Passenger Air Services Price Index (PASPI)

Detailed information for 2018





Record number:


The Passenger Air Services Price Index is an annual series measuring the price change for base air fares, providing indications of the overall trend of domestic and international fares over time. The index relates to the operations of major Canadian air carriers.

Data release - February 13, 2020


The Passenger Air Services Price Index is an annual series measuring the price change for base air fares (i.e. fares excluding taxes and surcharges), providing indications of the overall trend of domestic and international fares over time. Data collected for Canadian Level I carriers are used to produce annual price indexes.

The Passenger Air Services Price Index can be used by businesses to measure their performance against industry standards, to plan marketing strategies or to prepare business plans for investors. Governments use index data to develop national and regional economic policies and to develop programs to promote domestic and international competitiveness. The data are also used by trade associations, business analysts and investors to study the economic activity, performance and characteristics of the industry.

Statistical activity

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.


  • Prices and price indexes
  • Service price indexes
  • Transportation
  • Transportation by air

Data sources and methodology

Target population

The target population covers the scheduled operations of the Canadian air carriers classified to Level I. These are carriers that transport over 1 million revenue passengers (i.e. passengers for whose transportation an air carrier receives commercial remuneration) per year. Data collected covers only level I carriers, which accounted for over 90% of revenues in the industry from 2006.

The services covered fall under the North American Industry Classification System (NAICS) Canada 2012 number 4811101 - Scheduled air transportation, air passenger carriers, scheduled - and under the North American Product Classification System (NAPCS) Canada 2012 number 521511 - Scheduled Air Passenger Transportation Services.

Instrument design

This methodology does not apply.


This methodology type does not apply to this statistical program.

Data sources

Data are collected from other Statistics Canada surveys and/or other sources.

The source data comes from the Fare Basis Survey, conducted by Statistics Canada. This survey represents a regular and comprehensive source of fare type-specific data on passengers, revenues, and average air fares. It provides estimates of the average air fare paid and the proportion of passengers for each fare type (first class, business class, economy class, discount and other) for Canadian scheduled air carriers. The data are available by domestic and international sector, by province, and for selected cities. The air fare collected does not contain taxes or surcharges. The air carriers included are the Canadian Level I carriers.

The data are drawn from all "lifted" (i.e. flown) flight coupons in a carrier's system applicable to scheduled services. The air carriers are instructed to report passenger volume and revenue aggregated by fare basis code (denotes the applicable service, discount and restrictions on travel) and coupon origin and destination-OD- (identifies the two locations between which the coupon was used for passage) for each sample day.

Data are reported for all domestic and international coupon OD city-pairs, for which the origin or the destination is within Canada. The revenue reported is the allocated portion of the revenue from the ticket associated with a particular coupon. Where the coupon comes from a one coupon ticket, all the ticket revenue is allocated to that coupon; where the coupon comes from a multi-coupon ticket, the ticket revenue is prorated. The method used for proration is the "Straight Rate Proration Principle".

There is currently a nine month lag between the reference period and the release period. The survey is in the process of being revised and the intention is to reduce this lag period to three months.

Error detection

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 are 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 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 is defined as a unit value price, i.e. the average value by city-pair and by fare type (first class, business class, economy class and discount). It corresponds to the ratio between the annual values for passenger-revenues and the passenger-kilometre by city pair.

The weights correspond to the aggregates passenger-revenues by city pair and by fare group of the year preceding the reference period.

The revenues are derived from the Fare Basis Survey data (record number 2708).

The weights reference period is the year preceeding the reference periode of the most recent data released.

Weights are updated annually and correspond to the revenues of the year preceding the most recent reference period (e.g. the 2014 indexes are estimated using 2013 revenues as weights).

Estimates are produced by calculating a weighted average of price relatives, which are chained together to form an index series. The PASPI is a Laspeyres index that is chain linked annually with annually updated weights.

Quality evaluation

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 react appropriately to ensure that the survey's coverage of the industry is thorough. Particular attention is also given to ensuring that sampled products or services are representative of actual transactions happening in the market place. 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 include among others activities: analysis of price changes over time (including analysis of trends), at the business/company, industry, subsector and sector levels; certification of key contributors to price change; and 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 insights that inform the development and research agenda of the program.

Disclosure control

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 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.

Collected data are converted to price indexes and data are released as such, so that it is not possible to identify the suppliers of raw prices.

Revisions and seasonal adjustment

With each release, data for the previous year may have been revised. The indexes are not seasonally adjusted.

Data accuracy

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 indexes at all levels are considered to be statistically reliable.

The PASPI uses data derived from other Statistics Canada's surveys based on 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.

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