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- Articles and reports: 11F0027M2014092Geography: Province or territoryDescription:
Using data from the Provincial KLEMS database, this paper asks whether provincial economies have undergone structural change in their business sectors since 2000. It does so by applying a measure of industrial change (the dissimilarity index) using measures of output (real GDP) and hours worked. The paper also develops a statistical methodology to test whether the shifts in the industrial composition of output and hours worked over the period are due to random year-over-year changes in industrial structure or long-term systematic change in the structure of provincial economies. The paper is designed to inform discussion and analysis of recent changes in industrial composition at the national level, notably, the decline in manufacturing output and the concomitant rise of resource industries, and the implications of this change for provincial economies.
Release date: 2014-05-07 - Articles and reports: 75F0002M2008006Geography: Province or territoryDescription:
Comparisons of low income between regions may have impacts on policy choices. However, it is often argued that rankings of distributions are not robust and that they are also quite sensitive to methods of defining low income. This paper avoids these problems by using a stochastic dominance approach to compare regional low income profiles in Canada without arbitrarily specifying a low-income line. This analysis is carried out for the 10 provinces using the Survey of Labour and Income Dynamics for 2000. Robustness of the results is also verified with respect to different choices of spatial price deflators and equivalence scales. The extent to which the findings are sensitive to the choice of an absolute or a relative concept of low income is also examined. We show that, in most cases, dominance relations can be determined and regional low income can be ordered for a wide range of low-income lines. We also show that dominance results are robust to the choice of equivalence scales, while rank reversal occurs when alternative cost-of-living deflators are used. Switching from an absolute to a relative low-income concept only affects low-income rankings for Ontario, Quebec and the Prairie provinces, but not in the case of other provinces. Nevertheless, for all scales, we find that low income is greatest in British Columbia.
Release date: 2008-10-09 - Journals and periodicals: 84F0013XGeography: Canada, Province or territoryDescription:
This study was initiated to test the validity of probabilistic linkage methods used at Statistics Canada. It compared the results of data linkages on infant deaths in Canada with infant death data from Nova Scotia and Alberta. It also compared the availability of fetal deaths on the national and provincial files.
Release date: 1999-10-08 - 4. Project on Matching Census 1986 Database and Manitoba Health Care Files: Private Households Component ArchivedArticles and reports: 11F0019M1996091Geography: Province or territoryDescription:
Introduction: In the current economic context, all partners in health care delivery systems, be they public or private, are obliged to identify the factors that influence the utilization of health care services. To improve our understanding of the phenomena that underlie these relationships, Statistics Canada and the Manitoba Centre for Health Policy and Evaluation have just set up a new database. For a representative sample of the population of the province of Manitoba, cross-sectional microdata on individuals' health and socio-economic characteristics were linked with detailed longitudinal data on utilization of health care services.
Data and methods: The 1986-87 Health and Activity Limitation Survey, the 1986 Census and the files of Manitoba Health were matched (without using names or addresses) by means of the CANLINK software. In the pilot project, 20,000 units were selected from the Census according to modern sampling techniques. Before the files were matched, consultations were held and an agreement was signed by all parties in order to establish a framework for protecting privacy and preserving the confidentiality of the data.
Results: A matching rate of 74% was obtained for private households. A quality evaluation based on the comparisons of names and addresses over a small subsample established that the overall concordance rate among matched pairs was 95.5%. The match rates and concordance rates varied according to age and household composition. Estimates produced from the sample accurately reflected the socio-demographic profile, mortality, hospitalization rate, health care costs and consumption of health care by Manitoba residents.
Discussion: The matching rate of 74% was satisfactory in comparison with the response rates reported in most population surveys. Because of the excellent concordance rate and the accuracy of the estimates obtained from the sample, this database will provide an adequate basis for studying the association between socio-demographic characteristics, health and health care utilization in province of Manitoba.
Release date: 1996-03-30
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- Articles and reports: 11F0027M2014092Geography: Province or territoryDescription:
Using data from the Provincial KLEMS database, this paper asks whether provincial economies have undergone structural change in their business sectors since 2000. It does so by applying a measure of industrial change (the dissimilarity index) using measures of output (real GDP) and hours worked. The paper also develops a statistical methodology to test whether the shifts in the industrial composition of output and hours worked over the period are due to random year-over-year changes in industrial structure or long-term systematic change in the structure of provincial economies. The paper is designed to inform discussion and analysis of recent changes in industrial composition at the national level, notably, the decline in manufacturing output and the concomitant rise of resource industries, and the implications of this change for provincial economies.
Release date: 2014-05-07 - Articles and reports: 75F0002M2008006Geography: Province or territoryDescription:
Comparisons of low income between regions may have impacts on policy choices. However, it is often argued that rankings of distributions are not robust and that they are also quite sensitive to methods of defining low income. This paper avoids these problems by using a stochastic dominance approach to compare regional low income profiles in Canada without arbitrarily specifying a low-income line. This analysis is carried out for the 10 provinces using the Survey of Labour and Income Dynamics for 2000. Robustness of the results is also verified with respect to different choices of spatial price deflators and equivalence scales. The extent to which the findings are sensitive to the choice of an absolute or a relative concept of low income is also examined. We show that, in most cases, dominance relations can be determined and regional low income can be ordered for a wide range of low-income lines. We also show that dominance results are robust to the choice of equivalence scales, while rank reversal occurs when alternative cost-of-living deflators are used. Switching from an absolute to a relative low-income concept only affects low-income rankings for Ontario, Quebec and the Prairie provinces, but not in the case of other provinces. Nevertheless, for all scales, we find that low income is greatest in British Columbia.
Release date: 2008-10-09 - Journals and periodicals: 84F0013XGeography: Canada, Province or territoryDescription:
This study was initiated to test the validity of probabilistic linkage methods used at Statistics Canada. It compared the results of data linkages on infant deaths in Canada with infant death data from Nova Scotia and Alberta. It also compared the availability of fetal deaths on the national and provincial files.
Release date: 1999-10-08 - 4. Project on Matching Census 1986 Database and Manitoba Health Care Files: Private Households Component ArchivedArticles and reports: 11F0019M1996091Geography: Province or territoryDescription:
Introduction: In the current economic context, all partners in health care delivery systems, be they public or private, are obliged to identify the factors that influence the utilization of health care services. To improve our understanding of the phenomena that underlie these relationships, Statistics Canada and the Manitoba Centre for Health Policy and Evaluation have just set up a new database. For a representative sample of the population of the province of Manitoba, cross-sectional microdata on individuals' health and socio-economic characteristics were linked with detailed longitudinal data on utilization of health care services.
Data and methods: The 1986-87 Health and Activity Limitation Survey, the 1986 Census and the files of Manitoba Health were matched (without using names or addresses) by means of the CANLINK software. In the pilot project, 20,000 units were selected from the Census according to modern sampling techniques. Before the files were matched, consultations were held and an agreement was signed by all parties in order to establish a framework for protecting privacy and preserving the confidentiality of the data.
Results: A matching rate of 74% was obtained for private households. A quality evaluation based on the comparisons of names and addresses over a small subsample established that the overall concordance rate among matched pairs was 95.5%. The match rates and concordance rates varied according to age and household composition. Estimates produced from the sample accurately reflected the socio-demographic profile, mortality, hospitalization rate, health care costs and consumption of health care by Manitoba residents.
Discussion: The matching rate of 74% was satisfactory in comparison with the response rates reported in most population surveys. Because of the excellent concordance rate and the accuracy of the estimates obtained from the sample, this database will provide an adequate basis for studying the association between socio-demographic characteristics, health and health care utilization in province of Manitoba.
Release date: 1996-03-30
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