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Methodology changes to manufacturing, wholesale trade, and selected services statistics

This page describes changes we've made to the methodology used in the Economic Survey of Manufacturing, Wholesale Trade Survey, and Selected Services Survey quarterly statistics from the September 2015 quarter. It also gives details of new industries being covered by the Selected Services Survey. 

Why we are changing these surveys

We are changing the methodology in these surveys to:

  • make greater use of administrative data sources
  • reduce respondent burden
  • introduce a consistent methodology and processing system that allows for potential expansion of industry coverage in the future
  • enable the delivery of information at lower levels of detail for research and customised requests
  • improve the quality of the published series.

The changes will apply from:

  • Economic Survey of Manufacturing: September 2015 quarter published 8 December 2015
  • Wholesale Trade Survey: September 2015 quarter published 7 December 2015
  • Selected Services results published on Infoshare 7 December 2015. 

Summary of changes

Under the current design, we survey all the large businesses in each industry, plus a sample of medium-sized businesses. We supplement this with modelled tax data for the smaller businesses.

Under the new design, we will use administrative data (goods and services tax (GST) data, sourced from Inland Revenue) wherever possible, and will supplement this by surveying only the largest and most complex businesses. With this new design, we have reduced the number of businesses being surveyed by 50 percent and eliminated most of the small and medium-sized businesses from the survey entirely. Figure 1 compares the current and new designs.

Figure 1

The methodology changes have improved the quality of the series we publish. This is largely because we effectively have a full coverage of all businesses within an industry, rather than relying upon a smaller sample to represent the entire population.

With this new design, we will also expand the scope of the Selected Services Survey to cover three additional industries:

  • MN111 – Scientific, architectural, and engineering services
  • MN112 – Legal and accounting services
  • MN114 – Veterinary and other professional services.

We have also reduced the number of variables being collected for the Economic Survey of Manufacturing and Wholesale Trade surveys. We will no longer collect (or publish) information on manufacturing salaries and wages; and we won’t split wholesale stocks into stocks of ‘finished goods’ and ‘raw materials’.

Overview of changes by survey

Here is an outline of the changes that affect each of the three surveys.

See Methodology changes for more detailed information about the methods used to calculate each of the variables.

Quarterly Economic Survey of Manufacturing

We will use GST data to measure sales, purchases, stocks of raw materials, and stocks of finished goods, wherever possible. This will be supplemented by data collected directly (by questionnaire) from key contributors to each industry.

We will no longer collect or publish data on salaries and wages. Comparable data for total manufacturing is available from the Quarterly Employment Survey (published as part of the Labour Market Statistics release).

We will continue to publish quarterly sales, purchases, stocks of raw materials, and stocks of finished goods.

Quarterly Wholesale Trade Survey

We will use GST data to measure sales and total stocks wherever possible. This will be supplemented by data collected directly (by questionnaire) from key contributors to each industry. We will also collect stock data directly from a sample of businesses.

We will no longer collect or publish separate figures for stocks of finished goods and stocks of raw materials.

We will continue to publish quarterly sales and total stocks data.

Quarterly Services Survey

We will publish sales data for three new service industries for the first time from the September 2015 quarter:

  • MN111 – Scientific, architectural, and engineering services
  • MN112 – Legal and accounting services
  • MN114 – Veterinary and other professional services

We will continue to publish quarterly sales data for the two existing industries:

  • RS211 – Repair and maintenance
  • RS212 – Personal care, funeral and other services.

We will use GST data to measure sales wherever possible. This will be supplemented by data collected directly (by questionnaire) from key contributors to each industry. 

Scope and coverage

The scope and coverage of the Economic Survey of Manufacturing and the Wholesale Trade Survey have not changed from the previous design, while the coverage of the Selected Services Survey has been widened.

Population of interest

Economic Survey of Manufacturing

The target population is all kind-of-activity units (KAUs) on Statistics NZ’s Business Register (BR) that are operating in New Zealand and are classified to:

  • Australian and New Zealand Standard Industrial Classification 2006 (ANZSIC06) Division C – Manufacturing.
Wholesale Trade Survey

The target population is all KAUs on Statistics NZ’s BR that are operating in New Zealand and are classified to:

  • ANZSIC06 Division F – Wholesale Trade.
Selected Services Survey

The target population is all KAUs on Statistics NZ’s BR that are operating in New Zealand and are classified to the following New Zealand Standard Industrial Output Categories (NZSIOCs):

  • MN111 – Scientific, architectural, and engineering services
  • MN112 – Legal and accounting services
  • MN114 – Veterinary and other professional services
  • RS211 – Repair and maintenance
  • RS212 – Personal care, funeral and other services.  

Methodology changes

The series for these three surveys are produced using GST data wherever possible. We have done extensive work over the last few years on GST data and have established that it is a reliable measure of activity in these industries apart from the largest and most complex businesses.

We have developed robust methods of transforming the data, which is submitted at different frequencies, to a quarterly frequency. In addition, we have developed methods of detecting and removing sales and purchases of large capital items, which can at times occur in the GST data. These are not part of the conceptual measure of sales required for national accounts purposes.

We supplement the GST data for each of the series with survey data for large and complex businesses which meet the following criteria:

  • A $100 million significance rule – if an enterprise, or group of enterprises linked by ownership, have an annual GST turnover of more than $100 million.
  • A 3 percent industry dominance rule – if an enterprise makes more than a 3 percent contribution to annual total income for an industry.
  • All enterprises that have a significant level of activity across multiple industries.

More detail on the GST data assessment and methodology changes is available on request from info@stats.govt.nz.

Sales

Under the new design, we will only survey the largest and most complex businesses. For the remaining businesses, we will apply a statistical model to their GST data to determine sales.

GST sales for each non-surveyed business in the population is subject to modelling to: 

  • transform the GST data to a quarterly frequency; and
  • apportion data between members of GST groups.
Standardising the GST reference period to quarterly

Inland Revenue collects GST data as part of administering New Zealand’s taxation system. It is not primarily designed to produce economic statistics.

We have developed methods to transform the GST data, which can be submitted monthly, two-monthly, or six-monthly; to a quarterly frequency.

Sales for monthly returns are added together to get their quarterly sales. For two-monthly and six-monthly GST filers, some modelling and forward-casting is required to estimate a quarterly value.

Example 1 – For a business that files GST two-monthly, we may need to estimate their quarterly sales based on just two months data. To do this, we apply a modelling factor to their two-monthly sales, to estimate their quarterly sales.

Example 2 – For a business that files GST six-monthly, we may need to estimate their quarterly sales without any data from the period of interest. In this case, we disaggregate their sales into three two-monthly portions, and then apply a forward-casting factor to estimate their most recent sales. We then convert this two-monthly estimate into a quarterly estimate, as above.

Accounting for GST groups

Where one business reports GST on behalf of a number of other businesses that are linked by ownership (GST groups); the GST data must be apportioned between these different businesses.

For GST groups, data from the Inland Revenue’s employer monthly schedule is used as follows:

  • simple groups (where one group member has fewer than 80 percent of the group’s employees) – all sales are assigned to the dominant group member
  • complex groups (where each individual group member has more than 80 percent of the group’s employees) – GST sales are apportioned between group members in proportion with their share of the group's employees.

Purchases

Purchases data is collected and published for the Quarterly Economic Survey of Manufacturing. As with sales, we will only survey the largest and most complex businesses and use GST data to model purchases for the businesses that are not surveyed. The same modelling methods are used for GST purchases as are used for GST sales.

Stocks

Quarterly stock (inventory) measures are used in the production of gross domestic product (GDP). In the current sub-annual designs for manufacturing and wholesale trade stocks are primarily measured from data collected in the postal surveys.

Under the new design, we will continue to collect stocks data for large and complex businesses. However, there is no quarterly stocks data available for other businesses from administrative sources.

We have a range of methods to estimate stocks for businesses that are not surveyed. Different methods are better suited to different conditions depending on the size of the industry and the contribution of the surveyed units. The aim is to use the best method available for each industry.

The three methods used to estimate the value of stocks for a given industry are:

  • Benchmark to annuals: This approach is used where the surveyed businesses capture quarterly change in stocks (from one quarter to the next quarter), but do not accurately capture the level of stocks. Stock levels will be obtained by ‘rating up’ the aggregate stock series using data from the Annual Enterprise Survey.
  • Model from annuals: This approach is used for some smaller industries where the stock levels remain relatively consistent over time. A model is used to calculate the sub-annual stock estimates – using quarterly GST sales or purchases in combination with stocks obtained from the Annual Enterprise Survey. The model is updated on an annual basis when new data becomes available.
  • Stratified random sample: In industries where these methods are not suitable a stratified random sample survey is used. Sampled businesses receive a stocks-only questionnaire.

The following table details the method used for each industry:  

Industry  Stock estimation method used 
Meat and dairy product manufacturing  Benchmark to annuals 
Seafood processing Benchmark to annuals 
Fruit, oil, cereal, and other food manufacturing  Benchmark to annuals
Beverage and tobacco product manufacturing  Benchmark to annuals 
Textile, leather, clothing, and footwear manufacturing  Model from annuals 
Wood and paper product manufacturing  Benchmark to annuals 
Printing  Model from annuals 
Petroleum and coal product manufacturing  Benchmark to annuals
Chemical, polymer, and rubber product manufacturing  Benchmark to annuals 
Non-metallic mineral product manufacturing  Model from annuals 
Metal product manufacturing  Benchmark to annuals 
Transport equipment, machinery, and equipment manufacturing  Stratified random sample 
Furniture and other manufacturing Model from annuals 
Basic material wholesaling  Benchmark to annuals 
Machinery and equipment wholesaling  Stratified random sample 
Motor vehicle and motor-vehicle parts wholesaling  Benchmark to annuals 
Grocery, liquor, and tobacco product wholesaling Benchmark to annuals
Other goods wholesaling  Stratified random sample 
Commission-based wholesaling  Model from annuals 

Linking data from the new methodology with historic series

To ensure continuity, we will link data produced using the new methodology with previous manufacturing and wholesale data using the June 2015 quarter as the linking period. Each published industry has been back-cast with previously published percentage movements maintained. This has resulted in some level changes at the published industry level. In all cases these level changes are well within the sample error of the previous design. As we have maintained the changes at the industry level there are some small changes at the total manufacturing and total wholesale trade levels.

We also took the opportunity to make some revisions to unit-based records in some industries. Again this has changed the levels in those industries, but we have retained the previously published industry movements. The industries where this occurred were:

  • meat and dairy product manufacturing
  • seafood processing
  • fruit, oil, cereal, and other food manufacturing
  • petroleum and coal product manufacturing
  • grocery, liquor, and tobacco product wholesaling.

For the Selected Services Survey the existing series are being replaced with the new method back to 2004. The new methodology has provided a much more consistent time series than the previous design, which had high sample errors. We will be using postal data collected during the September 2015 quarter to assist with back-casting series as well is in creating the back series for the services industries added as part of the new design.

These changes will not result in any revisions to GDP statistics.

Seasonal adjustment

Seasonally adjusted and trend series have been produced using the X-13ARIMA-SEATS package developed by the U.S. Census Bureau. As we have maintained the previously published industry movements for manufacturing and wholesale trade data there is minimal change to the seasonally adjusted movements over time.

Data comparability over time

Figures 2–6 show the comparison between previously published data for Manufacturing and Wholesale Trade and the series using the new design.

Please note these back-cast series are released for information, and are based on data available at the time of compilation. Because we are still receiving and analysing data for the September 2015 quarter, there may be some changes. Therefore, treat the series presented in these graphs as provisional at this stage. 

Figure 2

Graph, Total manufacturing sales, Quarterly, June 2008 to June 2015

Figure 3

Figure 4 

Figure 5

Figure 6

New time series families

We have created new families and time series identifiers for the data produced using our new methodology. The old families will no longer be updated, and will be labelled as discontinued on Infoshare. The old series will still be accessible by selecting the ‘show discontinued’ option from Infoshare.

Quarterly Economic Survey of Manufacturing

The Infoshare family for the new data is:

  • Industry by variable – Subannual Financial Collection (Qtly–Mar/Jun/Sep/Dec).

This replaces:

  • Industry by variable (Qtly–Mar/Jun/Sep/Dec).

The new time series identifiers differ from the old ones by just one character – an ‘F’ has been inserted in the second position after the dot. For example:  

 Series description Old series identifier  New series identifier 
 Total manufacturing sales in current prices, unadjusted  MFGQ.SZ1CA  MFGQ.SFZ1CA
 Meat and dairy finished good stocks in constant prices, unadjusted  MFGQ.SA5KA  MFGQ.SFA5KA

Quarterly Wholesale Trade Survey

The new time series identifiers differ from the old ones by just one character: an ‘F’ has been inserted in the second position after the dot. For example:  

 Series description Old series identifier  New series identifier 
 Total wholesale trade sales in current prices, actual  WTSQ.SZ1CA WTSQ.SFZ1CA 
 Basic material wholesaling stocks in current prices, seasonally adjusted  WTGQ.SA9CS  WTSQ.SFA9CS

Selected Services Survey

We modified the time series identifiers to include the full NZSIOC industry codes rather than a single Alpha character for each series. For example: 

Existing series  New series  Industry  Actual/seasonally adjusted/trend 
 SSSQ.SA1A SSSQ.SFRS2111CA Repair and maintenance  Actual
 SSSQ.SA1S SSSQ.SFRS2111CS Repair and maintenance Seasonally adjusted
 SSSQ.SA1T SSSQ.SFRS2111CT  Repair and maintenance  Trend
 SSSQ.SB1A SSSQ.SFRS2121CA  Personal care, funeral and other services  Actual
 SSSQ.SB1S SSSQ.SFRS2121CS Personal care, funeral and other services Seasonally adjusted
 SSSQ.SB1T SSSQ.SFRS2121CT  Personal care, funeral and other services  Trend
  SSSQ.SFMN1111CA  Scientific, architectural, and engineering services Actual
  SSSQ.SFMN1111CS  Scientific, architectural, and engineering services Seasonally adjusted
  SSSQ.SFMN1111CT  Scientific, architectural, and engineering services Trend 
  SSSQ.SFMN1121CA  Legal and accounting services  Actual 
  SSSQ.SFMN1121CS  Legal and accounting services Seasonally adjusted
  SSSQ.SFMN1121CT  Legal and accounting services  Trend 
  SSSQ.SFMN1141CA  Veterinary and other professional services  Actual
  SSSQ.SFMN1141CS  Veterinary and other professional services Seasonally adjusted 
  SSSQ.SFMN1141CT  Veterinary and other professional services  Trend 
SSSQ.SZ1A   - Total services  Actual
SSSQ.SZ1S   - Total services  Seasonally adjusted 
SSSQ.SZ1T   - Total services  Trend 

Contact

For more technical information, please contact:

Citation
Statistics NZ (2015). Methodology changes to manufacturing, wholesale trade, and selected services statistics. Retrieved from www.stats.govt.nz.

ISBN: 978-0-908350-23-0
Published 27 November 2015 
Page updated 30 November 2015

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