An alternative hedonic residential property price index for Indonesia using big data: The case of Jakarta - Arief Noor Rachman (Eurostat Review on National Accounts and Macroeconomic Indicators (EURONA), 2019)
Monitoring property price dynamics is a necessary task for central banks in order to maintain financial stability in the economy. Big data offers potential as a new source of data that might be used to produce official statistics on property. In this paper, we develop an alternative residential property price index (RPPI) for the secondary market for houses from online residential property listings using the time-dummy hedonic regression method. The dataset is based on residential property advertisement listings from Indonesia's major property web portals from January 2016 to September 2018. For this prototype index, the study initially focuses on Jakarta, the capital city of Indonesia. Our regression outputs generally show promising results and have the potential to become an official housing index. Future development will extend the index coverage to other large cities in the country and improve the characteristic variables in the model.
Keywords: C43; E30; R31; 330; residential property prices index; big data; hedonic regression time-dummy method