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The Program for International Student Assessment (PISA) is a collaborative effort among member countries of the OECD, designed to assess, on a regular basis, the achievement of 15-year-olds in reading, mathematical and scientific literacy through a common international test.

This report presents initial results for Canada, Canadian provinces and selected countries from PISA 2000. Reading literacy is the major focus of PISA 2000, with mathematical and scientific literacy as minor domains.

This report also includes results from the Youth in Transition Survey (YITS), a Canadian longitudinal survey designed to examine the patterns of, and influences on, major transitions in young people's lives, particularly with respect to education, training and work.

Thirty-two countries participated in PISA 2000. In Canada, approximately 30,000 15-year-old students from more than 1,000 schools participated.

This table is part of the topic "Families and Household Living Arrangements," which presents data on census families, including the number of families, family size and family structure. The 2001 Census data also include persons living in families, with relatives and with non-relatives, and living alone.

Family structure refers to the classification of census families into families of married couples, common-law couples (including same-sex couples) and lone-parent families.

This table can be found in the Topic Bundle: Families and Household Living Arrangements, 2001 Census, Catalogue No. 97F0005XCB2001000.

It is also possible to subscribe to all the day-of-release bundles. For more information, refer to Catalogue No. 97F0023XCB.

This table is available FREE on the Internet, Catalogue No. 97F0005XIE2001001.

This table is part of the topic "Families and Household Living Arrangements," which presents data on census families, including the number of families, family size and family structure. The 2001 Census data also include persons living in families, with relatives and with non-relatives, and living alone.

Family structure refers to the classification of census families into families of married couples, common-law couples (including same-sex couples) and lone-parent families.

This table can be found in the Topic Bundle: Families and Household Living Arrangements, 2001 Census, Catalogue No. 97F0005XCB2001000.

It is also possible to subscribe to all the day-of-release bundles. For more information, refer to Catalogue No. 97F0023XCB.

This table is available FREE on the Internet, Catalogue No. 97F0005XIE2001002.

This table is part of the topic "Families and Household Living Arrangements," which presents data on census families, including the number of families, family size and family structure. The 2001 Census data also include persons living in families, with relatives and with non-relatives, and living alone.

Family structure refers to the classification of census families into families of married couples, common-law couples (including same-sex couples) and lone-parent families.

This table can be found in the Topic Bundle: Families and Household Living Arrangements, 2001 Census, Catalogue No. 97F0005XCB2001000.

It is also possible to subscribe to all the day-of-release bundles. For more information, refer to Catalogue No. 97F0023XCB.

This table is available FREE on the Internet, Catalogue No. 97F0005XIE2001003.

This table is part of the topic "Families and Household Living Arrangements," which presents data on census families, including the number of families, family size and family structure. The 2001 Census data also include persons living in families, with relatives and with non-relatives, and living alone.

Family structure refers to the classification of census families into families of married couples, common-law couples (including same-sex couples) and lone-parent families.

This table can be found in the Topic Bundle: Families and Household Living Arrangements, 2001 Census, Catalogue No. 97F0005XCB2001000.

It is also possible to subscribe to all the day-of-release bundles. For more information, refer to Catalogue No. 97F0023XCB.

This table is available FREE on the Internet, Catalogue No. 97F0005XIE2001004.

This table is part of the topic "Families and Household Living Arrangements," which presents data on census families, including the number of families, family size and family structure. The 2001 Census data also include persons living in families, with relatives and with non-relatives, and living alone.

Family structure refers to the classification of census families into families of married couples, common-law couples (including same-sex couples) and lone-parent families.

This table can be found in the Topic Bundle: Families and Household Living Arrangements, 2001 Census, Catalogue No. 97F0005XCB2001000.

It is also possible to subscribe to all the day-of-release bundles. For more information, refer to Catalogue No. 97F0023XCB.

This table is available FREE on the Internet, Catalogue No. 97F0005XIE2001005.

This table is part of the topic "Families and Household Living Arrangements," which presents data on census families, including the number of families, family size and family structure. The 2001 Census data also include persons living in families, with relatives and with non-relatives, and living alone.

Family structure refers to the classification of census families into families of married couples, common-law couples (including same-sex couples) and lone-parent families.

This table can be found in the Topic Bundle: Families and Household Living Arrangements, 2001 Census, Catalogue No. 97F0005XCB2001000.

It is also possible to subscribe to all the day-of-release bundles. For more information, refer to Catalogue No. 97F0023XCB.

This table is available FREE on the Internet, Catalogue No. 97F0005XIE2001006.

This table is part of the topic "Families and Household Living Arrangements," which presents data on census families, including the number of families, family size and family structure. The 2001 Census data also include persons living in families, with relatives and with non-relatives, and living alone.

Family structure refers to the classification of census families into families of married couples, common-law couples (including same-sex couples) and lone-parent families.

This table can be found in the Topic Bundle: Families and Household Living Arrangements, 2001 Census, Catalogue No. 97F0005XCB2001000.

It is also possible to subscribe to all the day-of-release bundles. For more information, refer to Catalogue No. 97F0023XCB.

This table is available FREE on the Internet, Catalogue No. 97F0005XIE2001040.

This table is part of the topic "Families and Household Living Arrangements," which presents data on census families, including the number of families, family size and family structure. The 2001 Census data also include persons living in families, with relatives and with non-relatives, and living alone.

Family structure refers to the classification of census families into families of married couples, common-law couples (including same-sex couples) and lone-parent families.

This table can be found in the Topic Bundle: Families and Household Living Arrangements, 2001 Census, Catalogue No. 97F0005XCB2001000.

It is also possible to subscribe to all the day-of-release bundles. For more information, refer to Catalogue No. 97F0023XCB.

This table is available FREE on Internet, Catalogue No. 97F0005XIE2001041.

This table is part of the topic "Housing," which presents 2001 Census data on dwellings, including structural type of dwelling, number of rooms and bedrooms, condition of dwelling and period of construction, as well as data on households, including household maintainer and tenure (owned, rented and band housing).

This table can be found in the Topic Bundle: Housing, 2001 Census, Catalogue No. 97F0006XCB2001000.

It is also possible to subscribe to all the day-of-release bundles. For more information, refer to Catalogue No. 97F0023XCB.

This is available FREE on the Internet, Catalogue No. 97F0006XIE2001001.

This table is part of the topic "Housing," which presents 2001 Census data on dwellings, including structural type of dwelling, number of rooms and bedrooms, condition of dwelling and period of construction, as well as data on households, including household maintainer and tenure (owned, rented and band housing).

This table can be found in the Topic Bundle: Housing, 2001 Census, Catalogue No. 97F0006XCB2001000.

It is also possible to subscribe to all day-of-release bundles. For more information, refer to Catalogue No. 97F0023XCB.

This is available FREE on the Internet, Catalogue No. 97F0006XIE2001002.

In this paper, we discuss the application of the bootstrap with a re-imputation step to capture the imputation variance (Shao and Sitter 1996) in stratified multistage sampling. We propose a modified bootstrap that does not require rescaling so that Shao and Sitter's procedure can be applied to the case where random imputation is applied and the first-stage stratum sample sizes are very small. This provides a unified method that works irrespective of the imputation method (random or nonrandom), the stratum size (small or large), the type of estimator (smooth or nonsmooth), or the type of problem (variance estimation or sampling distribution estimation). In addition, we discuss the proper Monte Carlo approximation to the bootstrap variance, when using re-imputation together with resampling methods. In this setting, more care is needed than is typical. Similar results are obtained for the method of balanced repeated replications, which is often used in surveys and can be viewed as an analytic approximation to the bootstrap. Finally, some simulation results are presented to study finite sample properties and various variance estimators for imputed data.

Local polynomial regression methods are put forward to aid in exploratory data analysis for large-scale surveys. The proposed regression methods are put forward to aid in exploratory data analysis for large-scale surveys. The proposed method relies on binning the data on the x-variable and calculating the appropriate survey estimates for the mean of the y-values at each bin. When binning on x has been carried out to the precision of the recorded data, the method is the same as applying the survey weights to the standard criterion for obtaining local polynomial regression estimates. The alternative of using classical polynomial regression is also considered and a criterion is proposed to decide whether the nonparametric approach to modeling should be preferred over the classical approach. Illustrative examples are given from the 1990 Ontario Health Survey.

A compositional time series is defined as a multivariate time series in which each of the series has values bounded between zero and one and the sum of the series equals one at each time point. Data with such characteristics are observed in repeated surveys when a survey variable has a multinomial response but interest lies in the proportion of units classified in each of its categories. In this case, the survey estimates are proportions of a whole subject to a unity-sum constraint. In this paper we employ a state space approach for modelling compositional time series from repeated surveys taking into account the sampling errors. The additive logistic transformation is used in order to guarantee predictions and signal estimates bounded between zero and one which satisfy the unity-sum constraint. The method is applied to compositional data from the Brazilian Labour Force Survey. Estimates of the vector of proportions and the unemployment rate are obtained. In addition, the structural components of the signal vector, such as the seasonals and the trends, are produced.

In this Issue is a column where the Editor biefly presents each paper of the current issue of Survey Methodology. As well, it sometimes contain informations on structure or management changes in the journal.

Using data from the Assets and Debts Survey of 1984 and the Survey of Financial Security of 1999, we document the evolution of wealth inequality in Canada between 1984 and 1999. Our main findings are as follows: 1) wealth inequality has increased between 1984 and 1999, 2) the growth in wealth inequality has been associated with substantial declines in real average and median wealth for young couples with children and recent immigrants, 3) real median wealth and real average wealth rose much more among family units whose major income recipient is a university graduate than among other family units, 4) real median and average wealth fell among family units whose major income recipient is aged 25-34 and increased among those whose major income recipient is aged 55 and over, 5) the aging of the Canadian population over the 1984-1999 period has tended to reduce wealth inequality, 6) diverging changes in permanent income do not explain a substantial portion of the growing gap between low-wealth and high-wealth family units. Factors that may have contributed to rising wealth inequality - which cannot be quantified with existing data sets - include differences in the growth of inheritances, inter vivos transfers, rates of return on savings and number of years worked full-time. In particular, rates of return on savings may have increased more for wealthy family units than for their poorer counterparts as a result of the booming stock market during the 1990s.

This, the first issue of 2002 presents an opportunity to recapitulate some of the findings that we have reported during the life of the Bulletin. In an interview, Dr. Fred Gault, Director of Statistics Canada's Science, Innovation and Electronic Information Division, discusses some of the findings on innovation, e-commerce, emerging technologies, Internet use, the telecommunications industry, R&D and commercialization.

Canadian manufacturing firms fall into two groups: The first uses patents and trademarks as a part of successful innovation strategy consisting of regular R&D financed by R&D grants and tax credits introducing world-first innovations. These are usually large firms in the technology-intensive core sector. The second group includes firms of all sizes in all sectors that rely mostly on trade secrets. They typically transfer technology from abroad by introducing Canada-first innovations and rely on government information services more than on R&D grants and tax credits.

In September 2000, a small international group met to develop a survey on knowledge management. Creating the pilot questionnaire required a cooperative effort on behalf of survey taking experts, knowledge management specialists and policy analysts. Bringing together a preliminary questionnaire that met the basic requirements of a group of dynamic and outspoken experts, each with individual and collective objectives was not a simple task.

According to the report Profile of Spin-off Firms in the Biotechnology Sector, three out of every 10 companies in Canada's rapidly expanding biotechnology sector in 1999 were spin-offs. These firms, which range from corporate spin-offs to biotechnology companies created by universities and research hospitals, accounted for more than one-quarter of total revenues in 1999.

Given that science and technology skills are a high priority for maintaining Canada's competitive advantage in the new economy, the obvious question is: Where do S&T skills come from and how does Canada compare with other countries? Read the findings from a recent Statistics Canada study that examines the ins and outs of the science stream, starting in Grade 4 through to the workforce.

This paper compares six definitions of the word 'rural' from databases at Statistics Canada. Each definition emphasizes different criteria (population size, density, context) and has different associated thresholds. The size of the territorial units (building blocks) from which each definition is constructed also varies.

This practical and informative guide for the construction industry will assist in navigating through numerous Statistics Canada products and services.

This guide presents information of interest to users of data from the Survey of Household Spending. Data are collected via paper questionnaires and personal interviews conducted in January, February and March after the reference year. Information is gathered about the spending habits, dwelling characteristics and household equipment of Canadian households during the reference year. The survey covers private households in the 10 provinces and the 3 territories. (The territories are surveyed every second year, starting in 2001.) This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. There is also a section describing the various statistics that can be created using expenditure data (e.g., budget share, market share and aggregates).

This document outlines the structure of the January 2001 Survey of Labour and Income Dynamics (SLID) labour interview, including question wording, possible responses and the flow of questions.

This paper presents the questions, possible responses and question flows for the 2001 Survey of Labour and Income Dynamics (SLID) preliminary questionnaire.

This document presents the information for the Entry Exit portion of the Survey of Labour and Income Dynamics (SLID) Labour interview.

Like most statistical agencies, Statistics Canada publishes three Gross Domestic Product (GDP) series. These are the output-based GDP, the income-based GDP and the expenditure-based GDP. This document is aimed at describing the concepts, definitions, classifications and statistical methods underlying the output-based GDP series, also known as GDP by industry or simply monthly GDP.

The report is organized into seven chapters. Chapter 1 defines what GDP by industry is, describes its various uses and how it connects with the other components of the Canadian System of National Accounts. Chapter 2 deals with the calculation of the GDP by industry estimates. Chapter 3 examines industry and commodity classification schemes. Chapter 4 discusses the subject of deflation. The choice of deflators, the role of the base year and the method of rebasing are all addressed in this chapter. Chapter 5 looks at such technical issues as benchmarking, trading day and seasonal adjustment. Chapter 6 is devoted to the presentation of the GDP by industry, detailing the format, release dates and modes of dissemination, as well as the need and the frequency of revising the estimates. Finally, Chapter 7 reviews the historical development of monthly GDP from 1926 to the present.

The Forward Sortation Areas Boundary File Reference Guide is available for the following product: Forward Sortation Areas Boundary File (Catalogue no. 92F0170XCE). The reference guide describes the content and applications of these products, as well as data quality, record layouts and other information.

This user's guide provides a detailed description of the CD-ROM Income trends in Canada (Catalogue no. 13F0022XCB). It also provides a glossary and a description of the major concepts, as well as an overview of the data source, the Survey of Labour and Income Dynamics (SLID).

The Provincial Economic Accounts will adopt the Fisher Volume Index, chained annually, as the official measure of real expenditure-based GDP. This change will be incorporated into the affected series back to 1981.