This study investigates the propagation power and effects of the coronavirus disease 2019 in light of published data. We examine the factors affecting COVID-19 together with the spatial effects, and use spatial panel data models to determine the relationship among the variables including their spatial effects. Using spatial panel models, we analyse the relationship between confirmed cases of COVID-19, deaths thereof, and recovered cases due to treatment. We accordingly determine and include the spatial effects in this examination after establishing the appropriate model for COVID-19. The most efficient and consistent model is interpreted with direct and indirect spatial effects.
Identifying the economic factors that affect economic growth is an important issue for each economy. It is a matter of debate to determine the building blocks of non-oil Gross Domestic Product (GDP) growth, especially in oil-rich countries, such as Azerbaijan. Using the Fully Modified Ordinary Smallest Square approach between 2005 and 2019, this study aims to investigate the relationship between real non-oil GDP growth of Azerbaijan and exchange rate and oil prices. Zivot-Andrews unit root test is applied to deal with structural breaks in data and the Gregory-Hansen (GH) test for robustness. While conventional unit-root tests decision that the series are not stationary at their level, the Ziwot-Andrews test decision that the series is stationary with structural break. According to the GH test result, there is a structural break date in the long-run relationship between the real nonoil GDP growth and the oil price and the USD/AZN exchange rate in early 2009. According to Fully Modified Ordinary Least Squared results, the increase in oil price increases real non-oil GDP growth, and the increase in USD/AZN exchange rate has a decreasing effect on it. This study contains considerable information for future economic policies for oil-rich countries that want to develop the non-oil sector.
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