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Agricultural Production Statistics: June 2014 (final)
Embargoed until 10:45am  –  13 May 2015
Data quality

Period-specific information
This section contains information about data that has changed since the last release.

General information
This section has information that does not change between releases.

Period-specific information

Survey information

This release contains final results for livestock, forestry, and arable crops from the 2014 Agricultural Production Survey. These final figures are at the regional level.

The 2014 survey was part of the current programme of agricultural production statistics that started in 2002. Previous censuses were held in 2002, 2007, and 2012, with annual sample surveys in 2003–06, 2008–11, and 2013.

Responses from farmers and foresters in the 2014 Agricultural Production Survey resulted in an estimated eligible population of 56,600 enterprises.

2014 questionnaire changes (from 2013)

Horticulture – in 2014, we included questions on the area of fruit trees and vines planted, and the area of vegetables and other horticulture crops harvested.

Farm practices – in 2014, we included questions on the irrigated area of the farm.

Sheep breeds – in 2014, we did not include questions on the breed of sheep.

Sample design

For the 2014 Agricultural Production Survey, we used a stratified sample design to select a sample from the population. In selecting this sample, we stratified the population by regional council area, ANZSIC06 group, and size group.

We determined the size groups as follows:

  • For businesses that had previously responded to one or more of the agricultural production censuses or surveys since 2002, we used the most-recent production data to form size groups. The variables used covered a range of livestock and cropping variables. Typically, three size groups were formed: small, medium, and large.
  • For new businesses or businesses that had not responded to any of the 2002 to 2013 agricultural collections, we took a random sample.

The 2014 survey had a sample size of 30,000 businesses.

We optimised the 2014 sample design to produce a specified sampling error for certain combinations of key variables and regions, but not all. Given the dynamic nature of the agricultural sector, the sample errors for 2014 may sometimes be smaller or larger than planned, particularly for sectors that change rapidly.

2014 sampling error and imputation levels

Sampling error and imputation levels for the 2014 Agricultural Production Survey

Relative sampling errors at 95% confidence interval (%)

% of total estimate imputed

Ewe hoggets put to ram

6

16

Breeding ewes (2-tooth and over) put to ram

3

15

Total sheep

3

15

Lambs born to ewe hoggets

7

15

Lambs born to ewes

3

15

Total lambs

3

15

Dairy cows and heifers, in milk or calf

3

24

Total dairy cattle

3

24

Calves born alive to dairy heifers/cows

3

25

Beef cows and heifers in calf (aged 1–2 years)

7

18

Beef cows and heifers in calf (aged 2 years and over)

4

14

Total beef cattle

3

16

Calves born alive to beef heifers/cows

4

16

Female deer mated

8

12

Total deer

7

13

Fawns born on the farm

8

12

Breeding sows (aged 1 year and over)

3

8

Mated gilts

3

7

Total pigs

2

9

Piglets weaned on the farm

3

7

Area of new forestry plantings (hectares)

24

3

Area of forestry replantings (hectares)

6

3

Exotic timber harvested (hectares)

3

4

Exotic timber harvested (cubic metres)

4

Wheat harvested (tonnage)

9

19

Wheat area harvested (hectares)

9

17

Barley harvested (tonnage)

7

17

Barley area harvested (hectares)

7

18

Maize grain harvested (tonnage)

15

14

Maize grain area harvested (hectares)

14

14

Apple (hectares)

1

9

Avocados (hectares)

3

18

Kiwifruit (hectares)

3

14

Wine grapes (hectares)

1

12

Blackcurrants (hectares)

32

3

Cherries (hectares)

4

10

Onions (hectares)

6

3

Potatoes (hectares)

8

7

Buttercup squash (hectares)

12

5

Peas (hectares)

15

12

Sweet corn (hectares)

18

9

Response rates

The estimated proportion of eligible businesses that responded to the 2014 Agricultural Production Survey for this final release was 80 percent. These businesses represent 86 percent of the total estimated value of agricultural operations.

General information

About the estimates

Figures in this release are rounded. We calculate all percentages in this release using unrounded figures. The figures from the agricultural production surveys may differ from those produced from other sources, such as the National Exotic Forestry Description Survey produced by the Ministry for Primary Industries, the Stock Number Survey from Beef and Lamb New Zealand Limited, and Dairy Statistics from Livestock Improvement Corporation Limited. These surveys use different survey frames and designs.

Population frame

The agricultural production surveys include all units identified on Statistics NZ's Business Frame as having agricultural activity. The Business Frame is a list of businesses in New Zealand, based on their registration for goods and services tax (GST) with Inland Revenue.

The compulsory registration level for GST is $60,000, so there is a partial and unquantifiable coverage of units below this level.

Survey population

The survey population for the agricultural production surveys is all businesses engaged in 'agricultural production activity' (including livestock, cropping, horticulture, and forestry), or which own land intended for agricultural activity. The survey population includes businesses engaged in agriculture or forestry production as a secondary activity.

Industries in scope

The survey population specifically includes businesses classified to the following ANZSIC06 codes:

  • A01 Agriculture
  • A0301 Forestry (excluding native forestry).

It also includes parts of:

  • L671200 Non-residential property operators
  • M691000 Scientific research services (agriculture-related research that involves land holding (excluding universities))
  • P802300 Combined primary and secondary education (agricultural high school operation)
  • P802400 Special school education (special needs education involving agricultural production activity)
  • P810200 Higher education (agriculture-related research undertaken by universities that involves land holding)
  • R912100 Horse and dog racing administration and track operation
  • R912900 Other horse and dog racing activities (racehorse training and racing stables operations)
  • R892200 Nature reserves and conservation parks operation.

The survey population specifically excludes:

  • A019300 Beekeeping
  • part of A019900 Other livestock farming nec (worm farming, pet breeding, dog breeding, cat breeding, bird breeding (except poultry, game birds, ostriches, and emus))
  • A017100 Poultry meat (except growers who also produce eggs for human consumption).

Population changes

For the 2002 Agricultural Production Census, we sourced the population from the Business Frame and the Inland Revenue Client Register. We checked these sources against industry lists and AgriBase to ensure all large units were included in the population.

After the 2002 Census, we use the Business Frame for the census and survey populations.

Survey content changes

Over the years, we have changed the core information we gather in agricultural production collections.

Since 2002, these collections have gathered information on livestock and arable farming, horticulture, and forestry with the following exception:

  • In 2004, 2006, 2008, 2010, and 2013, the surveys collected information on livestock and arable farming, and forestry (we did not collect horticulture production information).

Past questionnaire changes

Forestry

The reference date for forestry production estimates changed to 31 March in the 2005 Agricultural Production Survey. This change was made to allow the forestry section of the survey to align more closely with the National Exotic Forest Description survey run by the Ministry for Primary Industries.

For the 2002 Census, and the 2003 and 2004 surveys, the year-ended date was 31 December. For agricultural production collections before the 2002 Agricultural Production Census, the year-ended date was 30 June.

Fawns

Since the 2005 survey, the data relates to fawns born on the farm that were alive at four months. In 2003 and 2004, data related to fawns weaned on the farm. In 2002, data related to fawns born on the farm. The change took industry recommendations into account.

Deer

Deer figures since the 2004 survey are not directly comparable with 2002 and 2003 figures. Improvements we made to the questions about deer in the 2004, 2005, and 2006 surveys have resulted in improved deer number estimates. While it is not possible to quantify the exact extent of the previous undercoverage, we estimate an undercount of about 70,000 deer at 30 June 2002, and 50,000 at 30 June 2003.

Reliability of sample survey estimates

This release contains statistics from the 2002 to 2014 agricultural production collections. All results from these collections are subject to non-sampling error, and sampling error.

Non-sampling error arises from bias in the patterns of response and non-response, inaccuracies in reporting by respondents, and errors in recording and classifying data. Non-sampling error comprises coverage error, measurement error (which arise from respondents, questionnaires, and collection methods), non-response error, and processing error. We use procedures to detect and minimise these types of error, but they may still occur and are not easy to quantify.

Sampling error occurs because we base inferences about the entire population on information obtained from only a sample of that population. As 2003–06, 2008–11, and 2013 collections are sample surveys, not censuses, the results from these collections are also subject to sampling error.

Imputation

We impute values for farmers and foresters who do not return a completed questionnaire. Imputation involves replacing missing items with values based on other information available.

The method of imputation we use is random 'hot deck' imputation.

The Agriculture Production Survey uses random hot deck imputation. Using this method, we replace missing values of one or more variables for a non-respondent with observed values from a respondent with similar characteristics. The imputation class is formed from common characteristics such as regional council area, ANZSIC06 group, and production data from previous years. We randomly assign each non-respondent to a respondent in the same imputation cell, and the farm production data of the respondent is copied across to the non-respondent.

To improve the imputation process, we remove respondents with uncharacteristically high levels of agricultural activity from their respective imputation cells. It is unlikely that any of the non-respondents would have similar characteristics to them.

Confidentiality

Data collected and information contained in this release must conform to the provisions of the Statistics Act 1975. Published information must maintain the confidentiality of individual respondents. Figures in the tables affected by these provisions are denoted by 'C'.

Quality suppression

Data with high sample errors or imputation levels are suppressed and are indicated by 'S' in the table.

More information

See more information about the Agricultural Production Survey.

Statistics in this release have been produced in accordance with the Official Statistics System principles and protocols for producers of Tier 1 statistics for quality. They conform to the Statistics NZ Methodological Standard for Reporting of Data Quality.

Liability

While all care and diligence has been used in processing, analysing, and extracting data and information in this publication, Statistics NZ gives no warranty it is error-free and will not be liable for any loss or damage suffered by the use directly, or indirectly, of the information in this publication.

Timing

Our information releases are delivered electronically by third parties. Delivery may be delayed by circumstances outside our control. Statistics NZ accepts no responsibility for any such delay.

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