Series
Economic Survey of Manufacturing
en-NZQMS; Manufacturing Survey; Quarterly Manufacturing Survey; ESM;
en-NZStatistics New Zealand
en-NZThe Economic Survey of Manufacturing (ESM) is designed to provide short-term economic indicators for the manufacturing sector. In addition, the data is used to compile the manufacturing sector component of quarterly national accounts.
en-NZThe purpose of the Economic Survey of Manufacturing is to collect statistics from a cross section of New Zealand businesses involved in manufacturing. The financial data collected by this survey is used in the production of a range of economic indicators. An example is Gross Domestic Product (GDP), which measures economic activity in New Zealand. These statistics help government and other organisations in planning and decision making.
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Use of manufacturing data in quarterly national accounts A key use of the Economic Survey of Manufacturing is in the calculation of manufacturing value added for the compilation of quarterly Gross Domestic Product (GDP).
Base year manufacturing value added is extrapolated using volume indexes. For each ANZSIC division, volume indexes are calculated from deflated sales and the deflated finished goods stock change. Sub-indexes from the Producers Price Index (PPI) are used for deflating QMS sales and finished goods stocks.
QMS data is supplemented with production data for the following industries: Meat and dairy product Petroleum and industrial chemical Basic metal.
1958 - 1977 From 1958 to 1977 Statistics New Zealand conducted a quarterly survey of manufactured stocks. It was compiled on a sample basis and covered approximately 10 percent of all factories included in the annual Census of Industrial Production (now Manufacturing).
1977 - 1982 The subsequent survey commenced in June 1977. As an economic survey of manufacturing statistics, it was a more sophisticated base for economic projections than that available before 1977. The system was automated in 1981.
1982 - 1991 The survey was revised in 1982. A statistically representative sample of manufacturing units selected from the 1979 Census of Manufacturing replaced one third of the existing sample. The benchmarks used to rate-up sample totals were recalculated based on the 1979 Census.
1991 - 1998 The survey was revised again in 1991. The Department introduced a revised sample of businesses and made other technical changes to the Quarterly Economic Survey of Manufacturing from the March quarter 1991. The changes made resulted in improved statistics on manufacturing in New Zealand.
In order to provide a consistent longer term historical series, a compatible revised series going back over previous years was calculated. In contrast to the previous survey sample, which was based on the 1979 Census of Manufacturing, the revised sample was selected from the Statistics New Zealand Business Frame, a comprehensive and up to date list of all businesses in New Zealand. The use of this directory as the sample frame ensured a comprehensive coverage of the manufacturing sector and allowed for the timely inclusion of new manufacturing businesses.
The previous survey sample design, which was introduced in 1982 was improved to better reflect the manufacturing sector in 1991. The survey population of manufacturers was also extended to cover manufacturing businesses with less than 2 full-time equivalent persons engaged. These small businesses were excluded from the previous survey. The revised series of statistics for quarters prior to the introduction of the new survey included estimates for this extension to the population coverage, in order to ensure continuity of the series.
From March 1996 data onwards, the Economic Survey of Manufacturing was published according to the Australian New Zealand Standard Industrial Classification (ANZSIC). NZSIC data continued to be available until the survey was redesigned according to ANZSIC. Because of differences between the ANZSIC and NZSIC populations there was some under coverage in the published ANZSIC series.
1998 - 2001 From the June 1998 quarter, the overall number of variables collected from the Economic Survey of Manufacturing was reduced. Some variables were added to the survey for the Quarterly Profit Survey project. These were:
Variables which were no longer collected from the June 1998 quarter were:
The two main changes which affected the data published from June 1998 quarter were:
The sample was not reselected at this time.
Some formatting changes were made to the questionnaire in the September 1998 quarter.
2001 - The previous QMS series was based on a statistical sample that was first surveyed in the December 1992 quarter. The last quarter of the old QMS was June 2001. The QMS was a panel survey. Businesses had one chance of selection at their birth and those that were introduced then remained in the sample until either they ceased operation in the manufacturing industry, or the panel was reselected.
Over time, sample designs become less effective in representing the current population as a whole. While the original samples are maintained to include a representative selection of new businesses, periodically panel samples need to be refreshed to reflect changes in the composition of the population.
The QMS has been redesigned to provide better and more up-to-date coverage of the Manufacturing population. The new QMS design will allow changes in the composition of the population over time to be better represented in the survey.
Changes to the QMS include:
These changes have been made to ensure that the future estimates produced from the QMS accurately reflect activity in the manufacturing sector of the New Zealand economy.
During the June 2001 quarter, the QMS was calculated on both the old and new basis. The primary purpose of this "dual run" was to enable the comparison of the surveys run under the previous and redesigned methods, so that the two series could be linked at a single point in time. This facilitated the production of an analytical back series for the redefined output industries. Another important function of the dual run was to measure level shifts in the results coming from the two different designs so that the results can be verified and explained.
The content of the questionnaire was reviewed with a focus on meeting the core data requirements of users, while being mindful of the burden that such collection places on respondents. The number of variables collected on the questionnaire has, as a consequence, been significantly reduced. The following items have been removed from the questionnaire from the June 2001 quarter:
During consultation with users, it was determined that the existing Additions to Fixed Assets question was of limited use without a corresponding Disposals question also being asked. Users (both internal and external) identified Net Additions to Fixed Assets as being the information which was of most use to them. As a consequence, the following question has been added to the questionnaire from the June 2001 quarter:
The main industry affected by the population adjustments resulting from the change to an ANZSIC design was the Printing, Publishing and Recorded Media industry, which saw the level of sales recorded rise by $195 million for the June 2001 quarter as a result. Activities which have been brought into the scope of this industry under the ANZSIC design include:
The only other industry affected by the population expansion was Machinery and Equipment Manufacturing, which rose by $28 million. Activities which have been brought into the scope of this industry under the ANZSIC design include:
2008 Dairy industry quarters were standardised - Before December 2008, data for most dairy values were calculated on a non-standard quarter. This meant that the June quarter, for example, included dairy values for the months of March, April and May, while the standard June quarter includes April, May and June. From the June 2011 quarter onwards, Statistics NZ publishes standard quarter data. revising previously published data back to December 2008.
2010-11 The Australian and New Zealand Standard Industry Classification (ANZSIC 2006) was implemented in the Economic Survey of Manufacturing. Prior to April 2011, data had been collected, and information published, on an ANZSIC96 basis.
The process of implementing ANZSIC06 began with initial planning in July 2008 and ended with the release of quarterly ANZSIC06-based QMS estimates for the December 2010 quarter in April 2011.
The basic method of selecting a sample of businesses based on industry and size, and then weighting it to represent the population of businesses, did not change. There were some changes to sample selection and data collection for the surveys:
From April 2010 to September 2010, data was collected for the ANZSIC96 sample as well as for the new ANZSIC06 sample, providing an overlap to allow the old and new survey estimates to be linked. This ‘dual run’ was used to compare the series and assess the practical differences between the two different samples’ outputs. To ensure that outputs are useful to users, procedures are applied to the historical data collected on an ANZSIC96 basis to produce suitable surrogate ANZSIC06 time series for past time periods. The proportional method was used for manufacturing.
The expression base for the constant price estimates was also updated to September 2010 quarter prices.
Under ANZSIC96, 15 industries were surveyed. For ANZSIC06, the number was reduced to 13.
A paper discussing this implementation, Implementing ANZSIC 2006 in manufacturing, wholesale, and selected other services, is available.
2012 Additions and disposal of fixed assets ceased to be collected from the December 2012 quarter.
2015 We made changes to the methodology used in the Economic Survey of Manufacturing beginning with the Economic Survey of Manufacturing: September 2015 quarter, released on 8 December 2015. The changes are intended to:
Under the old design, we surveyed all the large businesses in each industry, plus a sample of medium-sized businesses. We supplemented this with modelled tax data for the smaller businesses.
Under the new design, we 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 eliminated most of the small and medium-sized businesses from the survey entirely.
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.
We have also reduced the number of variables being collected for the Economic Survey of Manufacturing. We will no longer collect or publish information on manufacturing salaries and wages.
See Methodology changes to manufacturing, wholesale trade, and selected services statistics for more detailed information about the methods used to calculate each of the variables.
2016 We made changes to the questionnaire used in the Economic Survey of Manufacturing beginning with the Economic Survey of Manufacturing: June 2016 quarter, released on 7 September 2016. We increased the number of variables being collected for the Economic Survey of Manufacturing. We began to collect information on earnings before interest and taxation (EBIT), and information on salaries and wages.
3 Quarterly
Quarterly National Accounts
Studies
Coverage
Economic Survey of Manufacturing
The Economic Survey of Manufacturing (ESM) provides short-term economic indicators for the manufacturing sector. The data is also used to compile the manufacturing sector component of the quarterly national accounts. Published values exclude Goods and Services Tax (GST).
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Methodology
Changes to the methodology for the Economic Survey of Manufacturing
See Economic Survey of Manufacturing: September 2015 quarter for changes we made to the methodology used in the Economic Survey of Manufacturing. The changes:
- make greater use of administrative data sources
- reduce respondent burden
- introduce a consistent methodology and processing system across the Economic Survey of Manufacturing, Wholesale Trade Survey, and quarterly Selected Services Survey
- enable the delivery of information at lower levels of detail for research and customised requests
- improve the quality of the published series.
Under the old design, we surveyed all the large businesses in each industry, plus a sample of medium-sized businesses. We supplemented this with modelled tax data for the smaller businesses.
Under the new design, we use administrative data (goods and services tax (GST) data, sourced from Inland Revenue) wherever possible, and supplement this by surveying only the largest and most complex businesses. With this new design, we have eliminated most small and medium-sized businesses from the survey entirely.
The methodology changes improve 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 on a smaller sample to represent the entire population.
We have also reduced the number of variables being collected for the Economic Survey of Manufacturing. We no longer collect or publish information on manufacturing salaries and wages.
See Methodology changes to manufacturing, wholesale trade, and selected services statistics for more detailed information about the methods used to calculate each of the variables.
Population
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.
Statistical design
The series we publish for this survey are produced using GST data wherever possible. After extensive work on GST data, we established that it is a reliable measure of activity in these industries apart from the largest and most complex businesses.
We supplement the GST data for each series with survey data for large and complex businesses that 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.
Sales and purchases
We have developed robust methods of transforming the GST 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 and purchases required for national accounts purposes.
Where a business reports GST on behalf of other businesses (referred to as GST groups), we apportion GST data between these different businesses using data from Inland Revenue’s employer monthly schedule.
Stocks
Under the new design, we collect stocks data for large and complex businesses. However, no quarterly stocks data is 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.
See Methodology changes to manufacturing, wholesale trade, and selected services statistics for more detail on the GST data assessment and methodology changes.
Non-response imputation
Postal data imputation
Although we attempt to achieve a 100 percent response rate, in practice this does not occur. We estimate values for these non-responding businesses using methods that include:
- historic imputation
- ratio imputation
- mean imputation.
Historic imputation involves multiplying the unit's response in the previous period by a non-response factor. The non-response factor is the average movement over the quarter for similar businesses.
Ratio imputation involves estimating the variable of interest from the unit's administrative data (GST sales), based on the relationship shown by similar businesses.
Mean imputation involves estimating a value for a unit by using the average value for a set of similar businesses.
Tax data imputation
In the administrative data (GST) we have late filers, which are not received in time for publication. We impute the GST data using the historic and mean methods described above.
We also use median imputation for a small number of units, where we take a median response from a unit's previous GST history.
Measurement errors
Model errors
Statistics NZ uses models to standardise the GST reference period to quarterly, which may include model errors. These errors measure the variability that occurs due to a statistical model being applied to produce estimates. It quantifies the cumulative effect of model 'imperfections'.
Other measurement errors
Errors can arise from biases in the patterns of response and non-response, inaccuracies in reporting by respondents, and errors in recording and coding data. The size of these errors is difficult to quantify. We revise data if significant errors are detected in subsequent quarters.
Seasonally adjusted and trend series
For any series, the survey estimates can be broken down into three components: trend, seasonal, and irregular. While seasonally adjusted series have the seasonal component removed, trend series have both the seasonal and irregular components removed. This reveals turning points and the underlying direction of quarterly movement.
We re-estimate seasonally adjusted and trend values quarterly when each new quarter’s data becomes available. Figures are therefore revised, with the largest changes normally occurring in the latest quarters. The seasonally adjusted and trend series are produced using the X-13ARIMA-SEATS package developed by the U.S. Census Bureau.
See seasonal adjustment within Statistics NZ
Seasonally adjusted series
Seasonal adjustment removes the estimated impact of regular seasonal events, such as annual cycles in agricultural production, pre-Christmas shopping, and summer holidays, from statistical series. This makes figures for adjacent periods more comparable.
For the ESM, removing the purchasing monopoly in the dairy industry in mid-2002 caused an abrupt change to seasonal variation in the meat and dairy industry. In response, we changed the calculation method for total sales from direct to indirect (whereby component industries are individually adjusted before being summed). We use both direct and indirect adjustment methods, according to appropriateness.
We use the following methods to seasonally adjust components:
| Component | Method |
|---|---|
| Sales volumes | |
| Total manufacturing | Indirect |
| Excluding meat and dairy product manufacturing | Direct |
| Meat and dairy product manufacturing | Direct |
| Sales values | |
| Total manufacturing | Direct |
| Excluding meat and dairy product manufacturing | Direct |
| Meat and dairy product manufacturing | Direct |
Trend series
Trend estimation removes the estimated impact of regular seasonal events and irregular short-term variation from statistical series. Trend estimates reveal the underlying direction of movement in a series, and are likely to indicate turning points more accurately than are seasonally adjusted estimates.
Standardising dairy industry quarters
Before December 2008, we calculated data for most dairy values on a non-standard quarter. This meant that the June quarter, for example, included dairy values for the months of March, April, and May, while the standard June quarter includes April, May, and June. From the June 2011 quarter onwards, we publish standard quarter data, revising previously published data back to December 2008.
Use in national accounts
A key use of the ESM is in the quarterly gross domestic product (GDP) for calculating manufacturing ‘value added’ (value of output after the cost of input materials and services has been deducted). GDP base-year manufacturing value added is moved forward using volume indexes that we calculate from ESM sales and finished-goods stock changes (deflated by sub-indexes of the producers price index – published as part of Business Price Indexes as of March 2015 quarter).
We supplement ESM volumes with quantity production data for the following industries: meat and dairy product manufacturing
- petroleum and industrial chemical
- manufacturing
- basic metal manufacturing.
The ESM is also used in the expenditure measure of GDP for compiling stock-change values at current and constant prices.
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