Paper awarded at joint event - 56th Annual Convention of ORSI and 10th International Conference on Business Analytics and Intelligence held at IISC Bangalore
26 December, 2023, Bengaluru: A paper, co-authored by Kapil Gupta, student of the Doctor of Philosophy (PhD) programme of IIM Bangalore (Decision Sciences area), has won the First Best Paper Award under the PhD Scholar Category (there were three best paper awards) at the joint event – 56th Annual Convention of ORSI and 10th International Conference on Business Analytics and Intelligence held at IISC Bangalore, from 18th to 20th December 2023. The paper is titled, ‘A Novel Spatio-Temporal Statistical Model to Analyze Real Estate Market in Bengaluru, India’, and has been co-authored with Prof. Soudeep Deb, faculty of the Decision Sciences area of IIM Bangalore, and Prof. Venkatesh Panchapagesan, Chairperson, Real Estate Research Initiative and faculty of the Finance & Accounting area of IIM Bangalore.
The evaluation was based on the full paper and multiple criteria, such as, the problem's relevance, methodology novelty, managerial and policy implications, how well the paper is written, etc.
Abstract of paper: Recent attention has been drawn to statistical research in real estate markets, aiming to comprehend the dynamic patterns of real estate prices in terms of space and time. This study contributes to this field by presenting compelling evidence of the spatial and temporal dependence in real estate prices. The authors introduce a spatio-temporal model that captures the intricate spatial and temporal dependencies of the real estate prices efficiently. The study approach, allowing multiple observations per unit, provides added benefits for practitioners. Authors implement their model through a Bayesian setup as it gives flexibility and computational advantage over other approaches. As a real-life application, they analyze house price data from Bengaluru from February 2015 to March 2020, covering 62 monthly time points and 76 micromarkets. Residual diagnostics confirm the model's effectiveness in capturing spatio-temporal dependence. Furthermore, the model demonstrates effectiveness in its predictive capabilities.