National Academies Press: OpenBook
« Previous: Critique
Suggested Citation:"Suggestions." 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 345

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.

DOCUMENTATION FOR MICROSIMULATION MODELS: A REVIEW OF TRIM2, MATH, AND HITSM 345 nationwide sample survey of over 60,000 households conducted during selected months by the Bureau of the Census…. The CPS is designed for income analyses.” In fact, the CPS is conducted monthly and is designed to derive estimates of unemployment. Page II-4 has a footnote that states: “Statistical matching is a variation on the data collection procedures used by the Bureau of the Census and other survey research organizations called ‘hot decking.'” In fact, statistical matching is a data imputation procedure, and its relationship to hot decking is arguable. A footnote on p. II-5 implies that subfamilies are composed of single-parent daughters of family heads when, in fact, subfamilies can be intact and can be single-parent males. These types of errors begin to erode the reader's confidence in the model because it appears that Lewin/ICF, Inc., did not have a complete understanding of the underlying data. Passages such as the following further erode the reader's confidence (Lewin/ICF, Inc., 1988: IV-88): The average LIHEAP benefit amounts reported in the March 1987 CPS varied substantially across income, fuel type, household size, and Census region groups. However, due to limited sample size, some of the estimated average benefits varied more than we felt reasonable. To reduce this apparently spurious variation, we estimated a regression of reported LIHEAP benefits as a function of income, household size, fuel type, and Census region. We then solved the estimated regression model to obtain estimates of average benefits for each income/fuel type/ household size/Census region group as shown in Table 38. In the HITSM simulations, eligible individuals were assigned the average benefit reported in the CPS for households of similar characteristics using the data in Table 38. Although it is not clear what is meant by “solved the estimated regression model,” this passage seems to indicate that Lewin/ICF did not believe the reported data because of excessive variation, so Lewin/ICF estimated a model with discrete independent variables and assigned predicted means to all observations. Suggestions Clearly, many of the problems with the HITSM documentation may simply reflect poor technical writing and may not be indicative of the quality of the model. However, Lewin/ICF needs to understand that in microsimulation, where the particular policies or scenarios being analyzed may never occur, the audience for the projections and analyses must rely on the communicated result to formulate judgments about a model. As a technical report, the HITSM documentation would be passable after careful editing and production. As far as providing model documentation to outside users of the model, the document the panel reviewed is inadequate.

Next: COMPARISONS WITH IEEE STANDARDS »
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!