Demographic Microsimulator for Integrated Urban Systems: Adapting Panel Survey of Income Dynamics to Capture the Continuum of Life

Bingrong Sun, Shivam Sharda, Venu Garikapati, Amine Bouzaghrane, Juan Caicedo, Srinath Ravulaparthy, Isabel Viegas De Lima, Ling Jin, Anna Spurlock, Paul Waddell

Research output: NRELPoster


Agent-based models (ABMs) simulate activity and travel decisions at the disaggregate level of households, and individuals. To do this, ABMs require detailed information pertaining to socioeconomic and demographic characteristics of individuals. Various synthetic population generators (SPGs) have been proposed to address this need. However, most of the SPGs currently in practice are cross-sectional in nature, and do not account for the interrelationships among household's or individual's life progression. This is a major shortcoming of SPGs as literature has shown that transportation decisions are impacted by lifecycle events that unfold over a span of time. While some demographic evolution simulators have been proposed to address this shortcoming, they: i) are developed using cross-sectional data, ii) do not capture the full spectrum of lifecycle events and their interdependency. Overcoming these drawbacks, this paper proposes a Demographic Microsimulator (DEMOS) which captures the 'continuum of life' by accounting for a range of household-, and individual-level lifecycle events. DEMOS is developed using the Panel Survey of Income Dynamics, which is one of the world's longest running longitudinal surveys. DEMOS sub-models consider key lifecycle events which are influenced by a host of demographic variables. The whole framework is applied to evolve the population of San Francisco Bay Area over a 9-year horizon. Results indicate that the household and individual evolution are tightly connected, and that the structural framework (i.e., model sequencing) is a key element in capturing the population trend accurately.
Original languageAmerican English
StatePublished - 2023

Publication series

NamePresented at the Transportation Research Board (TRB) 102nd Annual Meeting, 8-12 January 2023, Washington, D.C.

NREL Publication Number

  • NREL/PO-5400-84809


  • agent-based models
  • demographic evolution
  • long-term forecasting
  • microsimulation
  • panel study of income dynamics


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