Paper reviews the classical methods of machine learning (supervised and unsupervised learning),gives examples of the application of different methods and discusses approaches that will be useful for empiricaleconomics research (on data from Ukrainian firms, banks and official state statistics). The different sectors ofeconomics are investigated: the multiple linear regression is used on macrolevel for macro production functionof Ukraine specification; logistic regression is used in bank sector for credit risk management with the scoringmodel; k-means, hierarchic clustering and DBSCAN are used in regional level for regions of Ukraine groupingbased on competitiveness; principal component analysis is used for firm’s financial stability analysis. All modelsshowed adequate simulation results according to the quality criteria of the models. So, the possibility ofclassic machine learning methods application for investigations of the processes and objects on different levelsof economics (micro, mezzo and macro) is demonstrated in the article.

COVID-19 is a huge problem for the sustainability of the global economy, both short and long term. The spread of COVID-19 has led to a decline in business and economic activity, as well as a contraction in production - virtually all world economies have shown a sharp decline in GDP. World experience shows that agriculture is less vulnerable to a pandemic. In general, there is a calmer reaction to the demand for agricultural products than for industrial ones. The impact of agricultural production volume on the real GDP of Ukraine is investigated with a distributed-lag model on the data for the period 2008-2020. The effects of the impact distribute almost evenly between the four quarters of the year, which means that the lockdown effects in the agriculture sector will affect the GDP of Ukraine for a long period. The decline in production, the closure of markets and borders, the cancellation of orders led to the fact that the agricultural sector faced serious logistical problems. In addition, the economic downturn has affected farmers’ access to financial resources. However, COVID-19 also opened new opportunities for the Ukrainian agricultural sector: accelerating and expanding the process of digitalization, the opportunity to expand the market for export products, and increase skilled and unskilled labor. The authors propose six steps to ensure the sustainable development of the agriculture sector of Ukraine.

The need for sustainable development of Ukrainian regions is due to the global threat of environmental degradation, the unstable situation in the world economy, low socio-economic indicators of the country and weak innovation activity. An important factor that has an influence on the economic development of regions is the ecological state of the environment. It plays one of the most important roles in the conducting of economic activities that require the use of natural resources. According to the results of the investigation, four clusters were formed. Cluster analysis made it possible to conduct a general assessment of the state of the regions of Ukraine, to form groups by similarity and to draw sound conclusions about the existence of similarities in the economy. The formation of clusters and the development of sustainable development policies for individual clusters, which should have significant differences, taking into account their specifics, will contribute to the more effective achievement of sustainable development goals.

The digitalization of agriculture is much slower than in other industries, due to the high cost of digital solutions and their complex functionality. Recently, the situation is changing, and now agriculture can get real benefits from technology with simple software solutions. Technologies used in agriculture include sensors, mobile devices, communication networks, drones, robotics, artificial intelligence, and others. These technologies provide an opportunity to improve the business processes of agriculture and increase its efficiency. In 2020, the agritech startup ecosystem of Ukraine has more than 70 startups that have been used for farm management, drones and remote sensing, precision farming, and urban agriculture. SWOT analysis indicate that the agritech startup ecosystem is characterized by more weaknesses and threats than strengths and opportunities. The Ukrainian agricultural sector has significant potential for increasing efficiency and development. Agriculture today needs startups that use information technology to address the balance of economic, environmental, and social efficiency to increase agricultural productivity.

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