Foreword

Acknowledgments

Introduction

Methodology

Farm performance in 2006-07

Irrigation infrastructure, management practices and intentions

Region profiles

Appendices

Farm profiles

Distributions of selected estimates

Survey methodology and definitions

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C Survey methodology and definitions

Target populations

ABARE surveys are designed and samples selected on the basis of a framework drawn from the Business Register — maintained by the Australian Bureau of Statistics (ABS). This framework includes agricultural establishments (that is, farms) classified by size and industry in each statistical local area. To be eligible for this survey, farms had to have engaged in irrigated agricultural activities during 2005-06, had an estimated value of agricultural operations of $40 000 or more, and be defined as broadacre, dairy or horticulture industry farms. The industry definitions used in this study are based on the Australian and New Zealand Standard Industrial Classification (ANZSIC). This classification is consistent with international standards and permits comparisons between industries, both within Australia and internationally. Farms assigned to a particular ANZSIC class means that they have a high proportion of their total output characterised by that class (refer to ABS 2006 for further information). The ANZSIC industry classes and associated codes associated with the broadacre, dairy and horticulture categories used for this study were as follows:

Broadacre Grain growing ANZSIC code 0121 Grain-sheep and grain-beef cattle farming ANZSIC code 0145 Rice growing ANZSIC code 0146 Other grain growing ANZSIC code 0149 Cotton growing ANZSIC code 0152 Beef cattle farming ANZSIC code 0142 Sheep–beef cattle farming ANZSIC code 0144 Sheep farming ANZSIC code 0141 Dairy Dairy cattle farming ANZSIC code 0160 Horticulture Grape growing ANZSIC code 0131 Apple and pear growing ANZSIC code 0134 Stone fruit growing ANZSIC code 0135 Citrus fruit growing ANZSIC code 0136 Other fruit and tree nut growing ANZSIC code 0139 Vegetable growing (under cover) ANZSIC code 0122 Vegetable growing (outdoors) ANZSIC code 0123

Survey design and sample weighting

The farm population to be surveyed was stratified by operation size using the estimated value of agricultural operations (EVAO). The size of each stratum was determined using the Dalenius-Hodges method (Lehtonen and Pahkinen 2004). The sample allocation to each stratum was done using a mixture of the Neyman allocation, which takes into account variability within strata of the auxiliary variable, in this case EVAO, and proportional allocation, which only considers the population number in each stratum. The Neyman allocation allocates large proportions of sample to strata with large variability, in the case of this survey, strata of larger farms (Lehtonen and Pahkinen 2004). The estimates presented in this report are calculated by appropriately weighting the data collected from each sample farm and then using the weighted data to calculate population estimates. Generally, larger farms have small weights and smaller farms have larger weights, reflecting the strategy of sampling a higher fraction of the larger farms than of small farms (the former having a wider range of variability of key characteristics).

Reliability of estimates

The reliability of the estimates of population characteristics presented in this report depends on the design of the sample and the accuracy of the measurement of characteristics for the individual sample farms.

Sampling errors

Only a small number of farms out of the total number of farms in a particular industry or region are surveyed. The data collected from each sample farm are weighted to calculate population estimates. Estimates derived from these farms are likely to be different from those that would have been obtained if information had been collected from a census of all farms. Any such differences are called ‘sampling errors’. The size of the sampling error is most influenced by the survey design and the estimation procedures, as well as the sample size and the variability of farms in the population. The larger the sample size, the lower the sampling error is likely to be. Hence, national estimates are likely to have smaller sampling errors than industry and state estimates. To give a guide to the reliability of the survey estimates, sampling errors have been calculated for all estimates in this report. These estimated errors, expressed as percentages of the survey estimates and termed relative standard errors (RSEs), are given next to each estimate in parentheses.

Calculating confidence intervals using relative standard errors

RSEs can be used to calculate ‘confidence intervals’ that give an indication of how close the actual population value is likely to be to the survey estimate. The standard error is obtained by multiplying the relative standard error by the survey estimate and dividing by 100. For example, if average total cash receipts are estimated to be $100 000 with a relative standard error of 6 per cent, the standard error for this estimate is $6000. One standard error equals $6000 and two standard errors equals $12 000. For a 66 per cent confidence interval, there is roughly a two in three chance that the ‘census value’ (the value that would have been obtained if all farms in the target population had been surveyed) is within one standard error of the survey estimate. This range of one standard error is described as the 66 per cent confidence interval. In this example, there is an approximately two in three chance that the census value is between $94 000 and $106 000, {$100 000 + or – $6 000}. For a 95 per cent confidence interval, there is roughly a 19 in 20 chance that the census value is within two standard errors of the survey estimates (the 95 per cent confidence interval). In this example, there is an approximately 19 in 20 chance that the census value lies between $88 000 and $112 000, {$100 000 + or – $12 000}. The size of the RSE is mainly influenced by the design of the survey, the sample size and the variability in the population. For example; the larger the sample size, the lower the RSE is likely to be.

Comparing estimates

When comparing estimates between two groups, it is important to recognise that the differences are subject to sampling error. As a rough rule of thumb, a conservative estimate (an overestimate) of the standard error of the difference can be constructed by adding the squares of the estimated standard errors of the component estimates and taking the square root of the result. For example if the estimates of farm cash income are $139 210 for irrigated horticulture in New South Wales and $162 020 for growers in Queensland, with the relative standard errors given as 33 and 26 per cent respectively. The difference between these two estimates is $22 810. The standard error of the difference can be estimated as: A 95 per cent confidence interval for the difference is: Hence, if 100 different samples are taken, in 95 of them, the difference between these two estimates is between –$149 797 and $195 417. Also, since zero is in this confidence interval, it is possible to say that the difference between the estimates is not statistically significantly different from zero at the 95 per cent confidence level.

Definition of terms

Owner manager: The primary decision maker for the business. This person is identified by discussion between interviewer and interviewee as (one of) the key decision maker(s). This person is usually responsible for the day to day operation of the business and may own or have a share in the business. Area of land at business premises: Includes all land operated by the business, whether owned or rented by the business. Labour: Measured in work-weeks, as estimated by the owner manager. It includes all work on the business by the owner manager, partners, family, hired permanent and casual workers, but excludes work done by contractors. Hired labour: Excludes the owner manager, partners and family labour, and work undertaken by contractors. Expenditure on contract services appears as a cash cost. Water rates: Expenditure on water, including temporary water purchases and all fees (including fixed charges) paid to irrigation authorities and relevant state agencies. Capital: The value of capital employed by the business is the market value of all the assets used including leased items but excluding machinery and equipment either hired or used by contractors. Market valuations were provided by the owner manager of surveyed businesses and included the market value of land and fixed improvements used by the business, excluding the value of the owner manager’s house. The house value deducted from the total value of land and fixed improvements was the present day replacement cost, depreciated for age. Debt: Estimated as business debt. It includes all debts attributable to the business excluding personal debt and underwritten loans. Information collected at the survey interview was supplemented by information in the business accounts. Total cash receipts: Total of revenues received by the business during the financial year, including revenues from the sale of sugar cane, other crops, livestock and livestock products. It includes revenue received from royalties, rebates, refunds, plant hire, contracts, insurance claims and compensation, and government assistance payments. Total cash costs: Payments made by the business for materials and services and for permanent and casual hired labour (excluding partner and other family labour). It includes the value of any lease payments on capital, produce purchased for resale, rent, interest, cropping and livestock related purchases. Capital and household expenditures are excluded from total cash costs. Handling and marketing expenses include commission, levies etc. for business produce sold. Administration costs include accountancy fees, banking and legal expenses, postage, stationery, subscriptions and telephone. Other cash costs include relatively small cost items like stores, advisory services and travelling expenses. Farm cash income: Total cash receipts minus total cash costs. Depreciation: Estimated by applying the diminishing value depreciation method to the market value of capital items at 30 June 2006. Capital items are categorised into several groups and relevant depreciation rates are applied. The capital groups include vehicles; handling, harvesting and packing equipment; cultivation and sowing equipment; computers, electronic and communications equipment; other plant and equipment; and buildings on the business premises. Imputed labour cost: Payments for owner manager and family labour may bear little relationship to the actual work input. An estimate of the labour input of the owner manager, partners and their families is calculated in work-weeks and a value is imputed at the relevant Federal Pastoral Industry Award rates. Farm business profit: Cash operating surplus plus buildup in trading stocks, less depreciation, less the imputed value of the owner manager, partner(s) and family labour. Profit at full equity: Return to capital and management plus interest, rent and finance lease payments. It is the return produced by all the resources used in the business. Rate of return: Is the return to all capital used. It is computed by expressing profit at full equity as a percentage of the total opening capital of the business. Equity ratio: Calculated as business equity as a percentage of owned capital at 30 June. Off-farm income: Income not derived from the surveyed farm business. It includes all off-farm income from wages and salaries, other businesses, other investments and Commonwealth social support payments. It is estimated for the owner manager and spouse only.