{"title":"Global Spread and Socio-Economic Determinants of COVID-19 Pandemic","authors":"Varinder Jain, Lakhwinder Singh","doi":"10.2139/ssrn.3748209","DOIUrl":"https://doi.org/10.2139/ssrn.3748209","url":null,"abstract":"Covid-19 pandemic being highly lethal has spread so swiftly across the globe that it has infected more than three million persons across 209 countries within a short time-span of 107 days since January 13, 2020 Given such situation, this paper examines differences across countries in terms of Covid-19 infections, testing and deaths A novel approach has been developed to examine socio-economic variables that determine a nation's exposure to Covid-19 infections and deaths The most important methodological contribution has been to devise an objective criterion for identifying the best and worst performing nations in terms of controlling infection and mortality of human beings An important finding emerging from the regression analysis establishes the fact that democracy and good governance plays significant role in curtailing mortality rates But, at the same time, there also takes place a rise in infected patients in the presence of democracy and higher per capita income These inferences are found to be robust and replicated on subsequent regression analysis of 24 33 million infections by August 27, 2020 The policy implication that results from the analysis is that in the absence of definite treatment (like vaccine), physical / social distancing, masks and hand-hygiene etc can save humans from infections and mortality","PeriodicalId":13563,"journal":{"name":"Insurance & Financing in Health Economics eJournal","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72995337","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":"Modeling Turning Points In Global Equity Market","authors":"D. Ahelegbey, Monica Billio, R. Casarin","doi":"10.2139/ssrn.3727784","DOIUrl":"https://doi.org/10.2139/ssrn.3727784","url":null,"abstract":"Turning points in financial markets are often characterized by changes in the direction and/or magnitude of market movements with short-to-long term impacts on investors' decisions. This paper develops a Bayesian technique to turning point detection in financial equity markets. We derive the interconnectedness among stock market returns from a piece-wise network vector autoregressive model. The empirical application examines turning points in global equity market over the past two decades. We also compare the COVID-19 induced interconnectedness with that of the global financial crisis in 2008 to identify similarities and the most central market for spillover propagation.","PeriodicalId":13563,"journal":{"name":"Insurance & Financing in Health Economics eJournal","volume":"110 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77697850","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":"Technology and Foreign Direct Investment’s Relationship With Trade","authors":"Martha Latinggi","doi":"10.2139/ssrn.3740012","DOIUrl":"https://doi.org/10.2139/ssrn.3740012","url":null,"abstract":"Trade plays an important role in contributing towards the economic performance of a country. For certain country, especially small nations, trade performance affect significantly the gross domestic product (GDP) of a country. In discussing this, there is a large body of literature which explain factors that influence trade. Population of trading countries, bilateral exchange rate, income of trading countries, trade agreements involving trading nations, geographical distance between trading nations, geographical condition between trading countries, the existence of multinational companies in partner trading countries, historical connection and similarities of language, foreign direct investment and technological advancement and adaptation, culture and food are among factors that have been discussed extensively in the literature.","PeriodicalId":13563,"journal":{"name":"Insurance & Financing in Health Economics eJournal","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78470433","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 global state of mental health: trends and correlates","authors":"Sumit S. Deole","doi":"10.2139/ssrn.3425624","DOIUrl":"https://doi.org/10.2139/ssrn.3425624","url":null,"abstract":"While mental health issues often hijack public health debates, a comprehensive analysis describing the state of global mental health is missing from the economics literature. This paper uses extensive country-level panel data for 170 countries spanning between 1990 and 2015 and provides new evidence on the trends and correlates of mental health. Contrary to popular belief, the mental health situation has been relatively stable globally and has shown slight improvement since the early 2000s. The improvement applies to male and female populations residing in richer and poorer countries in the world. The analysis of other mental illnesses shows that the state of depression disorders improved, whereas eating disorders, bipolar disorders, and Schizophrenia worsened during the sample period. Notably, the prevalence of drug and alcohol abuse disorders and anxiety disorders did not observe any change. Concerning country-level correlates of mental health, findings show that obesity prevalence is associated with worsened mental health, whereas HDI improves mental health. Interestingly, the country's access to digital technology (internet and mobile usage) and measures such as educational attainment, life expectancy, per capita healthcare spending, and per capita GDP are not associated with overall mental health. Finally, analysis of the gender gap in mental health indicates that mobile subscription rates are associated with reducing the gender gap, whereas obesity prevalence is related to its widening.","PeriodicalId":13563,"journal":{"name":"Insurance & Financing in Health Economics eJournal","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85492026","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":"Analyzing Structural Breaks and Volatility Spillover due to Infectious Disease in Japan: Using Spillover Networks","authors":"Hideto Shigemoto, Takayuki Morimoto","doi":"10.2139/ssrn.3715379","DOIUrl":"https://doi.org/10.2139/ssrn.3715379","url":null,"abstract":"In this paper, we investigate structural breaks and volatility spillover effects on the Japanese stock market. To detect structural breaks, we use an iterated cumulative sum of squares (ICSS) algorithm, which can identify multiple change points. To measure the volatility spillover effect, we apply the BEKK-GARCH model. As a result, many sectors have structural breaks that occurred after the novel coronavirus disease 2019 (COVID-19) shock after January 2020. Furthermore, we find that the transportation sector is heavily affected by volatility spillover during years of infectious disease outbreaks and a pure economic shock affects the financial sector.","PeriodicalId":13563,"journal":{"name":"Insurance & Financing in Health Economics eJournal","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76802887","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":"Online Appendix to the Deterrent Effect of Tort Law: Evidence from Medical Malpractice Reform","authors":"Zenon Zabinski, Bernard Black","doi":"10.2139/ssrn.3319933","DOIUrl":"https://doi.org/10.2139/ssrn.3319933","url":null,"abstract":"Full article is at: <a href=\"http://ssrn.com/abstract=2161362\">http://ssrn.com/abstract=2161362</a><br><br>This online appendix contains additional results for Zabinski and Black (2020), The Deterrent Effect of Tort Law: Evidence from Medical Malpractice Reform. <br><br>","PeriodicalId":13563,"journal":{"name":"Insurance & Financing in Health Economics eJournal","volume":"125 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91550219","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}
S. Rizvi, L. Yarovaya, Nawazish Mirza, Bushra Naqvi
{"title":"The impact of COVID-19 on valuations of non-financial European firms","authors":"S. Rizvi, L. Yarovaya, Nawazish Mirza, Bushra Naqvi","doi":"10.2139/ssrn.3705462","DOIUrl":"https://doi.org/10.2139/ssrn.3705462","url":null,"abstract":"This paper assesses the impact of the COVID-19 pandemic on valuation of non-financial firms in the European Union (EU) using a stress testing scenario approach. Particularly, the paper investigates to what extent the COVID-19 may deteriorate the value of non-financial firms in the 10 EU countries in order to provide a robust anchor to policy makers in formulating strategic government interventions. We utilize a sample of 5342 listed non-financial firms across 10 EU member states that have consistent analyst coverage from 2010 to 2019. First, we estimate the input sensitivities of free cash flow and residual income models using a random effect panel employed to in-sample data. Second, based on these sensitivities, we compute the model driven ex post valuations and compare their robustness with actual price and analyst forecasts for the same period. Finally, we introduce multiple stress scenarios that may emanate from COVID-19, i.e. decline in expected sales and increase/decrease in cost of equity.Our findings show a significant loss in valuations across all sectors due to a possible decline in sales and increase in cost of equity. In the extreme cases, average firms in some sectors may lose up to 60% of their intrinsic value in one year. The results remained consistent regardless of the cash flow or residual income driven valuation. While the impact of global financial crisis (2007-2008) and European crisis (2010-2012) on non-financial firms is well-documented, this paper is the first study that analyzed the impact of the COVID-19 crisis on the non-financial firms’ valuation in the European Union and reports that pandemic is the main driver behind the shareholder value destruction.","PeriodicalId":13563,"journal":{"name":"Insurance & Financing in Health Economics eJournal","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84892646","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}
I. B. P. Suamba, I Gusti Bagus Rai Utama, Ni Putu Dyah Krismawintari
{"title":"Social Ethics and Balinese Physical Distancing in Reducing the Spread of COVID-19","authors":"I. B. P. Suamba, I Gusti Bagus Rai Utama, Ni Putu Dyah Krismawintari","doi":"10.2139/ssrn.3693512","DOIUrl":"https://doi.org/10.2139/ssrn.3693512","url":null,"abstract":"The purpose of this study is to analyze how effective government policies are in implementing physical distancing in Bali. The survey was conducted to collect data using an online questionnaire by 109 people of different backgrounds and ages. After analyzing the data, the overall conclusion concludes that the appeal for physical distancing did not significantly affect several activities that could predictably increase the transmission of COVID-19 in Bali. On the same page, the COVID-19 outbreak felt by respondents has damaged their jobs in Bali, which is dominated by the tourism sector. It appears that there are two contradictions between physical distancing calls that are viewed as interfering with respondents' work activities. On the other hand, it is predicted that the outbreak of COVID-19 will increase if physical distancing is not performed, which is worse. This study recommended containing the spread of the COVID-19 outbreak.","PeriodicalId":13563,"journal":{"name":"Insurance & Financing in Health Economics eJournal","volume":"69 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81731355","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":"Multi-State Health Transition Modeling Using Neural Networks","authors":"Qiqi Wang, Katja Hanewald, Xiaojun Wang","doi":"10.2139/ssrn.3699161","DOIUrl":"https://doi.org/10.2139/ssrn.3699161","url":null,"abstract":"This article proposes a new model that combines a neural network with a generalized linear model (GLM) to estimate and predict health transition intensities. We introduce neural networks to health transition modeling to incorporate socioeconomic and lifestyle factors and to allow for linear and nonlinear relationships between these variables. We use transfer learning to link the models for different health transitions and improve the model estimation for health transitions with limited data. We apply the model to individual-level data from the Chinese Longitudinal Healthy Longevity Survey from 1998–2018. The results show that our model performs better in estimation and prediction than standalone GLM and neural network models. We provide new estimates of the life expectancies for a range of population subgroups. We also describe a wide range of possible applications for further health-related research, including risk prediction using health claim data and mortality prediction based on individual-level mortality data.","PeriodicalId":13563,"journal":{"name":"Insurance & Financing in Health Economics eJournal","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80921089","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 Review of COVID-19 and Its Waterfall Effect on the Changed World","authors":"M. Kapur, Tirupathi Anand, A. Banerjee","doi":"10.2139/ssrn.3688847","DOIUrl":"https://doi.org/10.2139/ssrn.3688847","url":null,"abstract":"2019 novel coronavirus has affected over 19.3 million people and caused over 718 thousand deaths globally (as at 7 August 2020). The disease was named as “Covid19” and the virus that causes it was Severe Acute Respiratory Syndrome Corona Virus -2 (SARS-COV-2). On the eve of 2020, when the whole world was celebrating the new year, the virus was unleashing and conquering new territories, minute by minute. So, how come a small virus that is said to have originated from Wuhan, China was able to create such a big havoc? How did a flu-like-symptom virus was able to shackle economies and change the world we live in? What caused Governments to announce relief, fiscal and economic packages to prevent the large-scale economic collapse? The response lies in the way the virus made man-kind to live in the new world. Social distancing was the new norm that led to fewer interactions among people. Next, mass scale shut downs announced by the governments led to closure of financial markets, stock exchanges, corporate offices, exchange of trade as well as several events. No country was immune by the shocks caused by the waterfall effect of COVID19. The compounding rate at which the virus spread hinted several sectors were going to be severely disrupted. The current paper will analyze the waterfall effect of COVID19 on several sectors in the first half of 2020 (Jan to June 2020) and ascertain the fiscal, economic and monetary policies announced by governments in the top 5 affected countries and UAE as at 7 August 2020. The study will qualitatively ascertain how lockdowns and social distancing changed the world we live in and provide certain recommendations for future pandemics/ crises as part of research contribution.","PeriodicalId":13563,"journal":{"name":"Insurance & Financing in Health Economics eJournal","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85072174","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}