PROJECTQuantitative Data Analysis

Project Navigation
  • 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

  • Profound social, economic, and demographic changes are transforming how we prepare for retirement. Employer-sponsored pension plans are fading away, Social Security is changing, costs for health care and long-term services and supports are rising, and the sheer increase in the older population is squeezing younger taxpayers.

    But there is good news, too. As women have worked and earned more, the generation now entering or nearing retirement has amassed more retirement savings and rights to future Social Security benefits than ever before. Older Americans are also better educated and healthier than previous generations, allowing many to work longer and earn more.

    How will these conflicting trends play out? How will coming generations fare in retirement? How might changes in Social Security, pension policy, and Medicare, as well as financing options for long-term services and supports, improve retirement security?

    The Urban Institute’s Dynamic Simulation of Income Model (DYNASIM) can help answer these questions. Using the best and most recent data available, it projects the size and characteristics—such as income and health status—of the US population for the next 75 years.

    DYNASIM can also describe “what if” scenarios, showing how outcomes would likely evolve under changes to public policies, business practices, or individual behaviors. With this model, we can show how different groups will fare over time, who is moving ahead and who is being left behind, and which groups would win and lose under various policy options.

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