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Migration

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The Daily


Thursday, September 27, 2007
2005/2006 

Between July 1, 2005 and June 30, 2006, Alberta experienced the highest net inflow of residents, posting a migration rate of 20.3 people for every 1,000 population. British Columbia was a distant second with a net migration rate of 12.3 people, while Ontario was third at 9.6 people. This ranking was unchanged from the previous year.

The data in this release include only people who moved between provinces, census metropolitan areas (CMAs) or census divisions, as well as those who moved into and out of the country. Net migration is the difference between the number of persons who moved into a census division or CMA and the number of persons who moved out.

The highest net inflow among the CMAs relative to the population size occurred in Calgary, which had a net inflow of 21.5 migrants for every 1,000 residents, followed closely by Edmonton with a net inflow of 21.0 migrants and Toronto with 17.3 migrants.

In absolute terms, Toronto had the highest net inflow, with 91,909 more people moving into the metropolitan area than moving out. Vancouver ranked second with a net inflow of 36,321 people, followed by Calgary (+22,961 people). Of the 27 CMAs, 23 had a net inflow from migration, while only 4 experienced a net outflow.

For Toronto, Vancouver, Calgary, Edmonton and Montréal (the CMAs with the highest net migration in absolute terms), the number of net migrants was highest in the 25-44 age group.

At the census division level, an important shift in rates of net gain per 1,000 population occurred between the 2004/2005 and 2005/2006 periods.

In 2004/2005, 4 of the 5 census divisions with the highest net gain in migrants for every 1,000 population were located near Montréal, with the census division of Mirabel leading the way.

In 2005/2006, Mirabel still ranked first, but this time it was followed by three census divisions from Alberta and two from Ontario. Mirabel had the highest net gain with 38.0 migrants for every 1,000 population, followed by Division No. 19 (in Alberta), which includes Grande Prairie, with a net gain of 34.1 migrants per 1,000 population.

The following four census divisions: Division No. 16 (in Alberta), which includes Fort McMurray; Division No. 8 (in Alberta), which includes Red Deer; York (in Ontario); and Peel (in Ontario) tied for third place with a net gain of 28.2 migrants for every 1,000 population.

Note: Migration data were derived by comparing the addresses supplied on personal income tax returns filed in the springs of 2005 and 2006. These flows were adjusted to July 2005 total population estimates.

Migration data reflect intraprovincial moves between CMAs or census divisions (areas such as counties, regional districts, and regional or district municipalities), as well as interprovincial and international moves. Moves across town or across the street are excluded.

International migration data differ from estimates released by the Demography Division. Both sets of data include immigrants and emigrants. However, the data associated with this release exclude net temporary emigrants and non-permanent residents who did not file an income tax return.

To calculate total population change, both migration (including the non-permanent resident population as well as returning emigrants and net temporary emigrants) and natural increase (births minus deaths) must be taken into account.

Migration estimates (91C0025, various prices) are available for the provinces and territories, CMAs and census divisions. Five tables covering these levels of geography provide data on the origin and destination, as well as the age, sex and median income of migrants.

Available on CANSIM: tables 111-0027 to 111-0031.

Definitions, data sources and methods: survey number 4101.

For more information, or to enquire about the concepts, methods or data quality of this release, contact Client Services (toll-free 1-866-652-8443; 613-951-9720; fax: 1-866-652-8444 or 613-951-4745; saadinfo@statcan.gc.ca), Small Area and Administrative Data Division.

Tables. Table(s).