Wholesale Services Price Index (WSPI)
Detailed information for second quarter 2023
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 - September 22, 2023
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 2020.
Collection period: Collection takes place during the quarter following the reference quarter.
- 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 Business-to-business electronic markets, agents and brokers.
Pricing methodologies and questionnaire design were researched and based on internationally accepted practice. The Wholesale Price Report (survey questionnaire) was developed and tested through consultation and collaboration with merchant wholesalers, industry experts and the Questionnaire Design and Research Centre at Statistics Canada.
The questionnaire, last revised in 2021, is designed to collect information on, among other variables, the average monthly purchase price (amount paid for the acquisition of a given product) and the average monthly selling price (amount received for selling the same product), excluding taxes. Respondents are asked to report (up to) six top-selling products from product categories pre-selected based on product wholesale revenue information collected by the Annual Wholesale Trade Survey (AWTS).
This is a sample survey with a longitudinal design.
The frame is part of Statistics Canada's Business Register classified to the wholesale sector (NAICS=41, excluding NAICS=419).
The sampling unit is establishment. The establishment, as a statistical unit, is defined as the most homogeneous unit of production for which the business maintains accounting records from which it is possible to assemble all the data elements required to compile the full structure of the gross value of production (total sales or shipments, and inventories), the cost of materials and services, and labour and capital used in production.
The population is stratified by 5-digit NAICS. In order to maximize the usage of AWTS product revenue information while minimizing response burden, the sample is selected to achieve a 60% overlap with AWTS sample. As such, each 5-digit NAICS is further stratified into AWTS vs. non-AWTS groups. Within each 5-digit NAICS × (AWTS vs non-AWTS) group, the largest establishments are selected into the sample with a probability of 100% ("take-all" method). The remaining establishments are selected according to the "take-some" method, where the probability of selection was proportional to the revenue of the establishment for the reference year.
SAMPLING AND SUB-SAMPLING
The sample is allocated to strata by revenue and selected based on probability proportional to size using Sequential Poisson sampling.
Establishments selected for the WSPI survey typically report a maximum of six products from product categories that generate the most wholesale revenue for their business. These product categories were chosen based on product wholesale revenue information reported in the AWTS survey or if this information is not available, on typical business activities conducted in their industry. Product classification is based on the North American Product Classification System (NAPCS) version 2017. Products from each category are chosen based on a judgmental sampling approach. Respondents select products that represent their wholesaling activity and meet the following criteria:
Is a major annual wholesale revenue generator for their business within the requested product category,
Is sold regularly throughout the year, and
Typically generates positive margins (i.e., sold at a higher price than it is purchased).
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
Following sample selection, new survey participants (respondents) are introduced to the survey through telephone calls and are set up to complete an initialization questionnaire. During this initial phase of data collection, respondents may be guided through the process of selecting representative products for which prices and their characteristics (specifications) will be monitored. This process typically spans several collection cycles until respondents become conversant with the survey.
In subsequent cycles, monthly data are collected on a quarterly basis via electronic questionnaire, 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 email, fax or letter in order to collect data.
Information about the time it takes respondents to complete the survey questionnaire is collected and monitored closely. Currently, it takes respondents an average of 20 minutes to complete the survey.
View the Questionnaire(s) and reporting guide(s) .
Error detection is conducted at the time of data collection and also 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.
Time and effort is devoted to keeping the specifications constant such that only the pure changes in price are tracked. Some information is also collected in order to ensure, as much as possible, that the collected data correspond to the same specifications over time. This constant quality price then feeds into the Canadian System of Macroeconomic Accounts (CSMA) estimates of constant dollar Gross Domestic Product (GDP).
Missing data are generally estimated by a systematized imputation process. In any given period, price data may not be available for estimation. In such cases, missing data are imputed using the average price movement of remaining units within the same stratum (overall mean or targeted mean imputation method).
The price of the wholesale service is defined as the margin price, which is the difference between the average purchase price and the average selling price of a given product. It is not a wholesale selling price.
The Wholesale Services Price Index (WSPI) uses establishment revenues and industry gross margins as its weighting sources. Establishment revenue data are derived from the Business Register and the industry gross margins from the Annual Wholesale Trade Survey (record number 2445). The weight reference period is currently 2020. Weights are updated during a sample/basket update which typically occurs every 5 years. The last update occurred with the release of third quarter 2022 data.
Estimates are produced by calculating a weighted average of price relatives by industry, which are chained together to form an index series. The WSPI is a Laspeyres type chain linked index, available at the Canada level only.
Linking of indexes
With the introduction of a new basket, historical estimates are linked to the new basket by maintaining the same historical monthly changes. This is done by calculating a link factor for each index series as the ratio of the new basket index series (2020=100) in the overlap period to the historical index series (2013=100). This link factor is applied to the historical index series to bring it up or down to the level of the new index.
The overlap period for WSPI is currently March 2022.
An in-depth assessment of quality is conducted prior to the dissemination of estimates. This assessment is based on two key elements of quality (accuracy and coherence), as defined in Statistics Canada's guidelines for the validation of statistical outputs.
The survey's data collection strategy is designed to ensure that targeted response rates are met every cycle. Analysts pay close attention to this metric and take the appropriate measures to ensure that the survey's coverage is thorough. Particular attention is also given to ensuring that sampled products or services are representative of actual transactions taking place in the market. These two activities, fundamental to the overall quality of the estimates, are done consistently.
Analysts also undertake additional validation activities every cycle to ensure the coherence of survey estimates. These activities include the analysis of price changes period-over-period and the analysis of trends at the business or company, industry, subsector and sector levels, the certification of key contributors to price change as well as the confrontation of estimates against other related data sources. Contextual analysis of survey results is also performed in light of prevailing economic conditions.
Engagements with relevant stakeholders are also undertaken periodically. Forums involving other Statistics Canada analysts, industry stakeholders and partners at other national and international statistical agencies provide valuable insight into the development and research agenda of the program.
Statistics Canada is prohibited by law from releasing any information it collects which could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various transformations are applied to collected price data in the calculation of price indexes, such that it is not possible to identify the raw price data obtained from any survey participant. Confidentiality rules are also applied to price indexes 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.
Revisions and seasonal adjustment
Data for the most recent quarter are preliminary. The previous quarter of the series is subject to revision. The indexes are not seasonally adjusted.
The statistical accuracy of this index depends on price and weight data obtained from sample surveys. Each type of input data is subject to its own errors. Processing procedures for editing and imputation are in place to ensure the quality of data. Consequently, the aggregate indices at all levels are considered to be statistically reliable.
The survey achieves about a 75% 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 errors occur when observations are made only on a sample and not on the entire population. All other errors that arise from the various survey phases are referred to as non-sampling errors. For example, non-sampling 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 an out of scope unit is included by mistake or when errors occur in data processing, such as coding or capture errors.
A systematized imputation process is used to impute for the non-response portion of the sample, achieving an effective 100% coverage. Non-response bias is also minimized during the same process.