How qualitative credit signals can reveal muni risks before ratios do

• Thesis: Overreliance on muni ratios undervalues qualitative factors

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• Observation: Wide-ranging federal and state policy choices, regulatory shifts, the vagaries of local economic patterns, cyber-security preparedness, adoption of AI protocols, and overall determinants of ESG resiliency, combined with management’s strategic objectives do not lend themselves to ratio analysis

• Call to action: Issuers, Muni Advisors, Legal Counsel, Underwriters/Bankers, Investors

Conventional wisdom tells us that numbers do not lie. Financial ratios and debt metrics provide an objective snapshot of an issuer’s fiscal condition and often serve as the starting point for credit decisions. But numbers alone rarely tell the entire story, and this is especially evident in the municipal bond market. At times, demand and market access matter more. 

An overreliance on ratios can create a false sense of certainty, obscuring the qualitative factors, structural risks, governance and political issues, and emerging trends that ultimately shape long-term credit performance. For market participants seeking a more complete view of municipal credit, it is strongly urged that ratios be considered as the starting point of the analysis — not the end of it. 

My comments are meant to engage with each key stakeholder group across the municipal bond market sphere, including issuers, municipal advisors, legal counsel, investment bankers/underwriters and institutional investors. In my opinion, it is important for those stakeholders who are advising issuers ahead of rating agency presentations and disclosure preparation to highlight those evolving qualitative factors having consequential impact on future credit quality. 

The importance of financial ratio analysis continues to evolve as qualitative factors take on greater forward-looking significance. By no means am I suggesting that ratios have lost their analytical value. I am simply saying that some have either been refined to reflect today’s realistic inputs or supplanted by more appropriate measures of municipal security credit quality. A disproportionate reliance on certain ratios and financial thresholds within a vacuum could result in a questionable credit assessment and lead to the wrong course of action. 

The municipal market has become increasingly adept at measuring what is easily quantifiable, but many of the factors that ultimately determine long-term credit quality are not captured through conventional financial ratios. Ratios cannot take account of legal covenants, climate and physical risks, cyber-preparedness, economic trends and demographic shifts, pension and OPEB management, and the political willingness to raise revenue or cut expenditures. 

Municipal bonds represent a very unique asset class. For non-practitioners, the world of public finance can seem off-putting. The uninformed often characterize the market as sleepy, boring and predictable, with only the federal tax-exemption as a benefit. There is also a misconception that municipal bonds only finance roads, bridges and schools, when in fact, the breadth and depth of financing is far more extensive. 

Many complex and nuanced transactions are underwritten in the public finance space for healthcare providers, airports, universities, affordable housing, P3s, tobacco securitizations and energy prepayment contracts. These structures require strong analytical rigor for both primary market review and secondary market surveillance. Rendering a comprehensive assessment requires consideration of many qualitative factors that go beyond the numbers. 

Lessons learned from Puerto Rico

While the market can tout favorable default and recovery statistics compared to other asset classes, munis can and do default. Puerto Rico’s default across the commonwealth’s central government and much of its revenue bond debt issuers, and the resultant establishment of PROMESA to facilitate bankruptcy proceedings outside of the U.S. bankruptcy code, and a labored restructuring and recovery process — which has not concluded yet, given the conflicting attempts to restructure Puerto Rico Electric Power Authority — is by far the largest municipal bond default. 

Approximately $70 billion in outstanding bonds and $55 billion in unfunded pension liabilities were affected. I would argue that while leverage and other financial data points signaled serious credit problems long before the commonwealth’s default, there was an undeniable fixation on a “too big to fail” or maybe even a “don’t worry, be happy” mentality when it came to Puerto Rico. There were very credible qualitative signs that all was not right.  

The commonwealth routinely revised its budgetary assumptions in a haphazard manner and was notoriously late with financial reporting. A declining tax base and economic contraction without a remedial plan further indicated a lack of managerial resolve. The repeal of Section 936 tax benefits beginning under the Clinton administration through a 10-year phase-out was not given sufficient consideration in my view. 

Let’s recall that Section 936 allowed U.S. corporations domiciled in Puerto Rico to receive a credit that effectively offset federal income taxes on qualifying Puerto Rico source income. This tax incentive attracted pharmaceutical, medical device and manufacturing companies to the commonwealth. 

The loss of Section 936 represented a significant qualitative warning sign preceding Puerto Rico’s fiscal crisis as it triggered a gradual departure or downsizing of many manufacturing firms, lowered high-paying employment, and weakened Puerto Rico’s economic growth and tax base. One-time budgetary fixes were often employed as opposed to long-term structural sustainability.   

There are plenty of instances where we have seen faulty assumptions and projections, overly optimistic expectations and unforeseen events derail the economics of structured finance and other speculative transactions. Even if initial assumptions were valid, perhaps there was a failure to perform appropriate stress testing. This is why skilled credit analysts are employed by rating agencies, bond insurers, investment banking firms and institutional investors. 

As someone who has spent many years following municipal credit developments, evolving public policy and cyclical market dynamics, I can assure you that the public finance ecosystem offers engagement, vibrancy, intellectual stimulation, structural sophistication and even competitive performance with compelling yield and income opportunities available across the asset class. 

I suggest any conversation with issuers, bond attorneys, municipal advisors and sell-side and buy-side professionals would echo my sentiments given the specialized and unique nature of many of the credit and structural concepts that frame the municipal securities market. From my perch, I have witnessed the creation of some of the most innovative financing vehicles designed to support infrastructure and other essential purpose projects throughout the United States.   

The municipal bond market is replete with inherent inefficiencies, and although these inefficiencies create opaqueness, they often provide investment opportunities. An expansive $4.3 trillion market with over 60,000 issuers, including conduits, and multiple credit types and complex structures, allows for pricing and rating anomalies. The over-the-counter, non-quoted nature of the muni market with inconsistent data availability, uneven disclosure practices and fragmented supply across broker-dealers creates further pricing variances and episodic price discovery.   

Making assessments of municipal security credit quality can be daunting given the wide-ranging factors that produce a credible rating and outlook assignment. Throughout this journey, there is exposure to inefficiencies and misguided assumptions that can often shape pricing distortions and liquidity weakness. 

Analytically, the process must include a fair amount of financial and operational statement review along with perfunctory consideration of ratio evaluations and trends. Municipal accounting practices differ significantly among issuers. Most municipal governments primarily use fund accounting and prepare their financial statements in accordance with standards set by the Governmental Accounting Standards Board. 

A municipal government’s general fund balance is different from its overall net position. A city may report a strong general fund balance under modified accrual accounting while simultaneously reflecting heavy long-term liabilities — such as pension obligations, other post-employment benefit (OPEB) liabilities, or bonded debt — all of which are shown in the government-wide accrual statements. The significance here is that financial ratios calculated from governmental fund statements often provide a useful snapshot of current liquidity and budgetary performance, but they may not account for a municipality’s long-term financial health or future credit direction. 

While corporations focus on profitability, municipal accounting is designed to demonstrate public accountability, legal compliance, and appropriate stewardship of taxpayer resources and trust. It is important to recognize that many municipal governments maintain different categories of funds, each having its own accounting rules. Governmental funds generally use modified accrual accounting, while proprietary funds and fiduciary funds use full accrual accounting. 

Wide-ranging federal and state policy choices, regulatory shifts, the vagaries of local economic patterns, cyber-security preparedness, adoption of AI protocols, and overall determinants of ESG resiliency, combined with management’s strategic objectives do not lend themselves to ratio analysis. Rather, they capture forward-looking risks and demand a very different type of qualitative assessment of which we are only now scratching the surface. 

For example, AI can help make the credit review process more efficient and timely in terms of monitoring and organizing disclosure filings, credit and sector-specific news items and changes to economic patterns. However, there is no replacement for human engagement as a necessary force to identify emerging risks by interpreting qualitative factors, and to determine responsive actions. Looking at this from a different angle, I would not expect AI to assess the likelihood of political leaders approving future utility rate increases or an electorate voting to approve a school budget. 

In my opinion, these are the types of factors that will demonstrate growing significance, but they too have practical limitations. Ratio analysis will always have a place in the overall credit assessment process, and for various reasons, certain investors will anchor their decision-making exclusively to these financial metrics.

One of my earliest observations as a credit analyst surrounded the inconsistency of specific ratio calculations. For example, my calculation of debt service coverage on a revenue bond may be different from what was being shown by the rating agencies. Other investors may also obtain different figures, with none of these results equaling the indenture calculation. Days cash on hand and debt per capita are other common ratios that give rise to differing calculations. 

Methodology variances, practical application and subjective philosophical nuances help explain multiple figures for the same metric calculated for the same time sequence. Let’s keep in mind that the bond indenture/trust agreement are enforceable legal and governing documents and therefore establish specific requirements for compliance purposes. 

These documents do not track evolving credit quality. Rather they are an important reference source where deal participants and investors can find express legal covenants, default provisions, bondholder rights and remedies and relevant definitions for financial and operational terms. 

In my opinion, the legal covenants enumerated within the bond documents merit top importance. A breach in any of these covenants would trigger a material event notification to the EMMA repository and likely signal distressed conditions. Having said this, compliance with all legal covenants does not necessarily mean the credit is in good financial health, and sole reliance on these measures could represent an oversimplification of the credit profile and potentially mask material credit problems that have yet to be identified. Many other credit attributes can be more predictive and offer a better way to gauge directional movement in these ratios and an issuer’s ability to meet future debt obligations. 

Covenants, and ratios more broadly, represent a point-in-time status check that can be viewed as backward-looking, and offer little in the way of a forecasting tool. Presumably, they are good barometers of an issuer’s present financial health and they signal compliance with legal and financial requirements. 

However, they would not reveal a finance director routinely misappropriating funds, unless such activity is egregious enough to produce a covenant breach. Legislative or regulatory changes are also outside of the scope of ratios and covenants. In the event that reserves are drawn upon, there is typically a replenishment period, it would be helpful to know if and when reserves will be restored.  

Covenants and ratios do not reflect cyberthreats and overall cyber-preparedness of hospitals, universities and airports. A review of many audited financial statements simply shows a line item in the notes section for outstanding indebtedness attesting to an issuer’s compliance with its covenants. Not all financial disclosures, however, include this language. Ratios do not reflect a bond’s legal security when it comes to the type of revenue lien, a presence of a reserve fund and specific covenant requirements. 

Away from indenture covenants, I recognize that rating agency methodologies reflect a large mix of credits for a given sector with modeling/scoring factors used for analytical comparisons across each sector. A rating is a predictive tool that assesses an issuer’s/obligor’s capacity and willingness to meet full and timely payment of principal and interest. In doing so, it measures a probability of default in tandem with a loss given default. 

A loss given default measures monetary loss after accounting for a recovery value. It is important to recognize that in a default or bankruptcy scenario, municipal governments continue to provide essential public services and maintain ongoing taxing or rate-setting authority. A debt restructuring, as opposed to a liquidation, sets municipal credits apart from corporate credits. This is why municipal bondholders often recover a significant portion of principal. 

Note that loss given default is not a “one-size fits all” concept and can be a distinguishing factor during the rating assignment process for bonds having a higher probability of default. Court proceedings, if applicable, could influence recovery value. The type of security pledge, legal protections, project essentiality and overall economic conditions further define recovery value. Ratios and covenants do not fully reflect these considerations. 

Rating agencies often calculate the same ratio differently than external stakeholders because they are looking at a longer-term horizon and incorporating certain factors that are more reflective of a sector taken as a whole for comparability purposes. Again, bond documents provide straight-forward definitions of certain financial terms, while rating agencies possess a degree of flexibility as to how they can express their calculations. I applaud rating agency efforts to periodically revise their rating criteria and methodologies in response to evolving conditions and lessons learned. 

Referring back to my debt service coverage example, an issuer may report an actual 1.36x debt service coverage ratio against an indenture requirement of 1.25x. This performance may also satisfy an additional bonds test as spelled out in bond documents. A rating agency’s calculation may show coverage at 1.15x because it excludes non-recurring revenues or normalizes expenses. 

An institutional investor, taking a more comprehensive and practical view of risk, may calculate coverage at 0.96x after adjusting for deferred maintenance, anticipated capital needs or other economic realities. Wide variances in calculations are used for illustrative purposes, although these types of results are possible. 

While an issuer may show 230 days cash on hand and meet the indenture requirement, a rating agency may calculate a smaller number if it excludes restricted cash, and an institutional buyer could omit bond proceeds and construction funds from the liquidity calculation.

Institutional investors take on duration, capital and liquidity risk. Their fundamental credit analysis is extremely important and their surveillance protocols must identify emerging credit erosion or improvement before a rating or outlook change occurs. As a former buyside credit analyst, I can recall going through a rigorous process of assigning internal ratings. At times, these ratings differed from those published by rating agencies.

Institutional investors take the evaluation even further by considering a bond’s relative value, the likelihood of spreads widening or tightening, call optionality, internal tax implications and duration risk. These factors are typically weighed against a fundamental credit analysis and often move the “decision to invest” needle. 

These considerations are understandably not part of the rating agency assessment. Having a clear understanding of bondholder rights and remedies in an event of default allows the institutional investor to stay multiple steps ahead of where the credit currently stands and provides investors with possible response scenarios should default occur.  

Different mathematical approaches for ratio calculations can all be justifiable thanks to the absence of a universally accepted accounting framework for municipal credit analysis. This stands in stark contrast to corporate finance practices, which typically have rigid guidelines surrounding financial metrics. 

Complex legal structures and revenue pledges further contribute to ratio irregularities in the muni market. In simple terms, multiple results for the same metric often reflect how stakeholders measure a multi-dimensional canvas of credit risk. The availability of data is not the issue, but a lack of standardization in how the data is interpreted can impact the credit dynamics.