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%
Filter results by
Search HelpKeyword(s)
Survey or statistical program
Results
All (3)
All (3) ((3 results))
- 1. Comparison of survey regression techniques in the context of small area estimation of poverty ArchivedArticles and reports: 12-001-X201000211378Description:
One key to poverty alleviation or eradication in the third world is reliable information on the poor and their location, so that interventions and assistance can be effectively targeted to the neediest people. Small area estimation is one statistical technique that is used to monitor poverty and to decide on aid allocation in pursuit of the Millennium Development Goals. Elbers, Lanjouw and Lanjouw (ELL) (2003) proposed a small area estimation methodology for income-based or expenditure-based poverty measures, which is implemented by the World Bank in its poverty mapping projects via the involvement of the central statistical agencies in many third world countries, including Cambodia, Lao PDR, the Philippines, Thailand and Vietnam, and is incorporated into the World Bank software program PovMap. In this paper, the ELL methodology which consists of first modeling survey data and then applying that model to census information is presented and discussed with strong emphasis on the first phase, i.e., the fitting of regression models and on the estimated standard errors at the second phase. Other regression model fitting procedures such as the General Survey Regression (GSR) (as described in Lohr (1999) Chapter 11) and those used in existing small area estimation techniques: Pseudo-Empirical Best Linear Unbiased Prediction (Pseudo-EBLUP) approach (You and Rao 2002) and Iterative Weighted Estimating Equation (IWEE) method (You, Rao and Kovacevic 2003) are presented and compared with the ELL modeling strategy. The most significant difference between the ELL method and the other techniques is in the theoretical underpinning of the ELL model fitting procedure. An example based on the Philippines Family Income and Expenditure Survey is presented to show the differences in both the parameter estimates and their corresponding standard errors, and in the variance components generated from the different methods and the discussion is extended to the effect of these on the estimated accuracy of the final small area estimates themselves. The need for sound estimation of variance components, as well as regression estimates and estimates of their standard errors for small area estimation of poverty is emphasized.
Release date: 2010-12-21 - 2. Pathways into the GIS ArchivedArticles and reports: 75-001-X200910813234Geography: CanadaDescription:
The probability of receiving GIS benefits is strongly correlated with people's income levels at younger ages, particularly to their earnings in their 40s. Negative labour market and health occurrences, including EI receipt and disability claims, having a low income and the receipt of social assistance benefits increased the probability of GIS receipt, while having an employer pension plan or RRSPs decreased the probability.
Release date: 2009-09-18 - 3. Welfare Dynamics in Canada: The Role of Individual Attributes and Economic-policy Variables ArchivedArticles and reports: 11F0019M2004231Geography: CanadaDescription:
In this paper, Canadian longitudinal tax-based data are used to estimate models of the receipt of social assistance, or welfare, in a given year as well as the underlying dynamics: entry onto social assistance from one year to another, exit from a given spell of social assistance and re-entry onto social assistance after the end of a previous spell.
Release date: 2004-10-25
Data (0)
Data (0) (0 results)
No content available at this time.
Analysis (3)
Analysis (3) ((3 results))
- 1. Comparison of survey regression techniques in the context of small area estimation of poverty ArchivedArticles and reports: 12-001-X201000211378Description:
One key to poverty alleviation or eradication in the third world is reliable information on the poor and their location, so that interventions and assistance can be effectively targeted to the neediest people. Small area estimation is one statistical technique that is used to monitor poverty and to decide on aid allocation in pursuit of the Millennium Development Goals. Elbers, Lanjouw and Lanjouw (ELL) (2003) proposed a small area estimation methodology for income-based or expenditure-based poverty measures, which is implemented by the World Bank in its poverty mapping projects via the involvement of the central statistical agencies in many third world countries, including Cambodia, Lao PDR, the Philippines, Thailand and Vietnam, and is incorporated into the World Bank software program PovMap. In this paper, the ELL methodology which consists of first modeling survey data and then applying that model to census information is presented and discussed with strong emphasis on the first phase, i.e., the fitting of regression models and on the estimated standard errors at the second phase. Other regression model fitting procedures such as the General Survey Regression (GSR) (as described in Lohr (1999) Chapter 11) and those used in existing small area estimation techniques: Pseudo-Empirical Best Linear Unbiased Prediction (Pseudo-EBLUP) approach (You and Rao 2002) and Iterative Weighted Estimating Equation (IWEE) method (You, Rao and Kovacevic 2003) are presented and compared with the ELL modeling strategy. The most significant difference between the ELL method and the other techniques is in the theoretical underpinning of the ELL model fitting procedure. An example based on the Philippines Family Income and Expenditure Survey is presented to show the differences in both the parameter estimates and their corresponding standard errors, and in the variance components generated from the different methods and the discussion is extended to the effect of these on the estimated accuracy of the final small area estimates themselves. The need for sound estimation of variance components, as well as regression estimates and estimates of their standard errors for small area estimation of poverty is emphasized.
Release date: 2010-12-21 - 2. Pathways into the GIS ArchivedArticles and reports: 75-001-X200910813234Geography: CanadaDescription:
The probability of receiving GIS benefits is strongly correlated with people's income levels at younger ages, particularly to their earnings in their 40s. Negative labour market and health occurrences, including EI receipt and disability claims, having a low income and the receipt of social assistance benefits increased the probability of GIS receipt, while having an employer pension plan or RRSPs decreased the probability.
Release date: 2009-09-18 - 3. Welfare Dynamics in Canada: The Role of Individual Attributes and Economic-policy Variables ArchivedArticles and reports: 11F0019M2004231Geography: CanadaDescription:
In this paper, Canadian longitudinal tax-based data are used to estimate models of the receipt of social assistance, or welfare, in a given year as well as the underlying dynamics: entry onto social assistance from one year to another, exit from a given spell of social assistance and re-entry onto social assistance after the end of a previous spell.
Release date: 2004-10-25
Reference (0)
Reference (0) (0 results)
No content available at this time.
- Date modified: