The assessment covered on this webpage represents one form of risk modeling – stochastic risk modeling. For more information and for other forms of risk modeling prepared by the Office of the State Actuary, please see the Commentary on Risk webpage.
Assessing risk using stochastic modeling allows actuaries to demonstrate and assess the effect of unexpected experience on pension plans. For example, how might investment returns below expectations or lower than expected state revenue growth impact their financial risks? How could the affordability and funded status of pension plans change in the future? Additionally, how do “past practices” in the areas of meeting funding requirements or enhancing benefit levels via legislation impact our pension plans if those practices continue?
To perform such risk assessments and answer questions like the ones above, we created a customized stochastic model and employ a range of assumptions that differ from the assumptions we use in our standard actuarial valuations. For more information on the underlying assumptions used in our most current Projections Model, please see the
Projections Model Assumptions and Methods.
Each year, we update our customized risk profile for the state pension plans administered by the Department of Retirement Systems following the completion of our annual actuarial valuation projections model. We consider a risk profile under two sets of assumptions (Current Law and Past Practices).
Current Law – Where we assume all plans receive the full, actuarially required contribution amount (subject to certain assumed maximums) and benefit provisions remain unchanged over time.
Past Practices – Where we assume all plans receive a percentage (less than 100 percent) of the actuarially required contribution and the Legislature enhances benefit provisions in the future consistent with past practices.
We display the risk measurements under the two sets of assumptions below. These tables were measured based on the most recent
Actuarial Valuation Report (AVR), and market returns through June 30, 2021. Please see the
Projections Model Assumptions and Methods webpage for additional assumptions beyond the AVR.