Through the spread of utilization of big data, artificial intelligence (AI), and Internet of Things (IoT) technology in recent years, due to the provision of data and technology, it is becoming possible to analyze industries and evidence-based policy making (EBPM) which was difficult hitherto. The purpose of this project is to develop new economic indicators that complement government statistics for the service industry where the proportion of the gross domestic product (GDP) and labor market has increased and statistical data is strongly required in order to grasp the actual state of the economy. Specifically, we aim to propose highly useful data points such as sales trends, competitiveness, business confidence, and productivity, and implement empirical analysis using them. Among the service industries, we attempt policy evaluation and proposals using EBPM methods with big data on infrastructure closely related to daily life such as logistics, communication, and finance.
December 19, 2017 - November 30, 2019
Major Research Results
RIETI Discussion Papers
"Comparison of Inbound and Domestic Tourists Destinations in Japan from 2011 to 2017: Zipf's law and Gibrat's law" (KONISHI Yoko and NISHIYAMA Yoshihiko)
"Measuring the Willingness to Pay and Implicit Discount Rates for High-efficiency Refrigerators: Evidence from the Japan retail market" (KONISHI Yoko, SAITO Takashi and ISHIKAWA Toshiki)