancing Efficiency and Decision-Making Through Machine Learning, Natural Language Processing, and Robotic Process Automation in Corporate Governance and Sustainability","authors":"Nitin Rane, Saurabh Choudhary, Jayesh Rane","doi":"10.2139/ssrn.4720591","DOIUrl":"https://doi.org/10.2139/ssrn.4720591","url":null,"abstract":"This research paper delves into the transformative possibilities of Artificial Intelligence (AI) within corporate finance, specifically focusing on its role in improving efficiency and decision-making processes. Through the utilization of machine learning, natural language processing (NLP), and robotic process automation (RPA), AI introduces innovative methods for enhancing corporate governance and sustainability practices. In the contemporary business landscape, corporations encounter mounting pressure to streamline operations while simultaneously addressing concerns regarding environmental, social, and governance (ESG) issues. Conventional finance methodologies often struggle to efficiently handle large volumes of data and extract actionable insights promptly. However, AI presents a shift in paradigm by enabling automated data analysis, recognizing patterns, and conducting predictive modeling, thus enabling finance professionals to make data-informed decisions swiftly and accurately. Machine learning algorithms play a pivotal role in detecting patterns and correlations within financial data, facilitating proactive risk management and strategic planning. Additionally, NLP technologies facilitate the extraction of valuable insights from unstructured data sources like regulatory filings, news articles, and social media, thereby enabling informed decision-making in corporate governance and sustainability endeavors. Moreover, RPA simplifies repetitive tasks and workflows, thereby reducing operational expenses and freeing up human resources for more strategic pursuits. Through the automation of routine processes such as data entry, reconciliation, and reporting, RPA enhances operational efficiency and ensures adherence to regulatory standards. Through the adoption of AI technologies, corporations can unlock novel avenues for innovation, optimize resource allocation, and promote sustainable growth within today's dynamic business milieu.","PeriodicalId":507782,"journal":{"name":"SSRN Electronic Journal","volume":"2 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141229124","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 Characterization of Stable Mechanisms That Minimize Manipulation","authors":"Camilo J. Sirguiado","doi":"10.2139/ssrn.4784280","DOIUrl":"https://doi.org/10.2139/ssrn.4784280","url":null,"abstract":"","PeriodicalId":507782,"journal":{"name":"SSRN Electronic Journal","volume":"134 50","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141281818","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":"The Gatekeeper's Dilemma: Political Selection or Team Effort","authors":"Jon H. Fiva, Federica Izzo, Janne Tukiainen","doi":"10.2139/ssrn.4691338","DOIUrl":"https://doi.org/10.2139/ssrn.4691338","url":null,"abstract":"","PeriodicalId":507782,"journal":{"name":"SSRN Electronic Journal","volume":"7 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141230540","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}
Khushboo Aggarwal, Rashmi Barua, Marian Vidal-Fernandez
{"title":"Still Waters Run Deep: Groundwater Contamination and Education Outcomes in India","authors":"Khushboo Aggarwal, Rashmi Barua, Marian Vidal-Fernandez","doi":"10.2139/ssrn.4761340","DOIUrl":"https://doi.org/10.2139/ssrn.4761340","url":null,"abstract":"","PeriodicalId":507782,"journal":{"name":"SSRN Electronic Journal","volume":"62 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141231390","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 assess the impact of geopolitical risk and world uncertainty on the sovereign debt risk of 26 European Economies during the period 1984-2022, through the implementation of OLS-Fixed Effects regressions and the Generalized Method of Moments (GMM). We find that geopolitical tensions and global uncertainty in border countries contribute to the rise of European country’s sovereign risk as measured by 5-and 10-year Credit Default Swaps (CDS) and bond returns. Moreover, this interconnection is more pronounced during turbulent times such as the subprime crisis. Lastly, we found that geopolitical tensions in other country’ groups such as South America and Asia have a significant impact on the government risks of European countries.
{"title":"Beyond Borders: Assessing the Influence of Geopolitical Tensions on Sovereign Risk Dynamics","authors":"António Afonso, José Alves, Sofia Monteiro","doi":"10.2139/ssrn.4659050","DOIUrl":"https://doi.org/10.2139/ssrn.4659050","url":null,"abstract":"We assess the impact of geopolitical risk and world uncertainty on the sovereign debt risk of 26 European Economies during the period 1984-2022, through the implementation of OLS-Fixed Effects regressions and the Generalized Method of Moments (GMM). We find that geopolitical tensions and global uncertainty in border countries contribute to the rise of European country’s sovereign risk as measured by 5-and 10-year Credit Default Swaps (CDS) and bond returns. Moreover, this interconnection is more pronounced during turbulent times such as the subprime crisis. Lastly, we found that geopolitical tensions in other country’ groups such as South America and Asia have a significant impact on the government risks of European countries.","PeriodicalId":507782,"journal":{"name":"SSRN Electronic Journal","volume":"19 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141233405","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}
Charlotte Lanièce Delaunay, Aryse Melo, Marine Maurel, C. Mazagatos, Luise Goerlitz, Joan O'Donnell, B. Oroszi, Noémie Sève, A. P. Rodrigues, Iván Martínez-Baz, Adam Meijer, I. Mlinarić, Neus Latorre-Margalef, M. Lazăr, Gloria Pérez-Gimeno, Ralf Dürrwald, Charlene Bennett, G. Túri, M. Rameix-Welti, R. Guiomar, Jesús Castilla, M. Hooiveld, S. Kurečić Filipović, Tove Samuelsson Hagey, F. Dijkstra, Vítor Borges, Violeta Ramos Marín, S. Bacci, Marlena Kaczmarek, E. Kissling
{"title":"Effectiveness of Covid-19 Vaccines Administered in the 2023 Autumnal Campaigns in Europe: Results from the Vebis Primary Care Test-Negative Design Study, September 2023–January 2024","authors":"Charlotte Lanièce Delaunay, Aryse Melo, Marine Maurel, C. Mazagatos, Luise Goerlitz, Joan O'Donnell, B. Oroszi, Noémie Sève, A. P. Rodrigues, Iván Martínez-Baz, Adam Meijer, I. Mlinarić, Neus Latorre-Margalef, M. Lazăr, Gloria Pérez-Gimeno, Ralf Dürrwald, Charlene Bennett, G. Túri, M. Rameix-Welti, R. Guiomar, Jesús Castilla, M. Hooiveld, S. Kurečić Filipović, Tove Samuelsson Hagey, F. Dijkstra, Vítor Borges, Violeta Ramos Marín, S. Bacci, Marlena Kaczmarek, E. Kissling","doi":"10.2139/ssrn.4806136","DOIUrl":"https://doi.org/10.2139/ssrn.4806136","url":null,"abstract":"","PeriodicalId":507782,"journal":{"name":"SSRN Electronic Journal","volume":"22 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141274196","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":"The Emergence and Historical Evolution of Innovation Networks: On the Factors Promoting and Hampering Patent Collaboration in Technological Lagging Economies","authors":"Sergio Barbosa, Patricio Sáiz, J. Zofío","doi":"10.2139/ssrn.4735338","DOIUrl":"https://doi.org/10.2139/ssrn.4735338","url":null,"abstract":"","PeriodicalId":507782,"journal":{"name":"SSRN Electronic Journal","volume":"94 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141234674","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}
Purpose- The main purpose of this article is to make a comprehensive review of existing studies on prepayment and default (competing risk). This review enables to shed light on the main determinant of prepayment and default as well as on methods used to model competing risk. Methodology- A comprehensive review of existing studies/articles. Findings- More recently proposed machine learning methods (Random Survival Forest and Random Competing Risks Forests, as well as the DeepHit model and Dynamic DeepHit model) enable to take into account the complex/no-linear response of prepayment and default to their determinant more efficiently. Conclusion- To model properly/correctly the prepayment and default risks it is important to consider the fact that the exercise of the prepayment option brings an end to the default option, and vice versa. These both risks should be modelled together: competing risk. Furthermore, models/methods accounting the complex/no-linear impact of explanatory variables on prepayment and default risks should be used; such as the Random Survival Forest and Random Competing Risks Forests, as well as the DeepHit model and Dynamic DeepHit model.
{"title":"Prepayment and Default risk: A Review","authors":"Sukriye Tuysuz","doi":"10.2139/ssrn.4823704","DOIUrl":"https://doi.org/10.2139/ssrn.4823704","url":null,"abstract":"Purpose- The main purpose of this article is to make a comprehensive review of existing studies on prepayment and default (competing risk). This review enables to shed light on the main determinant of prepayment and default as well as on methods used to model competing risk.\u0000Methodology- A comprehensive review of existing studies/articles.\u0000Findings- More recently proposed machine learning methods (Random Survival Forest and Random Competing Risks Forests, as well as the DeepHit model and Dynamic DeepHit model) enable to take into account the complex/no-linear response of prepayment and default to their determinant more efficiently.\u0000Conclusion- To model properly/correctly the prepayment and default risks it is important to consider the fact that the exercise of the prepayment option brings an end to the default option, and vice versa. These both risks should be modelled together: competing risk. Furthermore, models/methods accounting the complex/no-linear impact of explanatory variables on prepayment and default risks should be used; such as the Random Survival Forest and Random Competing Risks Forests, as well as the DeepHit model and Dynamic DeepHit model.\u0000","PeriodicalId":507782,"journal":{"name":"SSRN Electronic Journal","volume":"44 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141275695","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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