
|
||||
| Collecting economic survey data | ||||
| ABARE has been undertaking economic surveys of selected Commonwealth fisheries since the early 1980s and on a regular basis for particular fisheries since 1992. The current fisheries survey program involves surveying major Commonwealth fisheries every second year. The aim is to develop a consistent time series of economic information for each fishery. Such a database, in conjunction with scientific assessments of each fishery, is vital for assessing the economic performance of fisheries. Aggregated information from the surveys is made publicly available so the performance of fisheries and the impact of management policies can be independently assessed. ABARE surveys are designed and samples selected on the basis of information supplied by the Australian Fisheries Management Authority (AFMA). This information includes data on the size of the catch and boat characteristics. Because it is not possible to survey all the boats in a fishery, a sample of boats is selected based on how representative they are. Where possible, boats are classified into subgroups based either on the fishing method used (longline boats, purse seine boats, trawlers) or on the size of operations (typically small, medium and large producers). A number of representative boats from each subgroup are then targeted for the survey. In practice this sample is seldom fully realised. Non-response is relatively high across fishery surveys, reflecting the difficulty in contacting some operators and a reluctance of others to participate in the survey. Sample design and weighting systems have been developed to reduce the impact of non-response, but care is still required when interpreting the information from the surveys. Between January and July, an ABARE officer visits the owner of each boat selected in the sample. The officer interviews the boat owner to obtain physical and financial details of the fishing business for the survey years. In a number of instances the skipper of the boat is also interviewed. Further information is subsequently obtained from accountants, selling agents and marketing organisations on the signed authority of the survey respondents. The information obtained from various sources is reconciled to produce the most accurate description possible of the financial characteristics of each sample boat in the survey. |
||||
| The 2008 surveys | ||||
| ABARE surveyed two fisheries in 2008 – the eastern tuna and billfish fishery and the southern and eastern scalefish and shark fishery. Information was collected for the 2005-06 and 2006-07 financial years for both fisheries. The definitions of key variables used in this analysis are provided in box 2. |
||||
| Sample weighting | ||||
| All population estimates presented in this report are calculated from the weighted survey data of sample boats. A weight is calculated for each boat in the sample, based on how representative that boat is in the population. Sample weights are calculated such that the weights sum to the population of boats that the sample is representing, and the weighted sum of catch reported by the sample boats equals the total catch for the fishery according to AFMA logbook data. That is, where wi is the weight for the ith boat; xi is the catch for the ith boat; and X is the total catch for the target population. Technical details of the method of weighting used are given in Bardsley and Chambers (1984). |
||||
|
||||
| Reliability of estimates | ||||
| A relatively small number of boats out of the total number of boats in a particular fishery are surveyed. Estimates derived from these boats are likely to be different from those which would have been obtained if information had been collected from a census of all boats. How closely the survey results represent the population is influenced by the number of boats in the sample, the variability of boats in the population and most importantly the design of the survey and the estimation procedures used. To give a guide to the reliability of the survey estimates, measures of sampling variation have been calculated. These measures, expressed as percentages of the survey estimates and termed ‘relative standard errors’, are given next to each estimate in parentheses. In general, the smaller the relative standard error, the more reliable the estimate. |
||||
| Use of relative standard errors | ||||
| These relative standard errors can be used to calculate ‘confidence intervals’ for the survey estimate. First, calculate the standard error 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. There is roughly a two in three chance that the ‘census value’ (the value that would have been obtained if all boats in the target population had been surveyed) is within one standard error of the survey estimate. There is roughly a 19 in 20 chance that the census value is within two standard errors of the survey estimates. Thus, in this example, there is approximately a two in three chance that the census value is between $94 000 and $106 000, and approximately a 19 in 20 chance that the census value is between $88 000 and $112 000. |
||||
| Comparing estimates | ||||
| When comparing estimates across groups or years it is important to recognise that the differences are also subject to sampling error. As a rule of thumb, a conservative estimate of the standard error of the difference can be constructed by adding the squares of the estimated standard errors of the component estimates and then taking the square root of the result. For example, suppose the estimates of total cash receipts were $100 000 in one year and $125 000 in the previous year – a difference of $25 000 – and the relative standard error is given as 6 per cent for each estimate. The standard error of the difference can be estimated as: |
||||
| Non-sampling errors | ||||
| The values obtained in a survey may be affected by errors other than those directly related to the sampling procedure. For example, it may not be possible to obtain information from certain respondents, respondents may provide inaccurate information or respondents may differ from nonrespondents for a particular variable being surveyed. In conducting surveys, ABARE draws upon a depth of experience. The survey staff are generally very experienced and undergo rigorous pre-survey training, aimed at minimising nonsampling errors. However, when drawing inferences from estimates derived from sample surveys, users should bear in mind that both sampling and nonsampling errors occur. |
||||
|
||||
| Under the Fisheries Management Act 1991, one of the objectives of the Australian Fisheries Management Authority (AFMA) is to maximise the net economic returns to the Australian community from the management of Commonwealth fisheries. Maximising a fishery’s net economic returns involves maximising returns from the use of the natural resources (the fish stock). As part of monitoring performance of AFMA against this objective, ABARE’s economic surveys provide some of the necessary data to calculate performance indicators such as net returns and productivity indexes. In addition, survey data provides some of the necessary data to construct bioeconomic models. This section outlines how net returns are calculated using ABARE survey data. | ||||
| Net economic returns | ||||
| Net economic returns are the long-run profits from a fishery after all costs have been met, including fuel, crew costs, repairs and maintenance, the opportunity cost of capital, depreciation and opportunity cost of family and owner labour. Although they do not provide an indication of the potential returns available from a fishery in the long run, a time series of net returns may indicate in which direction net returns in a fishery are heading. For instance, a fishery in which estimated net returns are regularly close to zero or negative is probably not being managed effectively. A positive trend may suggest a fishery is approaching the point of maximum economic yield (MEY) – the level of catch/effort where the profits of a fishery are maximised. The measure of net returns of a fishery can be calculated by summing the net returns of each boat in a fishery. The net return of each boat can be defined as: R total cash receipts attributable to the fishery, excluding any receipts from leasing licences or quota; OC total operating cash costs less interest paid, less expenditure on leasing licences or quota, less licence fees and levies; K value of capital associated with vessel (depreciated replacement value); d depreciation rate for vessel; r real interest rate; and M costs of managing the fishery.Operating costs include day-to-day expenses such as fuel, crew costs, repairs, administration, gear etc. These cost items are usually easily identified in fishers accounts. Both receipts and operating costs exclude any income or costs from leasing in or leasing out quota and licences. These are excluded, because the amount fishers pay or accept for leasing quota and licences represents expected future profits which can be generated from the quota or licence. This is precisely what net returns are measuring. If leasing were included as revenues and costs, double counting would occur and estimates of net returns would be incorrect. Depreciation expense is the cost of capital becoming less valuable over time because of wear and tear and obsolescence. Depreciation expense is not consistently identifiable in fishers accounts, so ABARE calculates the depreciation of boats based on a capital inventory list collected during the surveys. The opportunity cost of owner and family labour is estimated at interview. Often owners and their families are involved in the operation of a boat, either as skippers and crew or onshore as accountants and shore managers. While some will be paid the market value for their labour, some will not be paid at all and others paid large amounts through ‘directors’ fees’ or ‘management fees’. ABARE survey officers ask survey respondents what market value of any owner and family labour is, and this amount is considered as a cost. The opportunity cost of capital is a return which would have been earned if the capital was invested elsewhere, rather than invested in fishing capital. The standard ABARE rate is 7 per cent a year, and this is used in this analysis. This cost is not identifiable in fishers’ accounts. The costs of managing a fishery are comprised of two components. Recovered management costs are those management costs paid for by industry members in the form of management levies. Non-recovered management costs are those costs of managing a fishery that are not paid for by industry but are paid for by government. Both components are included when calculating net economic returns. |
||||