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17 Note that the ABS Agricultural Census/Survey collects area and production data for a wide range of individual commodities within the irrigated commodity groups displayed in the list above. Appendix 1 provides more detail of which commodities comprise these groupings.
18 There were differences in data items (for production, area grown and area irrigated) collected on the Agricultural Census/Surveys in different years. This affects the availability of some commodities for some years. Appendix 2 outlines some of the specific differences and how they have been treated in compiling the estimates for this publication, thereby enabling the production of GVIAP estimates for each of the commodity groups displayed in the list above for every year from 2000-01 to 2006-07.
19 Note that in all GVAP tables, “Total GVAP” includes production from pigs, poultry, eggs, honey (2001 only) and beeswax (2001 only), for completeness. These commodities are not included in GVIAP estimates at all because irrigation is not applicable to them.
METHOD USED TO CALCULATE GVIAP
20 The statistics presented here calculate GVIAP at the unit (farm) level, using three simple rules:
21 These three rules apply to most commodities; however there are some exceptions as outlined below in paragraph 26. It is important to note that the majority of cases follow rules 1 and 3; that is, the commodity group on a particular farm is either 100% irrigated or not irrigated at all. For example, in 2004–05, 90% of total GVAP came from commodity groups that were totally irrigated or not irrigated at all. Therefore, only 10% of GVAP had to be "split" into either "irrigated" or "non-irrigated" using the “yield formula” (described below). The yield formula is explained in full in the information paper Methods of estimating the Gross Value of Irrigated Agricultural Production (cat. no. 4610.0.55.006).
22 Outlined here is the yield formula referred to in paragraph 20:
Yi = estimated irrigated production for the commodity (t or kg)
P = unit price of production for the commodity ($ per t or kg)
Q = total quantity of the commodity produced (t or kg)
Ad = area of the commodity that is not irrigated (ha)
Ydiff = yield difference factor, i.e. estimated ratio of irrigated to non-irrigated yield for the commodity produced
Yield difference factors
23 Yield difference factors are the estimated ratio of irrigated to non-irrigated yield for a given commodity group. They are calculated for a particular commodity group by taking the yield (production per hectare sown/grown) of all farms that fully irrigated the commodity group and dividing this "irrigated" yield by the yield of all farms that did not irrigate the commodity group. The yield difference factors used here were determined by analysing data from 2000–01 to 2004–05 and are reported for each commodity group in Appendix 1 of the information paper Methods of estimating the Gross Value of Irrigated Agricultural Production (cat. no. 4610.0.55.006). It is anticipated that the yield difference factors will be reviewed following release of data from the 2010-11 Agriculture Census.
24 In this report "yield" is defined as the production of the commodity (in tonnes, kilograms or as a dollar value) per area grown/sown (in hectares).
Commodity groups for which the yield formula is used
25 The GVIAP for the following commodities have been calculated using the yield formula, with varying yield differences:
Cereals for hay - yield formula with yield difference of 1.5
Pastures for hay - yield formula with yield difference of 2
Pastures for seed - yield formula with yield difference of 2
Sugar cane - yield formula with yield difference of 1.3
Other broadacre crops - yield formula with yield difference of 2
Fruit and nuts - yield formula with yield difference of 2
Grapes - yield formula with yield difference of 1.2
Vegetables for human consumption and seed - yield formula with yield difference of 1
Nurseries, cut flowers and cultivated turf - yield formula with yield difference of 1
Note: a yield difference of 1 implies no difference in yield between irrigated and non-irrigated production.
26 However not all agricultural commodity groups can be satisfactorily calculated using this formula, so the GVIAP for a number of commodity groups has been calculated using other methods:
Cotton - production formula (see paragraph 28).
Dairy production - assume that if there is any irrigation of grazing land on a farm that is involved in any dairy production, then all dairy production on that farm is classified as irrigated.
Meat cattle, sheep and other livestock - take the average of two other methods:
27 For more information on the “area formula” for calculating GVIAP please refer to the information paper Methods of estimating the Gross Value of Irrigated Agricultural Production (cat. no. 4610.0.55.006).
28 Cotton is the only commodity that makes use of the “production formula”. This formula is based on the ratio of irrigated production to total production and is outlined in the information paper Methods of estimating the Gross Value of Irrigated Agricultural Production (cat. no. 4610.0.55.006). The production formula is used for cotton because from 2000-01 to 2006-07 it was the only commodity for which actual irrigated production (kg) was collected on the ABS agricultural censuses and surveys.
Qd = non-irrigated production of cotton (kg)
P = unit price of production for cotton ($ per kg)
Qt = total quantity of cotton produced (kg) = Qi + Qd
29 Most of the irrigated commodity groups included in these tables are irrigated simply by the application of water directly on to the commodity itself, or the soil in which it is grown. The exception relates to livestock, which obviously includes dairy. For example, the GVIAP of "dairy" simply refers to all dairy production from dairy cattle that grazed on irrigated pastures or crops. Estimates of GVIAP for dairy must be used with caution, because in this case the irrigation is not simply applied directly to the commodity, rather it is applied to a pasture or crop which is then eaten by the animal from which the commodity is derived (milk). Therefore, for dairy production, the true net contribution of irrigation (i.e. the value added by irrigation, or the difference between irrigated and non-irrigated production) will be much lower than the total irrigation-assisted production (the GVIAP estimate).
30 The difference between (a) the net contribution of irrigation to production and (b) the GVIAP estimate, is probably greater for livestock grazing on irrigated crops/pastures than for commodity groups where irrigation is applied directly to the crops or pastures.
31 Similarly, estimates of GVIAP for all other livestock (meat cattle, sheep and other livestock) must be treated with caution, because as for dairy production, the issues around irrigation not being directly applied to the commodity also apply to these commodity groups.
32 The estimates presented in this product are underpinned by estimates of the Value of Agricultural Commodities Produced (VACP), published annually in the ABS publication Value of Agricultural Commodities Produced (cat. no. 7503.0). VACP estimates (referred to as GVAP in this product) are calculated by multiplying the wholesale price by the quantity of agricultural commodities produced. The price used in this calculation is the average unit value of a given commodity realised in the marketplace. Price information for livestock slaughterings and wool is obtained from ABS collections. Price information for other commodities is obtained from non-ABS sources, including marketing authorities and industry sources. It is important to note that prices are state-based average unit values.
33 Sources of price data and the costs of marketing these commodities vary considerably between states and commodities. Where a statutory authority handles marketing of the whole or a portion of a product, data are usually obtained from this source. Information is also obtained from marketing reports, wholesalers, brokers and auctioneers. For all commodities, values are in respect of production during the year (or season) irrespective of when payments were made. For that portion of production not marketed (e.g. hay grown on farm for own use, milk used in farm household, etc.), estimates are made from the best available information and, in general, are valued on a local value basis.
34 It should be noted that the estimates for GVIAP are presented in current prices, therefore changes between the years shown in these tables reflect the effects of price change. Future issues of this product will include national estimates on a chain volume basis.
35 The gross value of irrigated agricultural production for the MDB is only presented for 2000-01, 2005-06 and 2006-07. The 2000-01 and 2005-06 data are available because they are sourced from the Agricultural Census which supports finer regional estimates, while the 2006-07 data are able to be produced because of the improved register of agricultural businesses (described in paragraph 9). The ABS is still working on a methodology to produce estimates for the MDB for 2001-02 to 2004-05, and is hoping that in the next issue a full annual time series from 2000-01 will be available.
36 The data for the Murray-Darling Basin (MDB) presented in this publication for 2000-01 were derived from a concordance of Statistical Local Area (SLA) regions falling mostly within the MDB. The data for the MDB for 2006-07 were derived from a concordance of National Resource Management Regions (NRM) regions falling mostly within the MDB. The MDB data for 2005-06 were derived from geo-coded data. As a result, there will be small differences in MDB data across years.
COMPARABILITY WITH PREVIOUSLY PUBLISHED ESTIMATES
37 Because of this new methodology, the experimental estimates presented here are not directly comparable with other estimates of GVIAP released by ABS in Water Account, Australia, 2000-01 (cat. no. 4610), Characteristics of Australia’s Irrigated Farms, 2000-01 to 2003-04 (cat. no. 4623.0), Water Account, Australia, 2004-05 (cat. no. 4610) and Water and the Murray-Darling Basin, A Statistical Profile 2000-01 to 2005-06 (cat. no. 4610.0.55.007).
38 The differences between the methods used to calculate the GVIAP estimates previously released and the method used to produce the estimates presented in this product, are explained in detail in the information paper Methods of estimating the Gross Value of Irrigated Agricultural Production, 2008 (cat. no. 4610.0.55.006).
39 In particular some commodity groups will show significant differences with what was previously published. These commodity groups include dairy production, meat production and sheep and other livestock production.
40 The main reason for these differences is that previous methods of calculating GVIAP estimates for these commodity groups were based on businesses being classified to a particular industry class (according to the industry classification ANZSIC), however the new method is based on activity. For example, for dairy production, previous methods of calculating GVIAP only considered dairy production from dairy farms which were categorised as such according to ANZSIC. The new method defines dairy production, in terms of GVIAP, as “all dairy production on farms on which any grazing land (pastures or crops used for grazing) has been irrigated”. Therefore, if there is any irrigation of grazing land on a farm that is involved in any dairy production (regardless of the ANZSIC classification of that farm), then all dairy production on that particular farm is classified as irrigated.
41 Where figures for individual states or territories have been suppressed for reasons of confidentiality, they have been included in relevant totals.
RELIABILITY OF THE ESTIMATES
42 The experimental estimates in this product are derived from estimates collected in surveys and censuses, and are subject to sampling and non-sampling error.
43 The estimates for gross value of irrigated agricultural production are based on information obtained from respondents to the ABS Agricultural Censuses and Surveys. These estimates are therefore subject to sampling variability (even in the case of the censuses, because the response rate is less than 100%); that is, they may differ from the figures that would have been produced if all agricultural businesses had been included in the Agricultural Survey or responded in the Agricultural Census.
44 One measure of the likely difference is given by the standard error (SE) which indicates the extent to which an estimate might have varied by chance because only a sample was taken or received. There are about two chances in three that a sample estimate will differ by less than one SE from the figure that would have been obtained if all establishments had been reported for, and about nineteen chances in twenty that the difference will be less than two SEs.
45 In this publication, sampling variability of the estimates is measured by the relative standard error (RSE) which is obtained by expressing the SE as a percentage of the estimate to which it refers. Most national estimates have RSEs less than 10%. For some states with limited production of certain commodities, RSEs are greater than 10%. Estimates that have an estimated relative standard error higher than 10% are flagged with a comment in the publication tables. If a data cell has an RSE of between 10% and 25, these estimates should be used with caution as they are subject to sampling variability too high for some purposes. For data cells with an RSE between 25% and 50% the estimate should be used with caution as it is subject to sampling variability too high for most practical purposes. Those data cells with with an RSE greater than 50% indicate that the sampling variability causes the estimates to be considered too unreliable for general use.
RELATIVE STANDARD ERRORS, Gross Value of Irrigated Agricultural Production of Selected Commodities - At 30 June 2007
46 Errors other than those due to sampling may occur because of deficiencies in the list of units from which the sample was selected, non-response, and errors in reporting by providers. Inaccuracies of this kind are referred to as non-sampling error, which may occur in any collection, whether it be a census or a sample. Every effort has been made to reduce non-sampling error to a minimum in the collections by careful design and testing of questionnaires, operating procedures and systems used to compile the statistics.
47 Where figures have been rounded, discrepancies may occur between sums of the component items and totals.
48 ABS publications draw extensively on information provided freely by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated: without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.
FUTURE DATA RELEASES
49 It is anticipated that ABS will release these estimates on an annual basis.
Agricultural Commodities, Australia (cat. no. 7121.0)
Agricultural Commodities: Small Area Data, Australia (cat.no. 7125.0)
Characteristics of Australia’s Irrigated Farms, 2000-01 to 2003-04 (cat. no. 4623.0)
Methods of estimating the Gross Value of Irrigated Agricultural Production (Information Paper)(cat. no. 4610.0.55.006).
Value of Agricultural Commodities Produced, Australia (cat. no. 7503.0)
Value of Principal Agricultural Commodities Produced, Australia, Preliminary (cat. no. 7501.0)
Water Account, Australia (cat.no.4610.0)
Water and the Murray-Darling Basin, A Statistical Profile, 2000-01 to 2005-06 (cat. no. 4610.0.55.007)
Water Use on Australian Farms, Australia (cat. no. 4618.0)
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