A re-examination of the impact of credit ratings and economic factors on state bond yields

1994 ◽  
Vol 4 (1) ◽  
pp. 59-78 ◽  
Author(s):  
Chihwa Kao ◽  
Chunchi Wu
2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Radeef Chundakkadan

AbstractIn this study, we investigate the impact of the light-a-lamp event that occurred in India during the COVID-19 lockdown. This event happened across the country, and millions of people participated in it. We link this event to the stock market through investor sentiment and misattribution bias. We find a 9% hike in the market return on the post-event day. The effect is heterogeneous in terms of beta, downside risk, volatility, and financial distress. We also find an increase (decrease) in long-term bond yields (price), which together suggests that market participants demanded risky assets in the post-event day.


2020 ◽  
Vol 12 (1) ◽  
pp. 626-636
Author(s):  
Wang Song ◽  
Zhao Yunlin ◽  
Xu Zhenggang ◽  
Yang Guiyan ◽  
Huang Tian ◽  
...  

AbstractUnderstanding and modeling of land use change is of great significance to environmental protection and land use planning. The cellular automata-Markov chain (CA-Markov) model is a powerful tool to predict the change of land use, and the prediction accuracy is limited by many factors. To explore the impact of land use and socio-economic factors on the prediction of CA-Markov model on county scale, this paper uses the CA-Markov model to simulate the land use of Anren County in 2016, based on the land use of 1996 and 2006. Then, the correlation between the land use, socio-economic data and the prediction accuracy was analyzed. The results show that Shannon’s evenness index and population density having an important impact on the accuracy of model predictions, negatively correlate with kappa coefficient. The research not only provides a reference for correct use of the model but also helps us to understand the driving mechanism of landscape changes.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Abu Quwsar Ohi ◽  
M. F. Mridha ◽  
Muhammad Mostafa Monowar ◽  
Md. Abdul Hamid

AbstractPandemic defines the global outbreak of a disease having a high transmission rate. The impact of a pandemic situation can be lessened by restricting the movement of the mass. However, one of its concomitant circumstances is an economic crisis. In this article, we demonstrate what actions an agent (trained using reinforcement learning) may take in different possible scenarios of a pandemic depending on the spread of disease and economic factors. To train the agent, we design a virtual pandemic scenario closely related to the present COVID-19 crisis. Then, we apply reinforcement learning, a branch of artificial intelligence, that deals with how an individual (human/machine) should interact on an environment (real/virtual) to achieve the cherished goal. Finally, we demonstrate what optimal actions the agent perform to reduce the spread of disease while considering the economic factors. In our experiment, we let the agent find an optimal solution without providing any prior knowledge. After training, we observed that the agent places a long length lockdown to reduce the first surge of a disease. Furthermore, the agent places a combination of cyclic lockdowns and short length lockdowns to halt the resurgence of the disease. Analyzing the agent’s performed actions, we discover that the agent decides movement restrictions not only based on the number of the infectious population but also considering the reproduction rate of the disease. The estimation and policy of the agent may improve the human-strategy of placing lockdown so that an economic crisis may be avoided while mitigating an infectious disease.


2011 ◽  
Vol 26 (S2) ◽  
pp. 1795-1795
Author(s):  
D. Bhugra

IntroductionWith the process of globalisation in full flow, the movement of people and products across the globe has brought a series of difficulties. With migration the socio-economic status of the individuals may change with the likelihood that this status will be lower rather than higher, although depending upon the reasons for migration this may change too.ObjectivesLiterature shows that low socio-economic status is associated with a higher level of psychiatric morbidity.AimsWhether migration acts as a mediator needs to be investigated further.MethodsVarious studies have shown that rates of psychosis are elevated in migrants though these rates are differentially increased in different groups indicating that factors other than migration may be at play.ResultsIn this presentation the literature and link the acculturation and cultural identity with post-migration experiences will be reviewed.ConclusionA link exists between the perceptions within cultures and level of economic development of what constitutes mental health. The state of advancement of mental health services of a country will certainly have a large impact on prevalence rates. Further investigation should be carried out to examine in greater depth the relationship between social inequality and disorder prevalence, as distinct from income inequality.


1973 ◽  
Vol 26 (4) ◽  
pp. 575-583
Author(s):  
JOHN S. McCALLUM

2021 ◽  
Vol 24 (1) ◽  
pp. 38-54
Author(s):  
Tadeusz A. Grzeszczyk ◽  
Waldemar Izdebski ◽  
Michał Izdebski ◽  
Tadeusz Waściński

Poland is not one of the leaders in the use of renewable energy sources (RES), and most energy is still produced using hard coal and lignite. Therefore, there are noteworthy emissions of air pollution (including ashes and greenhouse gases), and the Polish energy sector is characterized by a substantial degree of carbonization, which, as a result, threatens to expressively increase the costs of electricity production, leading to financial penalties imposed by the EU. The aim of this paper is to analyze socio-economic factors influencing the development of the RES sector in Poland. According to this aim, expert research was carried out, in which the factors influencing development potential of RES were assessed at two levels (level II – 5 factors, level III – 15 factors) according to the factor tree analysis. Based on the analysis of the level II factors, it can be concluded that the development of the RES sector in Poland will depend to a decisive extent on factors such as: EU decisions and Polish legislation affecting the development of the RES sector in Poland, prices and availability of conventional energy carriers. Other two factors – regional policy on ecology and ecological awareness in Poland – have so far little impact on the development of this sector in the state. The analysis of the level III factors shows that the greatest impact on the development of the RES sector in Poland is the influence of European lobbying of manufacturers of machinery and equipment for renewable energy production on EU law, the impact of Polish lobbying of conventional energy producers on Polish law in the production of renewable energy and the influence of European lobbying of renewable energy producers into EU law.


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