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Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume II, Technical Papers by Division of Behavioral and Social Sciences and Education 9780309045421

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Description

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.

Table of Contents
  • Front Matter
  • Introduction
  • Model Design
  • Model Evaluation
  • Dynamic Simulation of Income Model 2 (DYNASIM2)
  • Social Policy Simulation Database/Model (SPSD/M)
  • REFERENCES
  • Databases and Methods of Data Enhancement
  • INTRODUCTION
  • DATA NEEDS FOR MODELING INCOME SUPPORT PROGRAMS
  • SURVEY DESIGN OF THE MARCH CPS AND THE SIPP
  • Population Coverage
  • Household and Individual Nonresponse
  • Item Nonresponse
  • Reporting Errors
  • Sample Size
  • Data Delivery
  • Income Accounting Period
  • Income Detail
  • Households and Families Versus Program Filing Units
  • Asset Holdings
  • 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
  • INTRODUCTION
  • File Treatment
  • Constrained and Unconstrained Statistical Matching
  • Choosing the Matching Variables
  • 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
  • Conditional Independence
  • Limitations in Modeling
  • Reweighting of File B Data Resulting From Statistical Matching
  • Iterative Proportional Fitting
  • More Data Collection
  • Multiple Matching and File Concatenation
  • Rough Sensitivity Analysis
  • CONCLUDING NOTE
  • REFERENCES
  • Model Design
  • INTRODUCTION
  • CONVERTING ANNUAL TO MONTHLY VALUES IN TRIM2, MATH, AND HITSM
  • HITSM
  • TRIM2
  • MATH
  • HITSM
  • TRIM2
  • Input Data
  • MATH
  • Comment
  • Evaluation of Alternative Months Procedures
  • Need for Further Validation
  • PARTICIPATION FUNCTIONS FOR SSI, AFDC, AND FOOD STAMPS IN TRIM2, MATH, AND HITSM
  • TRIM2
  • HITSM
  • TRIM2
  • TRIM2
  • MATH
  • Evaluation of Alternative Participation Functions
  • APPENDIX: PERFORMANCE OF THE AFDC CALIBRATION PROCESS IN TRIM2
  • REFERENCES
  • THE MODELS
  • STARTING DATABASES
  • SIMULATION OF LONGITUDINAL HISTORIES
  • Labor Force Simulations
  • PRISM Pension Coverage and Characteristics
  • Interactions Between Pension and Social Security Eligibility and Retirement in PRISM
  • Labor Force Simulations
  • Retirement in DYNASIM2
  • DYNASIM2 Pension Coverage and Characteristics
  • CONCLUSIONS
  • REFERENCES
  • Computing Technology
  • INTRODUCTION
  • Layered Structure
  • Single Period Versus Future Projections
  • Static Versus Dynamic Simulation
  • Historical Background
  • History
  • Database Creation
  • Database Structure and Size
  • SPSD/M Parameters
  • Model Execution
  • Comparing Model Runs
  • Output Facilities
  • Other Software Facilities
  • Availability, Customer Base, and Technical Support
  • Future Work
  • History
  • Database Creation
  • Database Structure and Size
  • Database Adjustment
  • Operating Characteristics
  • TRIM2 Parameters
  • Model Execution
  • Output Facilities
  • Other Software Facilities
  • Operating Environment
  • Comparison
  • Background
  • Informed Industry Observers
  • Specific Technical Product Information
  • Advances in Computer Processors
  • Advances in Primary Memory
  • Advances in Computer Systems Architecture
  • Economic Studies of Industry Performance
  • Assessment and Predictions
  • 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
  • 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
  • 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
  • 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
  • REFERENCES
  • INTRODUCTION
  • NATURE OF POPULATION PROJECTION MODELS
  • VALIDATING POPULATION PROJECTIONS
  • Sensitivity Analysis
  • External Validation
  • CONFIDENCE INTERVALS
  • CONCLUSIONS
  • REFERENCES
  • Model Documentation
  • INTRODUCTION
  • PURPOSES OF DOCUMENTATION AND EVALUATION CRITERIA
  • Critique
  • Suggestions
  • Critique
  • Suggestions
  • Critique
  • Suggestions
  • COMPARISONS WITH IEEE STANDARDS
  • REFERENCES


Book Information
ISBN 9780309045421
Author Division of Behavioral and Social Sciences and Education
Format Paperback
Page Count 368
Imprint National Academies Press
Publisher National Academies Press

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