Home buyers and sellers in the housing market fundamentally face two challenges - Search and Pricing.
Homes are a "one-of-a-kind" product, making them difficult to price and difficult for any buyer to search for their best fit.
For Search, an ecosystem of real estate agents, brokers, and realtors helps to some extent. But, these services come at a steep cost. For Pricing, home appraisers can help. But, there is little measurement of their accuracy.
Numerous technology platforms have emerged to overcome these challenges using Big-Data and AI.
What is the impact on Home buyers and sellers? What is the impact on the market? and what should policymakers do?
Academic Papers
“Does Machine Learning amplify pricing errors in housing market?: Economics of ML Feedback Loops”
Malik N. (USC), Manzoor, E.A. (Cornell)
Marketing Science Conference, June 2022. [video]
Conference on Information Systems and Technology, Oct 2022. Indianapolis, IN.
Conference on AI-ML-BA, December 2022 Cambridge, MA.
AI in Marketing (AIM) Conference, March 2023. Los Angeles, CA.
Workshop on Platform Analytics (WoPA), Apr 2023. San Diego, CA. [video]
“Why does my Zestimate fluctuate? Algorithmic Pricing and Ad Revenue Incentives”
Malik N. (USC) and Fu R. (NYU)
USC Marketing Department Quant Brown Bag, Oct 2021 and Nov 2022.
Marketing Science Conference, June 2023. Miami, FL.
Junior Faculty Development Forum, May 2023. St. Louis, MO.
“Algorithm failures and consumers response: Evidence from Zillow”
Troncoso I. (HBS), Fu R. (NYU), Malik N. (USC) and Proserpio D. (USC)
Conference on Information Systems and Technology (CIST), Oct 2023. Phoenix, AZ.
Workshop on Information Systems and Economics (WISE), Dec 2023. India.
USC Marketing Quant Brown Bag, Feb 2024. Los Angeles, CA.
Workshop on Platform Analytics (WoPA), Apr 2024. San Diego, CA. [video]
Other talks: Marketing Dynamics Conference 2023, North-East Marketing consortium 2023, University of Amsterdam, Universita di Bologna, Pontificia Universidad Catolica de Chile, University of Maryland, INSEAD.