Background to the survey
The Retail Trade Survey (RTS) is designed to provide short-term economic indicators of the retail trade sector. In addition, the data is used for the compilation of the retail trade sector component of quarterly national accounts (on the production side) and in the compilation of household consumption expenditure (on the expenditure side). The survey was last redesigned for the September 2003 quarter. For more details about the redesign refer to Retail Trade Survey – Redesign: September 2003 and the Retail Trade Survey – Survey design information paper.
The target population for this survey is all geographic units (GEOs) operating in New Zealand that are classified on Statistics New Zealand's Business Frame to the Australian and New Zealand Standard Industrial Classification (ANZSIC06) below:
- retail trade (ANZSIC division G)
- accommodation and food services (ANZSIC division H)
A geographic unit is included in an industry based on its predominant activity in terms of sales. For example, a footwear store will sell shoes and boots, but it may also sell bags and other accessories. The store will be classified to the footwear industry if most of its sales income comes from the sale of shoes and boots. Data is published for 15 industries, which are defined as follows:
|ANZSIC06 industries, class codes, and descriptions for the Retail Trade Survey|
|RTS industry and description used in published tables
||ANZSIC06 class and description|
|G1110 Motor vehicles and parts
||G391100 Car retailing|
|G391200 Motor cycle retailing|
|G391300 Trailer and other motor vehicle retailing|
|G392100 Motor vehicle parts retailing|
|G392200 Tyre retailing|
||G400000 Fuel retailing|
|G1210 Supermarket and grocery stores
||G411000 Supermarkets and grocery stores|
|G1221 Specialised food
||G412100 Fresh meat, fish, and poultry retailing|
|G412200 Fruit and vegetable retailing|
|G412900 Other specialised food retailing|
||G412300 Liquor retailing|
|G1311 Furniture, floor coverings, houseware, textiles
||G421100 Furniture retailing|
|G421200 Floor coverings retailing|
|G421300 Houseware retailing|
|G421400 Manchester and other textile goods retailing|
|G1312 Electrical and electronic goods
||G422100 Electrical, electronic and gas appliance retailing|
|G422200 Computer and computer peripheral retailing|
|G422900 Other electrical and electronic goods retailing|
|G1313 Hardware, building, and garden supplies
||G423100 Hardware and building supplies retailing|
|G423200 Garden supplies retailing|
|G1321 Recreational goods
||G424100 Sport and camping equipment retailing|
|G424200 Entertainment media retailing|
|G424300 Toy and game retailing|
|G424400 Newspaper and book retailing|
|G424500 Marine equipment retailing|
|G1322 Clothing, footwear, and accessories
||G425100 Clothing retailing|
|G425200 Footwear retailing|
|G425300 Watch and jewellery retailing|
|G425900 Other personal accessory retailing|
|G1330 Department stores
||G426000 Department stores|
|G1340 Pharmaceutical and other store-based retailing
||G427100 Pharmaceutical, cosmetic and toiletry retailing|
|G427200 Stationery goods retailing|
|G427300 Antique and used goods retailing|
|G427400 Flower retailing|
|G427900 Other store-based retailing nec|
|G1350 Non-store and commission-based retailing
||G431000 Non-store retailing|
|G432000 Retail commission-based buying/selling|
|H2120 Food and beverage services
||H451100 Cafes and restaurants|
|H451200 Takeaway food services|
|H451300 Catering services|
|H452000 Pubs, taverns and bars|
|H453000 Clubs (hospitality)|
|Note: nec = not elsewhere classified|
The survey population is stratified according to:
- ANZSIC06 RTS industries, as shown above
- size (in terms of rolling-mean employment)
- turnover (annualised GST sales).
Each industry contains between two and four substrata. Because of the contribution that large units make to the economic activity within each industry, they are all included in the sample. A portion of the remaining medium to large units is also included in the sample. In addition, small to medium-sized businesses have their data modelled from administrative data (GST) sourced from Inland Revenue. The Inland Revenue data have been forecast two to three months ahead. All retailing GEOs belonging to a selected 'enterprise' are included.
The sample is based on approximately 52,000 retail outlets in New Zealand. Around 2,500 enterprises (between 8,000 and 8,500 GEOs) have been selected in the RTS postal sample. The postal sample is supplemented by GST data representing smaller retailers, approximately 26,400 enterprises (26,500 GEOs).
Sample maintenance is the process that maintains the sample over time, to reflect 'births', 'deaths' and other structural changes identified on the Business Frame. The information for Business Frame changes can be from a variety of sources, including GST registrations and respondent contact.
New enterprises are identified when they register for GST. Once a month, the new enterprises are selected into the sample using the same criteria as for the original sample. These are referred to as births. When an enterprise ceases trading, its retailing GEOs are removed from the survey. These are referred to as deaths.
Enterprises can also enter or leave the survey sample if they are reclassified to a different industry. Reclassifications occur when an enterprise changes its main form of activity (eg from wholesale trade to retailing). These are usually identified in the Annual Frame Update Survey conducted in February of each year.
The sample for the RTS is reselected each month to ensure the sample reflects changes occurring in the retailing population.
Errors in the survey are divided into two classes:
Non-sampling error includes errors arising from biases in the patterns of response and non-response, inaccuracies in reporting by respondents, and errors in the recording and coding of data. The size of these errors is difficult to quantify. Statistics may be revised if significant errors are detected in subsequent quarters.
Sampling error is a measure of the variability that occurs by chance because a sample, rather than an entire population, is surveyed.
Australian and New Zealand Standard Industrial Classification system – New Zealand version 2006.
A register of all economically significant businesses operating in New Zealand. The population of the RTS is drawn from the Business Frame.
Deflators are indexes that measure the rate of price change of goods and services sold by each RTS industry. Deflators are not calculated for the subtotal or all industries total. For information on how deflators are calculated follow the link from the technical notes of this release on the Statistics NZ website.
An enterprise is a business entity operating in New Zealand, either as a legally constituted body such as a company, partnership, trust, local or central government trading organisation, or a self-employed individual.
A geographic unit is a subdivision of an enterprise. It is a separate operating unit engaged in New Zealand in one, or predominantly one, kind of economic activity from a single physical location or base.
Per head of population
The population measure used for the RTS is the estimated residential population. It excludes short-term visitors to New Zealand.
Sales volumes expressed in March 2010 quarter prices
A constant price estimate, from which the portion of the current price sales' movement caused by price changes has been removed.
Use of retail trade data in quarterly national accounts
A key use of the RTS is in the calculation of retail trade value added for the compilation of quarterly gross domestic product (GDP).
The quarterly GDP retail trade indicator uses retail sales volumes expressed in March 2010 quarter prices, by industry series from the RTS. These series are chain-linked to give constant price sales at the ANZSIC06 working industry level. The chain-linking weights are calculated using annualised quarterly current prices sales by RTS industry.
Seasonally adjusted series
The X-12-ARIMA package has been used to produce the seasonally adjusted estimates and trend estimates for sales in all subdivisions. Seasonal adjustment aims to eliminate the impact of regular seasonal events (such as annual cycles in agricultural production, winter, or annual holidays) on time series. This makes the data for adjacent months more comparable.
All seasonally adjusted figures are subject to revision each month. This enables the seasonal component to be better estimated and removed from the series.
For any series, the survey estimates can be broken down into three components: trend, seasonal, and irregular. While seasonally adjusted series have had the seasonal component removed, trend series have had both the seasonal and the irregular components removed. 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.
The trend series are calculated using the X-12-ARIMA seasonal adjustment package. They are based on a 13-term or 23-term moving average of the monthly seasonally adjusted series, and a five-term or seven-term moving average of the quarterly seasonally adjusted series, with an adjustment for outlying values.
Trend estimates towards the end of the series incorporate new data as they become available and can therefore change as more observations are added to the series. Revisions can be particularly large if an observation is treated as an outlier in one month, but is found to be part of the underlying trend as further observations are added to the series. Typically, only the estimates for the most recent month will be subject to substantial revisions.
In the October 2003 month, the RTS sample of geographic units changed. Data prior to the October 2003 month is an analytical back series, which has been derived to preserve industry movements at the national level. However, previously published regional movements may not have been preserved. Care should be taken when interpreting movements of regional series around the period of the redesign.
For more information, follow the link from 'Technical notes' of this release on the Statistics NZ website.
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