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Economic Survey of Manufacturing: September 2013 quarter
Embargoed until 10:45am  –  09 December 2013
Data quality

Period-specific information
This section contains data information that has changed since the last release.

General information
This section contains information that does not change between releases.

Period-specific information

Sample errors for September 2013 quarter

Sample errors for sales in the September 2013 quarter
Industry Sample error for sales value Sample error for change in sales
Percent
Meat and dairy product manufacturing 0.0 0.0
Seafood processing 0.0 0.0
Fruit, oil, cereal, and other food manufacturing 4.5 3.5
Beverage and tobacco product manufacturing 0.0 0.0
Textile, leather, clothing, and footwear manufacturing 8.4 6.1
Wood and paper product manufacturing 3.0 1.0
Printing 14.3  28.7
Petroleum and coal product manufacturing 0.0 0.0
Chemical, polymer, and rubber product manufacturing 2.3 1.8
Non-metallic mineral product manufacturing 5.6 1.1
Metal manufacturing 7.5 2.4
Transport equipment; machinery and equipment manufacturing 3.9 4.3
Furniture and other manufacturing 5.9 3.9
Total manufacturing 1.1 0.7

Industries with zero sample error are full-coverage industries. In these industries, all large firms are surveyed and all small to medium-sized firms are modelled using administrative data from Inland Revenue.

Imputation for September 2013 quarter

Imputed values as a percentage of sales in the September 2013 quarter
Industry Non-response Tax modelled
Percentage of sales
Meat and dairy product manufacturing 2.6 5.5
Seafood processing 6.6 12.3
Fruit, oil, cereal, and other food manufacturing 10.0   10.2 
Beverage and tobacco product manufacturing  7.5 15.4
Textile, leather, clothing, and footwear manufacturing 10.9  13.1 
Wood and paper product manufacturing 10.1

10.7

Printing    7.7   14.6
Petroleum and coal product manufacturing  0.0   0.9
Chemical, polymer, and rubber product manufacturing 11.7     8.8 
Non-metallic mineral product manufacturing 13.7   11.1
Metal manufacturing  7.2   14.3
Transport equipment; machinery and equipment manufacturing 13.6

  14.7 

Furniture and other manufacturing  17.2   13.2
Total manufacturing   7.3   9.6

Response rate

The response rate applies to the postal sample and gives the proportion of sales obtained from survey responses (compared with being imputed). The Economic Survey of Manufacturing (ESM) has a target response rate of 85 percent.

The response rate achieved for the September 2013 quarter was 93 percent.

General information

Measurement errors

The ESM applies imputation methods for estimating values for small firms and non-response. Like all statistical surveys, it is subject to measurement errors, including sample errors and non-sample errors. These measurement errors affect the accuracy of the published statistics.

Sample errors

The ESM is primarily a postal survey and is designed to give statistics at the following levels of accuracy (at the 95 percent confidence interval limit):

  • 5 percent for sales, salaries and wages, and value added at the total manufacturing level
  • 10 percent for sales, salaries and wages, and value added at the published industry level, where value added is calculated as follows:
    value added = sales – purchases + stock change

This means, for example, that there is a 95 percent chance that the true value of total manufacturing sales lies within 5 percent of the published estimate.

Sample errors, at the 95 percent confidence interval limit, are calculated each quarter for absolute values and for changes in value from the previous quarter.

Small firms

Small to medium-sized firms are generally not surveyed. Their variables are instead modelled from administrative data from Inland Revenue. Ratios calculated from the postal sample responses are applied to the administrative data to provide estimated values.

Non-response imputation

Although attempts are made to achieve a 100 percent response rate, in practice this does not occur. Values for non-responding businesses are estimated using a range of methods, including:

  • regression imputation
  • historic imputation
  • mean imputation.

Regression imputation involves estimating the variable of interest from the unit's administrative data (GST sales), based on the relationship shown by similar businesses.

Historic imputation involves multiplying their response in the previous period by a non-response factor. The non-response factor is the average movement over the quarter for similar businesses.

Mean imputation involves estimating a value for a unit by using the average value for a set of similar businesses.

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.

Seasonally adjusted and trend values are re-estimated quarterly when each new quarter’s data becomes available. Figures are therefore revised, with the largest changes normally occurring in the latest quarters. Estimates are produced by the X-12-ARIMA seasonal adjustment program, developed at the U.S. Census Bureau.

See seasonal adjustment within Statistics NZ for more information.

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, the calculation method for total sales was changed from direct to indirect (whereby component industries are individually adjusted before being summed). Direct and indirect adjustment methods are both used, according to appropriateness.

Components are seasonally adjusted using the following methods:

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, 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.

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 are calculated from ESM sales and finished good stock changes (deflated by sub-indexes of the producers price index).

ESM volumes are supplemented 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.

More information

See Economic Survey of Manufacturing for more information.

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 beyond our control. 

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