Survey methds and definitins August 2011
ABARES has cnducted surveys f selected Australian agricultural industries since the 1940s. These surveys prvide a brad range f infrmatin n the ecnmic perfrmance f farm business units in the rural sectr. This cmprehensive set f infrmatin is widely used fr research and analysis which frms the basis f many publicatins, briefing material and industry reprts. The annual agricultural surveys currently undertaken are: Australian Agricultural and Grazing Industries Survey (AAGIS) Australian Dairy Industry Survey (ADIS). Definitins f industries Industry definitins are based n the 2006 Australian and New Zealand Standard Industrial Classificatin (ANZSIC06). This classificatin is in line with an internatinal standard applied cmprehensively acrss Australian industry, permitting cmparisns between industries, bth within Australia and internatinally. Farms assigned t a particular ANZSIC have a high prprtin f their ttal utput characterised by that class. Further infrmatin n ANZSIC and n the farming activities included in each f these industries is prvided in Australian and New Zealand Standard Industrial Classificatin (ABS 2006, cat. n. 1292.0). The five bradacre industries cvered by AAGIS are: Wheat and ther crps industry (ANZSIC06 Class 0146 and 0149) farms engaged mainly in grwing rice, ther cereal grains, carse grains, ilseeds and/r pulses Mixed livestck-crps industry (ANZSIC06 Class 0145) farms engaged mainly in running sheep r beef cattle, r bth, and grwing cereal grains, carse grains, ilseeds and/r pulses Sheep industry (ANZSIC06 Class 0141) farms engaged mainly in running sheep Beef industry (ANZSIC06 Class 0142) farms engaged mainly in running beef cattle Sheep-beef industry (ANZSIC06 Class 0144) farms engaged mainly in running bth sheep and beef cattle.
The Australian Dairy Industry Survey (ADIS) cvers farms that are engaged in dairying. Target ppulatins The AAGIS is designed frm a ppulatin list drawn frm the Australian Business Register (ABR) and maintained by the Australian Bureau f Statistics (ABS). The ABR cmprises businesses registered with the Australian Taxatin Office (ATO). The ABR-based ppulatin list prvided t ABARES cnsists f agricultural establishments with their crrespnding statistical lcal area, ANZSIC, and a size f peratin variable. The ppulatin list fr the ADIS is a list f dairy farms that have paid levies based n their milk deliveries, surced frm the Levies Revenue Service. This list is prvided by Dairy Australia and cnsists f dairy businesses with their crrespnding regin and ttal milk prductin. The design measure fr ADIS is ttal milk prductin fr each dairy business n the frame. ABARES surveys target farming establishments that make a significant cntributin t the ttal value f agricultural utput (i.e. cmmercial farms). Farms excluded frm ABARE surveys will be the smallest units, and in aggregate will cntribute less than 2 per cent t the ttal value f agricultural prductin fr the industries cvered by the surveys. The size f peratin variable used in ABARES survey designs is usually estimated value f agricultural peratins (EVAO). Hwever, in sme surveys in recent years ther measures f agricultural prductin have als been used. EVAO is a standardised dllar measure f the level f agricultural utput. A definitin f EVAO is given in Agricultural Industries: Financial Statistics (ABS 2001, cat. n. 7506.0). Prir t 1986 87 the survey included establishments with an EVAO f $10 000 r mre. Between 1987-88 and 1991-92 the survey included establishments with an EVAO f $20 000 r mre. Between 1991-92 and 2003-04 the survey included establishments with an EVAO f $22 500 r mre. Since 2004-05 ABARES farm surveys included establishments classified as having an EVAO f $40 000 r mre. Survey design The target ppulatin is gruped int strata defined by ABARES regin, ANZSIC and size f peratin. The sample allcatin is a cmprmise between allcating a higher prprtin f the sample t strata with high variability in the size variable, and an allcatin prprtinal t the ppulatin f the stratum. A large prprtin f sample farms is retained frm the previus year s survey. The sample chsen each year maintains a high prprtin f the sample between years t accurately measure change while meeting the requirement t intrduce new sample farms t accunt fr changes in the target ppulatin, as well as t reduce the burden n survey respndents. The sample size fr AAGIS is usually arund 1600 and fr ADIS arund 300.
The main methd f cllectin fr bth surveys is face t face interviews with the wner manager f the farm. Detailed physical and financial infrmatin is cllected n the peratins f the farm business during the preceding financial year. Respndents t the AAGIS and ADIS are als cntacted by telephne in Octber each year t btain estimates f prjected prductin and expected receipts and csts fr the current financial year. ABARES surveys als allw supplementary questinnaires t be attached t the main r t the telephne surveys. These additinal questins help t address specific current issues. Sample weighting ABARES survey estimates are calculated by apprpriately weighting the data cllected frm each sample farm and then using the weighted data t calculate ppulatin estimates. Sample weights are calculated s that ppulatin estimates frm the sample fr numbers f farms, areas f crps and numbers f livestck crrespnd as clsely as pssible t the mst recently available ABS estimates frm data cllected frm Agricultural Census and Surveys. The weighting methdlgy fr AAGIS and ADIS uses a mdel-based apprach, with a linear regressin mdel linking the survey variables and the estimatin benchmark variables. The details f this methd are described in Bardsley and Chambers (1984)1. Fr AAGIS, the benchmark variables prvided by the ABS include: ttal number f farms in scpe area planted t wheat, rice, ther cereals, grain legumes (pulses) and ilseeds clsing numbers f beef and sheep. Fr ADIS, the benchmark variables prvided by Dairy Australia are: ttal number f in-scpe dairy farms ttal milk prductin. Generally, larger farms have smaller weights and smaller farms have larger weights, reflecting bth the strategy f sampling a higher fractin f the large farms than small farms (the frmer 1 Bardsley, P. and Chambers, R.L. 1984, Multipurpse estimatin frm unbalanced samples, Jurnal f Ryal Statistical Sciety, Series C (Applied Statistics), vl. 33, pp. 290 9.
having a wider range f variability f key characteristics and accunting fr a much larger prprtin f ttal utput) and the relatively lwer numbers f large farms. Reliability f estimates The reliability f the estimates f ppulatin characteristics published by ABARES depends n the design f the sample and the accuracy f the measurement f characteristics fr the individual sample farms. Sampling errrs Only a subset f farms ut f the ttal number f farms in a particular industry is surveyed. The data cllected frm each sample farm are weighted t calculate ppulatin estimates. Estimates derived frm these farms are likely t be different frm thse which wuld have been btained if infrmatin had been cllected frm a census f all farms. Any such differences are called sampling errrs. The size f the sampling errr is mst influenced by the survey design and the estimatin prcedures, as well as the sample size and the variability f farms in the ppulatin. The larger the sample size, the lwer the sampling errr is likely t be. Hence, natinal estimates are likely t have lwer sampling errrs than industry and state estimates. T give a guide t the reliability f the survey estimates, standard errrs are calculated fr all estimates published by ABARES. These estimated errrs are expressed as percentages f the survey estimates and termed relative standard errrs. Calculating cnfidence intervals using relative standard errrs Relative standard errrs (RSEs) can be used t calculate cnfidence intervals that give an indicatin f hw clse the actual ppulatin value is likely t be t the survey estimate. T btain the standard errr, multiply the relative standard errr by the survey estimate and divide by 100. Fr example, if average ttal cash receipts are estimated t be $100 000 with a relative standard errr f 6 per cent, the standard errr fr this estimate is $6000. This is ne standard errr. Tw standard errrs equal $12 000. There is rughly a tw in three chance that the census value (the value that wuld have been btained if all farms in the target ppulatin had been surveyed) is within ne standard errr f the survey estimate. This range f ne standard errr is described as the 66 per cent cnfidence interval. In this example, there is an apprximately tw in three chance that the census value is between $94 000 and $106 000 ($100 000 plus r minus $6000). There is rughly a 19 in 20 chance that the census value is within tw standard errrs f the survey estimate (the 95 per cent cnfidence interval). In this example, there is an apprximately
19 in 20 chance that the census value lies between $88 000 and $112 000 ($100 000 plus r minus $12 000). Cmparing estimates When cmparing estimates between tw grups, it is imprtant t recgnise that the differences are als subject t sampling errr. As a rule f thumb, a cnservative estimate f the standard errr f the difference can be cnstructed by adding the squares f the estimated standard errrs f the cmpnent estimates and taking the square rt f the result. Fr example, suppse the estimates f ttal cash receipts were $100 000 in the beef industry and $125 000 in the sheep industry a difference f $25 000 and the relative standard errr is given as 6 per cent fr each estimate. The standard errr f the difference can be estimated as: A 95 per cent cnfidence interval fr the difference is: $25 000 ± 1.96*$9605 = ($6174, $43 826) Hence, if a large number (twards infinity) f different samples are taken, in apprximately 95 per cent f them, the difference between these tw estimates will lie between $6174 and $43 826. Als, since zer is nt in this cnfidence interval, it is pssible t say that the difference between the estimates is statistically significantly different frm zer at the 95 per cent cnfidence level.
Regins Bradacre and dairy statistics are als available by regin. These regins, shwn in maps 2 and 3, represent the finest level f gegraphical aggregatin fr which the survey is designed t prduce reliable estimates. Figure 1 Map f Australia shwing Australian bradacre znes and regins Fr states ther than New Suth Wales and Victria, the Australian Dairy Industry Survey regins cmprise the entire state.
Figure 2 map f NSW and Victria shwing Australian Dairy industry survey regins Definitins f items Owner manager The primary decisin-maker fr the farm business. This persn is usually respnsible fr the day-t-day peratin f the farm and may wn r have a share in the farm business. Physical items Ttal area perated Includes all land perated by the farm business, whether wned r rented by the business, but excludes land share farmed n anther farm. Labur Measured in wrk-weeks, as estimated by the wner manager r manager. It includes all wrk n the farm by the wner manager, partners, family, hired permanent and casual wrkers and sharefarmers but excludes wrk by cntractrs. Hired labur Excludes the farm business manager, partners and family labur, and wrk by cntractrs. Expenditure n cntract services appears as a cash cst. Beef cattle Dairy cattle Cattle kept primarily fr the prductin f meat, irrespective f breed. Cattle kept r intended mainly fr the prductin f milk r cream.
Financial items Capital The value f farm capital is the value f all the assets used n a farm, including the value f leased items but excluding machinery and equipment either hired r used by cntractrs. The value f wned capital is the value f farm capital excluding the value f leased machinery and equipment. ABARES uses the wner manager s valuatin f the farm prperty. The valuatin includes the value f land and fixed imprvements used by each farm business in the survey, excluding land sharefarmed ff the sample farm. Residences n the farm are included in the valuatins. Livestck are valued at estimated market prices fr the land use znes within each state. These values are based n recrded sales and purchases by sample farms. Prir t 2001-02, ABARES maintained an inventry f plant and machinery fr each sample farm. Individual items were valued at replacement cst, depreciated fr age. Each year, the replacement cst was indexed t allw fr changes in that cst. Since 2001-02, ttal value f plant and machinery has been based n market valuatins prvided by the wner manager fr brad categries f capital such as tractrs, vehicles, irrigatin plant, etc. The ttal value f items purchased r sld during the survey year was added t r subtracted frm farm capital at 31 December f the relevant financial year, irrespective f the actual date f purchase r sale. Farm business debt Estimated as all debts attributable t the farm business, but excluding persnal debt, lease financed debt and underwritten lans including harvest lans. Infrmatin is cllected at the interview, supplemented by infrmatin cntained in the farm accunts. Change in debt Estimated as the difference between debt at 1 July and the fllwing 30 June within the survey year, rather than between debt at 30 June in cnsecutive years. It is an estimate f the change in indebtedness f a given ppulatin f farms during the financial year and is thus unaffected by changes in sample r ppulatin between years. Farm liquid assets Assets wned by the farm business which can be readily cnverted t cash. They include savings bank depsits, interest bearing depsits, debentures and shares. Excluded are items such as real estate, life assurance plicies and ther farms r businesses. Receipts and csts Receipts fr livestck and livestck prducts sld are determined at the pint f sale. Selling charges and charges fr transprt t the pint f sale are included in the csts f sample farms. Receipts fr crps sld during the survey year are grss f deductins made by marketing authrities fr freight and selling charges. These deductins are included in farm csts. Receipts fr ther farm prducts are determined n a farm-gate basis. All cash receipt items are the revenue received in the financial year.
Farm receipts and csts relate t the whle area perated, including areas perated by n-farm sharefarmers. Thus, cash receipts include receipts frm the sale f prducts prduced by sharefarmers. If pssible, n-farm sharefarmers csts are amalgamated with thse f the sample farm. Otherwise, the ttal sum paid t sharefarmers is treated as a cash cst. Sme sample farm businesses engage in ff-farm cntracting r sharefarming, emplying labur and capital equipment als used in nrmal n-farm activities. Since it is nt pssible t accurately allcate csts between ff-farm and n-farm peratins, the incme and expenditure attributable t such ff-farm peratins are included in the receipts and csts f the sample farm business. Ttal cash receipts Ttal f revenues received by the farm business during the financial year, including revenues frm the sale f livestck, livestck prducts and crps, plus the value f livestck transfers ff a prperty. It includes revenue received frm agistment, ryalties, rebates, refunds, plant hire, cntracts, sharefarming, insurance claims and cmpensatin, and gvernment assistance payments t the farm business. Ttal cash csts Payments made by the farm business fr materials and services and fr permanent and casual hired labur (excluding wner manager, partner and ther family labur). It includes the value f livestck transfers nt the prperty as well as any lease payments n capital, prduce purchased fr resale, rent, interest, livestck purchases and payments t sharefarmers. Capital and husehld expenditures are excluded frm ttal cash csts. Handling and marketing expenses include cmmissin, yard dues, levies etc. fr farm prduce sld. Administratin csts include accuntancy fees, banking and legal expenses, pstage, statinery, subscriptins and telephne. Cntracts paid refers t expenditure n cntracts such as harvesting. Capital and land develpment cntracts are nt included. Other cash csts include stres and ratins, seed purchased, electricity, artificial inseminatin and herd testing fees, advisry services, mtr vehicle expenses, travelling expenses and insurance. While ther cash csts may cmprise a relatively large prprtin f ttal cash csts, individually the cmpnents are relatively small verall, and as such, have nt been listed. Financial perfrmance measures Farm cash incme The difference between ttal cash receipts and ttal cash csts. Buildup in trading stcks The clsing value f all changes in the inventries f trading stcks during the financial year. It includes the value f any change in herd r flck size r in stcks f wl, fruit and grains held n the farm. It is negative if inventries are run dwn.
Depreciatin f farm imprvements plant and equipment Estimated by the diminishing value methd, based n the replacement cst and age f each item. The rates applied are the standard rates allwed by the Cmmissiner f Taxatin. Fr items, purchased r sld during the financial year, depreciatin is assessed as if the transactin had taken place at the midpint f the year. Calculatin f farm business prfit des nt accunt fr depreciatin n items subject t a finance lease because cash csts already include finance lease payments. Imputed labur cst Payments fr wner manager and family labur may bear little relatinship t the actual wrk input. An estimate f the labur input f the wner manager, partners and their families is calculated in wrk-weeks and a value is imputed at the relevant Federal Pastral Industry Award rates. Farm business prfit Farm cash incme plus buildup in trading stcks, less depreciatin and the imputed value f the wner manager, partner(s) and family labur. Prfit at full equity Farm business prfit, plus rent, interest and finance lease payments, less depreciatin n leased items. It is the return prduced by all the resurces used in the farm business. Rates f return Calculated by expressing prfit at full equity as a percentage f ttal pening capital. Rate f return represents the ability f the business t generate a return t all capital used by the business, including that which is brrwed r leased. The fllwing rates f return are estimated: rate f return excluding capital appreciatin rate f return including capital appreciatin. Farm business equity The value f wned capital, less farm business debt at 30 June. The estimate is based n thse sample farms fr which cmplete data n farm debt are available. Farm equity rati 30 June. Calculated as farm business equity as a percentage f wned capital at Off-farm incme Cllected fr the wner manager and spuse nly, including incme frm wages, ther businesses, investment, gvernment assistance t the farm husehld and scial welfare payments.