Farm Product Price Index (FPPI)

Detailed information for September 2017

Status:

Active

Frequency:

Monthly

Record number:

5040

The Farm Product Price Index (FPPI) is a monthly series that is published every quarter. The FPPI measures the changes in prices that farmers receive for the agriculture commodities they produce and sell.

Data release - December 6, 2017

Description

The Farm Product Price Index (FPPI) measures the changes in prices that farmers receive for the agriculture commodities they produce and sell. Commodities are priced at point of first transaction, where the fees deducted before a producer is paid are excluded, but bonuses and premiums that can be attributed to specific commodities are included.

The price index has separate crop and livestock indexes, a variety of commodity-group indexes such as cereals, oilseeds, specialty crops, cattle and hogs and an overall index - all available monthly and annually for the provinces and for Canada. The FPPI is an important indicator of the economic activity in the agriculture sector. Agriculture economists and analysts interested in the health of the agriculture sector, deflating agricultural commodity prices and policy development, use the series. The information provided by FPPI is useful to producers, producer groups, commodity analysts from the private sector such as grain companies and meat processors, international exporters, the banking sector and government agencies responsible for agriculture policies. The index compares, in percentage terms, current farm prices to prices in the time base period, 2007=100.

Reference period: The time period for which the FPPI equals 100; currently this is the year 2007.

Collection period: For most of the commodities included in the FPPI, the collection process occurs the first week following the reference month. Some of the data are collected quarterly.

Subjects

  • Agriculture
  • Agriculture price indexes
  • Farm financial statistics

Data sources and methodology

Target population

The universe includes all Canadian agriculture operations as defined by the Census of Agriculture.

Instrument design

This methodology does not apply.

Sampling

This is a sample survey with a longitudinal design.

The basket construction for FPPI is based on the Farm Cash Receipts series CANSIM table 002-0002, which measures all agriculture commodities, produced and sold outside the sector and farm-to-farm sales between provinces; all inter-farm sales within a province are excluded from farm cash receipts estimates. However some of the prices series, which are used in the Farm Cash Receipts and FPPI construction, are based on the Farm Product Prices Survey which includes sample surveys. For further information see record number 3436.

Data sources

Responding to this survey is mandatory.

Data are extracted from administrative files and derived from other Statistics Canada surveys and/or other sources.

The price data (Farm Product Prices Survey (FPPS) - record number 3436) and the Farm Cash Receipts (record number 3437) data used in the construction of the index are collected directly from survey respondents, extracted from administrative files and derived from other Statistics Canada surveys and/or other sources.

The prices for most agriculture commodities produced in Canada are collected and published monthly in CANSIM table 002-0043. Administrative price data come from a wide variety of sources. Many are collected directly from regulatory boards, such as the Egg Farmers of Canada, farm commodity groups, such as the Grain Farmers of Ontario and market associations such as CANFAX. Some data are collected and processed by provincial agricultural or statistical departments. Where administrative data are not available; prices are collected using the monthly Farm Product Prices Survey (record number 3436)

In rare cases where, for a particular commodity, there are no prices collected due to an insignificant level of production, proxy series are constructed. Proxy series may consist of several other reported series combined together.

Error detection

In the day-to-day collection and processing of the prices, great emphasis is placed on the examination and evaluation of prices. Subject matter officers monitor developments in the market, and review price changes both to validate them directly, and to ensure that changes are representative of the product price movement as a whole. In addition to the error detection methods applied to the FPPS, the index values are reviewed for outliers or unusual changes. A combination of judgment and outlier detection techniques is used to detect errors. In cases where unusual changes are not explained, follow up investigations are made.

Imputation

Imputation is generally used in instances for missing data. A price may be missing due to late reporting, or a commodity breaks its seasonal marketing pattern and was not sold in a particular month. Most commonly, the last reported price is used or an estimate is made based on the price trend observed for the same commodity in other provinces.

Estimation

Weights and Linking

The commodity weights used for the FPPI are based on the Farm Cash Receipts series, CANSIM table 002-0002. The FPPI is based on a five-year basket that is updated every year. This captures the continual shift in agricultural commodities produced and sold. There is a two-year lag in the years used to construct the basket because of the availability of farm cash receipts data and to reduce the number of revisions made to the index. Therefore, the years used to construct the basket for year y are y-6 to y-2.

The seasonal weighting pattern was derived using the monthly commodity marketings from 2006 to 2010. This weighting pattern remains constant and is updated periodically, for instance during intercensal revisions or when the time base is revised. The annual index number for a given year is a weighted average of the corresponding monthly index numbers.

Historical data

The historical series consist of all data for the months prior to January 2002. They were obtained by linking together indexes from the 2007-based FPPI series and the corresponding 1997-based FPPI series. These historical series were obtained by rebasing the 1997-based FPPI series using, as the rebasing factor, the ratio of 100 to the annual average index of 2007.

Quality evaluation

The commodity price data are monitored and examined through trend analysis and outlier detection. Some of the administrative source data are already audited by source organizations. Data are analyzed for time series consistency, links to current economic events, issues arising from the source data, and finally with respect to coherence.

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.

Revisions and seasonal adjustment

In general, the index is subject to revision for the current calendar year. In May and November the previous two calendar years may be subject to revision. Every five years a historical revision is done based on the results of the latest Census of Agriculture.

The FPPI is not adjusted for seasonality, but the seasonal basket is used since the marketing of virtually all farm products is seasonal. The index reflects the mix of agriculture commodities sold in a given month. The FPPI allows the comparison, in percentage terms, of prices in any given time period to prices in the base period, which at present is 2007=100.

Data accuracy

The accuracy of the quality evaluation depends on price and farm cash receipts based weight data. The methodologies of the index and the price series, which construct the index, have been designed to control error and to reduce the potential effects of these. However, both administrative and survey data are subject to various kinds of error. Administrative data may contain non-sampling error such as data capture errors, while survey data may suffer from both non-sampling and sampling error.

The statistical reliability of composite price indexes is more difficult to assess than that of most other statistical series due to the complex nature of the index, as well as the statistical problems associated with estimating composite price changes. Confidence intervals are not calculated due to the longitudinal nature of price index series. The published index series is believed to be sufficiently accurate for most practical purposes. Accuracy is best at higher geographic and commodity group levels due to the larger price sample sizes. Generally, data accuracy for a commodity group is higher at the Canada, East and/or West levels than at the provincial level.

Documentation

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