Retail Trade Survey Quarterly - Current

PDF Data Dictionary

Series Description

Title

Retail Trade Survey Quarterly - Current

Alternate Title

RTS

Rights

Statistics New Zealand

Abstract

The Retail Trade Survey measures the sales turnover and stock levels of a wide range of businesses that provide household and personal goods and services. Retailers include car yards, petrol stations, supermarkets, department stores, hardware retailers, cafes and restaurants, hotels and motels, and other store-based and non-store-based retailers. Retail Trade Survey statistics are published quarterly for the following variables: sales value of goods and services, by industry, and region; sales volume, by industry; value of stock held, by industry.

Purpose

The purpose of the survey is to provide short-term economic indicators of the retail trade sector. In addition, the data is used for compiling the retail trade sector component of the quarterly national accounts (on the production side) and in compiling household consumption expenditure (on the expenditure side). Results from the survey provide a valuable guide to retail trading and general economic conditions within New Zealand

Frequency
  1. Quarterly
Significant events impacting this study series

June 2015 – On the 30 October 2015 we released eight new percentage change series in the Retail Trade Survey. These include percentage change for the total and core retailing sales, in current and deflated prices, (Qtrly-Mar/Jun/Sep/Dec). Four of the series includes actual percentage change from the same period of previous year, while the remaining four series include seasonal adjusted percent change from the previous period which are recalculated each quarter.

September 2014 - upgraded the seasonal adjustment package for the retail trade series from X-12-ARIMA to X-13-ARIMA-SEATS, 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.

March 2012 - Data was revised for the March 2012 Quarter Statistics New Zealand has revised the release for Retail Trade Survey March 2012 quarter, first published on 14 May 2012. The previously produced time series estimates up to the December 2011 quarter, for supermarkets and grocery stores, core retail, and total retail, have been subject to revision. The revised release can be found at Retail Trade Survey March 2012 quarter. Following the release of retail trade statistics for the March 2012 quarter, a number of economic commentators queried the extent of the sales volumes decline in the supermarket and grocery stores. Statistics New Zealand holds itself to the highest standards and considered we had an obligation to further investigate the figures. Additional information and investigation allowed us to determine we had an anomalous result, which did not reflect the economic reality and therefore needed to be revised.

December 2010 - The change from a monthly to a quarterly collection meant there was a slight difference in the way the survey population is measured. Instead of the survey population being reviewed and adjusted every month, this is now done at the end of the quarter. Analysis has been done on the effect of this change to the survey population, which was found to be minimal. Therefore, no adjustment has been made to the survey to account for the slight variation in population between three monthly collections and one quarterly. No changes were made to the previously published actual quarterly retail data. Monthly retail trade data is not available after December 2010.

June 2010 - The Retail Trade Survey was updated to use a new version of the industrial classification from the June 2010 quarter. The industrial classification used by the Retail Trade Survey was updated to the Australian and New Zealand Standard Industrial Classification 2006 (ANZSIC06) from the June 2010 quarter. Before this, a 1996 version of the classification had been used. This was done to reflect changes that have occurred in the structure and composition of industries since the previous version of the classification (ANZSIC96) was developed. As part of this update the number of published retail industries has reduced from 24 to 15. An analytical back series has been produced, to retain comparability over time, and is available from 1995 for sales and stocks by industry, and from 2003 for regional sales, and sales volumes by industry. The Retail Trade Survey (RTS) backcast series was produced using two methods. The most recent portion of data (from August 2003 to March 2010) was calculated by re-weighting unit record data collected under the ANZSIC96 Retail Trade and Wholesale Trade Surveys. This method provides a relatively robust estimate of the historic time series. Unit record data is not available before August 2003, so the earliest portion of the backcast series (from 1995 to 2003) was estimated using a proportional method. The backcast sales volume series were calculated by splitting the ANZSIC06 data into its ANZSIC96 components, and deflating these by applying either ANZSIC96 retail trade deflators, or relevant CPI or PPI indexes. The resulting deflated subsets were then added together into their ANZSIC06 industries. Scaling factors were applied to the backcast data to remove any discontinuity in level.

September 2003 – The survey was redesigned for the September 2003 quarter. For more details about the redesign see:

Retail Trade Survey – Redesign: September 2003

Retail Trade Survey – Implementation of new survey design.

Usage and limitations of the data

The objective of the Retail Trade survey is to provide timely, short term, key indicator statistics on the retail sector of the economy. This provides a useful short term indicator for economic analysts and policy makers.

Retail sales are used in forecasting consumer demand, economic growth, inflation, interest rates, imports, the balance of payments and the exchange rate and are used in formulating government policy and Reserve Bank monetary policy. Retail sales are also used in comparison with business and regional sales by external users.

The main limitations of the Retail Trade data are the unavailability of a commodity breakdown, and sample error and confidentiality concerns with detailed data release. Sales are classified by industry and specific sales by commodity are not available. Sample errors and confidentiality may limit the availability of the data at detailed levels of ANZSIC and by region below Regional Council Areas.

Main users of the data

EXTERNAL: The Treasury, Reserve Bank, retail and wholesale merchants associations, businesses, regional councils, news media, economic agencies (NZIER, Berl, trading banks). INTERNAL: National Accounts Division, Marketing and Sales division, Customer services division.

Publication

Retail Trade Subject Page

Information paper

Implementing ANZSIC06 in the Retail Trade Survey

Information paper

Impact of the 22 February 2011 earthquake on the Retail Trade Survey

Information paper

Changes to Retail Trade Survey seasonal adjustment

Deflator Weights

Retail Trade Survey Deflator Weights

Studies

Coverage

Subjects
Business statistics, Business and agricultural surveys, Macroeconomic statistics, Economic accounts
Keywords
Sales value, Sales Volumes, Stock value, Regional Sales Values, Retail, Household consumption, Prices, Supermarket and grocery, Specialised food, Liquor, Non-store and commision-based retailing, Furniture, floor coverings, houseware, textiles, Electrical and Electronic goods, Hardware, building and garden supplies, Recreational goods, Department store, Pharmaceutical and other store-based retailing, Accommodation, Food and Beverage services, Motor-vehicles and parts, Fuel, Clothing, footwear and accessories
Date
March2011 -

Retail Trade Survey (Quarterly)

Name
Retail Trade Survey
Label
Retail Trade Survey (Quarterly)
Description

The Retail Trade Survey measures the sales turnover and stock levels of a wide range of businesses that provide household and personal goods and services. This data collection captures the methodological, collection and analysis information used in the Retail Trade Survey.

Methodology

Methodology

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)

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 tablesANZSIC06 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](http://www.stats.govt.nz/browse_for_stats/industry_sectors/RetailTrade/RTS-deflator-weights-info.aspx) 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.

Deflator Weights Retail Trade Survey

Label
Deflator Weights Retail Trade Survey

Methodology

Methodology

The Retail Trade Survey (RTS) deflators measure change in the prices of goods and services sold by businesses in the 15 retail industries. Movements in actual retail sales values can be explained 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.

The relative importance of the 41 industries that make up the 15 published retail industries is updated annually, based on sales for the latest year to June.

Current and previous RTS deflator weights are attached in the available files section of this page.

File nameQuarter implementedDetails
RTS deflator weights – September 2010 to June 2011September 2010
• Industry classification updated from Australian and New Zealand Standard Industrial Classification 1996 (ANZSIC96) to Australian and New Zealand Standard Industrial Classification 2006 (ANZSIC06).

• Commodity weights based on 2006/07 Household Economic Survey (HES) and other sources.

• Industry weights below the published level based on RTS sales for the year to June 2010.
RTS deflator weights – September 2011 to June 2012 September 2011
• Commodity weights based on 2009/10 HES and other sources.

• Industry weights below the published level based on RTS sales for the year to June 2011.
RTS deflator weights – September 2012 to June 2013 September 2012
• Commodity weights based on 2009/10 HES and other sources.

• Relative importance of cigarettes and tobacco updated, based on sales information for the year to June 2012.

• Industry weights below the published level based on RTS sales for the year to June 2012.
RTS deflator weights – September 2013 to June 2014 September 2013
• Commodity weights based on 2009/10 HES and other sources

• Relative importance of cigarettes and tobacco updated, based on sales information for the year to June 2013.

• Industry weights below the published level based on RTS sales for the year to June 2013.
RTS deflator weights – September 2014 to June 2015 September 2014
• Commodity weights based on 2009/10 HES and other sources.

• Industry weights below the published level based on RTS sales for the year to June 2014.
December 2014
• Commodity weights based on 2012/13 HES and other sources.
RTS deflator weights – September 2015 to June 2016 September 2015
• Commodity weights based on 2012/13 HES and other sources

• Relative importance of cigarettes and tobacco updated, based on sales information for the year to June 2015.

• Industry weights below the published level based on RTS sales for the year to June 2015.
RTS deflator weights – September 2016 to June 2017 September 2016
• Commodity weights based on 2012/13 HES and other sources

• Relative importance of cigarettes and tobacco updated, based on sales information for the year to June 2016.

• Industry weights below the published level based on RTS sales for the year to June 2016.
RTS deflator weights – September 2017 to June 2018 December 2017
• Commodity weights based on 2015/16 HES and other sources

• Industry weights below the published level based on RTS sales for the year to June 2017.

###September 2010 to June 2011 quarters

In 2010, the RTS was redesigned to reflect the updated industrial classification, ANZSIC06. The RTS deflators were redeveloped to deflate estimates of retail sales in current prices from the redesigned RTS.

The ANZSIC06 deflators were directly calculated to measure price change from the June 2010 quarter onwards. Before the June 2010 quarter, the deflators were derived from backcast estimates of retail sales in current and constant prices.

###September 2011 to June 2012 quarters

In 2011, the RTS deflator commodity weights were updated based mainly on information used in the CPI review: 2011, including household spending patterns, by industry, that were reported in the 2009/10 HES. The industry weights were also updated to reflect the relative importance of the 41 industries in the year to June 2011.

###September 2012 to June 2013 quarters In 2012, the RTS deflators were updated to reflect the relative importance of the 41 industries in the year to June 2012. In addition, the relative importance of cigarettes and tobacco were updated.

The update for cigarettes and tobacco was to reflect a drop in the quantity sold in retail outlets in the year to June 2012, compared with the year to June 2011, following excise-related price increases. Available information sources were also used to review and better reflect the relative importance of cigarettes and tobacco across the retail industries that sell these products.

###September 2013 to June 2014 quarters In 2013, the RTS deflators were updated to reflect the relative importance of the 41 industries in the year to June 2013. In addition, the relative importance of cigarettes and tobacco were updated.

The update for cigarettes and tobacco was to reflect a drop in the quantity sold in retail outlets in the year to June 2013, compared with the year to June 2012, following excise-related price increases.

###September 2014 to June 2015 quarters In September 2014, the RTS deflators were updated to reflect the relative importance of the 41 industries in the year to June 2014.

In December 2014, the RTS deflator commodity weights were updated based mainly on information used in the CPI Review: 2014, including household spending patterns, by industry, that were reported in 2012/13 HES.

###September 2015 to June 2016 quarters In 2015, the RTS deflators were updated to reflect the relative importance of the 41 industries in the year to June 2015. In addition, the relative importance of cigarettes and tobacco were updated.

The update for cigarettes and tobacco was to reflect a drop in the quantity sold in retail outlets in the year to June 2015, compared with the year to June 2014, following excise-related price increases.

###September 2016 to June 2017 quarters In September 2016, the RTS deflators were updated to reflect the relative importance of the 41 industries in the year to June 2016. In addition, the relative importance of cigarettes and tobacco were updated.

The update for cigarettes and tobacco was to reflect a drop in the quantity sold in retail outlets in the year to June 2016, compared with the year to June 2015, following excise-related price increases.

###September 2017 to June 2018 quarters In December 2017, the RTS deflator commodity weights were updated based mainly on information used in the CPI Review: 2017, including household spending patterns, by industry, that were reported in 2015/16 HES.

This update also included changing the RTS deflators to reflect the relative importance of the 41 industries in the year to June 2017.

###September 2018 to June 2019 quarters In September 2018, the RTS deflators were updated to reflect the relative importance of the 41 industries in the year to June 2018.

Page updated 26 November 2018

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