The multiemployer financing crisis provided the impetus for the formation of the Pension Analytics Group. We are a group of actuaries and economists who are concerned that the clock might run out before a viable solution for the multiemployer system's funding problems can be designed and implemented. Delay is costly: with each passing year, the adjustments needed to save the weakest multiemployer plans become increasingly harsh.
Because time is of the essence, we created MEPSIM to accelerate the dialogue between policymakers, stakeholders and multiemployer participants. MEPSIM is compact and flexible, and can be rapidly tailored to keep pace with the reform discussion.
Our modeling work is not limited to MEPSIM. We are currently developing two additional models: (1) a model for the analysis of public sector pension plans and (2) a model for evaluating Social Security (OASDI) reform options. Like MEPSIM, these models will be freely accessible to all internet users.
Emily Andrews, PhD, is our lead economist. Emily has over 30 years of experience analyzing the sustainability of retirement and pension systems. She has served as a director of research at EBRI, a senior researcher at Mathematica Policy Research, a senior economist at the World Bank, and a senior director at the Millennium Challenge Corporation.
Theodore (Ted) Goodman heads our modeling and simulation team. Ted has had a distinguished career as an actuary, with 35 years of experience designing models of single-employer and multiemployer pension plans, as well as retiree medical plans. As a consultant to the PBGC, Ted played a key role in the development of ME-PIMS, a stochastic actuarial / econometric model of the multiemployer pension system and its insurance program. Recently, Ted has designed, and is building, a compact (yet robust) model for simulating public sector pension plans using only the basic data available in valuation reports and other online sources.
The Pension Analytics Group is grateful to Patrick Wiese, an actuary with extensive experience using limited data sets -- such as the 5500 data which contains only basic macro-level information about each pension plan -- as a starting point for pension simulations. Patrick's initial advice and suggestions to our Group were invaluable, planting the seed which eventually grew into MEPSIM.