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The True Cost-of-Living Concept

  • R. L. Basmann
  • D. J. Slottje
  • K. Hayes
  • J. D. Johnson
  • D. J. Molina
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 316)

Abstract

This chapter examines the sensitivity of the cost of living to some aspects of price changes and income changes that cannot be detected by Laspeyres indexes such as the CPI-U and CPI-W. Although its content is confined to positive economic analysis, the article does cast light on normative choices in welfare policy. Formation of practical strategies in the negotiation of escalator clauses in private sector wage contracts involves consideration of both normative values and positive descriptions of the real environment. The same is true of policy choices in the political arena, for instance in the determination of cost-of-living adjustments (COLAs) in pensions and transfer payments. The price and income sensitivities of the cost of living, expressed as elasticities, are used to determine the size of COLAs required to keep real incomes of recipients constant.

Keywords

Marginal Rate Income Elasticity Price Vector Expenditure Share Commodity Group 
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References

  1. 6.
    See Basmann et al. (1985a), Fisher and Shell (1968, pp.97–101) Samuelson and Swamy (1974, pp. 585–586)Google Scholar
  2. 7.
    See Diamond (1984 p. 25) and Frentmp (1984 p.16)Google Scholar
  3. 9.
    Notice that this chapter has nothing to do with a test of the Pollak hypothesis that “the snob appeal” effect of prices is confined to the γ i, i = l,...,n, in (5.13) under the additional assumption that every random disturbance ui is identically zero, and γ i remain constant from observation to observation, cf. Pollak (1977, p. 70).Google Scholar
  4. 1.
    See Figure 5.1 aboveGoogle Scholar
  5. 2.
    There are several, more or less, trivial proofs in previous articles: Basmann et al. (1983, p. 412); Basmann et al. (1985b, p. 20).Google Scholar
  6. 13.
    This direct approach is often (not always) convenient in constructing (5.13) from previously estimated demand systems such as the translog system.Google Scholar
  7. 14.
    Derivations of the elasticities are given in Basmann and Slottje (1987)Google Scholar
  8. 15.
    ζ is the random disturbance in the j th expenditure share, M j /M The derivation of (5.19) is given in the article by Basmann et al. (1985a), pp. 73–75).Google Scholar
  9. 16.
    The formal properties of the CRES form have been studied by Mukerji (1963, p. 233), Gorman (1965), Hanoch (1971, pp. 708–711; 1975, pp. 416–418) and Barnett (1981), pp. 265–266). The CES form is a special case of CRES. For the GFT direct utility function yielding the Leser-Houthakker “addilog” demand function systems, see Basmann et al. (1985a, pp. 51–52).Google Scholar
  10. 17.
    In this study, the GFT utility function (5.13) is applied to the percapita expenditure and demand system for a group of consumers. There is no theoretical basis for expecting its derived demand systems to possess the properties of zero homogeneity, symmetry and negative semi-definiteness of substitution terms; cf. Schultz (1938, pp. 628–633). Testing whether the percapita demands are those of an “ideal” consumer is not relevant here.Google Scholar
  11. 21.
    Formulas (5.21) and (5.26) do make clear that only one numeraire specification is required for the computation of maximum likelihood estimates of demand function elasticities and index elasticities.Google Scholar
  12. 24.
    These elasticities are significant, only near the base year (1972) where that is to be expected on analytic grounds.Google Scholar
  13. 26.
    Mentioned in Sec. 5.5. This is the GFT class within which the CRES direct utility function was tested.Google Scholar
  14. 27.
    See Johnson (1987, 1988)Google Scholar

Copyright information

© Springer Science+Business Media New York 1988

Authors and Affiliations

  • R. L. Basmann
    • 1
  • D. J. Slottje
    • 2
  • K. Hayes
    • 2
  • J. D. Johnson
    • 4
  • D. J. Molina
    • 3
  1. 1.Department of EconomicsSUNY BinghamtonBinghamtonUSA
  2. 2.Department of EconomicsSouthern Methodist UniversityDallasUSA
  3. 3.Department of EconomicsUniversity of North TexasDentonUSA
  4. 4.Department of EconomicsUniversity of Mississippi UniversityUSA

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