Does internet search intensity predict house prices in emerging markets?: a case of India

Abstract

Purpose: The purpose of this paper is to examine whether internet search intensity, as captured by Google’s search volume index (SVI), predicts house price changes in an emerging market like India. Design/methodology/approach: Using data on Google’s SVI for four Indian cities and their corresponding house price index values, the authors examine whether abnormal SVI (growth in search intensity normalized by the national average) impacts abnormal house prices (house price change normalized by the national average). Findings: Like developed markets such as the USA, the authors find that internet search intensity strongly predicts future house price changes. A simple rebalancing strategy of buying a representative house in the city with the greatest change in search intensity and selling a representative house in the city with the smallest change in search intensity each quarter yields an annualized excess (over risk-free government T-bills) return of 4 percent. Originality/value: Emerging markets have low internet penetration and high information asymmetry with a dominant unorganized real estate market. The results are interesting as it sheds light on the nature and role of the internet as an infomediary even in emerging markets