Low income and inequality
Key indicators
Selected geographical area: Canada
-
$68,4000.9%
(annual change) -
$73,000
More low income and inequality indicators
Selected geographical area: Canada
-
9.8%
-
-0.040
-
11.1%
-
-3.3
-
$70,336
-
14.2%
-
17.0%
-
32.0%
-
Proportion of households contributing to TFSA, RRP or RRSP in 2015 - Canada
(2016 Census of Population)65.2%
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- 1. What can we learn about low-income dynamics in Canada from the Longitudinal Administrative Databank? ArchivedArticles and reports: 75F0002M2014002Description:
Statistics that depict the movements in the bottom end of the income distribution, such as the proportion of low-income persons exiting low income from one year to the next, provide important information for developing policy on poverty and income inequality. Since the mid 1990s, these statistics have been generated using data from the Survey of Labour and Income Dynamics (SLID). The longitudinal component of the SLID was discontinued in 2010. This paper examines new and alternative time series on low income dynamics that can be created using the Longitudinal Administrative Databank (LAD).
Release date: 2014-12-19 - Articles and reports: 11F0019M2014364Description:
During the 1980s and 1990s, immigration was associated with the rise in low-income rates and family-income inequality in Canada. Over the 2000s, there were significant changes in the labour market and in immigrant selection. This paper focuses on the direct effect of immigration on the change in low income and family-income inequality over the 1995-to-2010 period. The paper outlines recent trends in low-income rates and income inequality for both the Canadian-born and immigrants. The low-income rate in Canada fell during the 2000s. Was this driven in part by changes in economic outcomes among immigrants? Inequality increased considerably in the late 1990s. Did immigration contribute to this increase?
Release date: 2014-12-15 - 3. Low Income Lines, 2012-2013 ArchivedArticles and reports: 75F0002M2014003Description:
In order to provide a holographic or complete picture of low income, Statistics Canada uses three complementary low income lines: the Low Income Cut-offs (LICOs), the Low Income Measures (LIMs) and the Market Basket Measure (MBM). While the first two lines were developed by Statistics Canada, the MBM is based on concepts developed by Employment and Social Development Canada. Though these measures differ from one another, they give a generally consistent picture of low income status over time. None of these measures is the best. Each contributes its own perspective and its own strengths to the study of low income, so that cumulatively, the three provide a better understanding of the phenomenon of low income as a whole. These measures are not measures of poverty, but strictly measures of low income.
Release date: 2014-12-10 - Articles and reports: 12-001-X201400114000Description:
We have used the generalized linearization technique based on the concept of influence function, as Osier has done (Osier 2009), to estimate the variance of complex statistics such as Laeken indicators. Simulations conducted using the R language show that the use of Gaussian kernel estimation to estimate an income density function results in a strongly biased variance estimate. We are proposing two other density estimation methods that significantly reduce the observed bias. One of the methods has already been outlined by Deville (2000). The results published in this article will help to significantly improve the quality of information on the precision of certain Laeken indicators that are disseminated and compared internationally.
Release date: 2014-06-27 - Profile of a community or region: 99-014-X2011020Description:
Using 2011 National Household Survey (NHS) data, this profile provides a statistical overview of variables describing immigration and ethnocultural diversity, Aboriginal peoples, education, labour, mobility and migration, income and earnings, and housing and shelter costs.
In the National Household Survey product line, groups of related variables are referred to as 'release components of profiles.' These are made available with the major releases of variables of the NHS cycle, starting with the Immigration and Ethnocultural Diversity, and Aboriginal Peoples releases. Together, they will form a complete NHS Profile of all the variables for each level of geography. Profile-component data are available at the Canada, province and territory, census division and census subdivision levels, at the census metropolitan area and census agglomeration levels, census tract level, and at the federal electoral district (based on the 2013 Representation Order) level.
Release date: 2014-05-21
Data (1)
Data (1) ((1 result))
- Profile of a community or region: 99-014-X2011020Description:
Using 2011 National Household Survey (NHS) data, this profile provides a statistical overview of variables describing immigration and ethnocultural diversity, Aboriginal peoples, education, labour, mobility and migration, income and earnings, and housing and shelter costs.
In the National Household Survey product line, groups of related variables are referred to as 'release components of profiles.' These are made available with the major releases of variables of the NHS cycle, starting with the Immigration and Ethnocultural Diversity, and Aboriginal Peoples releases. Together, they will form a complete NHS Profile of all the variables for each level of geography. Profile-component data are available at the Canada, province and territory, census division and census subdivision levels, at the census metropolitan area and census agglomeration levels, census tract level, and at the federal electoral district (based on the 2013 Representation Order) level.
Release date: 2014-05-21
Analysis (4)
Analysis (4) ((4 results))
- 1. What can we learn about low-income dynamics in Canada from the Longitudinal Administrative Databank? ArchivedArticles and reports: 75F0002M2014002Description:
Statistics that depict the movements in the bottom end of the income distribution, such as the proportion of low-income persons exiting low income from one year to the next, provide important information for developing policy on poverty and income inequality. Since the mid 1990s, these statistics have been generated using data from the Survey of Labour and Income Dynamics (SLID). The longitudinal component of the SLID was discontinued in 2010. This paper examines new and alternative time series on low income dynamics that can be created using the Longitudinal Administrative Databank (LAD).
Release date: 2014-12-19 - Articles and reports: 11F0019M2014364Description:
During the 1980s and 1990s, immigration was associated with the rise in low-income rates and family-income inequality in Canada. Over the 2000s, there were significant changes in the labour market and in immigrant selection. This paper focuses on the direct effect of immigration on the change in low income and family-income inequality over the 1995-to-2010 period. The paper outlines recent trends in low-income rates and income inequality for both the Canadian-born and immigrants. The low-income rate in Canada fell during the 2000s. Was this driven in part by changes in economic outcomes among immigrants? Inequality increased considerably in the late 1990s. Did immigration contribute to this increase?
Release date: 2014-12-15 - 3. Low Income Lines, 2012-2013 ArchivedArticles and reports: 75F0002M2014003Description:
In order to provide a holographic or complete picture of low income, Statistics Canada uses three complementary low income lines: the Low Income Cut-offs (LICOs), the Low Income Measures (LIMs) and the Market Basket Measure (MBM). While the first two lines were developed by Statistics Canada, the MBM is based on concepts developed by Employment and Social Development Canada. Though these measures differ from one another, they give a generally consistent picture of low income status over time. None of these measures is the best. Each contributes its own perspective and its own strengths to the study of low income, so that cumulatively, the three provide a better understanding of the phenomenon of low income as a whole. These measures are not measures of poverty, but strictly measures of low income.
Release date: 2014-12-10 - Articles and reports: 12-001-X201400114000Description:
We have used the generalized linearization technique based on the concept of influence function, as Osier has done (Osier 2009), to estimate the variance of complex statistics such as Laeken indicators. Simulations conducted using the R language show that the use of Gaussian kernel estimation to estimate an income density function results in a strongly biased variance estimate. We are proposing two other density estimation methods that significantly reduce the observed bias. One of the methods has already been outlined by Deville (2000). The results published in this article will help to significantly improve the quality of information on the precision of certain Laeken indicators that are disseminated and compared internationally.
Release date: 2014-06-27
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