Likelihood of businesses or organizations to pass on cost increases due to tariffs to their customers over the next 12 months, fourth quarter of 2025

33-10-1074 · Occasional · 2025 to 2025

as of March 18, 2026

This table has no honest default view — 2 choices define what it even shows

0 of 2 chosen

Business characteristics has no overall total in this table — pick a value to chart it.
Likelihood of businesses or organizations to pass on cost increases due to tariffs to their customers over the next 12 months offers more than one statistic, with no default — pick a value to chart it.

What this table is broken down by — tap any row to change.

8 bars · Percent

Likelihood of businesses or organizations to pass on cost increases due to tariffs to their customers over the next 12 monthspick to chart

6 bars · Percent

Likelihood of business or organization to pass on cost increases due to tariffs to their customers over the next 12 months, very likely

Likelihood of business or organization to pass on cost increases due to tariffs to their customers over the next 12 months, somewhat likely

Likelihood of business or organization to pass on cost increases due to tariffs to their customers over the next 12 months, somewhat unlikely

Likelihood of business or organization to pass on cost increases due to tariffs to their customers over the next 12 months, very unlikely

Business or organization does not expect any cost increases due to tariffs

Likelihood of business or organization to pass on cost increases due to tariffs to their customers over the next 12 months, unknown

13 bars · Percent

This table reports one period, so a chart here compares across a category instead of over time.

This table has no single overall total — pick a value in each of: Business characteristics, Likelihood of businesses or organizations to pass on cost increases due to tariffs to their customers over the next 12 months.

Source: Statistics Canada

Open this table in R or Python

install.packages("cansim")
library(cansim)
get_cansim("33-10-1074")

# pip install stats-can
import stats_can

stats_can.zip_table_to_dataframe("33-10-1074")

via the community cansim (R) and stats_can (Python) packages.

This code runs against Statistics Canada's own API, not Vizchat.