A decomposition method based on a model of continuous change

Demography volume 45, pages785–801(2008)Cite this article

Abstract

A demographic measure is often expressed as a deterministic or stochastic function of multiple variables (covariates), and a general problem (the decomposition problem) is to assess contributions of individual covariates to a difference in the demographic measure (dependent variable) between two populations. We propose a method of decomposition analysis based on an assumption that covariates change continuously along an actual or hypothetical dimension. This assumption leads to a general model that logically justifies the additivity of covariate effects and the elimination of interaction terms, even if the dependent variable itself is a nonadditive function. A comparison with earlier methods illustrates other practical advantages of the method: in addition to an absence of residuals or interaction terms, the method can easily handle a large number of covariates and does not require a logically meaningful ordering of covariates. Two empirical examples show that the method can be applied flexibly to a wide variety of decomposition problems. This study also suggests that when data are available at multiple time points over a long interval, it is more accurate to compute an aggregated decomposition based on multiple subintervals than to compute a single decomposition for the entire study period.

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Author information

Affiliations

  1. CUNY Institute for Demographic Research, USA

    Shiro Horiuchi

  2. Department of Demography, University of California, Berkeley, USA

    John R. Wilmoth

  3. Huffi ngton Center on Aging and Molecular and Human Genetics, Baylor College of Medicine, USA

    Scott D. Pletcher

  4. Program in Urban Public Health, Hunter College, 425 East 25th Street, Box 816, 10010-2590, New York, NY

    Shiro Horiuchi

Authors
  1. Shiro Horiuchi
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  2. John R. Wilmoth
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  3. Scott D. Pletcher
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Corresponding author

Correspondence to Shiro Horiuchi.

Additional information

This research was supported by Grant R01-AG11552 from the National Institute on Aging. We are grateful to Juha Alho, Ronald Lee, and the anonymous reviewers for comments on earlier versions of this article. Joel E. Cohen gave us a useful technical suggestion. Supplementary documents for this article (including sensitivity analyses, additional examples, and a MATLAB program) are available online at http://www.demog.berkeley.edu/~jrw/Papers/decomp.suppl.pdf.

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Horiuchi, S., Wilmoth, J.R. & Pletcher, S.D. A decomposition method based on a model of continuous change. Demography 45, 785–801 (2008). https://doi.org/10.1353/dem.0.0033

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Keywords

  • Life Table
  • Total Fertility Rate
  • Decomposition Analysis
  • Decomposition Result
  • Decomposition Problem