Annual Greenhouse, Sod and Nursery Survey (GSNA)
Detailed information for 2022
The purpose of the survey is to collect information on the production and value of greenhouse products, nursery stocks and sod produced in Canada.
Data release - April 25, 2023
This survey collects data on greenhouse, sod and nursery operations in Canada. The data are used by federal and provincial agriculture departments and producer associations to perform market trend analysis and to study domestic production with particular interest on imports. This survey also contributes to the agricultural receipts program of Statistics Canada and ultimately the System of National Accounts.
The data are used by Agriculture and Agri-Food Canada and other federal departments to develop and administer agricultural policies. This information is also used by provincial departments for production and price analysis and for economic research.
The survey is administered as part of the Integrated Business Statistics Program (IBSP). The IBSP has been designed to integrate approximately 200 separate business surveys into a single master survey program. The IBSP aims at collecting industry and product detail at the provincial level while minimizing overlap between different survey questionnaires. The redesigned business survey questionnaires have a consistent look, structure and content.
The integrated approach makes reporting easier for firms operating in different industries because they can provide similar information for each branch operation. This way they avoid having to respond to questionnaires that differ for each industry in terms of format, wording and even concepts. The combined results produce more coherent and accurate statistics on the economy.
Reference period: Calendar year
- Agriculture and food (formerly Agriculture)
- Crops and horticulture
Data sources and methodology
The target population is all entities that operate any greenhouse, sod, or nursery operation and meet Statistics Canada's definition of a farm. A farm is defined as an operation that produces at least one agricultural product and will report revenue and/or expenses for that agricultural production to the Canada Revenue Agency. Several small populations are excluded from the target population of the Annual Greenhouse, Sod and Nursery Survey including farms in Canada's three territories, institutional farms, community farms, greenhouses that are marijuana producers and greenhouses or nurseries that produce tree seedlings for reforestation.
The observed population consists of establishments on Statistics Canada's Business Register that represent this target population. This frame of operations is derived using signals of agricultural activities on the latest set of tax declarations. To improve the overall coverage of this frame to the target population, information from additional sources including lists of special operations and survey feedback is used to include establishments which report their fiscal data differently.
The questionnaires were developed by subject matter experts through consultation with the provinces and industry experts. The Operations and Integration Division, Agriculture Commodities Section of the Collection, Planning and Research Division and the Enterprise Statistics Division of Statistics Canada conduct in-house testing for flow and consistency.
Subject matter experts may change, add or remove questions. This typically happens because of changes in market trends or because of information in debriefing reports from field staff.
New questions were pre-tested in the field in 2008 and 2016. This included testing the cognitive process of respondents in answering questions and other tests to obtain feedback for the design of the questionnaire.
This is a sample survey of farms with one of greenhouse, nursery or sod products with a cross-sectional design.
For each province, the farms are classified into one of four categories based on the presence or absence of greenhouse, sod and nursery activities and their primary NAICS value. The categories are Greenhouse - Floriculture, Greenhouse - Other, Sod and Nursery. Farms with multiple commodities are assigned to one category based on the importance of their contribution to each category at the provincial level. The category X province combination is called the sampling cell. The farms within each sampling cell are classified into size groups based on area. The sampling stratum is the (category X size) group within the province.
Small operations that have a total greenhouse area smaller than a provincial threshold for total greenhouse area (either floriculture or other greenhouse depending on how they were categorized), have a sod acreage smaller than a provincial threshold for total sod and have a nursery acreage smaller than a provincial threshold for total nursery are excluded from the sample (Take none); these thresholds are set so that all farms with an acreage greater than any of the four thresholds represent 95% of greenhouse - floriculture, greenhouse - other, sod and nursery acreage in the province together.
In each sampling cell, a threshold for the respective commodity acreage was defined using the sigma-gap method, based on the importance of that commodity to the sampling cell totals. All operations with the acreage above one of the thresholds were selected in the sample (Take-all).
For the remaining units, the Geometric method was used to divide the strata into 2 groups based on acreage, the large and medium-sized Take-some.
Sampling and sub-sampling
A sample was selected by stratified random sampling. Note that while strictly not a census, this sample includes all farms in the population except those in the Take-none portion.
Data collection for this reference period: 2023-01-03 to 2023-02-08
Responding to this survey is mandatory.
Data are collected directly from survey respondents.
Data are collected annually using an e-mail invitation to open, complete and submit an electronic questionnaire. If the questionnaire is not completed on-line by the deadline, the respondent will be contacted for a scheduled telephone interview.
View the Questionnaire(s) and reporting guide(s) .
New IBSP tools will be utilized to conduct data editing.
The following methods will be employed:
1) Top 20 contributor analysis (macro/micro)
2) Use of historical data for comparison and possible imputation. (micro/macro)
3) Use of various ratios (e.g. price/area) and provincial averages to impute incorrect or missing data (micro)
4) Industry Research - in consultation with the LAOS team (Large Agricultural Operation Statistics), Internet, provincial and industry specialists.
An automated imputation process based primarily on historical data and donor imputation is used. The strategy also uses various ratios (e.g. price/area) and provincial averages. This imputation strategy is used to impute incorrect or missing data for respondents as well as to impute all missing data for non-respondents.
The survey data collected are weighted within each stratum in order to produce estimates representative of the population. A ratio adjustment based on the survey estimates compared to the 2016 Census of Agriculture is applied to the estimates to account for the small non-sampled Take-None units. The estimated variances are a combination of variance due to imputation and sampling variance.
Data verification and analysis of the top contributors and historical comparisons are performed before a final estimate is disseminated. Different sources of information are used to validate provincial estimations. No other surveys are available to compare directly with these survey results.
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.
In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada generalized confidentiality 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
This methodology does not apply to this survey.
All surveys are subject to sampling and non-sampling errors. Sampling errors occur because population estimates are derived from a sample of the population rather than the entire population. Non-sampling error is not related to sampling and may occur for various reasons during the collection and processing of data. For example, non-response is an important source of non-sampling error. Under or over-coverage of the population, differences in the interpretations of questions and mistakes in recording, coding and processing data are other examples of non-sampling errors. To the maximum extent possible, these errors are minimized through careful design of the survey questionnaire, verification of the survey data, and follow-up with respondents when needed to maximize response rates.
Measures of sampling error are calculated for each estimate. Also, when non-response occurs, it is taken into account and the quality is reduced based on its importance to the estimate. Other indicators of quality are also provided such as the response rate. Both the sampling error and the non-response rate are combined into one quality rating code. This code uses letters that range from A to F where A means the data is of excellent quality and F means it is unreliable. These quality rating codes can be requested and should always be taken into consideration.
For the Annual Greenhouse, Sod and Nursery survey the majority of estimates at the Canada level for the variables that are more frequently reported (area, investment, expenditures, sales, etc.) have a quality rating of A or B which makes them very reliable. Estimates for some variables at the national and provincial level have a wider range of quality ratings. Quality ratings are available upon request.
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