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AbstractThis paper develops a multilevel structural factor model to study international output comovement and its underlying driving forces. Our method combines a structural vector autoregression with a multilevel factor model, which helps us understand the economic meaning of the estimated factors. Using quarterly data of real GDP growth covering 9 emerging Asian economies and G‐7 countries, we estimate a global supply factor, a global demand factor, and group supply and demand factors for each group of the economies. We find that although the role of the global factors has intensified over the past 15 years for most of the economies, output fluctuations in Asia have remained less synchronized with the global factor than those in the industrial countries. The Asian regional factors have become increasingly important in tightening the interdependence within the region over time. Therefore, although emerging Asian economies cannot 'decouple' completely from the advanced economies, they have, nonetheless, sustained a strong independent cycle among themselves. We also find that synchronized supply shocks contributed more to the observed synchronization in output fluctuations among the Asian economies than demand shocks. This points to the role of productivity enhancement and transmission of other supply shocks through, for example, vertical trade integration, rather than dependence on external demand, as the primary source of business cycle synchronization in emerging Asia.

During presidential elections and showbusiness or social news events, society has begun to address the risk of fake news. The Sustainable Development Goals 4 for Global Education Agenda aims to "ensure inclusive and equitable quality education and promote lifelong learning opportunities for all" by 2030. As a result, various nations have deemed media literacy education a required competence in order for audiences to maintain a discerning attitude and to verify messages rather than automatically believing them. This study developed a highly efficient message discrimination method using new technology using artificial intelligence and big data information processing containing general news and content farm message data on approximately 938,000 articles. Deep neural network technology was used to create a news source credibility identification system. Media literacy was the core of the experimental course design. Two groups of participants used different methods to perform message discrimination. The results revealed that the system significantly expanded the participants' knowledge of media literacy. The system positively affected the participants' attitude, confidence, and motivation towards media literacy learning. This research provides a method of identifying fake news in order to ensure that audiences are not affected by fake messages, thereby helping to maintain a democratic society.

China has been moving to a more market oriented financial system, which has implications for the monetary policy environment. The paper investigates the stability of the money demand function (MDF) in light of progress in financial sector reforms that, for example, have resulted in significant financial innovation (so-called shadow banking) and more liberalized interest rates. The analysis of international experience suggests that rapid development of the financial system often leads to structural shifts in the MDF. For example, financial innovation and liberalization alter the sensitivity of