8169.0 - Experimental Estimates for Australian Industry adjusted for Off-June Year Reporting, 2011-12  
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 26/07/2013   
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Contents >> Concepts and Methods >> Methodology

METHODOLOGY

This paper describes a new methodology developed with the aim of measuring and removing the impact of off-June reporting on estimates published in Australian Industry (cat. no. 8155.0).

In summary the experimental estimates presented in the Appendix of this paper were derived by the following process:

  • For each in-scope EAS ANZSIC subdivision, subdivision off-June factors were determined for each data item and each of the off-June reporting types;
  • QBIS units with incorrectly reported or unrepresentative data in the ANSZIC subdivision were removed from contributing to the subdivision factors;
  • Significant EAS units that were also selected in the QBIS collection were assessed for appropriateness to receive an individualised (unit) off-June factor (instead of receiving a subdivision factor);
  • Off-June reporting EAS businesses were then assigned either a unit factor (if deemed appropriate) or its respective ANZSIC subdivision and off-June type factor. New values are calculated for these businesses, representing an estimate of how the business would have reported for the standard financial year (that is, 1 July to 30 June). Final aggregated data is then produced on a standard financial year basis.


Creating subdivision off-June year factors

It was necessary to create twenty-one separate factors for each in scope ANZSIC subdivision, as demonstrated in Table 2.2.

2.2 THE 21 OFF-JUNE YEAR MODELLING FACTORS REQUIRED FOR EACH ANZSIC SUBDIVISION

Sales and service income
Wages and salaries
Other expenses
Closing inventories of raw materials
Opening inventories of raw materials
Closing inventories of finished goods
Opening inventories of finished goods

ANZSIC Subdivision
Dec-11
Dec-11
Dec-11
Dec-11
Dec-11
Dec-11
Dec-11
ANZSIC Subdivision
Mar-12
Mar-12
Mar-12
Mar-12
Mar-12
Mar-12
Mar-12
ANZSIC Subdivision
Sep-12
Sep-12
Sep-12
Sep-12
Sep-12
Sep-12
Sep-12



The factors were formulated from a subset of businesses sampled in the QBIS which met the following criteria:
  • For sales and service income, wages and salaries and other expenses factors: Reported a non-zero value for these data items for the seven relevant quarters which cover all possible types of reporting periods. For example, for 2011-12 the relevant quarters are March 2011 through September 2012. This condition eliminated businesses which either started up or closed down during the period;
  • For inventory factors: Reported a non-zero value for sales and service income and inventories for eight relevant quarters (December 2010 through September 2012 to ensure an opening inventory value;
  • Did not report a value for the above items in one quarter greater than 10 times that of an adjacent quarter. This condition eliminated businesses with extreme values; and
  • Had an employment size of 20 or more. This removed small businesses, whose data are not expected to be impacted by off-June reporting in the EAS.

Where there were five or less contributing QBIS businesses in an ANZSIC subdivision, it was considered that the number of observations was insufficient for producing the off-June factors. In those cases the off-June factors were produced at ANZSIC division level.

Sales and service income, other expenses and inventories factors were not generated for Education and training and Health care and social assistance (ANZSIC Divisions P and Q respectively), as the information is not collected by QBIS (see Scope and Population above). For the same reason, inventory factors could only be generated for Mining, Manufacturing, Wholesale trade, Retail trade, Accommodation and food services (ANZSIC Divisions B, C, F, G and H respectively) and two subdivisions in the Electricity, gas, water and waste services Division; Electricity supply and gas supply (ANZSIC Subdivisions 26 and 27 respectively).

For each data item, quarterly weighted QBIS data reported by the subset of businesses established above were summed to give an aggregate value for each in scope ANZSIC subdivision. These aggregate quarterly values were then used to create factors that model the impact of off-June reporting for each of the four data items, by each in scope subdivision.

To calculate each factor, a ratio of the summed data from the four quarters of the standard financial year is divided by the summed annualised data from the four quarters of the relevant off-June reporting period, as described by Equation 2.1.

EQUATION 2.1. CALCULATING OFF-JUNE FACTORS

Equation: Equation for calculating off-June factors

where Q is quarterly QBIS data aggregated by industry subdivision for the subset of businesses identified above.

Since inventories are stock variables (that is, represent a quantity existing at a particular point in time) the formulae for deriving inventories factors differed slightly, as described by Equation 2.2.

EQUATION 2.2. CALCULATING OFF-JUNE INVENTORIES FACTORS

Equation: Equation for calculating off-June inventories factors

Factors were produced for opening and closing inventories, by type of inventory. The types of inventories specified were raw materials inventories and finished goods inventories (including work-in-progress).

The factors generated in these equations give an indication of the variability in trading conditions between off-June reporting periods and the standard Australian financial year. A factor of 1 indicates no variability, implying there is no effect of off-June reporting on estimates published in Australian Industry (cat. no. 8155.0). Conversely, the further a factor lies from 1, the greater the impact of off-June reporting on industry estimates.

An example of the calculation of factors for Subdivision 14, Wood product manufacturing is provided below. Quarterly sales and service income estimates derived from in-scope QBIS data (see Table 2.3) were used to produce off-June factors (see Example 2.1) which were applied to EAS estimates of sales and service income.

2.3 CALCULATING FACTORS - EXAMPLE: SALES OF GOODS AND SERVICES, SUBDIVISION 14 WOOD PRODUCT MANUFACTURING

Sales and service income estimates derived from in scope QBIS data(a)
Quarter
$m

Mar-11
1 459
Jun-11
1 640
Sep-11
1 765
Dec-11
1 636
Mar-12
1 445
Jun-12
1 486
Sep-12
1 531

(a) Estimates shown in the table have been included for illustrative purposes only.


EXAMPLE 2.1. CALCULATING FACTORS: Sales of goods and services, Subdivision 14 Wood product manufacturing

Equation: Example for calculating factors for Sales of goods and services income


Quality assurance of subdivision off-June year factors

To validate ANZSIC subdivision off-June factors (derived from QBIS data), the following processes were used:
  • Subdivision factors that were more than two standard deviations from the across-economy mean of that particular data item and off-June type were identified.
  • The QBIS data reported by the top contributors were assessed for consistency between reporting quarters or valid explanation for any differences. Based on these investigations, a decision was made to include or exclude the 'top contributor' unit's data from contributing to the off-June factor. Top contributors to the factors were identified. To do this, units were individually removed and the factor was re-derived. If the absolute difference from the original to the re-derived factors was more than 0.02 for sales, wages and expense factors and 0.05 for inventory factors, then the unit was considered a top contributor.
  • By using this methodology, top contributor units were isolated for one of two reasons; either their data showed a significantly different trend to the rest of their industry (ANSZIC subdivision) or their data (consistent or inconsistent) heavily influenced the magnitude of the factor (e.g. a unit's data contributes 30% of all data feeding into a particular off-June factor).
  • A unit's data was generally excluded from the subdivision factor if there was evidence to suggest that the business had undergone activities/events that could not be considered representative of the rest of the industry subdivision. In instances where no evidence exists on which to base the decision to include or exclude a unit's data in the derivation of the factor, the default decision was to include the unit's data to the off-June factor.


Creating unit off-June factors

The use of unit off-June factors were introduced for estimates presented in this paper. Unit off-June factors were applied to improve the accuracy of off-June adjusted estimates. Unit factors were derived similarly to subdivision factors. The difference between the unit and subdivision factor is that a business' unit factor is derived by using its reported QBIS data only (where the subdivision factor uses all in-scope QBIS data for that subdivision).


Quality assurance of unit off-June factors

Assessment was made on the consistency between reported EAS data and reported QBIS data for the relevant four quarters to ensure that the data was correct. Where there was consistency between the two data sources, the unit received a unit factor. Where consistency did not exist between EAS and QBIS data the unit received the subdivision factor.

In assessing a business' suitability for a unit off-June factor, suitability of QBIS data was also reviewed for inclusion in subdivision factors, based on the criteria described above (see Quality assurance of subdivision off-June factors).


Applying factors to EAS data

The quality assured off-June factors are then applied to the relevant off-June reporting EAS units.

If an EAS unit was deemed suitable for a unit factor, its reported EAS data is adjusted by its unit factor. Where an EAS unit was not deemed suitable or assessed to receive a unit factor, then its corresponding ANZSIC subdivision's factor for its particular off-June type was applied to reported EAS data.

The off-June year factors are applied to only selected data items from the EAS. The adjusted items are shown in Table 2.4, as well as the factors which were used to adjust them. Note that not all components of the published items have been adjusted, due to a lack of available QBIS data from which to create appropriate factors.

Diagram: Table showing the QBIS factors and adjusted EAS data items




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