A review of the blue economy, potential, and opportunities in seven Caribbean nations pre-COVID-19

Caribbean countries face many challenges to effectively implement and benefit from the blue economy. This study synthesized current available information from the literature about the main blue economy activities in the Bahamas, Barbados, Belize, Guyana, Jamaica, Trinidad and Tobago, and Suriname, prior to the COVID-19 pandemic, to highlight their value in the context of blue economic recovery. This timestamp of data provides a point of comparison to understand the vulnerability of blue economy sectors to external shocks. The top performing sectors prior to the pandemic were shipping and tourism, both of which were significant contributors to the GDP. The other sectors (e.g. fisheries, aquaculture, pharmaceuticals, etc.) in some countries were well established and in others, at a minimum, displayed potential for continued development. To valorize the blue economy in a post pandemic recovery, there are three core areas of opportunity: sustainable resource extraction and production;cultivated economic development;and improved ecosystem economic valuations. Harnessing these opportunities will require a transition from a traditional ocean economy towards a coordinated blue economy, including the adoption of effective governance and sustainability principles, improved social, economic, and environmental valuations, and sustainable financing, as well as a more regional coordinated approach to the management of resources.

The Application of ARIMA Model in Retailing Industry and Forecasting on Economic Trend of Industry

The COVID-19 pandemic has severely impacted our lives, and many industries are experiencing instability. We are curious to see whether retailing businesses, one of the most robust industries in US, have been affected, and if affected, how have the industry been affected. In order to gain the required insight, we first acquire stock prices of six representative retailing companies in US, then we apply ARIMA model on the data to forecast their trends in the near future, which will imply the general robustness of the industry. This procedure includes testing the stationary of time series data of stocks, and finding the suitable ARIMA parameters for each stock, using various methods. Accuracy metrics are brought into discussion to determine how accurate our forecast is. Finally, we draw the conclusion that ARIMA model, being a suitable method for our case of study, has given us desirable result: the stocks of 6 selected retailing companies will perform steadily with slight increase at the end of the year. There are several practical values or our research: By applying ARIMA models on stocks of retailing companies, we discovered that application of such models on retailing industry is not only pragmatic, but effective;and the results of our analysis provide future researchers with insight of economy of this era of pandemic. © 2022 SPIE.

The Effects of Homeownership on Wealth Distribution

Within the broader context of new dimensions of poverty such as housing poverty, energy poverty, etc., this article describes dependencies between household income, real estate ownership and socio-economic trends. We argue that income is not the principal determinant for home ownership rate, but rather recent lifestyle changes can better explain the homeownership decreasing trend in developed economies. Job mobility, family formation determinants and demographical trends seem to find well-supported basis in literature and data. Using data for the US states we have proved that the decreasing rate of home ownership may be explained by social aspects of changing lifestyle such as increasing share of population moving from rural areas to cities, age of marriage, divorce rate, career-oriented lifestyle, rather than by the frequently cited price-income ratio. We have also observed a short-term correlation between financing availability and homeownership rate, but we conclude that property prices would adjust to lose monetary policy without any long-term effect on homeownership rate. It results that government or monetary policies aimed to cushion the housing unavailability (recently increasing value of price-income) ratio may distort the housing market. We propose a new insight in the housing availability discussion.

Using machine learning techniques to study economic trends in various U.S. industries in the post-epidemic era

The aim of the project is to predict and analyse broad trends across the US economy using stock data from mainstream companies in six industries on Forbes 2000 and data from COVID-19. A time series analysis approach was used to predict the daily increases in each company's share price. The following five supervised learning techniques (logistic regression, random forest, decision tree, neural network and XGBoost) were used. As the accuracy of the results predicted by the different models for each company varies considerably, only the results predicted by the most accurate model for each company have been selected for analysed. The results show that the Electronic Pleased Technology Industry and the Social Entertainment Internet Industry remain break-even for COVID-19;the E-Commerce Industry shows a significant increase;The Financial Services Industry shows a significant drop in share price, while the Insurance Industry and Pharmaceutical Industry show a small drop in share price. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.

The New Great Depression in the Context of Coronavirus Pandemic: A Test of Keynesian Theory for Russian Regions

J.M. Keynes is the author of the economic model which made it possible to overcome the Great Depression in the United States. The cornerstone of the theory is income. The regulatory measures of J.M. Keynes start from the fact that the behavior of the population in the long and short term is different. Using the data on the income of the population in the regions of Russia before the crisis and during crisis periods (caused by the coronavirus pandemic) of 2018–2020, the authors test a hypothesis connected with the transformation of behavior models. In particular, the issue of changes in the proportions of savings and consumption of the population in the regions of Russia was studied. To confirm the hypothesis defined in the study, the clustering of regions was carried out, which allows us to draw conclusions about the isolation of more homogeneous groups of regions. The identified five clusters allow us to fully determine the main trends of consumer behavior and confirm the hypothesis set in the study. The results obtained allow us to speak about the relevance of the application of J.M. Keynes’ approaches to this crisis situation. It is also important to speak about the possibility of further research of the policy proposed at the moment which deals with the issues facing the global economy. The calculation of the ratio of the marginal and average consumption rate makes it possible to use the tools of the US economic policy of the early 20 th century in the modern social and economic reality. Using this research, the trends were identified and new threats associated with the virtualization of the economy were identified, which can become a kind of a trigger for a new Great Depression. The most important tasks at the moment are a deep fundamental study and description of the patterns of development of regional economic systems of various types and an analysis of the impact of various negative factors and shocks on their dynamics.Alternate : Дж.Ðœ. Кейнса принято считать автором экономической модели, позволившей преодолеть Великую депрессию в США. Краеугольным камнем теории является доход. Регуляционные меры Дж.Ðœ. Кейнса исходили из того, что поведение населения в долгосрочном и краткосрочном периодах отличается. По данным о доходах населения в регионах России докризисного и кризисного (вызванного пандемией коронавируса) периодов 2018–2020 гг. авторы тестируют гипотезу, связанную с трансформацией моделей поведения. Ð’ частности, исследовался вопрос изменения пропорций сбережения и потребления, осуществляемых населением регионов России. Для подтверждения поставленной в исследовании гипотезы проведена кластеризация, позволяющая сделать выводы относительно более однородных групп регионов. Выделенные пять кластеров позволяют в полной мере определить основные векторы потребительского поведения и подтвердить поставленную в исследовании гипотезу. Полученные результаты позволяют говорить об уместности применения подходов Дж.Ðœ. Кейнса к данной кризисной ситуации, а также о возможности дальнейшего исследования политики, предлагаемой в настоящий момент, для решения во ¿Ñ€Ð¾ÑÐ¾Ð², стоящих перед мировой экономикой. Определение соотношения предельной и средней нормы потребления дает возможность имплементации инструментов экономической политики США начала ХХ в. в современную социально-экономическую реальность. На основе проведенного исследования были определены тренды и выявлены новые угрозы, связанные с виртуализацией экономики, которые могут стать своеобразным триггером новой Великой депрессии. Важнейшими задачами в настоящий момент нам видятся глубокое фундаментальное изучение и описание закономерностей развития региональных экономических систем различных типов, а также анализ влияния различных негативных факторов и шоков на их динамику.

The fourth industrial revolution and higher education in africa: A systematic review and implications

The fourth industrial revolution is upon us with several countries being in the preliminary stages. It is said to change the way we live and the way we work. The fourth industrial revolution is about digitalisation and automation of work and is viewed by many as the most important societal and economic trend in the world. This is a trend that will change the nature of work, societies, and businesses in the coming decades. The fourth industrial revolution has a significant impact on education systems around the world which is why Africa needs to continuously research how best they can incorporate the fourth industrial revolution into their current education systems. The Covid-19 pandemic has led to a massive impact on people in all industries and sectors around the world including the education sector. Furthermore, the Covid-19 pandemic is forcing most universities to use online distance learning and e-learning as this has increasingly become important in maintaining prominent levels of adaptation in the future. This is one of the reasons why the fourth industrial revolution has become an important subject. This paper looked at the fourth industrial revolution and what it means for higher education in Africa. The methodology includes reviewing of 42 scholarly journal articles. The main purpose of this study was to get an understanding of the emerging technologies in industries and education and the threats and opportunities that are posed by the fourth industrial revolution in Africa. The paper concluded by reviewing journal articles on how best African universities can create capacity for the fourth industrial revolution. © the authors, 2021. All Rights Reserved.

Comparative study between admission, orthopaedic surgery, and economic trends during Covid-19 and non-Covid-19 pandemic in an Italian tertiary hospital: a retrospective review.

BACKGROUND: The COVID-19 pandemic represents one of the most massive health emergencies in the last century and has caused millions of deaths worldwide and a massive economic and social burden. The aim of this study was to evaluate how the COVID-19 pandemic-during the Italian lockdown period between 8 March and 4 May 2020-influenced orthopaedic access for traumatic events to the Emergency Department (ER). METHODS: A retrospective review of the admission to the emergency room and the discharge of the trauma patients' records was performed during the period between 8 March and 4 May 2020 (block in Italy), compared to the same period of the previous year (2019). Patients accesses, admissions, days of hospitalisation, frequency, fracture site, number and type of surgery, the time between admission and surgery, days of hospitalisation, and treatment cost according to the diagnosis-related group were collected. Chi-Square and ANOVA test were used to compare the groups. RESULTS: No significant statistical difference was found for the number of emergency room visits and orthopaedic hospitalisations (p < 0.53) between the year 2019 (9.5%) and 2020 (10.81%). The total number of surgeries in 2019 was 119, while in 2020, this was just 48 (p < 0.48). A significant decrease in the mean cost of orthopaedic hospitalisations was detected in 2020 compared (261.431 euros, equal to - 52.07%) relative to the same period in 2019 (p = 0.005). Although all the surgical performances have suffered a major decline, the most frequent surgery in 2020 was intramedullary femoral nailing. CONCLUSION: We detected a decrease in traumatic occasions during the lockdown period, with a decrease in fractures in each district and a consequent decrease in the diagnosis-related group (DRG).