Projecting Longitudinal Earnings Patterns for Long-Run Policy Analysis: Technical Paper 2003-02

Working Paper
April 2, 2003

Amy Rehder Harris and John Sabelhaus

This paper presents a method for projecting person-level labor force participation and earnings for the U.S. population in a dynamic micro-simulation setting. A dynamic micro-simulation model starts with economic and demographic data for a current sample of the population, then stochastically "ages" that sample forward through time, ultimately generating a longitudinal micro data file, which is useful for studying Social Security and other long-term issues. The stochastic projections described here proceed in four steps: in each year, every person is sequentially assigned labor force participation, hours worked, unemployment spells, and earnings. The equations used to project the sequence of outcomes are designed to generate realistic cross-sectional and longitudinal heterogeneity, to capture cohort-level trends, and to be consistent with the underlying macro/policy environment in which the outcomes are projected. The projections suggest significant increases in the overall percentage of females in the labor force and the share of females working full time. Also, the relative earnings of lower-educated males are expected to continue declining, while the relative earnings of higher-educated females are projected to rise disproportionately.