PROJECTQuantitative Data Analysis

• Project Home
• Inference
• Impact Analysis
• Bias
• Experiments
• Paired Testing
• Quasi-experimental Methods
• Difference-in-Difference and Panel Methods
• Instrumental Variables
• Propensity Score Matching
• Regression Discontinuity
• Regression Techniques
• Generalized Linear Model
• Linear Regression
• Logit and Probit Regression
• Segregation Measures
• Inequality Measures
• Decomposition Methods
• Descriptive Data Analysis
• Microsimulation
• The Dynamic Simulation of Income Model DYNASIM
• The Health Insurance Policy Simulation Model HIPSM
• The Model of Income in the Near Term (MINT)
• The Transfer Income Model TRIM
• The Tax Policy Center Microsimulation Model
• Performance Measurement and Management

• Microsimulation is used to estimate how demographic, behavioral, and policy changes might affect individual outcomes, and to better understand the effects of current policies.

How does it work?

In the social sciences, a microsimulation model is a computer program that mimics the operation of government programs and demographic processes on individual ("micro") members of a population—people, households, or businesses, for example. For each observation in a large-scale survey, the computer program simulates outcomes of interest—such as income tax liabilities or Social Security benefits—by applying actual or hypothetical program rules to the survey data about that observation. Microsimulation models also include methods to estimate behavior, such as enrolling in employer-sponsored health insurance or applying for food stamps. Each individual result—a family's simulated tax liability, a person's Social Security benefit, and so on—is multiplied by whatever "weight" is associated with the unit in the survey data. The weighted individual results are added together to obtain aggregate results.

Microsimulation models can be divided into two broad classes: static and dynamic. Dynamic microsimulation models can "age" the population measured by a survey many decades into the future by applying demographic and economic processes—births, deaths, marriage, divorces, employment, retirement, and so on—year by year, person by person; and can then run simulations on an aged population. Static models focus on the present, past, and near future; their strength lies in detailed simulations of government programs and their interactions.

Microsimulation models require substantial time to develop and maintain, but allow analyses usually not supported by macroeconomic or cell-based models. Microsimulation models capture interactions between multiple programs or policies, tabulate results by a wide variety of socioeconomic characteristics, and allow almost unlimited "what if" testing of prospective government policies.

Research examples

The following four microsimulation models were developed and are maintained at the Urban Institute:

Research Methods Microsimulation modeling Research methods and data analytics Data analysis Quantitative data analysis