Computing Multivariate-Weighted Consumer Price Index: An Application Manual in R

Abstract

A multivariate weighting approach for consumer price indexing (CPI) was proposed in previous works led by this author, validated, and proved to be most efficient when compared with the expenditure-based weighting system. The approach requires that weights are generated from the same price data, making it possible to generate both base and current year weights conveniently at the same time without having to conduct costly household expenditure survey (HES). This eliminates the widely reported weight and formula biases associated with CPI formulation. This manual therefore: (1) highlights the main problems of weight and formula biases in index numbers; (2) provides detail and historical background to the various index formulas; (3) establishes the theoretical underpinning of the proposed multivariate weighting method for indexing; and (4) provides R algorithms for computing index using the multivariate weighting method under stated scenarios. Ultimately, this manual provides a step-by-step R algorithm for potential users of the proposed alternative weighting scheme to conveniently compute CPI, since the computations involved in adopting the new weighting approach are laborious.