Empirical measurement of an inflation index: a multiple-indicators distributed-lag approach

Keshab Shrestha

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Abstract

Zellner (1970) considered an interesting model containing an unobservable variable that was treated as a linear combination of many observable variables. Goldberger (1972a, b, 1974) extended Zellner’s model to the case of several dependent variables in the multiple causes model (MCM) and the multiple indicator multiple cause model. This article presents a dynamic extension of the MCM that allows for a geometrically distributed lag in the unobservable variable. The maximum likelihood estimation technique for the parameters of the model is derived. The model is then used to obtain the empirical measurement of the inflation index at the wholesale level. Furthermore, it is shown that under certain conditions an increased number of indicators leads to a more efficient estimator.

Original languageEnglish
Pages (from-to)219-225
Number of pages7
JournalJournal of Business and Economic Statistics
Volume7
Issue number2
DOIs
Publication statusPublished - Apr 1989
Externally publishedYes

Keywords

  • Efficient estimator
  • Maximum likelihood
  • Unobservable variable

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