Open Source Model Assigns Credit Scores to 260 California Cities

May 13, 2013, 12:01 ET from Public Sector Credit Solutions

WALNUT CREEK, Calif., May 13, 2013 /PRNewswire/ -- A municipal credit research group has published credit scores for 260 California cities calculated with an open source credit model. The group, Public Sector Credit Solutions (PSCS), developed the model with a grant from the California Debt and Investment Advisory Commission (CDIAC) – a unit of the State Treasurer's Office (STO). The PSCS research, which has recently been submitted for peer review, does not represent the opinion of CDIAC or STO, nor do the credit scores reflect the views of CDIAC, STO or any other public agency.

The model is based on an analysis of municipal bond defaults ranging from the Depression era to those of Stockton and San Bernardino in 2012. City bond defaults in the Depression were largely attributable to high debt service burdens and declining revenues – factors which can also affect municipal solvency today. The more recent defaults were closely associated with low or negative general fund balances and general fund deficits.  The PSCS credit scoring model takes into account all of these factors as well as public employee pension costs.

The credit scores and supporting research study are available on a new web site at The free site contains a variety of financial data for each city in addition to their credit scores. All the scores are summarized on an Excel workbook on the site or directly at The draft study, co-authored with San Jose State University economist Dr. Matthew Holian, has been posted on the Social Science Research Network, a working paper repository, at The study contains a history of California city bond defaults and also discusses recent defaults, bankruptcies and state takeovers elsewhere in the US.

The municipal credit scores take the form of default probabilities – estimates of the likelihood that a given city will fail to service its debt obligations over the course of one year. Investors can use the default probabilities to determine whether the interest rate on a city's bonds compensates them for the credit risk they are assuming. The vast majority of cities have default probabilities below 2%, but a few are higher.

Data for the scoring model was collected from audited financial statements each city is required to file. The PSCS model could also be run with projected revenue and expenditure data to provide a more forward looking measure of credit risk.

Contact: Marc Joffe, +1-415-578-0558,

SOURCE Public Sector Credit Solutions