Separating the Good From the Bad From the Ugly: Indicators for Housing Market Analysis

Brian A. Mikelbank, Cleveland State University
Charlie Post, Cleveland State University

Data Shop

Data Shop, a department of Cityscape, presents short articles or notes on the uses of data in housing and urban research. Through this department, PD&R introduces readers to new and overlooked data sources and to improved techniques in using well-known data. The emphasis is on sources and methods that analysts can use in their own work. Researchers often run into knotty data problems involving data interpretation or manipulation that must be solved before a project can proceed, but they seldom get to focus in detail on the solutions to such problems. If you have an idea for an applied, data-centric note of no more than 3,000 words, please send a one-paragraph abstract to david.a.vandenbroucke@hud.gov for consideration.

Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the U.S. Census Bureau or the Bureau of Labor Statistics. The research in this article does not use any confidential Census Bureau information.

In the years before the current housing crisis, the Urban Center at Cleveland State University regularly produced housing indicators for the city of Cleveland, Ohio, and other geographic subareas within the Cleveland metropolitan area. As the housing market deteriorated into crisis, traditional market price and volume indicators became less useful, and analysts at the Center faced the fundamental challenge of determining what was occurring in these local housing markets.

Many local jurisdictions are undoubtedly exploring this same, uncharted territory. Those who analyze local housing markets need to gauge the (sometimes volatile) health of that market. Although national and regional indicators (for example, the S&P/Case-Shiller® Home Price Indices) are available for analysis, they provide no information on local market performance, and information at the municipal or neighborhood level is often crucial to making strategic planning decisions.

This article presents four lessons the Center learned about Cleveland’s local housing market and the data and tools used to identify the lessons. Although these approaches may not be as useful in every market, they may serve as a starting point for similar analyses and discussion.