This discussion paper presents research findings on the development of a new rent index utilizing rental listing big data, conducted by the Director-General for Policy Planning (Economic and Fiscal Analysis) at the Cabinet Office.
The research was conducted as a joint study by Kitaoji Ko, Ogino Hideaki, and Tsujimura Ryujin, published as DP25-3 in the Economic and Fiscal Analysis Discussion Paper Series. To capture market trends more precisely than conventional rent statistics, the study developed new analytical methods utilizing big data from internet rental listing information.
The research identifies limitations of existing rent statistics, including sample size constraints, regional and property attribute biases, and time lag issues, and validates the effectiveness of big data utilization in solving these problems. Specifically, it proposes methods for constructing new rent indices by statistically processing large volumes of rental listing data collected from real estate information websites and performing quality adjustments.
The analysis results reveal detailed market trends, regional differences, and price fluctuation patterns by property attributes that were not visible in conventional statistics. Particularly, changes in the rental market due to the impact of COVID-19 and inter-regional migration of housing demand accompanying the spread of teleworking are shown to be more clearly captured by the new index.
The research outcomes are expected to serve as important basic materials for policymakers and researchers, while also contributing to improving transparency in the real estate market and developing statistical infrastructure for appropriate policy decisions. As a case study in developing statistical methods utilizing big data, it also suggests applicability to other economic statistical fields.
The article concludes that as a new statistical compilation method in the digital age, big data utilization has been empirically demonstrated to play an important role in improving the accuracy of economic analysis and verifying policy effectiveness.