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To augment the amount of available information, data from different sources are increasingly being combined. These databases are often combined using record linkage methods. When there is no unique identifier, a probabilistic linkage is used. In that case, a record on a first file is associated with a probability that is linked to a record on a second file, and then a decision is taken on whether a possible link is a true link or not. This usually requires a non-negligible amount of manual resolution. It might then be legitimate to evaluate if manual resolution can be reduced or even eliminated. This issue is addressed in this paper where one tries to produce an estimate of a total (or a mean) of one population, when using a sample selected from another population linked somehow to the first population. In other words, having two populations linked through probabilistic record linkage, we try to avoid any decision concerning the validity of links and still be able to produce an unbiased estimate for a total of the one of two populations. To achieve this goal, we suggest the use of the Generalised Weight Share Method (GWSM) described by Lavallée (1995).

This paper presents weighting procedures that combine information from multiple panels of a repeated panel household survey for cross-sectional estimation. The dynamic character of a repeated panel survey is discussed in relation to estimation of population parameters at any wave of the survey. A repeated panel survey with overlapping panels is described as a special type of multiple frame survey, with the frames of the panels forming a time sequence. The paper proposes weighting strategies suitable for various multiple panel survey situations. The proposed weighting schemes involve an adjustment of weights in domains of the combined panel sample that represent identical time periods covered by the individual panels. A weight adjustment procedure that deals with changes in the panels over time is discussed. The integration of the various weight adjustments required for cross-sectional estimation in a repeated panel household survey is also discussed.

This article reviews the methods that may be used to produce direct estimates for small areas, including stratification and oversampling, and forms of dual-frame estimation.

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.

Using 2001 Census data, this day-of-release table provides a statistical overview of the languages, mobility and migration variables for Canada, provinces, territories, census divisions and census subdivisions.

On each of the days of release, profile component data will be available for particular topics at the Canada, province/territory, census division and census subdivision levels. Profile component data for all other standard areas, including census metropolitan areas, census agglomerations, census tracts, federal electoral districts (based on the 1996 Representation Order), dissemination areas and forward sortation areas, will be available approximately four weeks after the initial release.

In the census product line, groups of variables, such as this one, are referred to as electronic components of profiles. These are made available in each of the eight major releases of variables of the census cycle. 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.

This table is part of the 2001 Census topic "Language Composition of Canada," which shows 2001 Census data on the language composition of Canada, by mother tongue and other variables, as well as on languages spoken at home and knowledge of English, French and non-official languages. These data were collected for a sample comprising 20% of the Canadian population.

This data table can be found in the Topic Bundle: Language Composition of Canada, 2001 Census, Catalogue No. 97F0007XCB2001000

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

This table is available FREE on the Internet, Catalogue No. 97F0007XIE2001001.

This table is part of the 2001 Census topic "Language Composition of Canada," which shows 2001 Census data on the language composition of Canada, by mother tongue and other variables, as well as on languages spoken at home and knowledge of English, French and non-official languages. These data were collected for a sample comprising 20% of the Canadian population.

This data table can be found in the Topic Bundle: Language Composition of Canada, 2001 Census, Catalogue No. 97F0007XCB2001000

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

This table is available FREE on the Internet, Catalogue No. 97F0007XIE2001002.

This table is part of the 2001 Census topic "Language Composition of Canada," which shows data on the language composition of Canada, by mother tongue and other variables, as well as on languages spoken at home and knowledge of English, French and non-official languages. These data were collected for a sample comprising 20% of the Canadian population.

This data table can be found in the Topic Bundle: Language Composition of Canada, 2001 Census, Catalogue No. 97F0007XCB2001000

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

This table is available FREE on the Internet, Catalogue No. 97F0007XIE2001003.

This table is part of the 2001 Census topic "Language Composition of Canada," which shows data on the language composition of Canada, by mother tongue and other variables, as well as on languages spoken at home and knowledge of English, French, and non-official languages. These data were collected for a sample comprising 20% of the Canadian population.

This data table can be found in the Topic Bundle: Language Composition of Canada, 2001 Census - Catalogue No. 97F0007XCB2001000

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

This table is available FREE on the Internet, Catalogue No. 97F0007XIE2001004.

This table is part of the topic "Language Composition of Canada," which presents 2001 Census data on the language composition of Canada, by mother tongue and other variables, as well as on languages spoken at home and knowledge of English, French and non-official languages. These data were collected for a sample comprising 20% of the Canadian population.

This data table can be found in the Topic Bundle: Language Composition of Canada, 2001 Census, Catalogue No. 97F0007XCB2001000

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

This table is available FREE on the Internet, Catalogue No. 97F0007XIE2001005.

This table is part of the topic "Language Composition of Canada," which presents 2001 Census data on the language composition of Canada, by mother tongue and other variables, as well as on languages spoken at home and knowledge of English, French and non-official languages. These data were collected for a sample comprising 20% of the Canadian population.

This data table can be found in the Topic Bundle: Language Composition of Canada, 2001 Census, Catalogue No. 97F0007XCB2001000

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

This table is available FREE on the Internet, Catalogue No. 97F0007XIE2001006.

This table is part of the topic "Language Composition of Canada," which presents 2001 Census data on the language composition of Canada, by mother tongue and other variables, as well as on languages spoken at home and knowledge of English, French and non-official languages. These data were collected for a sample comprising 20% of the Canadian population.

This data table can be found in the Topic Bundle: Language Composition of Canada, 2001 Census, Catalogue No. 97F0007XCB2001000

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

This table is available FREE on the Internet, Catalogue No. 97F0007XIE2001007.

This table is part of the topic "Language Composition of Canada," which presents 2001 Census data on the language composition of Canada, by mother tongue and other variables, as well as on languages spoken at home and knowledge of English, French and non-official languages. These data were collected for a sample comprising 20% of the Canadian population.

This data table can be found in the Topic Bundle: Language Composition of Canada, 2001 Census, Catalogue No. 97F0007XCB2001000

It is also possible to subscribe to all the day-of-release bundles. Refer to catalogue No. 97F0023XCB for more information.

This table is available FREE on the Internet, Catalogue No. 97F0007XIE2001008.

This table is part of the topic "Language Composition of Canada," which presents 2001 Census data on the language composition of Canada, by mother tongue and other variables, as well as on languages spoken at home and knowledge of English, French and non-official languages. These data were collected for a sample comprising 20% of the Canadian population.

This data table can be found in the Topic Bundle: Language Composition of Canada, 2001 Census, Catalogue No. 97F0007XCB2001000

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

This table is available FREE on the Internet, Catalogue No. 97F0007XIE2001009.

Retirement issues is an occasional digest and newsletter designed for executives concerned with questions closely linked to the social institution called "retirement" and for researchers whose work addresses these and related questions. Each issue provides a quick survey of selected research findings, key points in discussion papers on theoretical and policy issues, lists of upcoming conferences and other events in which retirement will be prominent, and topics of related research underway at universities and elsewhere.

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.