Local Government Fiscal Early Warning Systems: A Good Idea Whose Time Has Come
Two years ago, Treasurer Bill Lockyer called for an early warning system to detect signs of financial trouble in California local governments before they faced bankruptcy. By proactively identifying at-risk cities, the system could create an opening for local experts and external advisors to intervene before any given situation spun out of control. As the California Policy Center (CPC) showed last month, such a system is possible, and it can be built from components already available to the State Controller’s Office (SCO). So, while the state does not yet have an early warning system, incoming Controller Betty Yee will have the raw materials to implement one.
For the CPC study, we gathered audited financial statements from over 490 California cities and counties. All but the very smallest local governments are required to produce financial statements for bond investors and/or the federal government. The statements follow Governmental Accounting Standards and include an opinion from an independent accounting firm. These audits are also filed with SCO, which provides lists of current and delinquent filers on its single audit status web page.
Once we obtained the documents, we extracted key fiscal variables and ran them through a scoring model that I previously created as part of a study for the California Debt and Investment Advisory Commission (CDIAC). In the CPC project, we identified the thirteen cities facing the highest risk of bankruptcy and provided brief summaries of their recent financial history.
Our findings were picked up in the Los Angeles Times and a couple of other local media outlets. Managers in two of the cities we listed – Compton and San Fernando – wrote rejoinders to our findings which are being posted on CPC’s web site. The fact that they took the time to consider and question our findings is great, since the purpose of a system like this is to stimulate discussion about local government fiscal sustainability.
Meanwhile, SCO has taken an initial step in the same direction. In an October 2013, Fox & Hounds post, Dr. Max Neiman and I proposed some enhancement to SCO’s century-old process of gathering local government financial information. Each year, SCO sends a data collection form to local agencies and compiles the results in the Cities and Counties Annual Reports. Unfortunately, these data sets arrive well after fiscal year end, are not consistent with audited financials and have not been delivered in a user-friendly form.
Earlier this fall, SCO introduced a new web site which provides better ways to interact with the data in an intuitive and visually pleasing manner. SCO now also offers its entire local government fiscal data set in Excel form. Finally, the new site provided 2013 fiscal data somewhat faster than in years past.
But the SCO data continues to differ from that contained in audits. For example, San Bernardino’s 2012 general fund balance was -$12.209 million according to the city’s audited financials but +$206 million on the SCO’s website (which refers to the balance as “fund equity”). King City’s 2013 general fund balance is shown as -$3.78 million on its audit, but only -$1.89 million on the SCO site – a big difference for a town of 12,000 people. In my CDIAC study, I found that very low or negative general fund balances are a harbinger of bankruptcy. I may not have made this finding if I had had to rely upon the SCO data.
As Dr. Neiman and I discussed last year, SCO data cannot reconcile to audited financials for two reasons. First, cities and counties must submit collection forms before the local governments have a chance to complete their annual financial audits. Second, the financial statement items in SCO’s collection instrument do not correspond to items that appear in statements meeting standards set by the Governmental Accounting Standards Board (GASB).
To eliminate the discrepancies and make its data useful for an early warning system, SCO should replace the existing collection process with the submission of audited statements. This is especially convenient for cities and counties because they already send their audits to SCO. The Controller could save work for local government finance officers and produce more accurate data by extracting financial statement information from the audited financials it already receives rather than obtaining a second set of incompatible, unaudited data from cities and counties, as it does now.
The main barrier to implementing this idea is that financial audits typically take the form of Adobe PDFs, so financial statement items must be re-entered or extracted from the reports. Numerous open source and licensed tools are available for PDF data extraction: many are listed here. For the recent CPC study, we worked with a data collection firm named Civic Partner that applies such tools to local government financial statements. Longer term, local governments should be encouraged to file their financial audits in a “machine readable” form such as eXtensible Business Reporting Language (XBRL), as Dr. Neiman and I suggested in our previous post.
Once the data is cleaned up, SCO can use it in a fiscal stress scoring model. While I like the one I have built, there are a number of alternatives from which to choose. A good example of an effective, high profile scoring system is the one used in New York State. Comptroller Thomas D. Napoli assigns fiscal stress scores to over 2,000 counties, cities and school districts. In 2013, the system classified 26 local governments in its “Significant Stress” category.
More than two years have passed since the last California city filed a Chapter IX bankruptcy. While it may be tempting to think that this problem has gone away, it is more likely that municipal fiscal crises are simply in a state of temporary abeyance due to the overall health of California’s economy. It is now – in this benign period – that we have best opportunity to create a robust early warning system. When the next recession hits, it will already too late. Like the rainy day fund created by Proposition 2, early warning systems need to be built during flush times, so that they are there for us when the next wave of problems strikes.
Marc Joffe founded Public Sector Credit Solutions in 2011 to educate policymakers, investors and citizens about government credit risk. PSCS research has been published by the California State Treasurer’s Office, the Mercatus Center and the Macdonald-Laurier Institute among others. Prior to starting PSCS, Marc was a Senior Director at Moody’s Analytics. He has an MBA from New York University and an MPA from San Francisco State University.