In this article, we discuss a new proposed concept of economic engineering that seeks to innovate a new model by combining the theories of Karl Marx and Adam Smith, taking into consideration main economic factors to create a sustainable and inclusive economic system that addresses existing challenges and provides a roadmap for future economic growth. Through a brief analysis of the existing gaps between Marxist and Smithian economics, we developed a new economic matrix that leverages the strengths of both theories while also incorporating the latest insights from modern economic research. Our novel approach to economic engineering represents a fresh perspective on the economy and offers practical tool for addressing the most pressing challenges facing society today.

The aim of this article is to examine the impacts of Coronavirus Disease -19 (Covid-19) vaccines on economic condition and sustainable development goals. In other words, we are going to study the economic condition during Covid19. We have studied the economic costs of pandemic, benefits in terms of gross domestic product (GDP), public finances and employment, investment on vaccines around the world, progress and totally the economic impacts of vaccines and the impacts of emerging markets (EM) on achieving sustainable development goals (SDGs), including no poverty, good health and well-being, zero hunger, reduced inequality etc. The importance of emerging economies in reducing the harmful effects of the Corona has also been noted. We have tried to do experimental results and forecast daily new death cases from Feb-2020 to Aug-2021 in Iran using Artificial Neural Network (ANN) and Beetle Antennae Search (BAS) algorithm as a case study with econometric models and regression analysis. The findings show that Covid19 has had devastating economic and health effects on the world, and the vaccine can be very helpful in eliminating these effects specially in long-term. We observed that there is inequality in the distribution of Corona vaccines in rich countries compared to poor which EM can decrease the gap between them. The results show that both models (i.e., Artificial intelligence (AI) and econometric models) almost have the same results but AI optimization models can robust the model and prediction. The main contribution of this article is that we have surveyed the impacts of vaccination from socio-economic viewpoint not just report some facts and truth. We have surveyed the impacts of vaccines on sustainable development goals and the role of EM in achieving SDGs. In addition to using the theoretical framework, we have also used quantitative and empirical results that have rarely been seen in other articles.

Using a desktop review of literature, the effect of illegal capital flows on the economic performance of Sub-Saharan Africa is examined. The review focus on articles with attention to illegal capital flows and their effects on the economic performance of Sub-Saharan Africa as a whole. By way of sampling method, purposive sampling was used, and so the desktop review focused purposively on articles published on issues of illicit financial flows and their effects on the economic performance of Ghana and Sub-Saharan Africa as a whole. The review found a high propensity of trade mis-invoicing and thus high illicit financial flows, transactions across boarders from developing countries and for that matter Sub-Saharan Africa to the developed economies. Therefore, the research recommends that customs divisions in sub-Saharan Africa should have up-to-date commodity-level world pricing information to make relatively better comparisons to detect mis-pricing and avoid such falsification and manipulation in trade. Given the high propensity of trade mis-invoicing resulting in high illicit financial flows, we recommend that cross-border transactions from developing sub-Saharan African countries be subjected to heightened scrutiny to curtail any potential traces of falsification in trade for tax evasion.

The number of poor people continues to rise in Africa, despite a slow decline in the poverty rate. Africa with a population of 422 million poor people, representing about 70 per cent of the world's poorest people shows that the global burden of poverty has shifted from the rest of the world to Africa. This paper discussed the causes of poverty on the continent and various responses by stakeholders toward accelerating its poverty reduction. It was found that with the available statistics and projections, Africa will still fall short of eradicating poverty by 2030, but it can bring it to a low level. The study, therefore, recommends that African policymakers should aim for growth that is inclusive and sustainable. International support from the world bank, ODA, G7, and others will play a vital role, especially through technology and resource transfers, also African continent need to improve its resource mobilization.

The linkage between fiscal policy and economic growth has attracted the attention of empirical investigators in economic literatures. This study systematically reviewed sub-Saharan African literatures just to examine the relationship between fiscal policy and economic growth. To achieve the objective of the study, 11(eleven) empirical literatures in 7(seven) Sub-Saharan African literature studied between the year 2013 and 2020 were selected. As regard to sampling, random sampling was used to enhance the representatives of the sample. The criteria for selection were the relevance of the topic and the geographical area of studies. In this procedure, the first geographical area and then studies were selected. In the second stage relevance of the studies was considered as inclusion crateria. Descriptive statistics was used for data analysis. The result shows that the studies selected for review are more interested in the long-run relationship between fiscal policy and economic growth than its short-run effect. This implies that Sub-Saharan African countries are using fiscal policy for economic growth rather than stabilization. Regarding consensus on the relationship between the two variables, majority of the literature selected for review found that fiscal policy is positively and significantly affecting the economic growth of the Sub-Saharan African countries. The major fiscal policy tools used in the selected literature are government expenditure and tax reflecting the similarity of economic structures and compositions in sub-Saharan Africa. In conclusion, the compositions of fiscal policy instruments are almost similar in sub-Saharan Africa. The policy implication is that policymakers in sub-Saharan Africa should give due attention to the composition of fiscal policy tools.

The Nigerian Government both previous and present has introduced several policies and programmes to reduce or proffer remedial measures to militate against the negative impact of high inflationary levels on the Nigerian economy. All these measures have not led to a productive result as the inflation rate has continued to sour higher over the years. This paper aimed at examining the economic influence of the determinant factors that influence inflationary trends that are multi-dimensional and dynamic which continue to defy solutions. The data used for this work was sourced from the National Bureau of Statistics and Central Bank of Nigeria, from 1983 to 2020. The ordinary least square approach was used to analyze the data and the result shows that consumer’s price index, interest rate and total export has a positive effect on Nigeria inflation, but only the Consumer’s Price Index (CPI) have a statistically significant effect on the Nigeria inflation at 99% confidence interval. Result also shows that the exchange rate, foreign reserve, money supply, real GDP, real income and total imports has a negative effect though not statistically significant on the Nigeria inflation rate. The result of the granger causality test shows exchange rate and total imports to granger cause Nigeria inflation. It is recommended that Government should improve locally manufacture products to meet international demands to reduce total imports.

This article discusses the effect of the oil shock on some OECD oil-importing countries such as Canada, France, Italy, China, and the United States and some OPEC oil-exporting countries such as Algeria, Iran, Kuwait, Saudi Arabia, and Venezuela. The model is estimated for the years 1976-2021. five annual variables are used for each country. The variables within the model include real oil prices, GDP growth, inflation, real wages, and real effective exchange rates. Real GDP is the main variable that shows the effects of oil prices on the economy, and the impact of oil prices on other model variables will indirectly affect economic activities. For this purpose, we estimate the vector autoregression model. Estimates obtained for different countries show that oil price shocks are one of the variables affecting economic growth. Also, in oil-exporting countries, oil shocks on economic growth are positive and negative in oil-importing countries. Also, Covid-19 is studied as an effective parameter in creating oil shocks.

The growing complexity of the operating environment urges pharmaceutical innovation. This essay addresses the need for the integration of advanced technologies in the pharmaceutical supply chain. It justifies the value proposition and presents a concrete use case for the integration of deep learning insights to make data-driven decisions. The supply chain has always been a priority for the pharmaceutical industry; research and development recognizes companies' increasing investment in big data strategies, with plans for a CAGR in big data tool adoption. The work presented herein has a preliminary explorative character to recuperate and integrate evidence from partly overlooked practical experience and know-how. The practical relevance of the essay is directed toward practitioners in pharmaceutical production, supply chain management, logistics, and regulatory agencies. The literature has shown a long-term concern for enhanced performance in the pharmaceutical supply chain network. This essay demonstrates the application of deep learning-driven insights to reveal non-evident flow dependencies. The main aim is to present a comprehensive insight into deep learning-driven decision support. The supply chain is portrayed in a holistic manner, seeking end-to-end visibility. Implications for public policy are discussed, such as data equity: many countries are protecting their populations and economic growth by building resilience and efficiency to ensure the capacity to move goods across supply chains. The implementation strategy is covered. The combined reduction of variability, efficiency as matured richness, reliability (on stochastic flows and their understanding through deep learning and data), and system noise (increased dampening through the inclusiveness of all stakeholders) results in increased responsiveness of supply chains for pharmaceutical products. Future work involves the integration of external data, closing the loop between planning and its application in reality.