Retail Trade Survey (Quarterly)

Population Our target population for this survey is all GEOs operating in New Zealand that are classified on Statistics NZ's Business Frame to the Australian and New Zealand Standard Industrial Classification 2006 (ANZSIC06) below: retail trade (ANZSIC division G) accommodation and food services (ANZSIC division H) Collection instruments Quarterly survey of retail trade Goods and services tax returns Payday filing (PAYE returns) Industry descriptions A GEO is included in an industry based on its predominant activity in terms of sales. For example, a petrol station will sell petrol and diesel, but it may also sell car parts and grocery items. We classify the store to the fuel retailing industry if most of its sales income comes from the sale of fuel. We publish data for 15 industries, which are defined as follows: ANZSIC06 industries, class codes, and descriptions for RTS RTS industry and description used in published tables ANZSIC06 class and description G1110 Motor vehicle and parts G391100 Car retailing G391200 Motor cycle retailing G391300 Trailer and other motor vehicle retailing G392100 Motor vehicle parts retailing G392200 Tyre retailing G1120 Fuel 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 G1222 Liquor 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 H2110 Accommodation H440000 Accommodation 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 Sample design We stratify the survey population according to: industries defined by the ANZSIC-based ANZIND classification at the inter-industry level size (in terms of rolling-mean employment) turnover (annualised GST sales). Each ANZIND inter-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. We also include a portion of the remaining medium to large units 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 are forecast two months ahead. We include all retailing GEOs belonging to a selected 'enterprise'. The sample is based on approximately 52,000 retail outlets in New Zealand. We select around 2,500 enterprises (between 8,000 and 8,500 GEOs) 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 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. We identify new enterprises when they register for GST. Once a quarter, 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, we remove its retailing GEOs 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). We usually identify these in the Annual Frame Update Survey conducted in February of each year. Sample reselection We select the sample for the RTS each quarter to ensure the sample reflects changes occurring in the retailing population. Measurement errors Errors in the survey are divided into two classes: Non-sampling error Non-sampling error includes errors arising 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 may revise if significant errors are detected in subsequent quarters. Sampling error Sampling error is a measure of the variability that occurs by chance because a sample, rather than an entire population, is surveyed. Use of retail trade data in quarterly national accounts A key use of the RTS is in calculating retail trade value added for compiling quarterly gross domestic product (GDP). The quarterly GDP retail trade indicator uses the 'retail sales volumes expressed in September 1995 quarter prices, by industry' series from the RTS. These series are chain-linked to give constant-price sales at the ANZSIC06 working-industry level. We calculate the chain-linking weights using annualised quarterly current-price sales, by RTS industry. Seasonally adjusted series We produce the seasonally adjusted and trend series using the X-13-ARIMA-SEATS package developed by the U.S. Census Bureau, to comply with international best practice. 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 quarters more comparable. We revise all seasonally adjusted figures each quarter. This enables the seasonal component to be better estimated and removed from the series. The X-13-ARIMA-SEATS seasonal adjustment package is very robust. However, problems occur when there is an abrupt change in the seasonal variation, as with other seasonal adjustment packages. Estimated trend For any series, we break the survey estimates down into three components: trend, seasonal, and irregular. While seasonally adjusted series have the seasonal component removed, trend series have 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. We calculate the trend series using the X-13-ARIMA-SEATS seasonal adjustment package. They are based on 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 we treat an observation as an outlier in one quarter, but find it to be part of the underlying trend as further observations are added to the series. Typically, only the estimates for the most-recent quarter will be subject to substantial revisions. Retail Trade Survey deflators The RTS deflators that appear in table 13 measure change in the prices of goods and services sold by businesses in the 15 retail industries. We can explain movements in actual retail sales values by changes in price, and by changes in volume. The deflators are used to remove the effect of price change, which allows change in the volume of retail sales to be estimated. The deflator for each industry consists of a 'basket' of indexes, drawn mainly from the consumers price index (CPI). The CPI indexes and other indicators in each deflator's basket represent the goods and services sold by the industry. Each good or service is weighted to reflect the relative importance of the mix of goods and services sold by the industry. See Retail Trade Survey deflator weights for more information about the RTS deflators. Regional estimates In the October 2003 month, we changed the RTS sample of GEOs. ANZSIC06-based regional data is not available before the December 2003 quarter. en-NZ