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Annual Enterprise Survey: 2012 financial year (provisional)
Embargoed until 10:45am  –  30 August 2013
Data quality

Period-specific information

This section is for information that changes between periods

General information

This section is for information that does not changes between releases

Period-specific information

Reference period

This is the first release of the Annual Enterprise Survey (AES) results for the 2012 financial year. Data was collected from businesses with balance dates between 1 October 2011 and 30 September 2012. These results are provisional and may be revised as further information becomes available over the next two years.

Accuracy of the data

As part of ongoing development to AES, we improved the survey by further increasing our use of administrative data to replace  sampled units  

Consistency with other periods or datasets

AES 2012 population

The population for the AES 2012 financial year was 439,563 units, consisting of:

  • 310,527 (70.6 percent) sourced from IR 10 information
  • 15,796 (3.6 percent) sourced from the postal survey
  • 4,976 (1.1 percent) sourced from other government data
  • 485 (0.1 percent) sourced from Ministry of Business, Innovation, and Employment data
  • 107,779 (24.5 percent) non-sample units.

In AES 2012, the postal survey unit responses were weighted to represent the non-sample units. The corporate response rate required for the postal collection is set at 85 percent of the industry's goods and services tax (GST) sales. The response rate in 2012 was 91 percent.

Graph, Annual enterprise survey population by source of data, 2003 to 2012 financial years.

Effect of the 2010/11 Canterbury and Christchurch earthquakes on 2011 and 2012 data

Large earthquakes occurred in Canterbury and Christchurch in September 2010 and February 2011. These earthquakes and their aftershocks had a significant influence on the ongoing economic output of businesses located in Christchurch. We saw continuing financial effects of these earthquakes in the 2012 financial results for the central government and the general insurance industries as claims continue to be settled. We are likely to see payments affecting these industries in future years.

Use of Charities Commission data in 2012

To continue to reduce respondent load, in the 2012 financial year AES sourced more data from the Charities Commission. In 2012,  we sourced 1,849 units from the Charities Commission, compared with 1,519 in 2011. We first used Charities Commission data in 2011.

Use of administrative data and its effect on published variables

Our main administrative data source (Inland Revenue's IR 10) is the primary source for capturing the agriculture, forestry, and fishing division (ANZSIC06 division A) in AES. In 2012 we used more administrative data for other industries as well. IR 10 data does not provide direct estimates of additions and disposals of fixed assets, so we use modelling to calculate these. The modelling of IR 10 data is currently under review, so additions and disposals of fixed assets have been suppressed from the 'all industries' table, all agricultural industries, and the accommodation industry tables in this release.

Our increased use of administrative data in 2012 has also caused discontinuity in shareholders' funds and owners' equity in the repairs and maintenance industry, and the accommodation industry.

Changes in depreciation legislation

On 1 April 2011 a new tax law was introduced that affected depreciation of buildings. This changed the depreciation rate to zero percent for most buildings with an expected life of 50 years or more. The effect of the law change is primarily seen in this release in the rental, hiring, and real estate services industry, which had a very strong $983 million (37.4 percent) decrease in depreciation in 2012. It was also the main contributor to the decrease in depreciation across all industries in the 2012 financial period (down $1,284 million or 5.9 percent).

General information

Data sources

Data used in AES is compiled from sources that include:

  • a sample survey of business financial data
  • business financial data from Inland Revenue (IR 10)
  • central government data from the Treasury's Crown Financial Information System
  • superannuation data from the New Zealand Companies Office (Ministry of Business, Innovation, and Employment)
  • local government data from Statistics NZ's local authority statistics
  • not-for-profit data from the Charities Commission.

Population

The target population for AES is all economically significant businesses (see 'Definitions' section) operating within New Zealand. However, some industries are excluded on pragmatic grounds. In total, industries covered in AES are estimated to contribute approximately 90 percent of New Zealand's gross domestic product (GDP).

The Australian and New Zealand Standard Industrial Classification 2006 (ANZSIC06) industry exclusions are:

  • residential property operators (L671100)
  • foreign government representation (O755200)
  • religious services (S954000)
  • private households employing staff and undifferentiated goods- and service-producing activities of households for own use (S960100-300).

Superannuation funds (K633000) are included in the population. However, they are excluded from the release tables.

Survey design 

AES is the principal collection vehicle for data used in compiling New Zealand's national accounts. The data collected feeds into calculating the economy's GDP, through the current price annual industry accounts, which are compiled within an input-output framework.

AES collects financial data for most industries operating in New Zealand's economy. The AES industries are based on ANZSIC06. AES is designed predominantly at the four-digit ANZSIC level (113 industries). Data at lower levels can also be produced (subject to confidentiality constraints) but it may have considerably higher sample errors. In addition, we have done limited analysis at this level.

The population for AES is selected from the Statistics NZ Business Frame.

The Business Frame is a database of all known individual private and public sector businesses and organisations engaged in producing goods and services in New Zealand that meet significance criteria. The Business Frame provides a consistent reference to standard classifications, which helps to integrate statistical outputs and allows it to be used as a classification tool. The frame also provides links to all economic and financial survey data, and the tax system, which means a more effective use of tax data that reduces respondent load.

The structure of each business on the Business Frame consists of an enterprise, a kind-of-activity unit (KAU), and a geographic unit. Collectively, they are referred to as statistical units. Larger or more complex businesses may have a number of statistical units. Each statistical unit is given an industry classification based on its predominant activity. Different divisions of a company may be spread across several industries, depending on how the company is structured. The collection unit for AES is the KAU. By definition, a KAU is engaged in predominantly one activity for which a single set of accounting records is available.

AES uses a stratified sample design to select the sample from units on the Business Frame. Each industry contains between one and four strata, defined by size of turnover (sourced from GST information) and rolling mean employment. Each industry has a full-coverage stratum made up of large units with significant economic activity within their industry group. The remaining strata contain a sample of medium-sized units, which are weighted to represent non-sampled units. For example, a unit may have a weight of five, meaning it represents itself and four other businesses. Smaller businesses have less chance of being selected, and consequently when selected have larger weights that represent more units. Most industries also have a tax stratum for smaller units, where IR 10 information is used instead of a postal survey response.

The wide range of activities undertaken by New Zealand businesses makes it necessary to have different types of questionnaires. All questionnaires capture financial performance and position information, but the format and the wording of the questionnaires are tailored to suit different groups of businesses.

AES is designed to measure industry levels for a given year. Incremental improvements in measurement, sample design, classification, and data collection may influence the inter-period movements, particularly over longer time periods. We have worked to minimise the impact of these changes and to present a consistent time series in the published tables.

Interpreting the data

AES provides a wealth of information to help users understand the structure and performance of industries within New Zealand's economy. When using AES data, it is important to be aware of a number of design issues that may affect results.

These issues are:

1. How companies structure themselves can affect how their data is captured and reported in AES. Large corporates often set up separate entities to manage different divisions of their business. These divisions are classified based on their predominant activity. For example, their administration (head office) and their asset-owning activities may be classified to management and related consulting services (in division M), and to financial asset investors (in division K), respectively. This may mean that a manufacturing unit will not have these support activities recorded in the manufacturing industry.

If a business is divided into different divisions, this can mean that AES results will include inter-company flows between divisions (gross flows).

2. AES time series can be affected by the restructuring of companies. For example, if divisions within a company were to be restructured or amalgamated, the following could happen:

  • consolidation of the units would remove the gross flows and leave net flows
  • the industrial classification of the resulting unit/s would be determined by predominant activity – activity in the other industries would disappear
  • value added would remain the same in both options.

The reverse may also occur, when restructuring results in net flows being represented in a gross form.

3. The 'all industries' table sums divisional tables and therefore includes gross flows.

4. We present AES results for a nominal March year. However, the data is collected from businesses with balance dates between 1 October in one year and 30 September the following year. The table below lists, for each industry, the predominant balance date by total income.

Predominant balance dates by industry
Industry Year ended
A – Agriculture, forestry, and fishing March
B – Mining December
C – Manufacturing March
D – Electricity, gas, water, and waste services June
E – Construction March
F – Wholesale trade March
G & H – Retail trade and accommodation March
I – Transport, postal, and warehousing June
J – Information media and telecommunications June
K – Financial and insurance services June
L – Rental, hiring, and real estate services March
M & N – Professional, scientific, technical, administrative, and support services March
O – Public administration and safety June
P – Education and training December
Q – Health care and social assistance June
R & S – Arts, recreation, and other services March
Note: This table is produced using weighted total income data and therefore reflects the population as it is represented in AES. The count of predominant balance dates may produce different results to this table, which is based on total income. This is because the count is dominated by the small businesses sourced from IR 10s, which have small values of total income.

5. In the postal collection, we specifically request additions and disposals of fixed assets. However, in the administrative data source (IR 10), only the closing book value of fixed assets and depreciation are requested. Hence, where IR 10s are used, we model values for additions and disposals.

6. Statistics NZ has a legal obligation to protect companies' privacy and industry-sensitive information.  We apply confidentiality rules to all tables released – to protect the information supplied by an individual company. Once all confidential financial items are identified, we suppress further items to complete the protection of the confidential value.

Use of AES data

In addition to its use in the national accounts regional GDP, GDP, and sectoral accounts, AES is also a data source for other existing and upcoming Statistics NZ outputs, including:

In recent years, there has been increased demand for non-standard output from users. Statistics NZ is providing more input into research surrounding these requests. Examples include:

  • frequent requests from other government departments, such as the Ministry of Business, Innovation and Employment
  • requests by turnover bands, which can add significant analytical value and is a popular request
  • requests from businesses for financial data to gauge their performance against industry averages

Availability of results

The supplementary tables available from the 'Downloads' box contain a selection of the tables available from AES. In most cases, tables are published to New Zealand Standard Industrial Output Classification (NZSIOC) level 4. In some cases, tables at an even less-aggregated level may also be available. 

Please contact our Information Centre to request information.

Confidentiality

Data collected and information contained in this publication must conform to the provisions of the Statistics Act 1975. This requires that published information maintains the confidentiality of individual respondents.

More information

See more information about the Annual Enterprise Survey.

Liability

While all care and diligence has been used in processing, analysing, and extracting data and information in this publication, Statistics NZ gives no warranty it is error free and will not be liable for any loss or damage suffered by the use directly, or indirectly, of the information in this publication.

Timing

Our information releases are delivered electronically by third parties. Delivery may be delayed by circumstances outside our control. Statistics NZ does not accept responsibility for any such delay.

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