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Suggested Citation:"Labor Force Simulations." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume II, Technical Papers. Washington, DC: The National Academies Press. doi: 10.17226/1853.
Page 131

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DYNASIM2 AND PRISM: EXAMPLES OF DYNAMIC MODELING 131 to stop working. Therefore, the transition probabilities between annual hours of work categories for individuals who accepted retirement income during the year were calculated separately from those of nonelderly nonretired workers. These transition probabilities vary by sex of the worker and whether he or she is receiving a pension or social security income. DYNASIM2 LABOR FORCE AND PENSION SIMULATIONS Labor Force Simulations In contrast to PRISM, which simulates most of the labor force experience variables by simulating transitions from one hours-of-work category to another, DYNASIM2 simulates labor force experience sequentially, as part of its Family and Earnings History Submodel. DYNASIM2 first simulates whether the individual participates in the labor force at all during the year. If the individual does participate, the model then simulates the number of hours of participation (both employed and unemployed time are included). Then the hourly wage is estimated. Then the model simulates whether the individual is unemployed during the year and, if so, the fraction of time in the labor force that the individual is unemployed. With this information, it is possible to combine the wage with hours of employment to estimate annual earnings. The labor force participation, hours, and wage equations were estimated in the early 1980s from several years of data from the Panel Study of Income Dynamics (PSID) (Holden, 1980).2 The labor force models are sound, basic economic models that include human capital variables (education and age) and control for the usual demographic variables (including race, sex, marital status, residence in the South, disabled, presence of young children, and others). In addition, the estimates of these labor force variables are linked across time and among one another through their error structures. The labor force participation equation has an error term that includes a serially correlated component, v, composed of last period's v, a serial correlation coefficient that is different for each of 16 demographic groups, and z, a transitory component that is selected each year for each individual. The error term also includes an individual-specific error term, u, which is fixed for each individual throughout his or her life, drawn from a normal distribution that has a different variance for each of the 16 demographic groups. Both of these components of the error term increase the stability across time among labor force participation decisions by each individual. The error term of the hours equation includes a serially correlated term (which differs across six demographic groups) and a second term that is shared 2The labor force participation equations drew on 13 years of data from the PSID, while the wage and hours equations were estimated from 9 years of data from the PSID.

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Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume II, Technical Papers Get This Book
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This volume, second in the series, provides essential background material for policy analysts, researchers, statisticians, and others interested in the application of microsimulation techniques to develop estimates of the costs and population impacts of proposed changes in government policies ranging from welfare to retirement income to health care to taxes.

The material spans data inputs to models, design and computer implementation of models, validation of model outputs, and model documentation.

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