Data and definitions

Box 1 Data source

Labour Force Survey (LFS)

This study uses annual data from Statistics Canada's Labour Force Survey (LFS) from 2001 to 2008. The LFS provides estimates of employment and unemployment.

The LFS covers the civilian, non-institutionalized population 15 years of age and over and excludes persons living on reserves and other Aboriginal settlements in the provinces, full-time members of the Canadian Armed Forces and the institutionalized population.

Since the LFS is a sample survey, all LFS estimates are subject to sampling variablity such as sampling error and non-sampling errors. Sampling errors associated with survey estimates are measured using coefficients of variation (CVs), which express the standard error as a percent of the estimate itself. The CV is used to give an indication of the uncertainty associated with the estimate. At the Canada and provincal level, the approximate coefficient of variation can be obtained from tables provided in Statistics Canada (2008).

All the data reported in this bulletin is defined as acceptable or better, that is with a CV of 15% or less. For employment in resource manufacturing and "other" manufacturing at the provincial level of geography, much of the year-to-year change in employment levels or the change in employment from the peak year to the level in 2008 had a CV between 15% and 30% and is indicated with an 'E' – data should be used with caution; or had a CV of 30% or greater and is indicated with an 'F' – the sample size is too small to produce reliable estimates and thus were not statistically significant.

North American Industry Classification System (NAICS)

This classification system is used for organizing economic data by industry, and is used by Canada, Mexico and the United States. It is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies.

In this study, the manufacturing sector (NAICS code 31 to 33) has been disaggregated into resource manufacturing and "other" manufacturing sub-sectors. See Appendix 1 for a detailed list.

For more information about NAICS, see Statistics Canada (2007).

Box 2 Geography definitions

This paper uses a geographical concept of Rural and Small Town Canada that is a component of Statistics Canada's "Statistical Area Classification" (Statistics Canada 2007a, 2007b). This classification was developed to provide a functional grouping of individuals according to the type of labour market in which they live.

Rural and small town ( RST ) areas include towns or municipalities (defined by census subdivisions or CSDs) outside of larger urban centres.

Larger urban centres (LUCs) include both census metropolitan areas (CMAs) and census agglomerations (CAs).

Census metropolitan areas (CMAs) have an urban core with a population of at least 100,000 (This definition changed marginally in 2006 but the data from the Labour Force Survey used in this bulletin is based on the 2001 delineation.)

Census agglomerations (CAs) have an urban core population of at least 10,000.

To approximate the functional labour market around their urban core, both CMAs and CAs include all neighbouring municipalities where 50% or more of resident employed individuals commute to the urban core. Commuting flows are a proxy for the economic and social integration between the urban core and the surrounding municipalities (For details on definitions and the delineation methodology, see Statistics Canada (2007a, 2007b)).

In Figures 1 and 2, the data shown for 1976 to 1993 use non-self representing units (NSRU) to proxy RST areas. NSRU areas are smaller municipalities (with a population generally less than 10,000 inhabitants). The data for 1987 to 1998 use the 1986 delineation of CMA/CA and non-CMA/CA areas. The data for 1996 to 2004 use the 1996 delineation of CMA/CA and non-CMA/CA areas. The data for 2001 to 2008 use the 2001 delineation of CMA/CA and non-CMA/CA areas.

Rural and Small Town Canada Analysis Bulletins address issues of interest to rural Canada such as employment trends, education levels, health status, Internet usage and number of firms by type, among others. There are a number of alternative ways to represent urban and rural areas (Puderer 2009, du Plessis et al. 2001). Analysts are encouraged to choose the geographic grid that best meets the requirements of the issue being considered and should bear this in mind when reviewing this study.