Overview

This report summarizes Canada’s international merchandise trade performance in dyes, pigments, and petrochemicals (NAPCS category 263) from 2017 to 2024, based on Statistics Canada data (Table 12-10-0168-01). It combines insights from export and import chart analyses, focusing on price and volume indices, terms of trade (ToT), and, growth rates. The analysis highlights key trends, volatility, and external influences shaping this sector.

Key Insights

We begin with an overview of trade indices over time, depicted in the line chart below. Each index is plotted on its own facet to show its trajectory since 2017.

Figure 1: Historical trade in dyes, pigments and petrochemicals (Monthly, Not Seasonally Adjusted)

1. Price Trends: Exports Strong, Imports Peaking and Cooling

Export Prices: Export prices rose steadily, increasing 40% above the 2017 baseline (index = 100) to ~140 by 2022, and stabilizing at that level through 2024. Annual growth averaged 5.16% YoY, with a peak of +40% in 2022 during global inflation.
Import Prices: Import prices surged more dramatically, climbing 80% above 2017 to ~180 by 2023, driven by global price shocks (e.g., oil, inflation). They cooled to ~150 in 2024, with YoY growth dropping to -8% after a 7.77% average annual increase.
Key Takeaway: Both export and import prices grew significantly, but imports saw sharper spikes and a recent decline, reflecting global market volatility. Export prices show more consistent strength.

2. Volume Trends: Stagnation Despite Volatility

Export Volumes: Export volumes were volatile, swinging between 90 and 130, but showed no net growth, returning to ~100 by 2024. YoY growth averaged -0.30%, with major shocks like a -24% drop in 2020 (COVID) and a +23% spike in March 2024.
Import Volumes: Import volumes also stagnated, fluctuating between 70 and 120, and ending at ~100 by 2024. They dropped to 70 in 2020 (-16% YoY), briefly peaked at 120 in 2021, and averaged a slight decline (-0.15% YoY).
Key Takeaway: Both export and import volumes failed to grow over the period, despite significant volatility driven by external shocks. This suggests supply or demand constraints in the sector.

3. Growth Patterns: Prices Lead, Volumes Lag

To quantify the patterns discussed, we compile summary statistics for the growth rates of each series. We look at the mean and standard deviation (SD) of each relevant growth rate over the full period. The table below presents these statistics for export price MoM, export volume MoM, import price YoY, and import volume YoY.

**Table 1: Growth Rate Statistics**
Statistic	Export.Price..MoM.	Export.Volume..MoM.	Export.Price..YoY.	Export.Volume..YoY.	Import.Price..MoM.	Import.Volume..MoM.	Import.Price..YoY.	Import.Volume..YoY.
Mean	0.38	0.97	5.16	-0.30	0.69	0.52	7.77	-0.15
SD	3.38	14.62	17.35	14.84	5.74	12.57	13.31	16.03

Export Growth:
- Prices grew steadily (0.38% MoM, 5.16% YoY), with moderate volatility (SD: 3.38% MoM, 17.35% YoY).
- Volumes were erratic (0.97% MoM, -0.30% YoY), with high volatility (SD: 14.62% MoM, 14.84% YoY), reflecting shocks like the 2020 crash and 2023 surge.
Import Growth:
- Prices grew faster (0.69% MoM, 7.77% YoY) but with variability (SD: 5.74% MoM, 13.31% YoY), peaking at +35% YoY in 2023.
- Volumes showed slight decline (-0.15% YoY) and high volatility (SD: 12.57% MoM, 16.03% YoY), with swings like -24% in April 2020 and +23% in August 2021.
Key Takeaway: Price growth drives trade value for both exports and imports, while volumes remain flat or slightly down, absorbing more short-term shocks.

4. Price-Volume Dynamics

We next examine the growth rates of these indices to assess volatility and momentum, using both month-over-month (MoM) changes and year-over-year (YoY) changes for exports and imports. This perspective highlights short-term fluctuations and longer-term annual shifts in trade.

Figure 2: Price and volume month on month growth rates in exports and imports

Figure 3: Price and volume year on year growth rates in exports and imports

5. Growth intensity map

Another way to visualize the volatility is a heatmap of growth rates over time. Below, we map each period’s growth rate as a color, which helps quickly identify periods of extreme change: red for contractions and blue for expansions.

Figure 4: Heatmap of month on month growth rates in imports and exports

Figure 5: Heatmap of year on year growth rates in imports and exports

The heatmap visually confirms the earlier observations. The export price MoM row (bottom) is mostly a light color (near white), indicating many months of minimal change, with only a few pale red or blue patches corresponding to moderate drops or rises.

A broadly consistent pattern to exports is shown for short term change in imports.

In contrast, the export and import volume YoY charts alternate between deeper reds and blues, reflecting the severe contractions in 2020 (dark red segment) and strong expansions in 2021 (dark blue segment), followed by continued variability into 2023–2024

6. Summary price and volume

Export Price vs. Volume: No clear correlation exists between export prices and volumes. High prices (e.g., 140) paired with both high and low volumes, suggesting inelastic demand—buyers continue purchasing despite price rises.
Import vs. Export Volumes: A weak link exists between import and export volumes. Both crashed in 2020, but otherwise moved independently, indicating exports in this sector don’t heavily rely on imported inputs.
Key Takeaway: Demand for Canada’s exports is relatively price-insensitive, and import volumes don’t directly drive export activity, pointing to separate market dynamics.

7. Seasonality

To investigate seasonality, the time series is decomposed using the STL (Seasonal-Trend Decomposition using Loess¹) method by Cleveland et al. (Cleveland et al., 1990). This method separates each index into trend, seasonal, and residual components for analysis.

Figure 6: STL Decomposition of unseasonally adjusted Trade Data - Export Price

Figure 7: STL - Export volume

Figure 8: STL - Import price

Figure 9: STL - Import volume

Seasonality: The seasonal components in both attachments show consistent, repeating patterns, suggesting that the data is influenced by seasonal effects, likely recurring at fixed intervals such as monthly or quarterly cycles. This is evident in both the import and export price and volume indices analyzed.

The variation in the amplitude of seasonal effects between different indices, such as stronger seasonal patterns in volume indices compared to price indices, which might reflect different underlying economic factors.

Both IMP PRICE IDX and IMP VOL IDX show consistent repeating patterns, with the seasonal component indicating periodic fluctuations likely tied to calendar cycles. Both EXP PRICE IDX and EXP VOL IDX also exhibit clear seasonal patterns, with the volume index showing a stronger amplitude, suggesting more pronounced seasonal effects in export volumes compared to prices.

To organize the key observations, the following table summarizes the range of values for each component across the datasets:

Table 2: Summary of STL Decomposition Components
Dataset	Data.Range	Remainder.Range	Seasonal.Range	Trend.Range
IMP PRICE IDX	110-180	-10 to 20	-5 to 10	110-160
IMP VOL IDX	70-130	-20 to 20	-5 to 10	80-100
EXP PRICE IDX	90-140	-5 to 10	-2 to 2	100-130
EXP VOL IDX	90-130	-20 to 20	-10 to 10	90-110

Major Shocks:
- 2020 (COVID): Export volumes dropped -24%, import volumes -16%, with slight price dips.
- 2021-2022 (Inflation/War): Export prices peaked at +40% YoY, import prices at +35% YoY, while volumes recovered briefly but remained volatile.
- 2023-2024: Export volumes spiked (+23% in Mar 2024), import prices cooled (-8% YoY in 2024).
Key Takeaway: Trade dynamics are driven by irregular external events (e.g., pandemics, inflation, geopolitical tensions), not seasonal cycles.

8. Terms of Trade: Temporary Gains, No Lasting Advantage

we assess the terms of trade (ToT) for this segment, defined as the ratio of the export price index to the import price index (expressed as a percentage). An increasing ToT implies that export prices are rising faster than import prices, which can indicate improving trade competitiveness or earning power for Canada (each unit of export buys more imports). A declining ToT suggests the opposite.

Figure 10: Terms of Trade as ratio of export prices to import price

ToT Movement: The Terms of Trade (Export Price / Import Price × 100) started at 100 in 2017, rose to 105 in 2020-2021 as export prices outpaced imports, but fell sharply to 70 by mid-2023 as import prices surged. It recovered to 90-95 in 2024 as import prices eased.
Key Takeaway: ToT reflects the imbalance between import and export price growth. The 2022-2023 decline reduced Canada’s purchasing power abroad, and while 2024 shows recovery, there’s no sustained improvement over 2017 levels.

2024 Signs of Stabilization

Exports: Prices held steady at ~140, while volumes saw a +23% MoM spike in March but ended near 100, showing no long-term growth.
Imports: Prices dropped to ~150 (-8% YoY), and volumes remained at ~100, indicating stagnation.
ToT: Improved to 90-95, reflecting a narrowing gap between export and import prices.
Key Takeaway: 2024 shows signs of stabilization, with cooling import prices and a recovering ToT, but volume growth remains elusive.

Drivers and Implications

Global Market Forces: Oil price swings, inflation, and geopolitical events (e.g., Ukraine war) heavily influenced price spikes, especially for imports. Global demand supported export price growth.
Domestic Factors: Flat volumes suggest potential demand slowdown, substitution with local production, or supply constraints.
Trade Policy: Agreements like USMCA and regulations may have subtly shaped trade flows, though not directly captured in the data.
Implication: The sector shows resilience in price growth but struggles with volume expansion, leaving it vulnerable to external shocks.

Conclusion

Canada’s trade in dyes, pigments, and petrochemicals from 2017 to 2024 is marked by strong price growth—exports up 40% and imports peaking 80% above 2017—but stagnant volumes for both. Export prices grew consistently, while import prices surged and then cooled, impacting the ToT, which saw a sharp decline in 2022-2023 before recovering in 2024. Volumes remained volatile, with no net growth, reflecting supply or demand constraints. Demand appears inelastic, and import-export volume links are weak, suggesting independent market dynamics. External shocks like COVID and inflation drove major changes, with 2024 showing stabilization but no long-term ToT advantage. Stakeholders should focus on hedging price risks, addressing volume constraints, and monitoring global trends to navigate ongoing uncertainty.

Report method

This report examines monthly international merchandise import and export price and volume indexes for dyes, pigments and petrochemical in Canada. Source for the indices is from Statistics Canada (Table 12-10-0168-01). The four specific Vector IDs are: 1566913117; 1566912967; 1566914935; 1566914785 that relate to import volume, import price, export volume and export price. These vectors represent the dyes, pigments and petrochemical industry which is 263 on the North American Product Classification System (NAPCS). The data series use customs data and are unadjusted for seasonality. The indices are Laspeyres weighted.

The data was extracted via a methodology detailed here, spans multiple years and is analyzed through various visualizations and tables generated in R. Our goal is to identify historical patterns, assess seasonality, and explore recent trends, providing insights into the industry’s workforce dynamics.

References

Cleveland, R. B., Cleveland, W. S., McRae, J. E., & Terpenning, I. (1990). STL: A seasonal-trend decomposition procedure based on LOESS. Journal of Official Statistics, 6(1), 3–73.

[The STL (Seasonal-Trend Decomposition using LOESS) method is a robust and versatile approach to decomposing a time series into three distinct components: trend, seasonal, and remainder (or residual). It was developed by Robert B. Cleveland and colleagues in 1990 and is useful for time series with strong seasonal patterns that may vary over time.]↩︎