The tool below shows our covariance analysis that was first published in the Spring 2007 Wharton Real Estate Review and is regularly updated in The Linneman Letter. This analysis examines how various economic indicators behave in individual metropolitan areas based on national economic changes. Specifically, for each MSA, we estimate a statistical equation, which summarizes how a 100-bp change in national employment affects local employment. The equation consists of a constant (“alpha”) for each market and a “beta,” which is a multiplier applied to the national percent change in employment. The alpha indicates MSA growth that is independent of national growth. If there is no national job growth, then the alpha is the expected annual change in MSA employment. The beta for the U.S. is defined as 1.0. An MSA with a beta of 1.0 registers (on average) an increase of 100 bps in employment growth (plus its alpha) when national employment rises by 100 bps. A beta that is less than 1.0 indicates that the MSA does not boom (or bust) to as great an extent as the national economy, while a beta of greater than 1.0 indicates that such an MSA experiences swings of greater magnitude (around its trend) than percentage changes at the national level.

​

The scatter plot shows where MSAs' alphas and betas fall. By default, the plot shows the top 50 MSAs (by employment) with the data starting in 1991. Results can be filtered by adjusting what rank you want shown, the starting date, setting a maximum or minimum alpha or beta, and by selecting specific MSAs. Page 2 has a table view of the alpha and beta stats for all MSAs, which can be sorted by clicking the column headers. This data is not available for download through this interface. If you have any questions about these tools or the data, contact Rosemary Sylvan.