摘要：The previous economic crisis has increased the attention of government to focus their activities more on economic stability. The development of government subsidies requires an analytically based analysis, one which would identify problematic areas of regional development more precisely. However, to monitor market changes in a highly dynamic market is time consuming and inefficient. Without proper market monitoring, the level of competitiveness within regions might decrease in the long run. Thus, the goal of the article is to establish the framework of a market trend monitoring system. To achieve this goal, the research methodology consists of a scientific literature analysis, an analysis of available data infrastructure for market trend analysis, and a statistical analysis together with a machine learning approach. The authors of the publication propose a market monitoring framework which would provide an infrastructure for evidencebased policy recommendations for government institutes and might provide guidelines of how to increase their competitiveness. A case study of real estate data and macroeconomic indicators of Lithuania was conducted, during which a clustering algorithm was applied to identify groups in Lithuania. The 60 municipalities of Lithuania were grouped into 4 clusters in terms of noteworthy relationships between industrial development and population size. In 3 of the clusters, the relationship of industrial growth and population was direct. In cluster 4, however, the relationship was opposite, a result which requires a further analysis of infrastructure and industrial sectors to provide more precise policy recommendations. The theoretical contribution and findings from the case study provides grounding to develop the market monitoring system.
关键词：evidenced-based policymaking;system thinking;market trends;competitiveness;regional development
