Wholesale Services Price Index (WSPI)
Detailed information for first quarter 2010
The purpose of this survey is to collect and compile data to measure the monthly change in the movement of the price of wholesale services. These prices are combined and chained to form a price index. The estimates are produced on a quarterly basis.
Data release - November 17, 2010
The purpose of this survey is to collect and compile data to measure the monthly change in the movement of the price of wholesale services. These prices are combined and chained to form a price index. The estimates are produced on a quarterly basis. These price data are combined to estimate a price index for the wholesale services sector that can be joined with other business service indexes to provide better estimates of real output and productivity, monitor inflation and feed an important research agenda at Statistics Canada.
These indexes are a part of the Services Producer Price Index program (SPPI) at Statistics Canada.
The SPPI program develops and produces price indexes for a wide range of business service categories. This initiative fills an important data gap in the area of economic statistics and has resulted in a more comprehensive set of service price indexes. It also allows Statistics Canada to produce more accurate estimates of real value added of the Gross Domestic Product and changes in productivity.
Reference period: The time period for which the WSPI equals 100; currently this is the year 2008.
- Prices and price indexes
- Retail and wholesale
- Service price indexes
Data sources and methodology
The target population consists of all statistical establishments on the Business Register (BR) primarily engaged in wholesaling and that are classified to NAICS 41 - Wholesale Trade under the North American Industry Classification System (NAICS), excluding Wholesale Agents and Brokers.
Pricing methodologies and questionnaire design were researched and based on internationally accepted practices and improved through consultation and collaboration with industry experts and the Questionnaire Design and Research Center at Statistics Canada.
This is a sample survey with a cross-sectional design and a longitudinal follow-up.
The frame is part of Statistics Canada's Business Register classified to the wholesale sector (NAICS=41). The population is stratified by 5-digit NAICS and by size based on revenue. The sample is allocated to strata by revenue and selected based on probability proportional to size using Sequential Poisson sampling. The sampling unit is establishment.
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
Data are collected from respondents through questionnaire mail out, while telephone communication (Computer Assisted Telephone Interviewing) is used for non-response and data follow-up. Several follow-up contacts can be made including sending out a reminder fax or letter in order to collect data.
View the Questionnaire(s) and reporting guide(s) .
Error detection is conducted both at the time of collection and during post collection processing, using a set of systematized error detection procedures to identify outliers and possible reporting anomalies. Records that fail these edits are reviewed for editing and correction when necessary or edit failure may trigger a follow-up with the respondent.
Non-response or missing prices are imputed using the averages of designated cells from within the same strata.
Estimates are produced by calculating a weighted average of price relatives by industry which are chained together to form an index series. The Services Producer Price Index for Wholesale Services is a national index that uses establishment revenues as its weighting source.
The survey methodology was designed to control for errors and to reduce their potential impact on estimates. The data is subject to collection and processing validations on key variables and most non-essential data. Analysis at the index level is also performed at various stages of aggregation. Qualitative assessment is done using an internationally developed framework for services producer price indexes that considers program elements such as the type of price being used, timeliness and relevance.
Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.
In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada Generalized Disclosure Control System (G-Confid). G-Confid is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.
Revisions and seasonal adjustment
The data are not seasonally adjusted, but are subject to an annual revision.
The survey achieves about a 70% response rate and uses a survey methodology designed to control errors and reduce their effect on estimates. However, the survey results remain subject to sampling and non-sampling error. Sampling error results when observations are made only on a sample and not on the entire population, while all other errors arising from the various survey phases are referred to as non-sampling errors. For example, these types of errors can occur when a respondent provides incorrect information or does not answer certain questions; when a unit in the target population is omitted or covered more than once; when a unit that is out of scope to the survey is included by mistake or when coding or capture errors occur.
The non-response portion of the sample is imputed to achieve an effective 100% coverage. Based on the observed weighted response rates, large units are more likely to be non-respondents.