Monthly seller’s bargaining power index constructed using open-source data

Abstract

Purpose

A tangible representation of the housing market hotness, namely, the index derived via Carrilo 2013’s concept, is widely used but difficult to construct, as it requires listing data of a geography which is not only inaccessible but also cumbersome to summarize. The purpose of this paper is to serve as a methodological extension of Carrilo 2013, presenting a process by which the seller’s bargaining power index can be easily constructed using open-source data.

Design/methodology/approach

The seller’s bargaining power index was first constructed using the open-source data by Zillow Research. Then, results verification approach including visualization, Pearson correlation test, Granger causality test and linear regression were used with the goal to generate empirical evidence and verify if the constructed index conforms with established relationships derived in past work, thereby substantiate accuracy of the constructed index.

Findings

Monthly seller’s bargaining power index was constructed for US as a whole and 250 metropolitan statistical areas through an automated process. The constructed index conforms with established evidence in terms of seasonality, trend and magnitude. The index also forms positive correlation with building permit/housing value/housing value increase rate, and negative correlation with inventory. It requires the explanatory power of multiple linear features to simulate the parameter. Seller’s bargaining power index at a national level can serve as a general indicator of economic strength, in parallel to number of building permit, housing starts and real gross domestic product. Quantitatively, the housing market of the USA is as “hot” during the COVID-19 pandemic as it was in the years before 2008. A healthy housing market appears to be one in which 75%−80% of the deals are in favor of the seller (take-it-or-leave-it). When said percentage reaches 90%, the market should be considered to be in a “bubble.”

Originality/value

This paper provides an easy pathway for future studies to simulate housing market hotness, and bring upon the benefit of convenience at low cost and in monthly frequency rather than quarterly or annually.

Citation

Zhang, X., Xu, S., Wang, Y. and Yang, E. (2024), "Monthly seller’s bargaining power index constructed using open-source data", International Journal of Housing Markets and Analysis, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJHMA-01-2024-0014