Abstract

PurposeThe purpose of this paper is to provide academic researchers and practitioners with a better understanding of the current Ivey Purchasing Managers Index (IPMI), with alternative IPMIs, and with their appropriateness as an indicator of the performance of the Canadian economy.Design/methodology/approachThe paper makes use of principal component analysis to investigate the choice of principal variables for computing new IPMIs based on monthly data for five Ivey indexes for the period from December 2000 to May 2006. Statistical tests were made for the validity of the existing and new IPMIs using two major indicators of Canadian business and economic activities.FindingsThe results suggest that a new composite purchasing managers index for Canada similar to its US counterparts be computed based on four identified Ivey indexes. For constructing a simpler and parsimonious IPMI, the results support Ivey's current practice of using only one Ivey index, namely, the Purchases index.Research limitations/implicationsThere was a limited amount of data used for the analysis (i.e. monthly data for less than six years). Also there are issues on data comparability between the Ivey data and the US data (i.e. the Ivey does not collect separate data for the manufacturing sector or the non‐manufacturing sector).Practical implicationsUsing a composite index akin to the PMI, business organizations and policymakers will have an accurate sense of what is happening in the Canadian economy. Furthermore, enhancing the power and accuracy of such an index will benefit supply professionals, economic forecasters, and policy experts.Originality/valueThe present study offers additional insights to both practitioners and academics. It helps supply chain managers and practitioners come up with a more reliable business strategy by providing them with a weighted composite index for the Canadian economy. It also makes contributions to the academic community in the area of statistical theory applied to supply management as it has introduced the principal components variable selection analysis in the construction of a new IPMI.

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