Energy Logistic Regression and Survival Model: Case Study of Russian Exports.

The importance of environmental sustainability is becoming more and more obvious, so the rationale behind long-term usage of solely non-renewable energy sources appeared questionable. This study aims to identify, using Kaplan-Meier survival analysis and logistic regressions, the main determinants that affect the duration of Russian non-renewable energy exports to different regions of the world. Data were retrieved from the databanks of the World Development Indicators (WDI), World Integrated Trade Solution (WITS), and the French Centre for Prospective studies and International Information (CEPII). The obtained results point to the fact that approximately 52% of energy products survive beyond their first year of trading, nearly 38% survive beyond the second year, and almost 18% survive to the twelfth year. The survival of Russian non-renewable energy exports differs depending on the region, and the affecting factors are of different importance. The duration of Russian non-renewable energy exports is significantly linked to Russia's GDP, Total export, and Initial export values. A decline in Russia's GDP by 1% is associated with an increasing probability of a spell ending by 2.9% on average, in turn growing Total export and Initial export values positively linked with the duration of non-renewable energy exports from Russia. These findings may have practical relevance for strategic actions aimed at approaching both energy security and environmental sustainability.

Services as a Determinant of Botswana's Economic Sustainability.

In 2015, the services sector contributed about 58 percent to the gross domestic product (GDP) in Sub-Saharan Africa (SSA), which was a significant increase from the 47.6 percent observed in 2005, and a shift from the mining, agriculture, and manufacturing sector. This increase calls to support services as the catalyst for sustained economic development as indicated by the structural transformation and modernization theories. The main objective of this paper was to examine the relationship between and the impact of services on the economic development in Botswana and make recommendations on how Botswana can apply well-directed policies to improve its services sector and diversify its impact on other sectors and GDP, making it less reliant on mining which is vulnerable to price volatilities. The paper applied econometric modeling and results of the Autoregressive-Distributed Lag (ARDL) Bounds test for cointegration indicate that services and other industries services, agriculture, industry, mining, and investment impact GDP over the short and long run. These variables impacted GDP and converged to equilibrium at the speed of 46.89 percent, with a percent change in services in the short and long run impacting GDP by 0.328 and 0.241 percentages, respectively, and the outcome of the Wald test indicated causality from services to GDP growth. The services sectors have contributed over 40 percent to the country's GDP from 1995 to the present, though the sectors have not gone without challenges with limitations such as limited infrastructure development; poverty and inequality; unemployment of over 20 percent; disease, which has dampened productivity; and lack of proper governance and accountability, which has created a habitat for an increase in cases of corruption in state and private entities. The findings of the study with the lessons learned from other studies with similar findings recommend that the government of Botswana should formulate suitable policies and strategies for services diversification. This is by expanding the market for the sector in areas such as tourism that were impacted by the COVID-19 pandemic, escalating investments by instituting strategies to attract and grow domestic and foreign investments, and improve on management of institutions and resources.

Influence of precipitation and temperature on maize production in the Czech Republic from 2002 to 2019.

Maize is one of the important food crops in the Czech Republic, its growth and productivity are influenced by climate change. This study investigated the influence of precipitation under recent climate change on maize yield both for grain and silage in the whole Czech Republic during 2002-2019. Total maize yield and yield rate increased in the Czech Republic from 1961 to 2010, but they became to decrease after 2010. This is in line with the tendency of decreased precipitation and an increase in temperature after 2010, and changes are especially significant during the maize growing period, which indicates the importance of temperature and precipitation. In detail, there is a low to moderate negative correlation (-0.39 to -0.51) between grain maize yield and the average temperature in August for almost all the regions. While there is a low negative correlation between silage maize yield with the average temperature in July and August from some regions. The precipitation in July exhibited moderate to high positive correlation (0.54-0.79) to grain maize yield rate for almost all the regions, and it had low to moderate positive correlation (0.35-0.70) to silage maize yield rate for all the regions. Water deficit exhibited a negative correlation with both maize yield rate and its influence mainly in July for silage but both in July and August for grain. Farmer's profit from grain maize is influence by yield rate, temperature, precipitation, and water deficit. A positive correlation was found between profit and grain yield rate and precipitation from July and August, while a negative correlation was detected between profit and water deficit and the average temperature in July and August. In conclusion, our results pointed out the factors influencing maize yield rate under changing climate conditions in the Czech Republic, and it warrants further studies on how to maintain maize production in a changing climate.

Sugar Futures as an Investment Alternative During Market Turmoil: Case Study of 2008 and 2020 Market Drop.

In times of turbulent financial markets, investors all around the globe seek for opportunities protecting their portfolios from devastating losses. Historically, commodities were regarded as a safe haven providing sound returns which offset potential losses arising from dropping equity prices in times of market turmoil. While sugar would have provided a proper hedge against crashing equity markets during the initiation of the 2007 bear market and the onset financial crisis, sugar prices dropped likewise equity during the outbreak of COVID-19 and the consequent market shock. The goal of the paper is to elaborate on the differences in sugar price dynamics during the aforementioned economic disruptions by employing a multiple linear regression approach using data from the last quarter 2007 as well as the first quarter of 2019. The findings suggest that the behavioral differences stem from the deep link between oil and sugar prices. While oil did not influence the price of sugar during the outbreak of the financial crisis, it had tremendous influence on sugar prices during the outbreak of the corona crisis. Currently, sugar provides a substantial upside for an investor's portfolio since the demand and supply-side shock on oil prices due to corona crisis as well as the Saudi-Russian oil price war drove oil prices and consequently sugar prices to a historic low. Sugar futures provide the advantage of offering a smaller contract size compared to oil futures, and even though both commodities trade in contango as of March 2020, the sugar future curve is by far not as steep as the oils. Resultingly, investors benefit from lower rollover costs while prospering from a potential surge in oil prices.