Fitch Ratings has published an exposure draft outlining proposed revisions to its rating criteria for U.S. local governments.
Fitch estimates roughly 35% of its local government ratings would be affected by the criteria change. The rating changes, evenly split between upgrades and downgrades, are anticipated to be mostly one-notch.
"The proposed criteria and rating model will better differentiate credits within a highly compressed rating portfolio, enhance communication around rating positioning and transition, and improve criteria usability," Fitch Senior Director Michael Rinaldi said Thursday during an online presentation.
The primary goal is to provide a more consistent and transparent view of credit quality by combining the output of a rating model with analytical judgment, Rinaldi said.
Fitch will apply the existing criteria to existing local government ratings, but it will apply the criteria described in the
For instance, in doing annual surveillance on an existing county's credit it would apply the current criteria, but if the county issues debt on a new credit, the new criteria would be applied, Renaldi explained.
The new rating criteria will also add some flexibility for analysts in cases where local governments are impacted by an extreme weather event, Rinaldi and Evette Caze, director of Fitch's U.S. Local Governments Group, said during the presentation.
The proposed framework reorganizes the issuer default rating analysis for U.S. local governments across three key rating drivers, from four in the previous framework, according to the draft.
The three drivers capture the issuer's financial profile; demographic and economic strength; and long-term liability burden. Previously the four drivers were organized as revenue framework; expenditure framework; operating framework; and long-term liability burden.
Fitch says the new framework introduces select economic, demographic and liability metrics conducive to a model-supported rating approach, and assesses unrestricted reserves and budget flexibility against fixed category-specific fund balance thresholds.
It assigns ratings equal to the issuer default rating for bonds backed by absolute and non-cancellable covenants to pay debt service, rather than a notch below the IDR.
"A feature worth close attention in the proposed model is the headroom tool, which will clearly show how close or how far a given rating is from the next rating level," Rinaldi said.
"We often get feedback that the line between AA and AA-minus is hard to see," Rinaldi said. "We acknowledge and agree with that sentiment. You can see in the draft chart where 8 is AA and 9 is AA-plus. The actual metric value as you see is 8.25 vs. 8.9, so you can evaluate how far the rating is from the next higher rating. And you can see in the model what would move that rating."
This would allow an issuer to see exactly how close they are to the AA-plus as opposed to the AA rating, and how much difference issuing an additional $100 million in debt might move the needle, Rinaldi said.
The new model could also "capture emergent risk like when a location is struck by a hurricane or some other natural disaster," he said. "Where short-term risk would not be captured through the model of the applied rating, based on historical and forward looking metrics, the model might understate the credit risk. There will be the ability for the analyst and rating's committee to notch down based on the model."
The rating agency released the exposure draft Sept. 21 and plans to publish the finalized version in January. In the interim, it is seeking public comments through Nov. 17 from market participants on the proposed changes. Respondents should email comments to
The proposed methodology that will affect issuer default ratings introduces new metrics conducive to a model-supported rating approach, yet broadly retains the same analytical concepts to derive local government ratings, according to the exposure draft.
The proposed methodology will formalize the relationship between credit metrics and ratings to facilitate peer comparisons, pro forma scenarios and the ability to provide more timely responses to changes in the macro environment.
