Keyword search

This paper highlights the Canadian Tourism Satellite Account (CTSA) developed by Statistics Canada. The CTSA provides an economic measure of the importance of tourism in terms of expenditures, Gross Domestic Product and employment for Canada. It permits a comparison of tourism with other industries within Canada since the concepts and methods used are based on the framework of the Canadian System of National Accounts. The study revealed that tourism is an important part of Canada's well diversified economy. This paper presents the results of the CTSA for reference year 2004.

This study was prepared by staff of the Research and Development Projects and Analysis Section, Income and Expenditure Accounts Division, Statistics Canada. The study was funded by the Canadian Tourism Commission.

Surveys are frequently required to produce estimates for subpopulations, sometimes for a single subpopulation and sometimes for several subpopulations in addition to the total population. When membership of a rare subpopulation (or domain) can be determined from the sampling frame, selecting the required domain sample size is relatively straightforward. In this case the main issue is the extent of oversampling to employ when survey estimates are required for several domains and for the total population. Sampling and oversampling rare domains whose members cannot be identified in advance present a major challenge. A variety of methods has been used in this situation. In addition to large-scale screening, these methods include disproportionate stratified sampling, two-phase sampling, the use of multiple frames, multiplicity sampling, panel surveys, and the use of multi-purpose surveys. This paper illustrates the application of these methods in a range of social surveys.

Randomized response strategies, which have originally been developed as statistical methods to reduce nonresponse as well as untruthful answering, can also be applied in the field of statistical disclosure control for public use microdata files. In this paper a standardization of randomized response techniques for the estimation of proportions of identifying or sensitive attributes is presented. The statistical properties of the standardized estimator are derived for general probability sampling. In order to analyse the effect of different choices of the method's implicit "design parameters" on the performance of the estimator we have to include measures of privacy protection in our considerations. These yield variance-optimum design parameters given a certain level of privacy protection. To this end the variables have to be classified into different categories of sensitivity. A real-data example applies the technique in a survey on academic cheating behaviour.

We examine overcoming the overestimation in using generalized weight share method (GWSM) caused by link nonresponse in indirect sampling. A few adjustment methods incorporating link nonresponse in using GWSM have been constructed for situations both with and without the availability of auxiliary variables. A simulation study on a longitudinal survey is presented using some of the adjustment methods we recommend. The simulation results show that these adjusted GWSMs perform well in reducing both estimation bias and variance. The advancement in bias reduction is significant.

Propensity weighting is a procedure to adjust for unit nonresponse in surveys. A form of implementing this procedure consists of dividing the sampling weights by estimates of the probabilities that the sampled units respond to the survey. Typically, these estimates are obtained by fitting parametric models, such as logistic regression. The resulting adjusted estimators may become biased when the specified parametric models are incorrect. To avoid misspecifying such a model, we consider nonparametric estimation of the response probabilities by local polynomial regression. We study the asymptotic properties of the resulting estimator under quasi-randomization. The practical behavior of the proposed nonresponse adjustment approach is evaluated on NHANES data.

In this paper a multivariate structural time series model is described that accounts for the panel design of the Dutch Labour Force Survey and is applied to estimate monthly unemployment rates. Compared to the generalized regression estimator, this approach results in a substantial increase of the accuracy due to a reduction of the standard error and the explicit modelling of the bias between the subsequent waves.

Estimation of small area (or domain) compositions may suffer from informative missing data, if the probability of missing varies across the categories of interest as well as the small areas. We develop a double mixed modeling approach that combines a random effects mixed model for the underlying complete data with a random effects mixed model of the differential missing-data mechanism. The effect of sampling design can be incorporated through a quasi-likelihood sampling model. The associated conditional mean squared error of prediction is approximated in terms of a three-part decomposition, corresponding to a naive prediction variance, a positive correction that accounts for the hypothetical parameter estimation uncertainty based on the latent complete data, and another positive correction for the extra variation due to the missing data. We illustrate our approach with an application to the estimation of Municipality household compositions based on the Norwegian register household data, which suffer from informative under-registration of the dwelling identity number.

This paper proposes an approach for small area prediction based on data obtained from periodic surveys and censuses. We apply our approach to obtain population predictions for the municipalities not sampled in the Brazilian annual Household Survey (PNAD), as well as to increase the precision of the design-based estimates obtained for the sampled municipalities. In addition to the data provided by the PNAD, we use census demographic data from 1991 and 2000, as well as a complete population count conducted in 1996. Hierarchically non-structured and spatially structured growth models that gain strength from all the sampled municipalities are proposed and compared.

Business surveys often use a one-stage stratified simple random sampling without replacement design with some certainty strata. Although weight adjustment is typically applied for unit nonresponse, the variability due to nonresponse may be omitted in practice when estimating variances. This is problematic especially when there are certainty strata. We derive some variance estimators that are consistent when the number of sampled units in each weighting cell is large, using the jackknife, linearization, and modified jackknife methods. The derived variance estimators are first applied to empirical data from the Annual Capital Expenditures Survey conducted by the U.S. Census Bureau and are then examined in a simulation study.

In large scaled sample surveys it is common practice to employ stratified multistage designs where units are selected using simple random sampling without replacement at each stage. Variance estimation for these types of designs can be quite cumbersome to implement, particularly for non-linear estimators. Various bootstrap methods for variance estimation have been proposed, but most of these are restricted to single-stage designs or two-stage cluster designs. An extension of the rescaled bootstrap method (Rao and Wu 1988) to stratified multistage designs is proposed which can easily be extended to any number of stages. The proposed method is suitable for a wide range of reweighting techniques, including the general class of calibration estimators. A Monte Carlo simulation study was conducted to examine the performance of the proposed multistage rescaled bootstrap variance estimator.

This product is a series of profiles for a number of census metropolitan areas, census agglomerations and communities across Canada with a large Aboriginal population, either in numbers or share of the area's total population. The series aims to present a demographic and socio-economic profile of the total Aboriginal population living in these areas. Demographic Data as well as information on living arrangements of children, education, labour, income, mobility, housing, and health are highlighted. While most of the focus is on adults, there is also limited information provided on children. Data showing comparisons between Aboriginal groups are provided for selected variables, as are comparisons with the non-Aboriginal population. Findings are based on the 2006 Census and the 2006 Aboriginal Peoples Survey.

This product is a series of profiles for a number of census metropolitan areas, census agglomerations and communities across Canada with a large Aboriginal population, either in numbers or share of the area's total population. The series aims to present a demographic and socio-economic profile of the total Aboriginal population living in these areas. Demographic Data as well as information on living arrangements of children, education, labour, income, mobility, housing, and health are highlighted. While most of the focus is on adults, there is also limited information provided on children. Data showing comparisons between Aboriginal groups are provided for selected variables, as are comparisons with the non-Aboriginal population. Findings are based on the 2006 Census and the 2006 Aboriginal Peoples Survey.

This product is a series of profiles for a number of census metropolitan areas, census agglomerations and communities across Canada with a large Aboriginal population, either in numbers or share of the area's total population. The series aims to present a demographic and socio-economic profile of the total Aboriginal population living in these areas. Demographic Data as well as information on living arrangements of children, education, labour, income, mobility, housing, and health are highlighted. While most of the focus is on adults, there is also limited information provided on children. Data showing comparisons between Aboriginal groups are provided for selected variables, as are comparisons with the non-Aboriginal population. Findings are based on the 2006 Census and the 2006 Aboriginal Peoples Survey.

This product is a series of profiles for a number of census metropolitan areas, census agglomerations and communities across Canada with a large Aboriginal population, either in numbers or share of the area's total population. The series aims to present a demographic and socio-economic profile of the total Aboriginal population living in these areas. Demographic Data as well as information on living arrangements of children, education, labour, income, mobility, housing, and health are highlighted. While most of the focus is on adults, there is also limited information provided on children. Data showing comparisons between Aboriginal groups are provided for selected variables, as are comparisons with the non-Aboriginal population. Findings are based on the 2006 Census and the 2006 Aboriginal Peoples Survey.

This product is a series of profiles for a number of census metropolitan areas, census agglomerations and communities across Canada with a large Aboriginal population, either in numbers or share of the area's total population. The series aims to present a demographic and socio-economic profile of the total Aboriginal population living in these areas. Demographic Data as well as information on living arrangements of children, education, labour, income, mobility, housing, and health are highlighted. While most of the focus is on adults, there is also limited information provided on children. Data showing comparisons between Aboriginal groups are provided for selected variables, as are comparisons with the non-Aboriginal population. Findings are based on the 2006 Census and the 2006 Aboriginal Peoples Survey.

The Lower Mainland ecoregion profile is the first in an upcoming series of ecoregion profiles. The information presented includes a brief description of the physical setting, a snapshot of land cover and use as well as selected statistics on the changing socio-economy in the region. This ecoregion will be the site for many of the activities associated with the 2010 Vancouver Winter Olympics.

This publication provides quarterly information on operational and financial variables related to the scheduled and charter operations of all Canadian-licensed air carriers classified into reporting levels I and II. Operational data (passengers, passenger-kilometres, goods carried, goods tonne-kilometres, etc.) and financial data (operating revenues, operating expenses, employment expenses) are presented. This publication also includes data highlights and some financial performance indicators and productivity measures.

The air fare data included in this publication relate to the scheduled operations of major Canadian air carriers. This publication provides information on average fares by sector and fare type group and average domestic fares for ten selected cities of enplanement. It also provides information on the distribution of passengers and passenger-kilometres by sector and fare type group. A series of air fare indexes by sector and fare type group is also presented. In addition to annual data, this publication also presents quarterly data. It also includes data highlights and a brief analysis.

This publication provides monthly information on key operational variables related to the scheduled and charter operations of Air Canada and WestJet. Operational data include passengers, passenger-kilometres, available seat-kilometres, goods carried, goods tonne-kilometres, hours flown and fuel. In addition to monthly data, this publication also presents annual data. Charts and data highlights supplement the tables.

This report provides trends on public school enrolments, educators and expenditures. It uses figures provided by provincial and territorial departments of education on public elementary and secondary schools.

The use of Computer Audio-Recorded Interviewing (CARI) as a tool to identify interview falsification is quickly growing in survey research (Biemer, 2000, 2003; Thissen, 2007). Similarly, survey researchers are starting to expand the usefulness of CARI by combining recordings with coding to address data quality (Herget, 2001; Hansen, 2005; McGee, 2007). This paper presents results from a study included as part of the establishment-based National Center for Health Statistics' National Home and Hospice Care Survey (NHHCS) which used CARI behavior coding and CARI-specific paradata to: 1) identify and correct problematic interviewer behavior or question issues early in the data collection period before either negatively impact data quality, and; 2) identify ways to diminish measurement error in future implementations of the NHHCS. During the first 9 weeks of the 30-week field period, CARI recorded a subset of questions from the NHHCS application for all interviewers. Recordings were linked with the interview application and output and then coded in one of two modes: Code by Interviewer or Code by Question. The Code by Interviewer method provided visibility into problems specific to an interviewer as well as more generalized problems potentially applicable to all interviewers. The Code by Question method yielded data that spoke to understandability of the questions and other response problems. In this mode, coders coded multiple implementations of the same question across multiple interviewers. Using the Code by Question approach, researchers identified issues with three key survey questions in the first few weeks of data collection and provided guidance to interviewers in how to handle those questions as data collection continued. Results from coding the audio recordings (which were linked with the survey application and output) will inform question wording and interviewer training in the next implementation of the NHHCS, and guide future enhancement of CARI and the coding system.

Business surveys differ from surveys of populations of individual persons or households in many respects. Two of the most important differences are (a) that respondents in business surveys do not answer questions about characteristics of themselves (such as their experiences, behaviours, attitudes and feelings) but about characteristics of organizations (such as their size, revenues, policies, and strategies) and (b) that they answer these questions as an informant for that organization. Academic business surveys differ from other business surveys, such as of national statistical agencies, in many respects as well. The one most important difference is that academic business surveys usually do not aim at generating descriptive statistics but at testing hypotheses, i.e. relations between variables. Response rates in academic business surveys are very low, which implies a huge risk of non-response bias. Usually no attempt is made to assess the extent of non-response bias and published survey results might, therefore, not be a correct reflection of actual relations within the population, which in return increases the likelihood that the reported test result is not correct.

This paper provides an analysis of how (the risk of) non-response bias is discussed in research papers published in top management journals. It demonstrates that non-response bias is not assessed to a sufficient degree and that, if attempted at all, correction of non-response bias is difficult or very costly in practice. Three approaches to dealing with this problem are presented and discussed:(a) obtaining data by other means than questionnaires;(b) conducting surveys of very small populations; and(c) conducting surveys of very small samples.

It will be discussed why these approaches are appropriate means of testing hypotheses in populations. Trade-offs regarding the selection of an approach will be discussed as well.

Telephone Data Entry (TDE) is a system by which survey respondents can return their data to the Office for National Statistics (ONS) using the keypad on their telephone and currently accounts for approximately 12% of total responses to ONS business surveys. ONS is currently increasing the number of surveys which use TDE as the primary mode of response and this paper gives an overview of the redevelopment project covering; the redevelopment of the paper questionnaire, enhancements made to the TDE system and the results from piloting these changes. Improvements to the quality of the data received and increased response via TDE as a result of these developments suggest that data quality improvements and cost savings are possible as a result of promoting TDE as the primary mode of response to short term surveys.

The Unified Enterprise Survey (UES) at Statistics Canada is an annual business survey that unifies more than 60 surveys from different industries. Two types of collection follow-up score functions are currently used in the UES data collection. The objective of using a score function is to maximize the economically weighted response rates of the survey in terms of the primary variables of interest, under the constraint of a limited follow-up budget. Since the two types of score functions are based on different methodologies, they could have different impacts on the final estimates.

This study generally compares the two types of score functions based on the collection data obtained from the two recent years. For comparison purposes, this study applies each score function method to the same data respectively and computes various estimates of the published financial and commodity variables, their deviation from the true pseudo value and their mean square deviation, based on each method. These estimates of deviation and mean square deviation based on each method are then used to measure the impact of each score function on the final estimates of the financial and commodity variables.

Non-response is inevitable in any survey, despite all the effort put into reducing it at the various stages of the survey. In particular, non-response can cause bias in the estimates. In addition, non-response is an especially serious problem in longitudinal studies because the sample shrinks over time. France's ELFE (Étude Longitudinale Française depuis l'Enfance) is a project that aims to track 20,000 children from birth to adulthood using a multidisciplinary approach. This paper is based on the results of the initial pilot studies conducted in 2007 to test the survey's feasibility and acceptance. The participation rates are presented (response rate, non-response factors) along with a preliminary description of the non-response treatment methods being considered.

Increasingly, children of all ages are becoming respondents in survey interviews. While juveniles are considered to be reliable respondents for many topics and survey settings it is unclear to what extend younger children provide reliable information in a face-to-face interview. In this paper we will report results from a study using video captures of 205 face-to-face interviews with children aged 8 through 14. The interviews have been coded using behavior codes on a question by question level which provides behavior-related indicators regarding the question-answer process. In addition, standard tests of cognitive resources have been conducted. Using visible and audible problems in the respondent behavior, we are able to assess the impact of the children's cognitive resources on respondent behaviors. Results suggest that girls and boys differ fundamentally in the cognitive mechanisms leading to problematic respondent behaviors.

The ÉLDEQ initiated a special data gathering project in March 2008 with the collection of biological materials from 1,973 families. During a typical visit, a nurse collects a blood or saliva sample from the selected child, makes a series of measurements (anthropometry, pulse rate and blood pressure) and administers questionnaires. Planned and supervised by the Institut de la Statistique du Québec (ISQ) and the Université de Montréal, the study is being conducted in cooperation with two private firms and a number of hospitals. This article examines the choice of collection methods, the division of effort among the various players, the sequence of communications and contacts with respondents, the tracing of families who are not contacted, and follow-up on the biological samples. Preliminary field results are also presented.

BackgroundThere has been a reluctance to conduct child related research studies with, rather than on children in the African continent. Several studies have embarked on this method, however, ethical and privacy challenges still prevail. The Amajuba Child Health and Wellbeing Research Project is a longitudinal study that was conducted with 725 children aged between 9 and 15 years old in KwaZulu Natal in South Africa and also faced the same challenges.

MethodsFocus group discussions and self administered questionnaires were used as data collection techniques for ACHWRP. One of ACHWRP's objectives is to document the consequences of parental or caregiver death on health and well-being of orphans in Amajuba District of KwaZulu Natal. Ethical clearance was received from two ethical review boards.

Lessons learnedEthical challenges included problems of coercion for participation, gatekeeper's and partner's roles, getting consent and assent, recruitment and referral system.Privacy challenges included data collection techniques, curiosity and destruction by members of the family during an interview, the setting where interviews are conducted, logistical issues and the method of recruitment's potential to compromise confidentiality.Resolutions: Detailed consent and assent forms with all relevant information are necessary. Careful selection of partnerships is crucial. Use of a venue that is far from the community is necessary, but in the process making sure that the participants are covered with regards to the expenses of travelling to the venue.

ConclusionConducting research with children entails investing more time and attention to the planning stage of the study.

Statistics Netherlands (SN) has been using electronic questionnaires for Business surveys since the early nineties. Some years ago SN decided to invest in a large scale use of electronic questionnaires. The big yearly production survey of about 80 000 forms, divided over many different economical activity areas, was redesigned using a meta database driven approach. The resulting system is able to generate non-intelligent personalized PDF forms and intelligent personalized Blaise forms. The Blaise forms are used by a new tool in the Blaise system which can be downloaded by the respondents from the SN web site to run the questionnaire off-line. Essential to the system is the SN house style for paper and electronic forms. The flexibility of the new tool offered the questionnaire designers the possibility to implement a user friendly form according to this house style.

Part of the implementation is an audit trail that offers insight in the way respondents operate the questionnaire program. The entered data including the audit trail can be transferred via encrypted e-mail or through the internet to SN. The paper will give an outline of the overall system architecture and the role of Blaise in the system. It will also describe the results of using the system for several years now and some results of the analysis of the audit trail.

Surveys that employ simultaneous web, CATI, and paper modes (or any two-way subset) are increasingly common. Mathematica Policy Research, Inc (MPR) has deployed several of these types of surveys in Blaise. This paper reviews MPR's experiences and issues with these efforts by addressing instrumentation, survey management, and other considerations. The paper emphasizes the electronic implementation of these surveys and covers topics that emerge solely from the surveys' multimode nature; that is, material that goes beyond the implementation of a single-mode survey.

This report presents the results of the 3rd Consensus Conference on Health Indicators that was convened in March 2009, including information that was presented at the conference, a summary of the consultation process leading up to the event, and the priority health areas deemed most important for future indicator development work.

The conference marked the 10th anniversary of the Health Indicators project, a collaboration between Statistics Canada and Canadian Institute for Health Information (CIHI). The goal of the project is to provide health regions, health care providers and the public in general with reliable and comparable data on the health of Canadians and to assist stakeholders and decision makers in the use and interpretation of the indicator data.

This guide presents information of interest to users of data from the Survey of Household Spending, which gathers information on the spending habits, dwelling characteristics and household equipment of Canadian households. The survey covers private households in the 10 provinces. (The territories are surveyed every second year, starting in 1999.)

This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. One section describes the various statistics that can be created using expenditure data (e.g., budget share, market share, aggregates and medians).

With the latest release of the bilateral Purchasing Power Parities estimates for Canada and the U.S., an improved projection methodology for the non-benchmark year has been employed. This note summarizes the new methodology and its rationale.

Statistics Canada produces monthly import and export merchandise trade price indexes. For the majority of these prices, Statistics Canada uses a variety of proxy measures to derive the price index in lieu of collecting observed import and export prices. The ability of these proxy measures to reflect international trade price movements during times of exchange rate volatility is limited. For this reason, the constant dollar trade estimates derived using these proxy price indexes have been refined with constant dollar adjustments following the appreciation of the Canadian exchange rate beginning at the end of 2002. This paper explains the rational and methodology behind these adjustments, as well as the impact on published trade and GDP estimates.

The Strengths and Difficulties Questionnaire (SDQ) is a parent-reported instrument designed to provide information on children's behaviours and relationships. The SDQ consists of 25 items which are grouped into five subscales: (1) pro-social, (2) inattention-hyperactivity, (3) emotional symptoms, (4) conduct problems, and (5) peer problems. The SDQ was used to provide information on children aged 2 to 5 years in the 2006 Aboriginal Children's Survey (ACS). Though validated on general populations, the constructs of the SDQ have not been validated for off-reserve First Nations, Métis and Inuit children in Canada. The first objective of this evaluation is to examine if the five subscales of the SDQ demonstrate construct validity and reliability for off-reserve First Nations, Métis and Inuit children. The second objective is to examine if an alternative set of subscales, using the 25 SDQ items, may be more valid and reliable for off-reserve First Nations, Métis and Inuit children.

With the release of the Financial Flow Accounts (FFA) on December 1st and the National Balance Sheet Accounts (NBSA) on December 14th, the Income and Expenditure Accounts Division will be publishing revised sector and category detail on CANSIM.

This report describes sampling and weighting procedures used in the 2006 Census. It reviews the history of these procedures in Canadian censuses, provides operational and theoretical justifications for them, and presents the results of the evaluation studies of these procedures.

Government financial reports are based on the organisation of each individual government and on their accounting and reporting practices. There is therefore little uniformity from one level of government to another or from one province to another. The Financial Management System (FMS) is an analytical framework designed to produce statistical series that are both consistent and compatible.

Written in plain English, the Financial Management System (FMS) manual was designed to assist you in better understanding the framework of the Financial Management System (FMS). It will explain the strengths and caveats of the FMS and will provide you with clear explanations of what is included in each revenue source and each expenditure function.

In 2008, Statistics Canada conducted the first Agricultural Water Use Survey. This pilot survey is part of the Canadian Environment Sustainability Indicators initiative and collects information on volumes of water used for irrigation, irrigated areas, irrigation practices and the quality of water used for agricultural purposes. This technical paper describes the methodology used for the pilot survey and includes recommendations for future cycles of the survey. The validation process seems to indicate that the method used to estimate the volumes of water used and the irrigated areas calculated underestimates the results. The report gives recommendations to minimize this bias in the next iterations of the survey. First, it is recommended to simplify the level of information collected by the survey; to review the sampling methodology; and to examine other means of collecting information on volumes of water used for irrigation. This pilot version of the survey remains a reliable source for consistent data on agricultural water use.

In this paper, we present the methodology developed by Statistics Canada to calculate the average annual water yield for Canada. Water yield, for the purposes of this paper, is defined as the amount of freshwater derived from unregulated flow (m³ s^-1) measurements for a given geographic area over a defined period of time. The methodology is applied to the 1971 to 2000 time period.

This research was conducted to fill data gaps in Statistics Canada's water statistics program. These gaps exist because estimates of freshwater flow for Canada have not been calculated regularly and have been produced using a variety of methods that do not necessarily generate comparable results. The methodology developed in this study produced results that are coherent through space and time. These results will be used in the future to investigate changes in water yield on a more disaggregated basis.

To achieve the water yield estimate a database of natural streamflow observations from 1971 to 2000 was compiled. The streamflow values were then converted to a runoff depth and interpolated using ordinary kriging to produce spatial estimates of runoff. The spatial estimates were then scaled to create a National estimate of water yield as a thirty-year average. The methodology and results were then validated using a stability analysis and several techniques involving uncertainty. The result of the methodology indicates that the thirty-year average water yield for Canada is 3435 km³.