Can online search sentiment predict housing demand in Indonesia?

Abstract

This study examines the role of online search-based sentiment in predicting housing demand in Indonesia. Using the generalized least squares (GLS) method, this study analyzes panel data from 11 cities in Indonesia during 2017.I-2024.IV. The results exhibit that in addition to housing prices, economic conditions, and demographic factors, housing demand is also impacted by psychological factors in the form of sentiment that can be predicted through online searches via Google trends, which are so-called online search sentiments. The strength of the relationship between online search sentiments and housing demand for sale and rental categories varies with the volatility of housing prices. Furthermore, we also found that the relationship between online search sentiment with the keyword "house for rent" and housing demand in the rental category is more substantial in cities outside Java. Our study can be utilized as a consideration for investors, consumers, and policymakers' decision-making, as well as the development of research in real estate economics.