National Academies Press: OpenBook
« Previous: Model Design
Suggested Citation:"Model Evaluation." 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 3

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

INTRODUCTION 3 They typically include static “aging” routines to bring their databases up to date or project them into the future. Such routines reweight the individual records to match outside control totals for key demographic characteristics and make other adjustments for changes in income and employment. Dynamic models operate on longitudinal databases that contain individual histories. They “grow” their databases forward in time by applying transition probabilities to each record for such events as birth, death, marriage, labor force status change, and so on. Within these two distinct model types, there are variations in handling common functions that result from such factors as differences in client needs and in styles of the model developers. In Chapter 3 Citro and Ross describe the different approaches taken by three static models—TRIM2, MATH, and HITSM (see below)—to two important functions of models that simulate income support programs such as AFDC and food stamps: the routines to simulate the participation decision and the routines to convert annual to monthly values. In Chapter 4 Ross compares and contrasts two major dynamic models—DYNASIM2 and PRISM (see below)—and reflects generally on the dynamic modeling approach. Computing Technology Given their complexity and size, microsimulation models are very dependent on computer hardware and software capabilities to operate in a cost-effective manner. Most models that are in widespread use today are designed for mainframe, batch-oriented processing that minimizes the cost of single computer runs but imposes barriers to access and inhibits flexible, timely adaptation to meet new policy needs. In Chapter 5 Cotton and Sadowsky compare and contrast the mainframe computing environment for the TRIM2 model with the personal computer-based environment for the model developed by Statistics Canada, SPSD/M (see below). Cotton and Sadowsky assess likely future directions for computer hardware and software that offer potential benefits for improved microsimulation model capabilities. Model Evaluation Assessment of the quality of outputs from models is a vitally important component of the process of using model estimates in the policy debate and of determining fruitful directions for investment in improved model capabilities. However, for a variety of reasons, validation of microsimulation models has been a largely neglected activity. In Chapter 6 Cohen discusses the potential for using relatively new, computer-intensive sample reuse techniques for developing variance estimates for the outputs of microsimulation models. In Chapter 7 Cohen reviews the scanty literature of previous microsimulation model validation studies.

Next: Dynamic Simulation of Income Model 2 (DYNASIM2) »
Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume II, Technical Papers Get This Book
×
Buy Paperback | $100.00
MyNAP members save 10% online.
Login or Register to save!
Download Free PDF

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.

  1. ×

    Welcome to OpenBook!

    You're looking at OpenBook, NAP.edu's online reading room since 1999. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

    Do you want to take a quick tour of the OpenBook's features?

    No Thanks Take a Tour »
  2. ×

    Show this book's table of contents, where you can jump to any chapter by name.

    « Back Next »
  3. ×

    ...or use these buttons to go back to the previous chapter or skip to the next one.

    « Back Next »
  4. ×

    Jump up to the previous page or down to the next one. Also, you can type in a page number and press Enter to go directly to that page in the book.

    « Back Next »
  5. ×

    To search the entire text of this book, type in your search term here and press Enter.

    « Back Next »
  6. ×

    Share a link to this book page on your preferred social network or via email.

    « Back Next »
  7. ×

    View our suggested citation for this chapter.

    « Back Next »
  8. ×

    Ready to take your reading offline? Click here to buy this book in print or download it as a free PDF, if available.

    « Back Next »
Stay Connected!