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- Stats in brief: 11-627-M2023036Description: From April 3rd to May 8th, 2023, Statistics Canada conducted the Canadian Survey on Business Conditions. The purpose of this survey is to collect information on businesses in Canada related to emerging issues. This infographic presents key results from this.Release date: 2023-05-29
- Articles and reports: 12-001-X202200100006Description:
In the last two decades, survey response rates have been steadily falling. In that context, it has become increasingly important for statistical agencies to develop and use methods that reduce the adverse effects of non-response on the accuracy of survey estimates. Follow-up of non-respondents may be an effective, albeit time and resource-intensive, remedy for non-response bias. We conducted a simulation study using real business survey data to shed some light on several questions about non-response follow-up. For instance, assuming a fixed non-response follow-up budget, what is the best way to select non-responding units to be followed up? How much effort should be dedicated to repeatedly following up non-respondents until a response is received? Should they all be followed up or a sample of them? If a sample is followed up, how should it be selected? We compared Monte Carlo relative biases and relative root mean square errors under different follow-up sampling designs, sample sizes and non-response scenarios. We also determined an expression for the minimum follow-up sample size required to expend the budget, on average, and showed that it maximizes the expected response rate. A main conclusion of our simulation experiment is that this sample size also appears to approximately minimize the bias and mean square error of the estimates.
Release date: 2022-06-21 - Classification: 12-604-XDescription:
The concordance table provides a link between data tables and the survey questions from the Survey of Innovation and Business Strategy (SIBS).
Release date: 2021-07-30 - 4. Comparison of the conditional bias and Kokic and Bell methods for Poisson and stratified samplingArticles and reports: 12-001-X201800254961Description:
In business surveys, it is common to collect economic variables with highly skewed distribution. In this context, winsorization is frequently used to address the problem of influential values. In stratified simple random sampling, there are two methods for selecting the thresholds involved in winsorization. This article comprises two parts. The first reviews the notations and the concept of a winsorization estimator. The second part details the two methods and extends them to the case of Poisson sampling, and then compares them on simulated data sets and on the labour cost and structure of earnings survey carried out by INSEE.
Release date: 2018-12-20 - 5. A method of determining the winsorization threshold, with an application to domain estimation ArchivedArticles and reports: 12-001-X201500114199Description:
In business surveys, it is not unusual to collect economic variables for which the distribution is highly skewed. In this context, winsorization is often used to treat the problem of influential values. This technique requires the determination of a constant that corresponds to the threshold above which large values are reduced. In this paper, we consider a method of determining the constant which involves minimizing the largest estimated conditional bias in the sample. In the context of domain estimation, we also propose a method of ensuring consistency between the domain-level winsorized estimates and the population-level winsorized estimate. The results of two simulation studies suggest that the proposed methods lead to winsorized estimators that have good bias and relative efficiency properties.
Release date: 2015-06-29 - Articles and reports: 12-001-X201400214097Description:
When monthly business surveys are not completely overlapping, there are two different estimators for the monthly growth rate of the turnover: (i) one that is based on the monthly estimated population totals and (ii) one that is purely based on enterprises observed on both occasions in the overlap of the corresponding surveys. The resulting estimates and variances might be quite different. This paper proposes an optimal composite estimator for the growth rate as well as the population totals.
Release date: 2014-12-19 - Articles and reports: 12-001-X201100111446Description:
Small area estimation based on linear mixed models can be inefficient when the underlying relationships are non-linear. In this paper we introduce SAE techniques for variables that can be modelled linearly following a non-linear transformation. In particular, we extend the model-based direct estimator of Chandra and Chambers (2005, 2009) to data that are consistent with a linear mixed model in the logarithmic scale, using model calibration to define appropriate weights for use in this estimator. Our results show that the resulting transformation-based estimator is both efficient and robust with respect to the distribution of the random effects in the model. An application to business survey data demonstrates the satisfactory performance of the method.
Release date: 2011-06-29 - 8. Small area estimation of the number of firms' recruits by using multivariate models for count data ArchivedArticles and reports: 12-001-X201000211379Description:
The number of people recruited by firms in Local Labour Market Areas provides an important indicator of the reorganisation of the local productive processes. In Italy, this parameter can be estimated using the information collected in the Excelsior survey, although it does not provide reliable estimates for the domains of interest. In this paper we propose a multivariate small area estimation approach for count data based on the Multivariate Poisson-Log Normal distribution. This approach will be used to estimate the number of firm recruits both replacing departing employees and filling new positions. In the small area estimation framework, it is customary to assume that sampling variances and covariances are known. However, both they and the direct point estimates suffer from instability. Due to the rare nature of the phenomenon we are analysing, counts in some domains are equal to zero, and this produces estimates of sampling error covariances equal to zero. To account for the extra variability due to the estimated sampling covariance matrix, and to deal with the problem of unreasonable estimated variances and covariances in some domains, we propose an "integrated" approach where we jointly model the parameters of interest and the sampling error covariance matrices. We suggest a solution based again on the Poisson-Log Normal distribution to smooth variances and covariances. The results we obtain are encouraging: the proposed small area estimation model shows a better fit when compared to the Multivariate Normal-Normal (MNN) small area model, and it allows for a non-negligible increase in efficiency.
Release date: 2010-12-21 - Articles and reports: 88F0006X2010004Description:
It is widely acknowledged that information and communications technologies (ICTs) have led to major innovations in business models and play an important role in firms' competitiveness and productivity.
Because of the lack of statistics, however, there have been few Canadian studies of the deployment of electronic business (e-business) processes within firms. E-commerce was one of the first online activities to attract attention, and we now know a little more about it, yet e-commerce is just one of the many business processes supported by Internet-based business networks. In Canada, very little information is available about how ICTs are used to manage operating processes such as the logistics functions of delivery and inventory management and the marketing and client relations functions.
In 2007, the Survey of Electronic Commerce and Technology collected data for the first time on the deployment of Internet-based systems to manage various e-business processes. The Survey also asked firms about the internal and external integration of the systems that manage those e-business processes.
Based on these new data, the study begins with a description of e-business adoption in Canada and then explores the benefits that firms see in doing business over the Internet. This study provides a clearer picture of how Canadian firms are deploying e-business processes, broken down by industry, size and type of e-business use.
Release date: 2010-07-08 - Articles and reports: 12-001-X201000111245Description:
Knowledge of the causes of measurement errors in business surveys is limited, even though such errors may compromise the accuracy of the micro data and economic indicators derived from them. This article, based on an empirical study with a focus from the business perspective, presents new research findings on the response process in business surveys. It proposes the Multidimensional Integral Business Survey Response (MIBSR) model as a tool for investigating the response process and explaining its outcomes, and as the foundation of any strategy dedicated to reducing and preventing measurement errors.
Release date: 2010-06-29
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- Stats in brief: 11-627-M2023036Description: From April 3rd to May 8th, 2023, Statistics Canada conducted the Canadian Survey on Business Conditions. The purpose of this survey is to collect information on businesses in Canada related to emerging issues. This infographic presents key results from this.Release date: 2023-05-29
- Articles and reports: 12-001-X202200100006Description:
In the last two decades, survey response rates have been steadily falling. In that context, it has become increasingly important for statistical agencies to develop and use methods that reduce the adverse effects of non-response on the accuracy of survey estimates. Follow-up of non-respondents may be an effective, albeit time and resource-intensive, remedy for non-response bias. We conducted a simulation study using real business survey data to shed some light on several questions about non-response follow-up. For instance, assuming a fixed non-response follow-up budget, what is the best way to select non-responding units to be followed up? How much effort should be dedicated to repeatedly following up non-respondents until a response is received? Should they all be followed up or a sample of them? If a sample is followed up, how should it be selected? We compared Monte Carlo relative biases and relative root mean square errors under different follow-up sampling designs, sample sizes and non-response scenarios. We also determined an expression for the minimum follow-up sample size required to expend the budget, on average, and showed that it maximizes the expected response rate. A main conclusion of our simulation experiment is that this sample size also appears to approximately minimize the bias and mean square error of the estimates.
Release date: 2022-06-21 - 3. Comparison of the conditional bias and Kokic and Bell methods for Poisson and stratified samplingArticles and reports: 12-001-X201800254961Description:
In business surveys, it is common to collect economic variables with highly skewed distribution. In this context, winsorization is frequently used to address the problem of influential values. In stratified simple random sampling, there are two methods for selecting the thresholds involved in winsorization. This article comprises two parts. The first reviews the notations and the concept of a winsorization estimator. The second part details the two methods and extends them to the case of Poisson sampling, and then compares them on simulated data sets and on the labour cost and structure of earnings survey carried out by INSEE.
Release date: 2018-12-20 - 4. A method of determining the winsorization threshold, with an application to domain estimation ArchivedArticles and reports: 12-001-X201500114199Description:
In business surveys, it is not unusual to collect economic variables for which the distribution is highly skewed. In this context, winsorization is often used to treat the problem of influential values. This technique requires the determination of a constant that corresponds to the threshold above which large values are reduced. In this paper, we consider a method of determining the constant which involves minimizing the largest estimated conditional bias in the sample. In the context of domain estimation, we also propose a method of ensuring consistency between the domain-level winsorized estimates and the population-level winsorized estimate. The results of two simulation studies suggest that the proposed methods lead to winsorized estimators that have good bias and relative efficiency properties.
Release date: 2015-06-29 - Articles and reports: 12-001-X201400214097Description:
When monthly business surveys are not completely overlapping, there are two different estimators for the monthly growth rate of the turnover: (i) one that is based on the monthly estimated population totals and (ii) one that is purely based on enterprises observed on both occasions in the overlap of the corresponding surveys. The resulting estimates and variances might be quite different. This paper proposes an optimal composite estimator for the growth rate as well as the population totals.
Release date: 2014-12-19 - Articles and reports: 12-001-X201100111446Description:
Small area estimation based on linear mixed models can be inefficient when the underlying relationships are non-linear. In this paper we introduce SAE techniques for variables that can be modelled linearly following a non-linear transformation. In particular, we extend the model-based direct estimator of Chandra and Chambers (2005, 2009) to data that are consistent with a linear mixed model in the logarithmic scale, using model calibration to define appropriate weights for use in this estimator. Our results show that the resulting transformation-based estimator is both efficient and robust with respect to the distribution of the random effects in the model. An application to business survey data demonstrates the satisfactory performance of the method.
Release date: 2011-06-29 - 7. Small area estimation of the number of firms' recruits by using multivariate models for count data ArchivedArticles and reports: 12-001-X201000211379Description:
The number of people recruited by firms in Local Labour Market Areas provides an important indicator of the reorganisation of the local productive processes. In Italy, this parameter can be estimated using the information collected in the Excelsior survey, although it does not provide reliable estimates for the domains of interest. In this paper we propose a multivariate small area estimation approach for count data based on the Multivariate Poisson-Log Normal distribution. This approach will be used to estimate the number of firm recruits both replacing departing employees and filling new positions. In the small area estimation framework, it is customary to assume that sampling variances and covariances are known. However, both they and the direct point estimates suffer from instability. Due to the rare nature of the phenomenon we are analysing, counts in some domains are equal to zero, and this produces estimates of sampling error covariances equal to zero. To account for the extra variability due to the estimated sampling covariance matrix, and to deal with the problem of unreasonable estimated variances and covariances in some domains, we propose an "integrated" approach where we jointly model the parameters of interest and the sampling error covariance matrices. We suggest a solution based again on the Poisson-Log Normal distribution to smooth variances and covariances. The results we obtain are encouraging: the proposed small area estimation model shows a better fit when compared to the Multivariate Normal-Normal (MNN) small area model, and it allows for a non-negligible increase in efficiency.
Release date: 2010-12-21 - Articles and reports: 88F0006X2010004Description:
It is widely acknowledged that information and communications technologies (ICTs) have led to major innovations in business models and play an important role in firms' competitiveness and productivity.
Because of the lack of statistics, however, there have been few Canadian studies of the deployment of electronic business (e-business) processes within firms. E-commerce was one of the first online activities to attract attention, and we now know a little more about it, yet e-commerce is just one of the many business processes supported by Internet-based business networks. In Canada, very little information is available about how ICTs are used to manage operating processes such as the logistics functions of delivery and inventory management and the marketing and client relations functions.
In 2007, the Survey of Electronic Commerce and Technology collected data for the first time on the deployment of Internet-based systems to manage various e-business processes. The Survey also asked firms about the internal and external integration of the systems that manage those e-business processes.
Based on these new data, the study begins with a description of e-business adoption in Canada and then explores the benefits that firms see in doing business over the Internet. This study provides a clearer picture of how Canadian firms are deploying e-business processes, broken down by industry, size and type of e-business use.
Release date: 2010-07-08 - Articles and reports: 12-001-X201000111245Description:
Knowledge of the causes of measurement errors in business surveys is limited, even though such errors may compromise the accuracy of the micro data and economic indicators derived from them. This article, based on an empirical study with a focus from the business perspective, presents new research findings on the response process in business surveys. It proposes the Multidimensional Integral Business Survey Response (MIBSR) model as a tool for investigating the response process and explaining its outcomes, and as the foundation of any strategy dedicated to reducing and preventing measurement errors.
Release date: 2010-06-29 - 10. Searching for the silver bullet: Are EIA's current tools adequate for designing and testing EIA business surveys? ArchivedArticles and reports: 11-522-X200800010947Description:
This paper addresses the efforts of the U.S. Energy Information Administration to design, test and implement new and substantially redesigned surveys. The need to change EIA's surveys has become increasingly important, as U.S. energy industries have moved from highly regulated to deregulated business. This has substantially affected both their ability and willingness to report data. The paper focuses on how EIA has deployed current tools for designing and testing surveys and the reasons that these methods have not always yielded the desired results. It suggests some new tools and methods that we would like to try to improve the quality of our data.
Release date: 2009-12-03
Reference (4)
Reference (4) ((4 results))
- Classification: 12-604-XDescription:
The concordance table provides a link between data tables and the survey questions from the Survey of Innovation and Business Strategy (SIBS).
Release date: 2021-07-30 - Surveys and statistical programs – Documentation: 68-514-XDescription:
Statistics Canada's approach to gathering and disseminating economic data has developed over several decades into a highly integrated system for collection and estimation that feeds the framework of the Canadian System of National Accounts.
The key to this approach was creation of the Unified Enterprise Survey, the goal of which was to improve the consistency, coherence, breadth and depth of business survey data.
The UES did so by bringing many of Statistics Canada's individual annual business surveys under a common framework. This framework included a single survey frame, a sample design framework, conceptual harmonization of survey content, means of using relevant administrative data, common data collection, processing and analysis tools, and a common data warehouse.
Release date: 2006-11-20 - Surveys and statistical programs – Documentation: 11-522-X20010016229Description:
This paper discusses the approach that Statistics Canada has taken to improve the quality of annual business surveys through their integration in the Unified Enterprise Survey (UES). The primary objective of the UES is to measure the final annual sales of goods and services accurately by province, in sufficient detail and in a timely manner.
This paper describes the methodological approaches that the UES has used to improve financial and commodity data quality in four broad areas. These include improved coherence of the data collected from different levels of the enterprise, better coverage of industries, better depth of information (in the sense of more content detail and estimates for more detailed domains) and better consistency of the concepts and methods across industries.
The approach, in achieving quality, has been to (a) establish a base measure of the quality of the business survey program prior to the UES, (b) measure the annual data quality of the UES, and (c) carry out specific studies to better understand the quality of UES data and methods.
Release date: 2002-09-12 - 4. Statistics Canada's Business Surveys ArchivedSurveys and statistical programs – Documentation: 61F0019X19990025579Geography: CanadaDescription:
The Unified Enterprise Survey (UES) incorporates several annual business surveys into an integrated survey framework. It aims to ensure Statistics Canada receives consistent and integrated data from many types and sizes of businesses, with enough detail to produce accurate provincial statistics. This year, 17 industry surveys are included in the UES, as well as two cross-industry surveys of large enterprises.
Release date: 1999-06-25
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