1 This publication contains final estimates from the 2013-14 Land Management Practices Survey (LaMPS). Included are detailed statistics on agricultural land use and land management practices being undertaken by agricultural businesses in Australia.
2 Data are available at national, state and territory as well as Australian Agricultural Environment (AAE) region levels.
3 The LaMPS is conducted on a biennial basis.
4 Estimates in this publication are based on information obtained from the LaMPS for the financial year ended 30 June 2014. A copy of the 2013-14 LaMPS survey form can be found under the Downloads tab of this publication.
SCOPE AND COVERAGE
5 The scope of the 2013-14 LaMPS was all businesses undertaking agricultural activity recorded on the ABS Business Register (ABSBR) above a minimum cut-off applied to the value of their agricultural production.
6 For the purposes of this survey a business is identified as undertaking agricultural activity as defined by the 2006 edition of the Australian and New Zealand Standard Industrial Classification (ANZSIC). For more information, please refer to Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006 (cat. no. 1292.0).
7 The ABSBR is based on the Australian Business Register (ABR) which is administered and maintained by the Australian Taxation Office (ATO). Most businesses and organisations in Australia are required to obtain an Australian Business Number (ABN) from the ATO for their business operations.
8 A minimum cut-off value of $5,000 was used to determine whether an agricultural business operation was in-scope for the 2013-14 LaMPS. This measure of size was based on the ABS’ Estimated Value of Agricultural Operations (EVAO) or a derived value based on turnover reported by an agricultural business operation in its Businesses Activity Statement (BAS).
9 The 2013-14 LaMPS final estimates are based on a response rate of 86% from a sample of approximately 52,000 agricultural businesses selected.
RELIABILITY OF ESTIMATES (SAMPLE ERROR)
10 The estimates in this publication are based on information obtained from respondents to the LaMPS for the year ended 30 June 2014. The sample population for the LaMPS is drawn from the total agricultural business population in scope of the collection. The estimates are subject to sampling variability; that is, they may differ from the figures that would have been produced if all businesses had been included in the survey.
11 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 responded or been reported for, and approximately nineteen chances in twenty that the difference will be less than two SEs.
12 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 published estimates have RSEs less than 10%. For some states with limited uptake of certain practices, RSEs are greater than 10%. Estimates that have an estimated relative standard error between 10% and 25% should be used with caution as they are subject to sampling variability too high for some purposes. Estimates with an RSE between 25% and 50% should also be used with caution as they are subject to sampling variability too high for most practical purposes. Estimates with an RSE greater than 50% indicate that the sampling variability causes the estimates to be considered too unreliable for general use.
RSEs for all estimates are available on request.
RELIABILITY OF ESTIMATES (NON-SAMPLE ERROR)
13 Editing is used in ABS business surveys to correct a number of non-sampling errors such as misunderstanding of questions or instructions, mis-coding, non-availability of data, non-response and non-contact. ABS Agricultural surveys output a large number of data items across multiple regions (Australia, State/Territory and sub-state regions) and industry breakdowns. While every effort is made to ensure these data items are of high quality, limited resources mean that not all potential non-sampling errors can be addressed in a timely manner.
A hierarchical significance based editing approach to these output estimates is utilised to maximise the effectiveness of editing on the quality of the estimates whilst managing the overall editing load. This approach involves ranking each of the estimates based on their significance relative to other estimates, with higher ranked estimates being investigated further. This targeted approach ensures that editing resources are focussed on the most important anomalies.
This hierarchical editing approach does mean that some estimates will have had less editing resource directed to them. A potential consequence of the reduced editing effort is that users may notice inconsistencies when comparing various population totals across different estimate types, especially in the case of smaller estimates and/or finer breakdowns.
ROUNDING AND CONFIDENTIALITY
Where figures for individual states or territories have been suppressed for reasons of confidentiality, they have been included in relevant totals.
Where figures have been rounded, discrepancies may occur between sums of the component items and totals.
ESTIMATION METHOD - CALIBRATION
While undertaking the 2013-14 LaMPS the ABS also conducted the Rural Environment and Agricultural Commodities Survey (REACS). The REACS collected a range of data on land use, crop and horticultural area and production, livestock numbers and farm management and demographic characteristics of farm operators. Whilst both collections were based on the same survey frame (all in scope agricultural businesses recorded on the ABSBR) they used different samples and therefore generated different estimates to each other for overlapping key land use data items.
The estimates of these overlapping key land use data items were not statistically significant from each other, however, to maintain coherence of land use estimates produced by both surveys, a calibration process was undertaken to align the REACS estimates to LaMPS estimates.
Calibration adjusts a business' weights in the sample in such a way that the estimates for specified benchmark data items align with the benchmark totals. The calibration algorithm aims to minimise the overall adjustment needed in the business' weights, while ensuring the calibrated weights remain within certain thresholds. In the case of REACS and LaMPS, the numbers of agricultural businesses in each region, and the area of agricultural land in each region, were used as benchmark data items.
Final estimates of agricultural commodities, value of agricultural commodities produced and water use by agricultural businesses are also available for the 2013-14 financial year. These estimates are located in:
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ABS DATA AVAILABLE ON REQUEST
As well as the statistics included in this and related publications, the ABS may have other relevant data available on request. Inquiries should be made to the National Information and Referral Service on 1300 135 070.
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
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