Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling

Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling

Volume II, Technical Papers

  • Publisher: National Academies Press
  • ISBN: 9780309045421
  • eISBN Pdf: 9780309593472
  • Place of publication:  United States
  • Year of digital publication: 1991
  • Month: January
  • Pages: 360
  • Language: English

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.

  • Improving Information for Social Policy Decisions
  • Copyright
  • Contents
    • Contents
    • Introduction
      • OVERVIEW
        • Databases and Methods of Data Enhancement
        • Model Design
        • Computing Technology
        • Model Evaluation
        • Model Documentation
      • MODELS
        • Dynamic Simulation of Income Model 2 (DYNASIM2)
        • Household Income and Tax Simulation Model (HITSM)
        • Micro Analysis of Transfers to Households (MATH) Model
        • Multi-Regional Policy Impact Simulation (MRPIS) Model
        • Pension and Retirement Income Simulation Model (PRISM)
        • Social Policy Simulation Database/Model (SPSD/M)
        • Transfer Income Model 2 (TRIM2)
      • REFERENCES
  • Databases and Methods of Data Enhancement
    • 1 Databases for Microsimulation: A Comparison of the March CPS and SIPP
      • INTRODUCTION
      • DATA NEEDS FOR MODELING INCOME SUPPORT PROGRAMS
      • SURVEY DESIGN OF THE MARCH CPS AND THE SIPP
      • SURVEY-BASED PROBLEMS
        • Population Coverage
        • Household and Individual Nonresponse
        • Item Nonresponse
        • Reporting Errors
        • Sample Size
        • Data Delivery
      • PROBLEMS OF VARIABLE MISSPECIFICATION
        • Income Accounting Period
        • Income Detail
        • Household Composition Reference Period
        • Households and Families Versus Program Filing Units
      • DATA OMISSIONS
        • Asset Holdings
        • Expenditures
        • Extended Families
        • Other Variables for Related Policy Issues
      • EVALUATION OF ESTIMATES OF PROGRAM PARTICIPANTS FROM CPS AND SIPP
      • THE DIVISION OF LABOR FOR PRODUCTION OF DATABASES FROM CPS AND SIPP
      • THE SUITABILITY OF CPS AND SIPP FOR INTEGRATED MODELING OF TAXES AND TRANSFERS
      • CONCLUSIONS
      • REFERENCES
    • 2 Statistical Matching and Microsimulation Models
      • INTRODUCTION
        • Definition of Statistical Matching
        • File Treatment
        • Constrained and Unconstrained Statistical Matching
        • Choosing the Matching Variables
      • EXAMPLES OF STATISTICAL MATCHES IN MICROSIMULATION MODELS
        • The EM-AF Statistical Match
        • Merge File of the Office of Tax Analysis
        • 1966 Merge File for Household Income Data
        • Statistics Canada SCF-FEX Match
        • AFDC-Census Match
      • STATISTICAL MATCHING: ADVANTAGES AND PROBLEMS
        • The Advantages of Statistical Matching
        • Problems Associated With Statistical Matching
          • Conditional Independence
          • Limitations in Modeling
          • Error Resulting From the Distance Between X(A) and X(B)
          • Reweighting of File B Data Resulting From Statistical Matching
      • ALTERNATIVES TO STATISTICAL MATCHING
        • Variance-Covariance Analysis
        • Iterative Proportional Fitting
        • More Data Collection
        • Multiple Matching and File Concatenation
        • Rough Sensitivity Analysis
      • CONCLUDING NOTE
      • REFERENCES
  • Model Design
    • 3 Alternative Model Designs: Program Participation Functions and the Allocation of Annual to Monthly Values in TRIM2, MATH…
      • INTRODUCTION
      • CONVERTING ANNUAL TO MONTHLY VALUES IN TRIM2, MATH, AND HITSM
        • Location of the Annual to Monthly Conversion in the Model Run Stream
          • TRIM2
          • MATH
          • HITSM
        • Determination of Monthly Labor Force and Employment Status
          • Input Data
          • TRIM2
          • MATH
          • HITSM
          • Comment
        • Determination of Monthly Earnings
          • Input Data
          • TRIM2
          • MATH
          • HITSM
          • Comment
        • Determination of Monthly Unearned Income
          • Input Data
          • TRIM2
          • MATH
          • HITSM
          • Comment
        • Evaluation of Alternative Months Procedures
        • Need for Further Validation
      • PARTICIPATION FUNCTIONS FOR SSI, AFDC, AND FOOD STAMPS IN TRIM2, MATH, AND HITSM
        • Supplemental Security Income Participation Functions
          • TRIM2
          • MATH
          • HITSM
          • Comment
        • AFDC Participation Functions
          • TRIM2
          • MATH
          • HITSM
          • Comment
        • Food Stamp Participation Functions
          • TRIM2
          • MATH
          • HITSM
          • Comment
        • Evaluation of Alternative Participation Functions
      • APPENDIX: PERFORMANCE OF THE AFDC CALIBRATION PROCESS IN TRIM2
      • REFERENCES
    • 4 DYNASIM2 and PRISM: Examples of Dynamic Modeling
      • THE MODELS
      • STARTING DATABASES
      • CONTROL TOTALS
      • SIMULATION OF LONGITUDINAL HISTORIES
      • PRISM LABOR FORCE AND PENSION SIMULATIONS
        • Labor Force Simulations
        • PRISM Pension Coverage and Characteristics
        • Interactions Between Pension and Social Security Eligibility and Retirement in PRISM
      • DYNASIM2 LABOR FORCE AND PENSION SIMULATIONS
        • Labor Force Simulations
        • Retirement in DYNASIM2
        • DYNASIM2 Pension Coverage and Characteristics
      • PROGRAM SIMULATIONS
      • CONCLUSIONS
      • REFERENCES
  • Computing Technology
    • 5 Future Computing Environments for Microsimulation Modeling
      • INTRODUCTION
        • Characteristics of Microanalytic Simulation Models
          • Layered Structure
          • Single Period Versus Future Projections
          • Static Versus Dynamic Simulation
        • Historical Background
      • CURRENT STATIC SOCIOECONOMIC MICRO ANALYTIC SIMULATION MODELS
        • Overview
        • SPSD/M
          • History
          • Database Creation
          • Database Structure and Size
          • Database Adjustment
          • Operating Characteristics
          • SPSD/M Parameters
          • Model Execution
          • Comparing Model Runs
          • Output Facilities
          • Auxiliary Models
          • Other Software Facilities
          • Operating Environment
          • Availability, Customer Base, and Technical Support
          • Future Work
        • TRIM2
          • History
          • Database Creation
          • Database Structure and Size
          • Database Adjustment
          • Operating Characteristics
          • TRIM2 Parameters
          • Model Execution
          • Comparing Model Runs
          • Output Facilities
          • Auxiliary Models
          • Other Software Facilities
          • Operating Environment
          • Availability, Customer Base, and Technical Support
          • Future Work
          • Comparison
        • Summary
      • ANTICIPATED ADVANCES IN COMPUTING AND INFORMATION TECHNOLOGY
        • Background
        • Informed Industry Observers
        • Specific Technical Product Information
          • Advances in Computer Processors
          • Advances in Primary Memory
          • Advances in Secondary Memory
          • Advances in Computer Systems Architecture
        • Economic Studies of Industry Performance
        • Analysis of Industry Information
        • Assessment and Predictions
      • FUTURE PROSPECTS FOR SOCIOECONOMIC MICROANALYTIC SIMULATION MODELS
        • Nature of the Demand for Microanalytic Simulation Models
        • Factors Affecting the Availability of Microsimulation Models
        • Functions of a System for Microanalytic Simulation
          • Larger Model Execution on the Desktop
          • Advances in Software Methodology
          • Model Specification
          • Object-Oriented Computing
          • Simulation Module Consistency
          • Advantages of Desktop-Based Environments
          • Summary
      • RECOMMENDATIONS AND CONCLUSIONS
        • Short-Term Issues
          • Porting TRIM2 to an MS-DOS Environment
          • Porting TRIM2 to a UNIX Environment
          • Translating TRIM2 Modules to the C Language
          • Benefits of Porting TRIM2
        • Medium-Term Issues
      • REFERENCES AND BIBLIOGRAPHY
  • Model Validation
    • 6 Variance Estimation of Microsimulation Models Through Sample Reuse
      • COMPUTATIONS OF MICROSIMULATION MODELS
      • NONPARAMETRIC VARIANCE ESTIMATION
      • MODELS AND VARIABILITY
      • BOOTSTRAPPING MICROSIMULATION MODELS
        • Incorporation of Sensitivity Analyses—Measurement of Total Uncertainty
        • Number of Replications Needed
        • Use of Resampling Techniques in Constructing Confidence Intervals
      • SUMMARY
      • REFERENCES
    • 7 Evaluations of Microsimulation Models: Literature Review
      • HENDRICKS AND HOLDEN (1976A)
      • HENDRICKS AND HOLDEN (1976B)
      • GENERAL ACCOUNTING OFFICE (1977)
      • HOLDEN (1977)
      • HAYES (1982)
      • JEFFERSON (1983)
      • HAVEMAN AND LACKER (1984)
      • ICF, INC. (1987)
      • KORMENDI AND MEGUIRE (1988)
      • BETSON (1988)
      • DOYLE AND TRIPPE (1989)
      • BEEBOUT AND HAWORTH (1989)
      • BURTLESS (1989)
      • DISCUSSION
      • REFERENCES
    • 8 A Validation Experiment with TRIM2
      • OVERVIEW OF THE EXPERIMENT
      • CHOICE OF MODEL YEAR, PROGRAM YEAR, AND COMPARISON VALUES
      • CHOICE OF COMPONENT MODULES AND ALTERNATIVES FOR STUDY IN TRIM2
      • OUTPUTS EXAMINED
      • ANALYSIS OF RESULTS
        • Total Variability Due to Use of Alternative Modules
        • Analysis of Variance Methods for Sensitivity Analysis and External Validation
        • Nonparametric Analysis
        • Analysis of Categorical Data
      • MAJOR CONCLUSIONS
      • LIMITATIONS OF THE PRESENT STUDY
      • DESIGN OF EXPERIMENT ISSUES
      • SUMMARY
      • REFERENCES
    • 9 Evaluating the Accuracy of U.S. Population Projection Models
      • INTRODUCTION
      • NATURE OF POPULATION PROJECTION MODELS
      • VALIDATING POPULATION PROJECTIONS
        • Sensitivity Analysis
        • External Validation
      • CONFIDENCE INTERVALS
      • CONCLUSIONS
      • REFERENCES
  • Model Documentation
    • 10 Documentation for Microsimulation Models: A Review of TRIM2, MATH, and HITSM
      • INTRODUCTION
      • PURPOSES OF DOCUMENTATION AND EVALUATION CRITERIA
        • TRIM2
        • Critique
        • Suggestions
        • MATH
        • Critique
        • Suggestions
        • HITSM
        • Critique
        • Suggestions
      • COMPARISONS WITH IEEE STANDARDS
      • REFERENCES

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