WASHINGTON — In response to a spate of municipal bankruptcies and ongoing fiscal challenges at the local level, the California treasurer’s office has embarked on a project aimed at predicting cities’ likelihood of defaulting on bonds.
The office of Treasurer Bill Lockyer has hired San Francisco-based research organization Public Sector Credit Solutions and San Jose State University economist Matthew Holian to head the effort, which aims to create a “default probability model for city bonds,” according to a media release.
Marc Joffe, principal consultant at Public Sector Credit, said the model will generate “numeric scores” that will quantify the likelihood of defaults. The model and default predictions for more than 200 California cities will be released in May 2013, he said. It will also be available for free download from the Internet.
Tom Dresslar, spokesperson for Lockyer, said the project will help give the state an early warning of cities in financial distress.
“The treasurer thought it was important to develop a model, empirically based, to identify cities that are in trouble and may run a greater risk of default on their obligations,” Dresslar said.
The project will help “raise red flags” at the state level, he said.
Lockyer said in the release that the model will also help make the financial conditions of municipalities more transparent to investors and the public.
The project became a “more immediate” objective of the treasurer following bankruptcies this year of three California cities — Stockton, Mammoth Lakes and San Bernardino — and “fiscal emergencies” in other municipalities, Dresslar said.
Next, he added, the state will work to create a “response system” to help assist troubled municipalities. But solutions may not come easy; California’s constitution largely prohibits the state from meddling in cities’ financial affairs, he said.
Joffe, a former senior director at Moody’s Analytics, will lead data collection efforts for the model, which will incorporate historic municipal default data from as far back as the great depression.
Holian, who could not immediately be reached for comment, specializes in urban policy analysis and will run statistical models, Joffe said.
The calculation for each city will be based on financial data found in the city’s financial statements, budgets and projections. The most telling numbers, he said, are interest expense, revenue and annual change in revenue.
While models used by credit rating agencies typically evaluate roughly 50 metrics, Joffe said his model will be able to make predictions with a handful of key data points. The model can be updated easily as new data becomes available, allowing for more “real time” analysis, he said.
“We want to give the market a simple model,” he said. “ You put in a bunch of ratios, and it spits out a result.”