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In the census product line, groups of variables, such as this one, are referred to as release components of profiles. These are made available with the major releases of variables of the census cycle, starting with age and sex. Together, they will form a complete cumulative profile of all the variables for each level of geography, plus one cumulative profile for the dissolved census subdivisions.

Starting with the age and sex major day of release, and on major days of release thereafter, profile component data will be available for particular topics at the Canada, province and territory, census division and census subdivision levels, at the census metropolitan area, census agglomeration and census tract levels, and at the federal electoral district (based on the 2003 Representation Order) level. Profile component data for all other standard areas, including dissemination areas, urban areas, designated places and forward sortation areas, will be available approximately four weeks after the major days of release.

The overall growth of government-owned infrastructure has been very similar across most regions over the past 44 years. With the exception of the Atlantic Provinces, the range of average annual capital growth from one region to the next has been very narrow, falling between 1.8% and 2.2% since 1961, according to a new study released in September 2007 in the Canadian Economic Observer.

Since 2000, governments have increased their infrastructure capital more than at any time since the 1960s and 1970s. However, the growth has not been strong enough to prevent more and more signs of wear in our infrastructure (the data are net of depreciation and in constant 1997 dollars). This is due to cuts in the 1990s when governments were grappling with significant budgetary deficits, as well as many of the assets built in the post-war infrastructure boom reaching the end of their life span.

This study analyses, from 1961 to 2005, government investment in infrastructure by different levels of government and type of asset by region.

This report looks at sport participation by Canadians, including information on sports activities of household members and whether they regularly participated in sports.

An urban area has a minimum population concentration of 1,000 persons and a population density of at least 400 persons per square kilometre, based on the current census population count. All territory outside urban areas is classified as rural. Taken together, urban and rural areas cover all of Canada. For the 2001 Census, there were 913 urban areas. In 2006, the number of urban areas decreased to 895.

Following the release of urban areas for the 2001 Census, in-depth analysis revealed that the land area of many urban areas had increased substantially and the boundaries of these urban areas were considered to be over-bounded. In response, the boundaries of nearly half of the 2001 urban areas were updated to rectify this over-bounding, either manually or automatically. This paper describes the post-censal update process of 2001 urban areas and addresses the impact on the 2001 modified population counts adjusted to 2006 urban area boundaries.

The paper also briefly describes and compares the delineation criteria for urban areas from the 1996 and 2001 Censuses.

The profiles include agricultural statistics on population and farm operators, land use and land practices, farm finances, crops and horticulture, and livestock for most communities at the census consolidated subdivision (CCS), census division (CD) and census agriculture region (CAR) geographic levels. The 2006 Agriculture Community Profiles provide free information from Statistics Canada's 2006 Census of Agriculture data.

This paper examines the presence of knowledge spillovers that affect the adoption of advanced technologies in the Canadian manufacturing sector. It examines whether plants that adopt advanced technologies are more likely to do so when there are other nearby plants that do so within a model of technology adoption.

Productivity and wages tend to be higher in cities. This is typically explained by agglomeration economies, which increase the returns associated with urban locations. Competing arguments of specialization and diversity undergird these claims. Empirical research has long sought to confirm the existence of agglomeration economies and to adjudicate between the models of Marshall, Arrow and Romer (MAR) that suggest the benefits of proximity are largely confined to individual industries, and the claims of Jacobs (1969) that such benefits derive from a general increase in the density of economic activity in a particular place and are shared by all occupants of that location. The primary goal of this paper is to identify the main sources of urban increasing returns, after Marshall (1920). A secondary goal is to examine the geographical distance across which externalities flow between businesses in the same industry. We bring to bear on these questions plant-level data organized in the form of a panel across the years 1989 and 1999. The panel data overcome selection bias resulting from unobserved plant-level heterogeneity that is constant over time. Plant-level production functions are estimated across the Canadian manufacturing sector as a whole and for five broad industry groups, each characterized by the nature of their output. Results provide strong support for Marshall's (1920) claims about the importance of buyer-supplier networks, labour market pooling and spillovers. The data show spillovers enhance plant productivity within industries rather than between them and that these spillovers tend to be more spatially extensive than previous studies have found.

The once scarce bison population continues to grow on Canadian farms. According to the 2006 Census of Agriculture, the bison herd, at 195,728 head, has increased 34.9% since 2001.

Shelter is the biggest expenditure most households make and its affordability can have an impact on the wellbeing of household members. For this reason, housing affordability is closely watched by a wide range of stakeholders - from housing advocates to policy analysts - interested in the welfare of Canadians. Measuring affordability involves comparing housing costs to a household's ability to meet them. One common measure is the shelter-cost-to-income-ratio (STIR). The 30% level is commonly accepted as the upper limit for affordable housing. Housing affordability is also a critical input to Canada Mortgage and Housing Corporation's core housing need indicator which is used by governments to help design, deliver, fund and evaluate social housing programs. This report, jointly authored by Statistics Canada and CMHC, focuses purely on the dynamics of housing affordability, not on core housing need. It examines the likelihood of spending 30% or more of household income on shelter, how often this occurs, whether it is occasional or persistent, and contrasts those spending 30% or more to those spending less. Cross-sectional estimates indicate that around 19% of Canadians lived in households spending more than the affordability benchmark in 2002. Longitudinally however, less than 9% lived in households that spent above the benchmark in each year between 2002 and 2004, while another 19% lived in households spending above the benchmark for either one or two years. The attributes associated with the highest probabilities of living in a household spending above the affordability benchmark were: living alone, being a female lone parent, renting, being an immigrant, or living in Vancouver or Toronto. In addition, those living in households experiencing some kind of transition between 2002 and 2004 period had a higher probability of exceeding the benchmark at least once during the period. Such transitions included renters with a change in rent-subsidy status, those who changed from owner to renter or vice versa, those who changed family type (for example, marrying or divorcing), and those who moved between cities. Notably, those experiencing these transitions did not exceed the benchmark persistently.

Using administrative data, this Juristat is intended to provide a profile of female offenders in Canada. Police-reported data are used to present information on the nature and extent of crime among female youth and adults in 2005 and then examine trends in the rate of female youth and adults charged by police with violent and property offences from 1986 to 2005. Data are compared with crime rates among male youth and adults to illustrate differences in levels and patterns of offending. The report also examines the processing of female youth and adults through the courts and provides characteristics of adult females under federal and provincial/territorial corrections. Again, comparisons are drawn with court activity involving males and with adults males under correctional services.

This publication presents quarterly information on Canada's National Income and Expenditure Accounts (NIEA), 1947-2008. It contains data on gross domestic product (GDP) by income and by expenditure, saving and investment, borrowing and lending of each of four broad sectors of the economy: (i) persons and unincorporated businesses, (ii) corporate and government business enterprises, (iii) governments and (iv) non-residents. Information is also provided for selected subsectors. The publication begins with an analysis of the economic developments in the most recent quarter. Some issues also contain more technical articles explaining national accounts methodology or analysing a particular aspect of the economy. The publication also includes a glossary, and is no longer being released.

Data for Canada, provinces, territories, census divisions, census subdivisions and dissemination areas are shown in this table.

This table is part of the topic 'Labour', which presents data on the paid work of the Canadian workforce, including detailed industry and occupation data, class of worker, and work activity during the reference year. The census is the only source of data covering the entire labour market, including Indian reserves, overseas households, and all provinces and territories.

This topic also presents data on the unpaid work of the Canadian workforce, including unpaid household work, unpaid child care, and unpaid senior care. These data, together with information on paid work, provide a more complete picture of the work activities of all Canadians.

It is possible to subscribe to all the day-of-release topic bundles. Refer to Catalogue no. 97-569-XCB for more information.

Data for Canada, provinces, territories, census divisions, census subdivisions and dissemination areas are shown in this table.

This table is part of the topic 'Income and earnings,' which presents data on the income of Canadian individuals, families, and households in the year 2005, including the composition of income, and data that serve to measure low income, known as the low income cut-off (LICO). The data also include the household incomes of Canadians by family type, age, and geography, as well as the household incomes of certain population groups (e.g., immigrants).

The composition of income includes earnings, income from government sources, and investments.

It is possible to subscribe to all the day-of-release bundles. Refer to Catalogue no. 97-569-XCB for more information.

A series of supporting data tables accompanies the Inuit analytical article from the 2006 Aboriginal Peoples Survey (APS). These tables provide data at the national level, for each of the four Inuit regions (Nunatsiavut, Nunavik, Nunavut and the Inuvialuit region), along with data for Inuit outside these regions for major themes covered in the analytical article. Data for the Inuit identity population aged 15 and over are provided for: Participation in harvesting activities; diagnosed with arthritis/rheumatism, high blood pressure, asthma, stomach problems or intestinal ulcers, heart problems, tuberculosis and diabetes; smoking status; self-rated health status and; reasons for not completing elementary or secondary school. For Inuit children aged 6 to 14, tables include: contact with a pediatrician, general practitioner or family physician in past 12 months; contact with another medical specialist and; food insecurity.

This publication presents early estimates of mineral production by class and by province, quantities and values.

The tables in the topic 'Labour' present data on the paid work of the Canadian workforce, including detailed industry and occupation data, class of worker, and work activity during the reference year. The census is the only source of data covering the entire labour market, including Indian reserves, overseas households, and all provinces and territories.

This topic also presents data on the unpaid work of the Canadian workforce, including unpaid household work, unpaid child care, and unpaid senior care. These data, together with information on paid work, provide a more complete picture of the work activities of all Canadians.

The tables in the topic "Income and earnings" present data on the income of Canadian individuals, families, and households in the year 2005, including the composition of income, and data that serve to measure low income, known as the low income cut-off (LICO). The data also include the household incomes of Canadians by family type, age, and geography, as well as the household incomes of certain population groups (e.g., immigrants).

The composition of income includes earnings, income from government sources, and investments.

This article profiles manure production in Canada and maps manure production by sub-sub-drainage area for 2006.

Data for Canada, provinces and territories are shown in this table.

This table is part of the topic 'Income and earnings,' which presents data on the income of Canadian individuals, families, and households in the year 2005, including the composition of income, and data that serve to measure low income, known as the low income cut-off (LICO). The data also include the household incomes of Canadians by family type, age, and geography, as well as the household incomes of certain population groups (e.g., immigrants).

The composition of income includes earnings, income from government sources, and investments.

It is possible to subscribe to all the day-of-release bundles. Refer to Catalogue no. 97-569-XCB for more information.

This table is available free on the Internet, Catalogue no. 97-563-XWE2006008.

Data for Canada, provinces and territories are shown in this table.

This table is part of the topic 'Income and earnings,' which presents data on the income of Canadian individuals, families, and households in the year 2005, including the composition of income, and data that serve to measure low income, known as the low income cut-off (LICO). The data also include the household incomes of Canadians by family type, age, and geography, as well as the household incomes of certain population groups (e.g., immigrants).

The composition of income includes earnings, income from government sources, and investments.

It is possible to subscribe to all the day-of-release bundles. Refer to Catalogue no. 97-569-XCB for more information.

This table is available free on the Internet, Catalogue no. 97-563-XWE2006009.

The context of the discussion is the increasing incidence of international surveys, of which one is the International Tobacco Control (ITC) Policy Evaluation Project, which began in 2002. The ITC country surveys are longitudinal, and their aim is to evaluate the effects of policy measures being introduced in various countries under the WHO Framework Convention on Tobacco Control. The challenges of organization, data collection and analysis in international surveys are reviewed and illustrated. Analysis is an increasingly important part of the motivation for large scale cross-cultural surveys. The fundamental challenge for analysis is to discern the real response (or lack of response) to policy change, separating it from the effects of data collection mode, differential non-response, external events, time-in-sample, culture, and language. Two problems relevant to statistical analysis are discussed. The first problem is the question of when and how to analyze pooled data from several countries, in order to strengthen conclusions which might be generally valid. While in some cases this seems to be straightforward, there are differing opinions on the extent to which pooling is possible and reasonable. It is suggested that for formal comparisons, random effects models are of conceptual use. The second problem is to find models of measurement across cultures and data collection modes which will enable calibration of continuous, binary and ordinal responses, and produce comparisons from which extraneous effects have been removed. It is noted that hierarchical models provide a natural way of relaxing requirements of model invariance across groups.

Dependent interviewing (DI) is used in many longitudinal surveys to "feed forward" data from one wave to the next. Though it is a promising technique which has been demonstrated to enhance data quality in certain respects, relatively little is known about how it is actually administered in the field. This research seeks to address this issue through behavior coding. Various styles of DI were employed in the English Longitudinal Study of Ageing (ELSA) in January, 2006, and recordings were made of pilot field interviews. These recordings were analysed to determine whether the questions (particularly the DI aspects) were administered appropriately and to explore the respondent's reaction to the fed-forward data. Of particular interest was whether respondents confirmed or challenged the previously-reported information, whether the prior wave data came into play when respondents were providing their current-wave answers, and how any discrepancies were negotiated by the interviewer and respondent. Also of interest was to examine the effectiveness of various styles of DI. For example, in some cases the prior wave data was brought forward and respondents were asked to explicitly confirm it; in other cases the previous data was read and respondents were asked if the situation was still the same. Results indicate varying levels of compliance in terms of initial question-reading, and suggest that some styles of DI may be more effective than others.

In longitudinal surveys nonresponse often occurs in a pattern that is not monotone. We consider estimation of time-dependent means under the assumption that the nonresponse mechanism is last-value-dependent. Since the last value itself may be missing when nonresponse is nonmonotone, the nonresponse mechanism under consideration is nonignorable. We propose an imputation method by first deriving some regression imputation models according to the nonresponse mechanism and then applying nonparametric regression imputation. We assume that the longitudinal data follow a Markov chain with finite second-order moments. No other assumption is imposed on the joint distribution of longitudinal data and their nonresponse indicators. A bootstrap method is applied for variance estimation. Some simulation results and an example concerning the Current Employment Survey are presented.

Sample weights can be calibrated to reflect the known population totals of a set of auxiliary variables. Predictors of finite population totals calculated using these weights have low bias if these variables are related to the variable of interest, but can have high variance if too many auxiliary variables are used. This article develops an "adaptive calibration" approach, where the auxiliary variables to be used in weighting are selected using sample data. Adaptively calibrated estimators are shown to have lower mean squared error and better coverage properties than non-adaptive estimators in many cases.

We propose a method for estimating the variance of estimators of changes over time, a method that takes account of all the components of these estimators: the sampling design, treatment of non-response, treatment of large companies, correlation of non-response from one wave to another, the effect of using a panel, robustification, and calibration using a ratio estimator. This method, which serves to determine the confidence intervals of changes over time, is then applied to the Swiss survey of value added.

The analysis of stratified multistage sample data requires the use of design information such as stratum and primary sampling unit (PSU) identifiers, or associated replicate weights, in variance estimation. In some public release data files, such design information is masked as an effort to avoid their disclosure risk and yet to allow the user to obtain valid variance estimation. For example, in area surveys with a limited number of PSUs, the original PSUs are split or/and recombined to construct pseudo-PSUs with swapped second or subsequent stage sampling units. Such PSU masking methods, however, obviously distort the clustering structure of the sample design, yielding biased variance estimates possibly with certain systematic patterns between two variance estimates from the unmasked and masked PSU identifiers. Some of the previous work observed patterns in the ratio of the masked and unmasked variance estimates when plotted against the unmasked design effect. This paper investigates the effect of PSU masking on variance estimates under cluster sampling regarding various aspects including the clustering structure and the degree of masking. Also, we seek a PSU masking strategy through swapping of subsequent stage sampling units that helps reduce the resulting biases of the variance estimates. For illustration, we used data from the National Health Interview Survey (NHIS) with some artificial modification. The proposed strategy performs very well in reducing the biases of variance estimates. Both theory and empirical results indicate that the effect of PSU masking on variance estimates is modest with minimal swapping of subsequent stage sampling units. The proposed masking strategy has been applied to the 2003-2004 National Health and Nutrition Examination Survey (NHANES) data release.

The design of a stratified simple random sample without replacement from a finite population deals with two main issues: the definition of a rule to partition the population into strata, and the allocation of sampling units in the selected strata. This article examines a tree-based strategy which plans to approach jointly these issues when the survey is multipurpose and multivariate information, quantitative or qualitative, is available. Strata are formed through a hierarchical divisive algorithm that selects finer and finer partitions by minimizing, at each step, the sample allocation required to achieve the precision levels set for each surveyed variable. In this way, large numbers of constraints can be satisfied without drastically increasing the sample size, and also without discarding variables selected for stratification or diminishing the number of their class intervals. Furthermore, the algorithm tends not to define empty or almost empty strata, thus avoiding the need for strata collapsing aggregations. The procedure was applied to redesign the Italian Farm Structure Survey. The results indicate that the gain in efficiency held using our strategy is nontrivial. For a given sample size, this procedure achieves the required precision by exploiting a number of strata which is usually a very small fraction of the number of strata available when combining all possible classes from any of the covariates.

Optimum stratification is the method of choosing the best boundaries that make strata internally homogeneous, given some sample allocation. In order to make the strata internally homogenous, the strata should be constructed in such a way that the strata variances for the characteristic under study be as small as possible. This could be achieved effectively by having the distribution of the main study variable known and create strata by cutting the range of the distribution at suitable points. If the frequency distribution of the study variable is unknown, it may be approximated from the past experience or some prior knowledge obtained at a recent study. In this paper the problem of finding Optimum Strata Boundaries (OSB) is considered as the problem of determining Optimum Strata Widths (OSW). The problem is formulated as a Mathematical Programming Problem (MPP), which minimizes the variance of the estimated population parameter under Neyman allocation subject to the restriction that sum of the widths of all the strata is equal to the total range of the distribution. The distributions of the study variable are considered as continuous with Triangular and Standard Normal density functions. The formulated MPPs, which turn out to be multistage decision problems, can then be solved using dynamic programming technique proposed by Bühler and Deutler (1975). Numerical examples are presented to illustrate the computational details. The results obtained are also compared with the method of Dalenius and Hodges (1959) with an example of normal distribution.

This paper considers the optimum allocation in multivariate stratified sampling as a nonlinear matrix optimisation of integers. As a particular case, a nonlinear problem of the multi-objective optimisation of integers is studied. A full detailed example including some of proposed techniques is provided at the end of the work.

The present work illustrates a sampling strategy useful for obtaining planned sample size for domains belonging to different partitions of the population and in order to guarantee the sampling errors of domain estimates be lower than given thresholds. The sampling strategy that covers the multivariate multi-domain case is useful when the overall sample size is bounded and consequently the standard solution of using a stratified sample with the strata given by cross-classification of variables defining the different partitions is not feasible since the number of strata is larger than the overall sample size. The proposed sampling strategy is based on the use of balanced sampling selection technique and on a GREG-type estimation. The main advantages of the solution is the computational feasibility which allows one to easily implement an overall small area strategy considering jointly the sampling design and the estimator and improving the efficiency of the direct domain estimators. An empirical simulation on real population data and different domain estimators shows the empirical properties of the examined sample strategy.

This guide focuses on the following demographic variables: First official language spoken, Home language, Knowledge of non-official languages, Knowledge of official languages, Language of work, and Mother tongue.

Provides information that enables users to effectively use, apply and interpret data from the 2006 Census. Each guide contains definitions and explanations on census concepts. Additional information will be included for specific variables to help general users better understand the concepts and questions used in the census.

This guide focuses on the following demographic variables: Place of birth, Generation status, Citizenship and Immigration.

Provides information that enables users to effectively use, apply and interpret data from the 2006 Census. Each guide contains definitions and explanations on census concepts. Additional information will be included for specific variables to help general users better understand the concepts and questions used in the census.

These guides provide information that enables users to effectively use, apply and interpret data from the 2006 Census. Each guide contains definitions and explanations on census concepts. Additional information will be included for specific variables to help general users better understand the concepts and questions used in the census.

These guides provide information that enables users to effectively use, apply and interpret data from the 2006 Census. Each guide contains definitions and explanations on census concepts, data quality and historical comparability. Additional information will be included for specific variables to help general users better understand the concepts and questions used in the census.