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Housing and Transportation Cost Index: Research Paper

Executive Summary

In 2024, Statistics Canada and Housing, Infrastructure and Communities Canada collaborated on the adaptation of an existing composite index for estimating the expense of housing and transportation in Canada. This index is based on the Center for Neighborhood Technology’s Housing + Transportation (H+T®) Affordability Index (Center for Neighborhood Technology 2017). This methodology was first applied in the United States, and this report documents its first application in Canada. By combining Census data and data from other statistical programs, a composite index (the H+T Index) for all Aggregate Dissemination Areas (ADA) (Statistics Canada 2021a) of Canada (except for Territories and First Nations) was derived.

• The H+T Index represents the share of household income allocated to housing and transportation; hence it varies from 0 to 1; for a given geographic area, the higher the index, the more expensive the area.
• Conversely, the lower the index, the less expensive the area.

Aggregate Dissemination Areas are classified in three groups:

• the first group contains ADAs belonging to a Census Metropolitan Area (CMA) (Statistics Canada 2021b);
• the second group contains ADAs belonging to a Census Agglomeration (CA) (Statistics Canada 2021b);
• the third group contains the remaining ADAs, representing Rural and Small Town (RST) Canada (Plessis et al. 2001).

In the first group (metropolitan areas), the following is observed:

• Suburban and peri-urban areas that seem to have a comparative advantage due to low housing costs become less attractive once transportation costs are taken into consideration. This supports the creation of a more comprehensive index to understand the accurate cost of housing.
• The range of the median H+T Index by CMA varies from 0.203 in Thunder Bay to 0.344 in Guelph.
• In general, housing and transportation are less expensive in CMAs in Quebec and Atlantic Canada than in CMAs in Ontario, the Prairies and British Columbia.
• Large metropolitan areas show a large variability; in the same metropolitan area, housing with substantially different degrees of expensiveness coexists.

In the second group (urban, non-metropolitan areas), the following is observed:

• The range of the median H+T Index by Census Agglomeration varies from 0.162 in Sorel-Tracy to 0.415 in Vernon.
• In general, housing and transportation are less expensive in CAs in Quebec and Atlantic Canada than in CAs in Ontario, the Prairies and British Columbia. Northern regions in Prairie provinces, in particular, are some of the most expensive.

Finally, in the third group (rural and small-town areas), the following is observed:

• The range of the median H+T Index in RST areas by Province varies from 0.225 in Prince Edward Island to 0.292 in Alberta.
• In general, housing and transportation are less expensive in RST areas in Eastern Canada than in RST areas in Western Canada.

Introduction

Measuring housing expensiveness provides great insights that can help governments and policy makers monitor access to good-quality affordable housing and evaluate and update current policies. On the other hand, classic location theory suggest that transportation costs are inversely correlated to land, hence housing, costs. Transport cost at a certain living location adds up to living cost, thus it should be considered to measure affordability. The Center for Neighborhood Technology created the Housing + Transportation (H+T®) Affordability Index (H+T Index), an encompassing measure of affordability of housing in the United States (US) calculated by including the transportation costs associated with a home’s location (Center for Neighborhood Technology 2017). The goal of the US H+T Index is to expand the definition of housing expensiveness to include transportation costs at a home’s location to better reflect the comprehensive cost of a household at the location of interest. In this study, we adapt the US H+T Index to create an index for measuring housing and transportation expensiveness for Canada. A summary of the methodology used to create the Canadian H+T Index is illustrated in the present report.

Methodology

The H+T Cost Index (H+T Index) considers the transportation costs associated with a home’s location to reflect the true cost of living at a certain location (Guerra and Kirschen 2016), (Center for Neighborhood Technology 2017), (Center for Neighborhood Technology 2022), (Econsult Corporation/Penn Institute for Urban Research 2012). Housing and transportation costs are estimated by a combination of Census data, survey data, and modelling. These costs are divided by the income to measure housing and transportation expensiveness. Location theory postulates that land value is inversely correlated to its accessibility cost. Hence, in core downtown areas land value is high, whereas transports cost are low. Conversely, in suburban areas increasing transportation costs are associated with decreasing land value (Alonso 1964).

The methodology was originally developed in the United States by the Center for Neighborhood Technology, a non-profit organization committed to research and development for urban neighborhoods quality of life. In order to obtain a comparable index for Canada, several modifications had to be introduced. In particular, the transportation component of the H+T index was adapted to the data availability in Canada.

In this report, the modified methodology is applied to most of Canada. Territories are excluded, for lack of reliable data. First Nations reserves or settlements too are out of the scope of this study, because some of the concepts used in the methodology cannot be applied^Note . Inuit regions are excluded from the study due to the peculiarities of modes of transportation in Northern Canada, and lack of data. Métis settlements in Alberta^Note are included in the study.

Housing cost component

The Housing Cost is defined as the fraction of monthly income spent on housing costs, either for owned or rented property. For a given census geographic area, the Housing Cost Index is calculated as:

$$H=o\times \frac{{\tilde{C}}_o}{{\tilde{I}}_o}+r\times \frac{{\tilde{C}}_r}{{\tilde{I}}_r},$$

where o indicates the fraction of households owning their dwelling and r indicates the fraction of households renting their dwelling; all types of households are included in this study. This includes private as well as collective dwellings (Statistics Canada 2021c), such as subsidized housing and senior residences. The median monthly shelter costs for owned and rented dwellings are indicated respectively by ${\tilde{C}}_o$ and ${\tilde{C}}_r$. Shelter costs for owner households include, where applicable, mortgage payments, property taxes and condominium fees. For renter households, shelter costs include the rent. All costs include, where applicable, the costs of electricity, heat, water and other municipal services (Statistics Canada 2021d). Home insurance costs are not included. Finally, ${\tilde{I}}_o$ indicates the median before-tax monthly household income for homeowners and ${\tilde{I}}_r$  the same, for home renters.

All quantities used in this equation are extracted from the 2021 Census microdata for the geographic units of reference, with minor modifications:

• the median before-tax monthly household income is obtained by using the Census variable Median total income of household in 2020, divided by 12. Incomes are adjusted by the median hourly wage increase from 2020 (reference year for the 2021 Census income statistics) to 2023 (latest year with available data). Adjustment coefficients are shown on Table 1;
• the fractions o and r are obtained by using the variables Owner and Renter, divided by the variable Total - Private households by tenure ^Note ;
• shelter costs ${\tilde{C}}_o$  and ${\tilde{C}}_r$  are obtained by using the variables Median monthly shelter costs for owned dwellings and Median monthly shelter costs for rented dwellings, after adjusting for inflation between 2021 and 2024, according to the May 2024 Consumer Price Index (Statistics Canada 2024). The inflation coefficients by Province are shown on Table 2.

A few notes about monthly income: this study uses before-tax household income to maintain consistency with other Housing-related studies developed at Statistics Canada. When given a choice between average and median Census values, median values were used to minimize the effect of outliers.

The Housing Cost Index can vary between 0 and 1. A value of 0 would indicate that housing costs nothing; in practice this value is never encountered. Similarly, a value of 1 would indicate that the entirety of a household’s monthly income is spent on housing. This value is also never encountered in practice.

Data table for Chart 1

Data table for Chart 1 Table summary
The information is grouped by Region (appearing as row headers), Median, Interquartile Range, Minimum and Maximum, calculated using housing cost index, , and Maximum units of measure (appearing as column headers).

Region	Median	Interquartile Range	Minimum	Maximum
	housing cost index
Notes: Minimum: Saint John 0.125; Maximum: Barrie 0.216. Source: Statistics Canada.
Prairies	0.201	0.018	0.174	0.209
British Columbia	0.193	0.012	0.173	0.198
Ontario	0.178	0.023	0.149	0.216
Atlantic	0.149	0.022	0.125	0.175
Quebec	0.139	0.012	0.126	0.157

Figure 1 is a boxplot^Note showing a comparison of Housing Cost indices for the 41 CMAs in Canada, by region (Statistics Canada 2021f). For each CMA, the median index of the corresponding ADAs, weighted by population, was computed. We can observe that housing is less expensive in Quebec and Atlantic Canada than in Ontario, the Prairies and British Columbia. For an extended view of the Housing Cost Index for all the 41 Census Metropolitan Areas, please consult the Appendix.

Transportation cost component

The Transportation costs model developed by the Center for Neighborhood Technology is a regression model using socioeconomic variables, city density and commuting data (Center for Neighborhood Technology 2022). This approach is not feasible for Canada, as some of the data sources available in the United States have no counterpart in Canada – for example, the Canadian Vehicle Survey, which reports on annual car use, was last collected in 2014^Note . Transportation costs are evaluated using the Survey of Household Spending (SHS). The SHS is a survey conducted every 2 years in the 10 provinces and the 3 territorial capitals; it collects detailed information on household expenditures. It also collects information on household demographic characteristics and certain dwelling characteristics (e.g., type, age and tenure), as well as certain information on household equipment (e.g., electronics and communications equipment). In addition, income information from personal income tax data is combined with the survey data (Statistics Canada 2023). It must be noted that the SHS only covers monetary costs. It does not cover opportunity costs, traffic congestion costs, environmental costs, nor other externalities associated with time spent commuting. For our study, we selected from the SHS the following expenditures:

• Private transportation (survey question TR002).
• City or commuter bus, subway, street car and commuter train (survey question TR051).
• Inter-city bus (survey question TR055).

These expenditures are annual and can be aggregated either at the Census Division (CD) or at the Provincial level. The three expenditures were added together and divided by 12 to calculate the monthly average. These results were kept only for those Census Divisions where:

• the survey was answered by at least 15 respondents;
• the Standard Error of the mean expenditure were less than 35% of the mean expenditure.

For Census Divisions that failed at least one of the above criteria, the Provincial monthly average was used instead. The most recent data available for the SHS was collected in 2021. Inflation adjustment was applied to bring the expenditures to May 2024 dollars. The inflation coefficients used are shown on Table 3.

Transportation costs are transferred from the Census Division (CD) level to the Aggregate Dissemination Area (ADA) level by spatial location: all ADAs contained in one CD receive the same transportation cost. This cost is then divided by the median before-tax household income to obtain the Transportation Cost Index. The transportation model is less granular than the housing model since it is based on CDs rather than ADAs. Many neighbouring ADAs, in particular in large cities, are assigned the same transportation costs. This approximation for the first iteration of the Transportation model is expected to be rectified in future iterations, with the acquisition of additional data sources.

Figure 2 shows Transportation Cost Indices in Census Metropolitan Areas, by region. For each CMA, the median index of the corresponding ADAs, weighted by population, was computed. The range of the median Transportation Cost Index by Census Metropolitan Area varies from 0.053 in Thunder Bay to 0.216 in Saguenay. We observe that transportation is the least expensive in Ontario and the most expensive in the Prairies, but the difference between regions is not as marked as Housing. There is however a large variance withing each region. For more details on the Transportation Cost Index for all the 41 Census Metropolitan Areas, please consult the Appendix.

Data table for Chart 2

Data table for Chart 2 Table summary
The information is grouped by Region (appearing as row headers), Median, Interquartile Range, Minimum and Maximum, calculated using transportation cost index, , and Maximum units of measure (appearing as column headers).

Region	Median	Interquartile Range	Minimum	Maximum
	transportation cost index
Notes: Minimum: Thunder Bay 0.053; Maximum: Saguenay 0.216. Black dots in the chart represent outliers. Source: Statistics Canada.
Prairies	0.120	0.019	0.064	0.130
Atlantic	0.113	0.012	0.103	0.124
Quebec	0.112	0.018	0.086	0.216
British Columbia	0.100	0.031	0.065	0.141
Ontario	0.094	0.023	0.053	0.161

H+T Cost Index

The combined Housing and Transportation (H+T) Cost Index is given by the sum of the Housing and Transportation indices, since both are expressed as fractions of the median before-tax household income. The H+T Index varies from 0 to 1; for a given geographic area, the higher the index, a greater proportion of income being spent on housing and transportation. Theoretically, an index value of 0 means housing and transportation are free, whereas an index value of 1 means that the entirety of a household’s income is spent on housing and transportation. As these extremes are not feasible due to the universal presence of both H+T and other costs, the value of the H+T Cost Index in Canada ranges from 0.128 to 0.591.

Figure 3 shows the distribution of H+T Cost indices in all Census Metropolitan areas across Canada. For each CMA, the median index of the corresponding ADAs, weighted by population, was computed. We observe the following:

• The range of the median H+T Cost Index by Census Metropolitan Area varies from 0.203 in Thunder Bay to 0.344 in Guelph.
• In general, housing and transportation are less expensive in Census Metropolitan Areas in Quebec and Atlantic Canada than in Census Metropolitan Areas in Ontario, the Prairies and British Columbia.
• Large metropolitan areas show a large variability; in the same metropolitan area, housing with substantially different degrees of H+T expensiveness coexists.

Data table for Chart 3

Data table for Chart 3 Table summary
The information is grouped by Region (appearing as row headers), Median, Interquartile Range, Minimum and Maximum, calculated using H+T cost index, , and Maximum units of measure (appearing as column headers).

Region	Median	Interquartile Range	Minimum	Maximum
	H+T cost index
Notes: Minimum: Thunder Bay 0.203; Maximum: Guelph 0.344. Black dots in the chart represent outliers. Source: Statistics Canada.
Prairies	0.315	0.040	0.269	0.342
British Columbia	0.298	0.041	0.265	0.312
Ontario	0.276	0.040	0.203	0.344
Atlantic	0.265	0.042	0.225	0.298
Quebec	0.250	0.020	0.234	0.342

Figure 4 shows the H+T Cost Index in Census Agglomerations (CA) across Canada. For each CA, the median index of the corresponding ADAs, weighted by population, was computed. We observe the following:

• The range of the median H+T Cost Index by CA varies from 0.162 in Sorel-Tracy to 0.415 in Vernon.
• Housing and transportation are more expensive in Census Agglomerations in the Prairies than in the rest of Canada.

Data table for Chart 4

Data table for Chart 4 Table summary
The information is grouped by Region (appearing as row headers), Median, Interquartile Range, Minimum and Maximum, calculated using H+T cost index, , and Maximum units of measure (appearing as column headers).

Region	Median	Interquartile Range	Minimum	Maximum
	H+T cost index
Notes: Minimum: Sorel-Tracy 0.162; Maximum: Vernon 0.415. Black dots in the chart represent outliers. Source: Statistics Canada.
Prairies	0.311	0.047	0.231	0.392
British Columbia	0.301	0.062	0.210	0.415
Ontario	0.284	0.041	0.230	0.384
Atlantic	0.281	0.054	0.212	0.366
Quebec	0.278	0.051	0.162	0.349

Figure 5 displays the H+T Index for Rural and Small Town (RST) areas^Note . It shows the following:

• The range of the median H+T Index in rural area by Province varies from 0.225 in Prince Edward Island to 0.292 in Alberta. Hence, the range of the provincial median index is considerably smaller for RST areas than for CMAs or CAs.
• Housing and transportation are more expensive in Aggregate Dissemination Areas in rural areas in Eastern Canada than in rural areas in Western Canada.

Data table for Chart 5

Data table for Chart 5 Table summary
The information is grouped by Region (appearing as row headers), Median, Interquartile Range, Minimum and Maximum, calculated using H+T cost index, , and Maximum units of measure (appearing as column headers).

Region	Median	Interquartile Range	Minimum	Maximum
	H+T cost index
Notes: Black dots in the chart represent outliers. Source: Statistics Canada.
Prairies	0.287	0.041	0.192	0.505
British Columbia	0.274	0.052	0.194	0.474
Ontario	0.257	0.079	0.155	0.503
Atlantic	0.257	0.030	0.146	0.358
Quebec	0.256	0.048	0.150	0.416

Conclusions

The Housing and Transportation Cost Index provides a better estimate of the expenses incurred by households due to geographic location; peripheral areas that seem to have a comparative advantage due to low housing costs become less attractive once transportation costs are taken into consideration.

This methodology is expected to be further refined in the future, as new data on housing and transportation become available, along with regular updates of the index.

Acknowledgements

The authors would like to thank Wei Lan, Di Ying and Olfa Khazri for their help with the Survey of Household Spending; Patricia Conor, Beau Khampoune and Yves Gilbert for their help with the Vehicle Registration data; Jean-Philippe Deschamps-Laporte, Larry McKeown, Jason Gilmore for their methodological review; the Consumer Prices Division and Producer Prices Division for feedback on the study; Chris Li, Alessandro Alasia, Clément Yélou and Mahamat Hamit-Aggar for helping with the editorial process and internal reviews. Finally, we would like to thank Catalina Barinas, Matthew Quance, Bruno Tavares and Yanick Clement-Godbout at Housing, Infrastructure and Communities Canada for their support in preparing this study.

References

Alonso, William. 1964. Location and Land Use: Toward a General Theory of Land Rent. Publications of the Joint Center for Urban Studies. Harvard University Press. https://books.google.ca/books?id=_UUFvAEACAAJ.

Center for Neighborhood Technology. 2017. “H+T Index Methods.”

Center for Neighborhood Technology. 2022. “H+T Index Methods.”

Econsult Corporation/Penn Institute for Urban Research. 2012. “Review of the Center for Neighborhood Technology’s Housing and Transportation Affordability Index.” https://www.hud.gov/sites/documents/HTA-INDEX.PDF.

Guerra, Erik, and Mariel Kirschen. 2016. “Housing Plus Transportation Affordability Indices: Uses, Opportunities, and Challenges.” OECD/ITF Discussion Paper 14. https://www.itf-oecd.org/housing-plus-transportation-affordability-indices-uses-opportunities-challenges.

Mcgill, Robert, John W. Tukey, and Wayne A. Larsen. 1978. “Variations of Box Plots.” The American Statistician 32 (1): 12–16. https://doi.org/10.1080/00031305.1978.10479236.

Plessis, Valerie du, Roland Beshiri, Ray D. Bollman, and Heather Clemenson. 2001. “Definitions of Rural.” Rural and Small Town Canada Analysis Bulletin 3 (3). https://www150.statcan.gc.ca/n1/en/catalogue/21-006-X2001003.

Statistics Canada. 2021a. “Dictionary, Census of Population, 2021 – Aggregate dissemination area (ADA).” https://www12.statcan.gc.ca/census-recensement/2021/ref/dict/az/Definition-eng.cfm?ID=geo053.

Statistics Canada. 2021b. “Dictionary, Census of Population, 2021 – Census metropolitan area (CMA) and census agglomeration (CA).” https://www12.statcan.gc.ca/census-recensement/2021/ref/dict/az/Definition-eng.cfm?ID=geo009.

Statistics Canada. 2021c. “Dictionary, Census of Population, 2021 – Household.” https://www12.statcan.gc.ca/census-recensement/2021/ref/dict/az/Definition-eng.cfm?ID=households-menage007.

Statistics Canada. 2021d. “Dictionary, Census of Population, 2021 – Shelter Cost.” https://www12.statcan.gc.ca/census-recensement/2021/ref/dict/az/Definition-eng.cfm?ID=households-menage033.

Statistics Canada. 2021e. “Dictionary, Census of Population, 2021 – Tenure.” https://www12.statcan.gc.ca/census-recensement/2021/ref/dict/az/Definition-eng.cfm?ID=households-menage024.

Statistics Canada. 2021f. “Variant of Standard Geographical Classification (SGC) 2021 for Statistical area classification by Province and Territory.” https://www23.statcan.gc.ca/imdb/p3VD.pl?Function=getVD&TVD=1348372.

Statistics Canada. 2023. “User Guide for the Survey of Household Spending, 2021.” https://www150.statcan.gc.ca/n1/pub/62f0026m/62f0026m2023001-eng.htm.

Statistics Canada. 2024. “Table 18-10-0004-01 Consumer Price Index, monthly, not seasonally adjusted.” https://doi.org/10.25318/1810000401-eng.

Appendix A — Distribution of Housing and Transportation Costs

Data table for Chart 6

Data table for Chart 6 Table summary
The information is grouped by CMA (appearing as row headers), Median, Interquartile Range, Minimum and Maximum, calculated using housing cost index, , and Maximum units of measure (appearing as column headers).

CMA	Median	Interquartile Range	Minimum	Maximum
	housing cost index
Notes: Black dots in the chart represent outliers. Source: Statistics Canada.
Barrie	0.216	0.023	0.152	0.244
Red Deer	0.212	0.014	0.164	0.226
Toronto	0.206	0.044	0.104	0.289
Calgary	0.201	0.046	0.100	0.262
Edmonton	0.201	0.036	0.116	0.250
Oshawa	0.198	0.030	0.165	0.260
Lethbridge	0.197	0.029	0.167	0.224
Kelowna	0.196	0.029	0.133	0.233
Vancouver	0.194	0.039	0.116	0.351
Abbotsford - Mission	0.193	0.019	0.164	0.221
Saskatoon	0.192	0.027	0.135	0.239
Guelph	0.189	0.038	0.143	0.216
Victoria	0.187	0.039	0.106	0.240
Kingston	0.186	0.033	0.136	0.226
Kitchener - Cambridge - Waterloo	0.186	0.033	0.109	0.238
Chilliwack	0.185	0.051	0.118	0.233
Hamilton	0.183	0.029	0.120	0.224
Regina	0.183	0.027	0.123	0.229
Nanaimo	0.181	0.049	0.143	0.229
Brantford	0.179	0.043	0.133	0.223
St. Catharines - Niagara	0.178	0.035	0.118	0.222
Halifax	0.174	0.038	0.110	0.276
Winnipeg	0.172	0.031	0.099	0.229
Peterborough	0.171	0.048	0.126	0.241
London	0.171	0.040	0.134	0.253
Kamloops	0.170	0.027	0.127	0.204
St. John's	0.161	0.028	0.128	0.208
Belleville - Quinte West	0.161	0.044	0.118	0.231
Ottawa - Gatineau	0.158	0.031	0.103	0.226
Greater Sudbury / Grand Sudbury	0.157	0.025	0.126	0.189
Montréal	0.156	0.018	0.105	0.355
Windsor	0.151	0.033	0.101	0.232
Thunder Bay	0.151	0.029	0.093	0.199
Moncton	0.149	0.033	0.103	0.186
Québec	0.139	0.019	0.091	0.184
Sherbrooke	0.137	0.012	0.114	0.154
Drummondville	0.131	0.015	0.098	0.157
Saguenay	0.129	0.005	0.096	0.163
Fredericton	0.127	0.048	0.096	0.188
Trois-Rivières	0.126	0.017	0.103	0.147
Saint John	0.124	0.026	0.079	0.190

Figure 6 is a boxplot showing a comparison of Housing Cost Indices for the 41 CMAs in Canada. We observe the following:

• The range of the median Housing Cost Index by Census Metropolitan Area varies from 0.125 in Saint John to 0.214 in Barrie.
• In general, housing is less expensive in Quebec and Atlantic Canada than in Ontario, the Prairies and British Columbia.
• Large metropolitan areas show a large variability; in the same metropolitan area, expensive housing and inexpensive housing coexist.

Data table for Chart 7

Data table for Chart 7 Table summary
The information is grouped by CMA (appearing as row headers), Median, Interquartile Range, Minimum and Maximum, calculated using transportation cost index, , and Maximum units of measure (appearing as column headers).

CMA	Median	Interquartile Range	Minimum	Maximum
	transportation cost index
Notes: Black dots in the chart represent outliers. Source: Statistics Canada.
Saguenay	0.216	0.042	0.175	0.427
Windsor	0.167	0.078	0.101	0.346
London	0.162	0.080	0.083	0.269
Guelph	0.154	0.048	0.114	0.225
Kamloops	0.141	0.054	0.118	0.223
Lethbridge	0.136	0.043	0.098	0.208
Calgary	0.135	0.047	0.070	0.223
Saskatoon	0.131	0.041	0.086	0.227
Kelowna	0.127	0.035	0.076	0.182
Trois-Rivières	0.126	0.058	0.091	0.207
Halifax	0.124	0.047	0.079	0.249
Winnipeg	0.124	0.044	0.071	0.265
Edmonton	0.124	0.048	0.078	0.246
St. John's	0.122	0.031	0.089	0.191
Belleville - Quinte West	0.120	0.032	0.091	0.169
Drummondville	0.119	0.026	0.096	0.236
Fredericton	0.113	0.035	0.073	0.261
Moncton	0.113	0.032	0.079	0.183
Montréal	0.112	0.038	0.035	0.325
Peterborough	0.111	0.034	0.081	0.200
Québec	0.110	0.049	0.056	0.209
Greater Sudbury / Grand Sudbury	0.109	0.032	0.078	0.208
Saint John	0.105	0.037	0.067	0.228
Victoria	0.104	0.029	0.064	0.159
Kingston	0.103	0.049	0.077	0.173
Kitchener - Cambridge - Waterloo	0.102	0.043	0.072	0.170
Sherbrooke	0.100	0.046	0.056	0.193
Vancouver	0.100	0.028	0.063	0.270
Hamilton	0.096	0.041	0.053	0.180
Regina	0.096	0.035	0.066	0.203
Oshawa	0.093	0.032	0.061	0.204
Toronto	0.092	0.032	0.034	0.216
Nanaimo	0.091	0.018	0.074	0.138
Barrie	0.089	0.018	0.063	0.154
St. Catharines - Niagara	0.080	0.023	0.057	0.123
Brantford	0.079	0.030	0.059	0.126
Ottawa - Gatineau	0.078	0.033	0.050	0.168
Chilliwack	0.078	0.027	0.059	0.120
Abbotsford - Mission	0.065	0.027	0.051	0.113
Red Deer	0.064	0.025	0.047	0.092
Thunder Bay	0.053	0.015	0.035	0.073

Figure 7 shows a comparison of Transportation Cost Indices for all Census Metropolitan Areas across Canada. We observe the following:

• The range of the median Transportation Cost Index by Census Metropolitan Area varies from 0.0523 in Thunder Bay to 0.214 in Saguenay.
• Large metropolitan areas show a large variability; in the same metropolitan area, transportation shows a wide range of expensiveness.

Data table for Chart 8

Data table for Chart 8 Table summary
The information is grouped by CMA (appearing as row headers), Median, Interquartile Range, Minimum and Maximum, calculated using H+T cost index, , and Maximum units of measure (appearing as column headers).

CMA	Median	Interquartile Range	Minimum	Maximum
	H+T cost index
Notes: Black dots in the chart represent outliers. Source: Statistics Canada.
Guelph	0.348	0.066	0.258	0.433
London	0.343	0.098	0.225	0.509
Saguenay	0.342	0.047	0.292	0.591
Calgary	0.341	0.066	0.180	0.455
Edmonton	0.328	0.067	0.199	0.467
Lethbridge	0.321	0.039	0.282	0.423
Windsor	0.318	0.089	0.202	0.578
Saskatoon	0.314	0.051	0.222	0.451
Kamloops	0.312	0.048	0.266	0.427
Kelowna	0.311	0.075	0.269	0.380
Barrie	0.303	0.038	0.215	0.396
Toronto	0.300	0.062	0.161	0.475
Kitchener - Cambridge - Waterloo	0.298	0.067	0.192	0.409
Halifax	0.295	0.088	0.225	0.473
Winnipeg	0.295	0.062	0.170	0.492
Vancouver	0.294	0.053	0.193	0.472
Oshawa	0.292	0.055	0.244	0.452
Victoria	0.290	0.050	0.183	0.399
Kingston	0.282	0.088	0.219	0.390
Peterborough	0.282	0.084	0.222	0.442
St. John's	0.281	0.057	0.217	0.398
Red Deer	0.277	0.036	0.211	0.301
Hamilton	0.275	0.059	0.177	0.400
Belleville - Quinte West	0.272	0.079	0.238	0.399
Montréal	0.269	0.052	0.154	0.557
Regina	0.269	0.054	0.197	0.401
Nanaimo	0.269	0.071	0.230	0.347
Brantford	0.263	0.055	0.205	0.349
Greater Sudbury / Grand Sudbury	0.260	0.057	0.216	0.393
Abbotsford - Mission	0.259	0.046	0.224	0.311
Fredericton	0.252	0.081	0.171	0.331
Québec	0.250	0.057	0.147	0.383
Chilliwack	0.250	0.037	0.196	0.354
St. Catharines - Niagara	0.248	0.048	0.185	0.342
Trois-Rivières	0.245	0.073	0.210	0.354
Drummondville	0.245	0.044	0.194	0.393
Moncton	0.244	0.058	0.211	0.370
Ottawa - Gatineau	0.236	0.057	0.161	0.361
Sherbrooke	0.233	0.051	0.187	0.335
Saint John	0.220	0.039	0.190	0.363
Thunder Bay	0.205	0.046	0.130	0.270

Data table for Chart 9

Data table for Chart 9 Table summary
The information is grouped by CA (appearing as row headers), Median, Interquartile Range, Minimum and Maximum, calculated using H+T cost index, , and Maximum units of measure (appearing as column headers).

CA	Median	Interquartile Range	Minimum	Maximum
	H+T cost index
Notes: Black dots in the chart represent outliers. Source: Statistics Canada.
Vernon	0.415	0.093	0.332	0.591
Steinbach	0.392	0.000	0.392	0.392
Wetaskiwin	0.377	0.000	0.377	0.377
High River	0.375	0.000	0.375	0.375
Timmins	0.368	0.047	0.345	0.439
Prince Albert	0.367	0.011	0.270	0.376
Cape Breton	0.366	0.085	0.260	0.451
Winkler	0.354	0.027	0.329	0.383
Truro	0.343	0.017	0.334	0.441
Hawkesbury	0.343	0.005	0.338	0.349
Elliot Lake	0.342	0.000	0.342	0.342
Duncan	0.342	0.059	0.293	0.446
Camrose	0.341	0.028	0.313	0.369
Strathmore	0.339	0.000	0.339	0.339
Courtenay	0.334	0.039	0.263	0.402
Okotoks	0.329	0.012	0.310	0.334
Lloydminster	0.328	0.044	0.309	0.402
Port Alberni	0.328	0.045	0.241	0.330
Yorkton	0.326	0.032	0.267	0.331
Grande Prairie	0.323	0.037	0.299	0.382
Penticton	0.322	0.043	0.263	0.413
Lachute	0.321	0.000	0.321	0.321
Prince George	0.320	0.082	0.279	0.444
Brandon	0.318	0.026	0.271	0.392
Kentville	0.317	0.018	0.293	0.329
New Glasgow	0.315	0.047	0.273	0.344
Alma	0.315	0.064	0.263	0.364
Ladysmith	0.313	0.018	0.295	0.331
Squamish	0.311	0.019	0.293	0.330
Owen Sound	0.310	0.035	0.225	0.366
Nelson	0.310	0.040	0.271	0.350
North Battleford	0.299	0.025	0.274	0.324
Sainte-Agathe-des-Monts	0.298	0.014	0.284	0.312
Salaberry-de-Valleyfield	0.294	0.050	0.265	0.324
Pembroke	0.274	0.044	0.230	0.318

Data table for Chart 10

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Data table for Chart 11

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