AI Analysis: Industrial product price index, by major product group, monthly

Executive Summary

Canada's Industrial Product Price Index (Statistics Canada, Table 18100265) spans nearly 70 years of monthly data (1956–2026) across 24 product groups, with the total IPPI rising more than 10-fold from 13.3 in January 1956 to 140.2 in March 2026 — approximately 40% above the 2020 base level. Price dynamics vary dramatically by sector, with Primary Non-Ferrous Metals showing the highest volatility (range of 202.9, peak of 280.4) while Cannabis products posted the highest and most stable average index (133.68, range of just 3.1). The post-2021 inflation surge stands out as the most significant anomaly in the dataset's history, driving sharp month-over-month price swings concentrated around global supply chain disruptions.

Key Findings

• The total IPPI increased more than 10-fold over 70 years, rising from 13.3 in January 1956 to an all-time high of 140.2 in March 2026, placing current prices approximately 40% above the 2020 base year.
• Primary Non-Ferrous Metals was the most volatile product group, recording the dataset's highest index value of 280.4 and a range of 202.9 across the full period.
• Cannabis products had the highest mean index value (133.68) with the narrowest range in the dataset (just 3.1), indicating consistently elevated but stable pricing since tracking began.
• Lumber and Wood Products also exhibited high volatility with a range of 182.3, reflecting well-documented commodity price boom-and-bust cycles.
• Across 11,399 observations, the overall mean index is 80.2 and median is 82.7 (base 2020=100), with the middle 50% of all values falling between 62.7 and 95.9 — indicating most product groups cluster in a moderate price band.
• No statistical outliers (z-score > 2.5) were detected across 843 monthly data points, yet several months recorded month-over-month swings exceeding 3%, concentrated around the COVID-19 era and the 2021–2022 global inflation surge.
• Most of the 19 product groups included in the correlation analysis show positive correlations with one another, reflecting broad macroeconomic cycles that tend to lift industrial prices across sectors simultaneously.