Price indexes allow the comparison of two sets of prices, either over time (temporal index) or regions (spatial index) for a common product or group of products. There is extensive theory and information on price indexes available¹ and within this section, users will be provided with a detailed snapshot of price index theory that falls within the scope of the Producer and International Trade Price Indexes.

A price index allows users to assess and compare sets of prices and the basis point for the development of a price index is to designate one set of prices as the ‘reference set’ and another set of prices as the ‘comparison set’. The designated reference set, or ‘reference price set’ is usually assigned an ‘index value’ of 100, which is the customary value used commonly by price statisticians².

Most users of price indexes require a continuous series of index numbers at specific time intervals. There are two options for applying the above formulae when compiling a price index series:

(i) select one period as the reference and separately calculate the movement between that period and each other period, which is called a direct index, or
(ii) calculate the period to period movements and chain link these (i.e. calculate the movement from the first period to the second, the second to the third with the movement from the first period to the third obtained as the product of these two movements).

The calculation of direct and chain linked indexes over three periods (0, 1, and 2) using observations on three products, is shown in Table 3.2. The procedures can be extended to cover many periods.

A common problem confronted by index compilers is how to measure the price of products in the index whose price may change several times during an index compilation period. For example, in Australia petrol prices change almost daily at the terminal gate while the Producer Price Index (PPI) is quarterly. Taking more frequent price readings and calculating an average is one approach to deriving an average quarterly price. A more desirable approach, data permitting, would be to calculate unit values and use these as price measures¹².

The unit value for a product for a specified period is the value divided by quantity transacted in the period. The use of unit values is problematic and is not generally recommended, since any change in product quality, product mix, or timing can seriously distort the average unit price. However, for a highly volatile but narrowly defined product like petroleum, this method may be suitable.

The use of fixed weights (as in a Laspeyres type formula) over an extended period of time is not a sound index construction practise. For example, weights in a Producer Price Index should be changed to reflect changes in production patterns or structural changes to the economy over time. Production patterns change in response to longer-term movements in relative prices, changes in preferences and the introduction of new products (and the displacement of other products).

When adopting a Fixed Weighted Index formula two approaches are generally used. One is to hold the weights constant over as long a period as seems reasonable, starting a new index each time, the weights are changed. This means that a longer-term series is not available. The second is to update the weights more frequently and to chain, as discussed above, to produce a long-term series. The latter is the more common practice.

The behaviour of the various formulae when chaining is explored below in table 3.4 by adding two more periods. In period 3, prices and quantities are returned to their reference period values and in period 4 the reference period prices and quantities are ‘shuffled’ between products. The period 3 situation is sometimes described as ‘time reversal’ and the period 4 situation as ‘price bouncing’¹³.

Under the three formulae, the index number under direct estimation returns to 100.0 when prices and quantities of each product return to their reference period levels. However, the chained index numbers do not (although the chained Fisher Ideal index might generally be expected to perform better than the chained Laspeyres or Paasche).

There are obvious attractions in frequent chaining. However, chaining in a fixed-weight index can lead to biased estimates. This can occur if there is seasonality or cycles in the price and chaining coincides with the top and bottom of each cycle. For this reason, it is generally accepted that chaining should not be done at intervals of less than one-year l. The conceptual underpinning of chaining is that the traditionally expected inverse relationship between prices and quantities actually applies in practise (i.e. growth in quantities is higher for those products whose prices increase less in relative terms).

As different index number formulae will produce different results, there is a need for some investigation to determine which formulae are more appropriate. Two main approaches have been used, such as the evaluation of the performance of the formulae against a set of predetermined desirable mathematical properties or tests, the so-called 'axiomatic' approach and the economic approach.

The volume and complexity of the available transactions from which to obtain prices means that it is not possible to collect prices from every provider and for every product or to take into account every price at which products are sold. Consequently, it is necessary to adopt a sampling approach to obtain transaction prices for representative products from selected businesses.

This section will provide a broad overview of sampling methods used by the ABS in the compilation of the Producer and International Trade Price Indexes.

Sampling Methods

There are two primary sampling methods used by the ABS:

• Probability Sampling; and
• Non-Probability Sampling

Probability sampling

Probability sampling is the selection of a sample of producers and products from a population of industrial activity in which each producer and product has a known chance of selection. Under this approach, all producers and products have a known probability (chance) of inclusion in the sample. The key benefits of probability sampling are that sampling design controls for sampling error and allows for its measurement. There are, however, disadvantages associated with this approach.

The use of probability sampling requires identification of all units (e.g. producers and products) in all industries of the economy that are in-scope of the price index (known as the sampling universe). This requirement translates into the need for an up to date sampling frame of products. The practical difficulties in satisfying this requirement mean that there are high costs in the design, implementation, and ongoing administration of probability samples for price index purposes.

Non-probability sampling

Non-probability sampling is known as judgmental or purposive sampling, or expert choice, and samples are chosen by experts to be representative. In a price indexes context this involves index compilers selecting producers and products from which to obtain prices using available information on the relative importance of individual producers and products.

A key benefit of non-probability sampling is that it can be used where the sample population is not known. However, it is not possible to produce a measure of sampling error for indexes compiled from non-probability samples. It is generally accepted that price indexes are an area of statistics where the risks in not using a probability sample are relatively low, as the diversity of price change charged by various producers over time is usually small.¹

Sampling for the Producer and International Trade Price Indexes

Non-probability sampling is used by the ABS to compile the Producer and International Trade Price Indexes.² This is primarily due to the lack of available data to undertake a probability sampling approach, which as explained above, requires a significant data sampling frame of products which is not available to the ABS.

The non-probability sampling approach uses available data to build a picture of the overall market for a particular industry. It is used to determine who the potential providers are, their relative importance, what particular products they sell, who they sell to, and their pricing policies. A range of information sources are used in the selection of products and corresponding businesses. These include market reports, industry associations, ABS industry census data and other related surveys, and discussions with potential providers. This information is used to develop a comprehensive understanding of the market.

The index compiler uses this information to make appropriate judgements in the sample selection process.

The effectiveness of the non-probability sampling approach depends on the index compiler’s ability to construct product samples that produce price movements that are representative of price movements of all in-scope products. This is achieved by: 

• sampling products to represent the price movements for all the products which come within the scope of the particular price index
• sampling providers to represent all the suppliers/users of the selected products. In general, the aim is to cover businesses which account for a high proportion of sales or purchases of the products in the index
• sampling products from each provider to represent the whole product range within the selected product group
• obtaining prices for each sampled product which best represent the price movements of all transactions in the selected product group.

The Survey of Producer Prices is the authorised survey tool administered by the ABS to collect the pricing data used in the compilation of the Producer and International Trade Price Indexes.

The Survey of Producer Prices collects pricing data, reasons for price movements, and details regarding changes in product characteristics from producers that are enrolled within the survey. Enrolment into the survey is done on purposive basis and requires additional information regarding sales data, purchasing information to gauge representativeness and contact details for persons responsible for pricing information.

The Survey of Producer Prices administered by the ABS meets the confidentiality requirements of the Census and Statistics Act by ensuring that information provided to the ABS is: 

• securely maintained
• only used for statistical purposes
• published statistics do not enable the identification of an individual or business
• microdata files are confidentialised to support research and analysis.

Further information on how the ABS keeps information confidential is available in the ABS Privacy Policy and the Survey Participant Information - How The ABS Keeps Your Information Confidential.

The choice of individual products to be priced is made in consultation with providers to the Survey of Producer Prices. This process ensures that the sampled products are clearly identified and described, that they are representative of the price behaviour of the products they represent and confirms that the product specifications will be available for pricing in future periods.

The representivity of the products in the price basket is regularly reassessed as over time specific types of products in the price basket appear and disappear. New products can appear because technical progress makes production of new products possible. Existing products often decrease in importance or disappear from the market altogether as new products appear. 

The forms for the Survey of Producer Prices are tailored specifically for each provider. The products priced and the descriptions of these products are tailored to individual providers and this process minimises the survey burden placed upon providers.

A price observation is the price of a specific product at a given point in time. To ensure consistency in the final index, a price observation should compare “like with like” in each different collection period. Product specifications are defined as tightly as possible so that the prices collected for a particular product can be compared from period to period and any changes in product specification characteristics (quality) can be identified. Further, the collection of additional information, or collecting data on a different pricing basis, allows the pricing data to be used in multiple ways. This re-use of price data is considered a mechanism whereby the ABS maximises the utility of collected pricing data.  Describing a specification in this way also assists the adjustment of the price associated with any changes in the product quality or the terms and condition of sale.

The main criteria that form part of a specification are listed in Table 3.6 Below.

The Survey of Producer Prices primarily uses a webform based tailored survey questionnaire.

Webforms provide a quick, easy and secure way to complete and submit survey data.

While the ABS sources the majority of its pricing data for the Producer and International Trade Price Indexes from the Survey of Producer Prices, other data sources are used to supplement the quarterly price collection.

Compilation of the Producer and International Trade Price Indexes uses data from other internal ABS sources in addition to that collected in quarterly survey forms.

The ABS also uses data that are readily available in the public domain, such as exchange rates, and some commodity data.

In addition, the ABS sources data from other Australian Government agencies (particularly for mineral fuels and some agricultural products). In the cases where internet prices reflect actual transaction prices the ABS will use this data to supplement its price samples. In some cases, the ABS purchases data from third parties, particularly when measurement of prices for groups of products requires additional specialist skills, such as bills of quantity data produced by quantity surveyors for the Outputs of the construction industry Producer Price Indexes.

Most individual products priced in the Producer and International Trade Price Indexes are priced once per quarter, using a point-in-time pricing mechanism. However, pricing occurs more frequently for products that exhibit volatile price behaviour. In such cases, collections are carried out monthly or even more frequently (for example, a series of daily commodity spot prices are collected.

The usual practice is to collect prices from all providers in each pricing period. However, there may be some cases where prices are generally stable, products take a long time to produce, or price changes happen at predetermined times. In these cases, it is not necessary to collect prices in every reference period. For example, education prices increases occur annually, hence prices are collected once a year.

Point-in-time prices relate to the price of a product on a particular day of the period (for example, the first day of the month, the nearest trading day to the fifteenth day of the month, middle day of the quarter). This approach makes the collection date straightforward for both the ABS and providers and means that comparisons from period to period will be consistent.

To mitigate short-term external influences (for example, extreme weather, labour stoppages, seasonality), the ABS spreads the pricing points to different positions over the 13 weeks of the reference quarter. This approach ensures the price of a particular product is observed at more than one point in time during the pricing period.

Types of prices

There are many different pricing types collected by the ABS through the Survey of Producer Prices and this section will explore the different pricing types currently in scope of the Producer and International Trade Price Indexes.

Transaction Prices

A transaction price is the value placed on an item (agreed upon by seller and buyer) at the point of transaction. It must reflect the actual prices paid to or received from producers after taking into account all discounts applied to the transaction whether they be volume discounts, settlement discounts or competitive price cutting discounts which are likely to fluctuate with market conditions.

The Producer and International Trade Prices attempt to measure actual transaction prices for the exchange of products. The price includes the impact of all discounts, surcharges, rebates, etc. for a unique customer or unique class of customer. It is not always possible to obtain a transaction price net of all discounts and inclusive of all surcharges. Care is taken to secure a type of price with a movement which closely proxies actual transaction prices.

Contract Prices

Contract pricing generally refers to a written sales instrument that specifies both the price and shipment terms. The contract may include arrangements for a single shipment or multiple shipments. The contract usually covers a period in excess of one quarter. Contracts are often unique in that not all the price-determining characteristics in one contract can be expected to be repeated exactly in any other contract. The challenge is to maintain a constant quality over time, especially when the contract expires and selection of a replacement product is necessary.

Contract terms may be unique to each agreement in terms of customised product features, negotiated price tied to the unique buyer/seller relationship, or quantity differences. In addition, contracts reflect supply and demand conditions at the time of entering into the contract. To maintain an accurate index where contract pricing is widespread, the ABS employs larger samples. This is to reflect the proper proportion of new contracts or renegotiated contracts being entered into in each pricing period.

Spot Market Prices

Spot market pricing (or simply spot price) may be defined as any short-term sales agreement. Generally, this refers to single-shipment orders with delivery expected in less than one month. Products sold on this basis are usually off-the-shelf and, therefore, are not subject to any customisation. These prices may be subject to discounting and directly reflect current market conditions. Spot market prices can be extremely volatile; in the case where this volatility is not experienced in actual transactions, the ABS adopts pricing methodologies that minimise this spot price volatility. For example, for crude petroleum oils, the ABS incorporate an average of daily prices into the price measurement for each period. Another solution the ABS adopts for homogeneous products that exhibit price volatility is to use average unit values.

Average Unit Values

Average unit values (or simply average prices) reflect multiple shipments of a given product within a consistently defined period, for which data are usually readily available. The advantage of average unit values is that they effectively increase the number of price observations used to calculate the index, thereby reducing sample variance. The reduction in variance is achieved because average unit values explicitly represent the entire population of transactions for a particular product, and so the concern when pricing a handful of single transactions does not apply. An average unit value does not take into account constant quality and is therefore used selectively.

Counterpart Pricing

Counterpart pricing is a term to reflect utilisation of a transaction price observed on a pricing basis that differs from the conceptual basis of the price index. For example, consider an input price index that measures the price of plumbing products purchased by builders for use in house construction. The conceptual basis for such a price index is to measure the purchasers’ price paid by the builder, inclusive of delivery charges. A counterpart price for this transaction would be the price received by the producer of the plumbing products; that is, the basic price. This basic price would differ from that paid by the builder in this case due to delivery costs. The counterpart pricing methodology is employed whenever a purchaser’s price is represented by a basic price, or vice versa.

Please note that the use of a counterpart pricing methodology has the implicit assumption that transport and distributive trade margins move proportionally with the basic price.

Model Pricing

Model pricing is an approach adopted to measure products that are unique in nature, i.e. a product that is only manufactured once to the specification of a customer. The model pricing approach defines a notional product (the model) that is to be priced over time. The circumstances that dictate the use of model pricing mean that the products are themselves unique, and frequently the products provided are complex in nature.

Transfer Pricing

Transfer prices are the prices adopted for bookkeeping purposes between affiliated enterprises under common management and may not correspond to prices that would be charged to independent parties. Affiliated enterprise may set the prices of transactions among themselves artificially high or low in order to affect an unspecified income payment or capital transfer.

Please refer below for issues relating to transfer pricing.

The appropriate price to obtain from a theoretical perspective should be the price at the time there is a change in ownership from the producer to the buyer. Unfortunately, it is frequently difficult to adhere to this theoretical requirement uniformly in practice. Therefore, the ABS generally use the concept of shipment price for the actual transaction occurring as close to the survey pricing date as possible. In most circumstances, the shipment price is final at the time of delivery to the customer.

An important caveat is made for the Import Price Index in this case (see below).

The Import Price Index measures the price of merchandise that is imported into Australia. A transaction is in scope of the Import Price Index if the merchandise crosses the Australian customs frontier during the reference period. However, that transaction, and hence the change of ownership, may have occurred prior to the reference period, with the difference in timing due to shipping times. For example, a shipment of cars may change ownership during the last week in March, but not arrive in Australia until early in April. In this instance, although the change of ownership occurred in the March quarter, the price measurement would be included in the June quarter Import Price Index.

This crossing customs frontier basis is the same as that adopted for Australian International Merchandise Trade statistics. It slightly differs from the conceptual bases of both the Australian National Accounts and Balance of Payments statistics. However, since both the Australian National Accounts and the Balance of Payments data use international trade data as a source, the data sets are consistent in practice. Adjustments for timing are made to the Australian National Accounts and the Balance of Payments in the case of large one-off purchases, typically of capital goods (for example, the purchase of a fleet of jet aircraft). Since by its very nature the Import Price Index cannot determine a price movement for one-off purchases, the Import Price Index is consistent with the compilation of both the Australian National Accounts and the Balance of Payments statistics.

Application of discounts

The identification of discounts is complicated in practice by a number of factors.

The pricing structure used by the company may be complex and the conditions under which discounts apply may be described in non-standard terms. Differences in pricing and discounting procedures between companies require data collection to be tailored to each company and the full level of discounts offered to major customers may only be known to senior company officials.

In clearly identifying discounts, it is convenient to classify the discounts into two categories: recurring discounts, and non-recurring discounts.

Recurring discounts generally reflect cost savings to the buyer and are generally on-going, recurring every time a sale is made that meets specified conditions. The most common types of discounts fall into this category (e.g. discounts based on type of customer, volume discounts, settlement discounts).

Non-recurring discounts are discounts that reflect the bargaining power of the buyer vis-a-vis the seller and/or current market conditions. This category includes various forms of competitive discounts (including those that appear in the guise of short-term changes to specific classes of customer and other recurring discounts).

Discounts are frequently commercially sensitive information. For example, knowledge of competitors’ discounts with major customers (or major suppliers) is of enormous commercial value; in other cases, such information may have significant public relations or political impacts.

Examples of discounting practises are:

• Competitive discounts reflecting unique supply or demand conditions, generally in specific markets for the product. These discounts are generally of short duration in any specific market area, but may be applicable in at least one market area on a frequent basis
• Surcharges are additions to the listed price. These are generally of short duration and reflect unusual cost pressures affecting the manufacturer (for example, fuel surcharges for road freight companies)
• Prompt payment discount for remitting payment within a fixed period such as ten days. These discounts are generally of small magnitude, remain unchanged for long periods, and are available to all customers
• Volume discounts are generally tied to specific order sizes and increase the larger the order. These discounts are generally available to all customers
• Class of customer discounts are specific to certain classes of buyer. Trade discounts are available to wholesalers to help cover their selling expenses. Advertising discounts are available to retailers to help cover their promotional expenses. These tend to be expressed as percentages and remain unchanged for long periods
• Financing discounts relate to providing assistance to customers to pay for the products they are purchasing. They may serve as a buy-down on the bank loan interest rate for those customers borrowing to pay for the product
• Cumulative volume discounts are offered to customers who purchase a certain amount of a product in units or sales in several shipments over a specific period.

The use of a personal interview and subsequent design of the questions in the Survey of Producer Prices allows the ABS to determine the current and likely future use of the discount practises described above, and to emphasise the importance of notifying the ABS of any change in, or future use of discounts (including non-recurring discounts).

Operational procedures for processing the Survey of Producer Prices, especially data editing and querying of providers, also focus on identifying changes in discounts and pricing policies.

There are a number of additional sources of information that are useful in revealing the existence of (or changes to) discounts:

• Industry and media reports – coverage on discounting, annual reports and competitive pricing for major products or product types is often freely available online. Intelligence from online resources can help determine competitive price discounting, as well as other price influences.
• Market research - gathered from ABS subject matter experts, industry associations and other Australian Government departments
• Confrontation of price data across other providers - it is a rare situation for a provider to set prices (and discounts) independent of competing providers. Differences in price levels (or in price movements) may indicate unreported discounts. Care must be used here to identify price-leaders in these circumstances, as discounts from competitors may occur in earlier or later periods.

In the case of volume discounts, the same customer may face varying prices for the same product purchased in consecutive periods, because different volumes are purchased in the two periods. In circumstances such as this, the unit price will vary simply because the volume of sales has changed rather than because of a change in the underlying price of the product. If it is determined that this is a typical occurrence for a particular product, the specification of the item will usually identify a certain volume for pricing purposes. That volume is then priced in each pricing period.

Also related to volume discounting is the common occurrence of providing a larger quantity of the product for the same price, sometimes for a limited period. Again, to ensure that price changes are correctly included in the price index, quantity details are also collected.

The overarching principle in the ongoing identification of discounts so that they may be correctly included in the final transaction price, is to record list price and discount as separate data items. In this manner, it is far more likely that a change in discount is correctly observed in calculation of the final transaction price.

A rebate is a type of discount where the discount is paid after the purchase and is normally based on the cumulative value of purchases over a specified time.

Rebates in price indexes pose major practical problems in that they are often determined by future events. For example, the buyer receives a rebate at the end of the financial year based on how much was purchased in the year. Thus, at the start of the year, while it is known that the buyer will receive a rebate, the precise amount is unknown. The particular problem posed by rebates of this sort is that the final price to be paid will not be known until after the end of the period concerned. This type of rebate is often referred to as a retrospective price fall.

The situation is often further complicated by the rebate being paid to the buyer in the form of a reduction in the cost of their purchase in a particular period. That is, the total rebate for all purchases in a previous year is applied to the price of purchases in a particular period. This practice results in a large price fall in the period in which it is applied.

Where the rebate is already in existence the rebate should be treated as a discount and deducted from the quarterly price, and not treated as retrospective price reductions. The basis for calculating the rebate should be the buyer's normal volume of purchases (if the buyer is a new customer then the basis for calculating the rebate should be the average quantity purchased by that category of buyer).

Changes in the level of rebates should only be reflected where the actual rebate for the same quantity purchased or sold changes. Changes in the rebates paid to a particular customer due to the customer changing their volume of purchases should not be reflected as price changes.

The rebate collected should be the rebate applicable to constant quantity and clearly detailed in the pricing specification.

Where rebates are specified in terms of monetary value of purchases it is important to realise that due to inflation, a monetary value does not represent a constant real quantity. As per the discussion above for discounts, any monetary values should be converted to quantity data.

If the quantity of a provider's sales changes significantly, the pricing specification should be changed to reflect this. The change in rebate associated with a change in volume should not affect the index.

Where a number of levels of rebates are offered it is necessary to ascertain the importance of each level of rebate and to price those that are significant.

On occasions rebates will be introduced retrospectively, that is a supplier introduces rebates based on a previous financial year’s purchases. Two types of practises arise here. The first practise is where prices for previous periods are amended prior to settlement. The second practise is where prices for a particular subsequent period are themselves amended to reflect price changes for earlier periods.

Example: consider a manufacturer of steel shelving who purchases sheets of stainless steel as a material input. This particular producer is offered a rebate of 5% if he buys more than 2000 tonnes in a calendar year. His purchasing data appear as follows:

Example below: Purchases of stainless steel

The producer exceeds 2000 tonnes purchased within the calendar year, and his supplier provides a 5% rebate for the year's purchases. This amounts to 5% of $1.0229 million dollars, or $51,145. The supplier provides this rebate by deducting this value from the quarter 1 of Year 2's total purchases.

 

In the Producer and International Trade Price Indexes, the rebate is shown in the quarter in which it is applied, resulting in a substantial price fall in quarter 1 of Year 2 and substantial offsetting price rise in quarter 2 of Year 2.

There are two reasons for this practice, stemming from the concept that the indexes measure the prices applying in a particular quarter:

• With regards to inflation and decision making, the prices applying in quarter 1 of Year 2 were those used in the index; that is, businesses were making decisions based on those prices and charging their buyers based on these prices (or equivalently improving margins for this quarter)
• With regards to use in the production of the Australian National Accounts, both the revenue data and expenditure data used in the compilation of the Australian National Accounts use the value data represented above. As the aim of the Australian National Accounts is to show change in volumes (quantities), the price data for quarter 1 of Year 2 must show a price fall commensurate with the payment of the rebate; failure to do so would result in a (false) fall in volumes in the Australian National Accounts. The correcting price rise in quarter 2 of Year 2 must similarly occur so as not to cause a false rise in volumes.

A unique product is a product that is only manufactured once to the specification of a customer. Within a group of products, each product will be different from the others, for example, industrial furnaces, ships and architectural services. In these cases, the price cannot be observed over future reporting periods.

The solution to this problem is based on the concept that products are a collection or bundle of different characteristics. For example, a ship can be considered as consisting of steel, engine components, navigational equipment, and so forth; an architectural service may consist of different numbers of hours of senior and junior architects’ time together with associated information technology and other materials. The challenge is to define a product in terms of its characteristics, and then determine a real price for that product in future periods even if such a product is not actually sold. This approach is called model pricing.

The model pricing approach defines a notional product (the model) that is to be priced over time. The circumstances that dictate the use of model pricing mean that the products are themselves unique, and frequently the products provided are complex in nature.

There are several techniques that may be used in identifying and describing a notional product. All such approaches require a high degree of interaction and cooperation with data providers, and these approaches are individually tailored to providers:

• Repeat recent sale: an actual product sold in a recent period is used as the notional product
• Base product: a base level or standard product is chosen as the notional product
• Hypothetical single product: a hypothetical product that is representative of the types of products produced by the provider
• Hypothetical component model: a notional model incorporating the key components from the various items produced.

A limitation of the model pricing approach is that the specified product must continue to be representative of the types of products being produced. This means that the notional model must be frequently checked for representativeness and updated and re-specified over time.

The ABS works with producers of unique products to apply price collection procedures that yield the correct price movement with the least burden placed on providers.

There are several techniques to repeatedly price these notional models:

• Single price approach: whereby the provider determines the price for the completed model and reports this back to the ABS.
• Component pricing: whereby prices of components are collected from a provider and aggregated in a pre-determined manner. This approach is readily applicable to the hypothetical component model, but is also applicable to other models where sufficient information regarding their composition is available. In practice component pricing is achieved in several ways:

              a. provider algorithm: in this case the provider agrees to collect prices for individual components and combines the price to one final price.

              b. ABS algorithm: in this case the provider agrees to report prices for individual components only, and the prices are combined to a final price by the ABS.

The ABS regularly re-visits providers who supply data using model pricing. These visits re-emphasise the importance of model pricing and are an opportunity to update the product specification for model pricing.

Transfer prices should be used with caution because transactions to another part of the same business (or to an affiliated business) may not reflect the true price (or true price movements) otherwise observed in the marketplace. The ABS only include a transfer price in the Producer and International Trade Prices when the price behaviour is confirmed to represent true market transactions.

Where the parties to the transactions are between affiliated enterprises in different countries, the prices adopted in their books for recording transactions in products may not correspond to prices that would be charged to independent parties. Transfer pricing to avoid tax is illegal in Australia, and consequently the distortions in economic statistics caused by transfer pricing through the customs frontier are not considered widespread. For these reasons, transfer prices are sometimes included in the Import Price Index and Export Price Index. This practice is consistent with the practical treatment of these value data (for merchandise crossing the customs frontier) in both the Australian System of National Accounts and the Balance of Payments and International Investment Position Manual Sixth Edition, frameworks.

02 February 2024

• Information was updated on "Returning the Survey form" from mail out-mail back survey as the primary collection method to webform based.

The weights used to compile price indexes determine the impact a particular price change will have on the overall index. This section of this release outlines the weighting methodology and sources adopted by the ABS for the Producer and International Trade Price Indexes.

Basic Price Index Structure

A diagrammatic overview of the typical structure of a price index is provided in Figure 3.1. At the top is the total value of products represented by the index. This is progressively divided into finer product groupings, following the structure of the classification until, at the lowest level, there are samples of prices for individual products. These highly detailed price samples are called elementary aggregates. Indexes are only published down to the regimen level as this is the level at which the structure and weights remain fixed between index reviews.

The division of products into finer product groupings is intended to reflect increasing levels of substitutability of the products in response to changes in relative prices.

For an output price index, the index structure reflects substitutability in terms of production, reflecting how producers change their outputs in response to the prices they are receiving in the marketplace. For an input price index, the index structure reflects substitutability in terms of consumption, reflecting how producers change their inputs in response to the prices they are paying in the marketplace.

Classifications play a vital role in determining the weights for price indexes. A classification not only helps determine the appropriate scope of the price index (and hence inclusions and exclusions from the value to be covered) but plays a critical role in defining a common language. That is, the classification is the common language that is used to relate the price index structure to its underlying value data.

The ABS use tools such as the Australian and New Zealand Standard Industry Classification to structure the Producer and International Trade Price Indexes on an industry basis, and further information on the applicable classification used for each Producer and International Trade Price Index can be found below.

The Producer Price Indexes are structured and compiled on an industry basis and the structure of the output price indexes include both products primary to an industry, but also include secondary production products and therefore, the weights of output price indexes are inclusive of both primary and secondary product expenditure.

Price indexes are constructed using a sample of transactions for a range of product types to represent a broad range of economic activity. This “chain of representativeness” is discussed in more detail in the Sampling section. One outcome of using sampling is that the selected products represent not only themselves but also other related products not included in the selected sample.

Some industries and products will have very small relative importance in terms of their share of total production. It may not be feasible to maintain a sample for these products, however their weight is still included in the overall index structure. This is achieved through the inclusion of empty node components. When empty node components are included in the index structure, they are weighted according to the value of the output (or input if it is an input price index) of the products represented by the component. When the index is compiled, the price movement of an empty node is derived by using the weighted average price movements of the sampled components within the product group to which the empty node belongs. This approach has the advantage of simplifying the inclusion of a component if it becomes feasible to collect a sample for that component.

An example of the empty node approach is illustrated in Figure 3.2 below, for Australian and New Zealand Standard Industry Classification Class 0139 Other Fruit and Tree Nut Growing (see Figure 6.2). In the example, not all products within the industry classification are included in the sample, specifically Other edible nuts (excluding Peanuts) nec. The value of Other edible nuts (excluding Peanuts) nec was $163.2m (2012-13), or 29.2% of the total value of Class 0139 Other Fruit and Tree Nut Growing. The value (price movement) of the empty node is derived by using the average price movements of the sampled components within the product group; which in this example would be derived from the price movements for bananas, orchard fruit and almonds and macadamias.

The weighting structure of a price index plays a large part in determining the accuracy and reliability of the index. Key factors in selecting the period used to calculate the weights are:

• The economic activity over the period should be reasonably normal/stable and representative of likely future activity
• Close to the link period (the period where the weights are introduced to the index series).

The weight reference period and the link period used in a price index formula are rarely the same period in practise. For reasons of stability and representativeness, the weight reference period is frequently a year or longer period. New weights are introduced during a specific period, known as the link period. For a Lowe price index, weights are price updated to account for price changes between the weighting period and the link period.

For example, the Import Price Index is re-weighted each year using the most recent financial year data sourced from the ABS International Trade in Goods and Services publication. The updated data is incorporated into the Import Price Index in the September Quarter, which means that in the September quarter each year the weight reference period is updated to the previous financial year, and the weights are price updated to the September quarter to take into account the change in prices between the conclusion of the financial year each year and the three months ending the September quarter.

 In satisfying the stability and representativeness criteria presented above, weights for the Producer and International Trade Price Indexes are sometimes taken from multiple periods. This practise is followed in those instances where a single year’s data may not be adequate, either because of unusual economic conditions (such as introduction of a new tax system), volatility observed in the marketplace or insufficient sample sizes from survey data. In such cases, an average of several years’ data provides the best weight reference period as it reduces the sampling and seasonal variance of the production or sales data for a given size of the annual sample. For example, whereas the Import Price Index uses weighting data from the most recent financial year, the Export Price Index uses data from the previous two years due to the volatility observed in key export commodities.

Frequency of weighting

The ABS periodically updates the weights of its price indexes to reflect changes in market structure. The faster the change in an economy’s market structure, the more frequently the weights in the indexes are updated.

Sourcing weighting data

The data used to create weights for price indexes are taken from various internal and external sources by the ABS. This section will explore the different weighting sources for the different index levels for the Producer and International Trade Price Indexes.

Upper-level weighting

Upper level weights are the weights that apply to the components of a price index structure between the root level and the regimen level. The weights, at the root level including the weight of the regimen level, are fixed in terms of underlying quantities until an index redesign takes place.

The majority of the Producer and International Trade Price Indexes use the Australian National Accounts or International Trade in Goods and Services as sources for upper level weights. For some Producer Price Indexes, the scope of activity covered by the price index does not align directly with the Australian National Accounts. This is particularly the case for the price index of Input to the house construction industry, which is weighted using a bills of quantity approach.

Lower-level weighting

Lower level weights are the weights that apply to the components of a price index structure below the regimen level down to the elementary aggregate. The weights, including the weight of the elementary aggregate (but not the price sample within the elementary aggregate) may be adjusted to reflect changes in either producer or purchaser behaviour in the market and hence changes in the relative importance of products in the basket. Furthermore, the effects of discontinued and new types of products can also be accommodated.

Product Specification weighting

The calculation of the broad price indexes starts with the measurement of the relative price change for an elementary aggregate, which represents the first level at which price observations are combined to calculate an index. At this level, weights are needed to combine individual price observations in order to calculate higher-level indexes. The elementary aggregate index covers all prices collected for one detailed product type. Each elementary aggregate is composed of price observations for products that are similar in terms of material composition, end use, and price behaviour.

It is important that the weight for each price observation covers the value of all products that the individual transaction represents. That is, most price observations will have a weight that represents other products and transactions in addition to the value of the sampled product alone. Micro-index weights are frequently adjusted to account for the introduction of new product varieties within a product type (such as a unit of sale or new flavour). Similarly, they are adjusted to account for the removal of discontinued individual product lines.

For example, consider an elementary aggregate for bottled beer for an output price index. The specifications within the elementary aggregate typically incorporate information on brewery, brand, bottle size and units of sale (such as 12 X750 ml bottles or 24 X375 ml bottles etc.). Through the process of sample selection, sampled products are selected to represent other products. A particular sampled product may be a best-selling brand of beer in a 24 X375 ml bottle carton; but the weight of the specification would include not only the value of sales of such a product but also the value of sales of other brand varieties sold by the particular brewery. The weight may also include the value of sales from other breweries.

In calculating such a weight, it is necessary to know several critical pieces of information regarding the values of transactions. Continuing the bottled beer example from above, the following data are required:

• the value of sales of the selected beer product (brewery, brand, size, units of sale)
• the value of sales of other brands of the same size from the selected brewery
• the value of sales of 24 X375 ml cartons of beer from other (non-sampled) breweries.

In general, value data (either revenue or expenditure) are required for the sampled product and also for any other products that are within scope of the elementary aggregate. Determining such information requires the co-operation of sample providers. The ABS generally collects this information via a personal visit during the activity known as a sample review.

The other key source of detailed product information used in micro-index weighting are industry associations, as described above for lower level weights.

Challenges in weighting product specifications

Determining value data at the product specification level is a difficult process that sometimes proves to be burdensome for sample providers. In addition, it can become an increasingly complex task to ensure that the micro-index weights are correctly maintained over time. Continuing the bottled beer example from above, the introduction of an immediately popular new brand (such as a boutique beer) requires collection of not only the sales revenue of the new product but also a measure of how the sales values of existing products have changed in response to the new competition. Collecting such information in a timely manner frequently proves difficult.

Equal weighting formulae

In the case where specification weighting might be difficult to achieve, an alternative is to adopt a micro-index formula where the sampled specifications have the same weight within an elementary aggregate. This process is currently applied to the Australian and New Zealand Standard Industry Classification  Class 0400 Accommodation Producer Price Index.

Australian National Accounts Input-Output (I-O) tables

The key sources of data for upper level weights for the Producer Price Indexes are the Australian National Accounts I-O tables and a full overview of the I-O tables is provided above. The I-O tables are primarily used for the upper level weights for the Producer Price Indexes.

In addition to broad data from I-O tables, other data sources used to construct the Australian National Accounts aggregates are frequently used in the estimation of lower level weights for Producer Price Indexes. The Australian National Accounts component data are generally more complete in terms of consistent coverage and valuation bases. The data used for lower-level weighting are at a more detailed level than published Australian National Accounts data.

International merchandise trade data

The key sources of data for upper level weights for the ITPIs are the values of imported and exported products from Australia’s international merchandise trade statistics. These data are compiled (on a trade basis) from information submitted by exporters and importers or their agents to the Department of Home Affairs.

The conceptual framework used in compiling Australia's merchandise trade statistics can be found in International Merchandise Trade, Australia: Concepts, Sources and Methods.

For lower level weights, data provided by the Home Affairs is coded to very detailed levels of the Harmonised System (HS) trade classification. This data is used to construct representative weights for the lowest level of classification.

The use of International Merchandise Trade data for both upper and lower level weighting is described above. Data provided by Home Affairs is coded to very detailed levels of the Harmonised System (HS) trade classification. Value data at the product level is used to construct representative weights for the sampled products within the finest level of classification.

ABS economic surveys

ABS economic surveys are also used in the production of lower level weights for the Producer Price Indexes. These data typically provide information on type and characteristics of producers, as well as some detailed information on revenue. In addition, these ABS surveys frequently provide information regarding industry outputs in terms of quantity measures. Deriving lower level weights from these quantity data requires combination with measures of average prices.

Examples of the use of ABS survey data for lower level weights include:

• A range of revenue estimates from the program of Annual Integrated Collections are adopted to weight lower level components of the Services industry Producer Price Indexes.
• A range of quantity, expenditure and revenue estimates from the Building and Construction Statistics program are adopted to weight the lower level components of a number of different Producer Price Indexes, including the Output of the Construction Industries.
• Revenue estimates from the International Trade in Goods and Services are used in weighting the Services industry Producer Price Indexes, particularly regarding transport (freight) activities.

Australian Taxation Office

The Business Activity Statement is a tax return lodged with the Australian Taxation Office in respect of:

• Goods and Services Tax (GST)
• Pay as you go (PAYG) withholding and instalments
• Fringe benefits tax (FBT) instalments.

The Business Activity Statement must be lodged by all registered businesses, including government entities for each tax period. Since Goods and Services Tax is levied on revenue from sales, the Business Activity Statement data provide information on output (revenue) by size and type of business. These aggregate data can be incorporated into lower level weights for a range of Producer Price Indexes.

Bills of Quantity

Bills of quantity are documents produced in the building industry by professionals such as quantity surveyors. These documents break construction projects down into elements or products, and then quantify the inputs required for each product. In this way the types and quantities of materials required can be established. The price of the quantity of each specific material is determined so that the materials can be represented in value terms rather than as quantities.

The ABS use bills of quantity approach to select a basket of products to be priced each period and to derive weights for those products for its Construction Industries Producer Price Indexes.

For the Input to the House Construction Industry Producer Price Index, the ABS employs quantity surveyors to undertake this exercise for a selection of typical or representative house designs (for example, brick veneer house 100m2, double brick house 180m2 etc.). Product values for different house designs are then weighted together based on the relative shares of the different house designs in total house construction. Products are then aggregated into broad product types. The fixed basket (and hence the upper level weights) is then determined using the values of the broad product types. The bill of quantities approach is refined further in practise by allowing the share of construction of different house types to vary by capital city.

For the Output of the Construction Industry Producer Price Indexes, the bills of quantities approach is used as part of the process of determining lower level weights. Here the representative designs are not of houses but of residential and non-residential building types. Rather than restrict the bill of quantities to just building materials, the approach adopted in parts of the general construction price index includes work in place, which covers labour, plant and materials, plus margins.

Administrative data

A wide variety of administrative data on production values are available from public and private organisations and are now widely used by the Producer and International Trade Price Indexes to support lower level weighting. Examples of data obtained include: data for agricultural and mining activities, production and consumption of energy and outputs and consumption of transport services.  

Industry associations

Another source for weighting data is industry associations. Many associations conduct surveys of their membership that include detailed information on value of sales by product. Alternatively, where production of a type of product is dominated by one or two large firms, the market shares for these firms can be a source of weighting data. Both types of data are adopted for use in Producer Price Indexes, particularly for the Services Industries.

Across all indexes, missing price observations occur on a regular basis and this could be due to factors such as:

• temporary out of stock items,
• discontinued items,
• or seasonal elements.

In any price reference period, these factors can make it impossible to obtain a price measure for a particular product.

The ABS employs a number of imputation methods to address temporarily missing observations within price indexes. These include:

• the imputation a movement for the product based on the price movement for all other products in the sample
• the use the price movement from another price sample, or
• repeat the previous period’s price of the product (also called carry forward method).

These options are known as imputation.

Their purpose is to calculate a price for the temporarily missing product. The aim of imputation is to provide prices such that the resulting movement in the price index is the same as would have been calculated had all prices been observed. In achieving such a result, it is necessary to make an assumption regarding the price behaviour of the temporarily missing product.

The second approach to imputation for the Producer and International Trade Price Indexes is to use the price movement from another related sample or comparable product. This approach is used in cases where price changes from a comparable product (or products) from a similar type of provider can be expected to be similar to the missing product.

Carry forward imputation

The rationale for adopting a carry forward imputation is that failure to observe a price for a product reflects no transactions for the product, and hence there can be no price change. However, each product in the price sample represents similar products purchased and sold elsewhere in the marketplace, and such an assumption does not hold in most cases. Application of this method of imputation when transactions are actually occurring in a marketplace (but not observed by the sample) consistently biases the index towards zero (that is, biased downward when prices are rising and biased upward when prices are falling).

It is for these reasons that the price statisticians apply this imputation mechanism only under specific conditions where it is known that failure to observe a transaction means that no transactions are occurring (such as where there is only one sale per year of a type of agricultural crop, for example, or where the price changes only once per year during annual price setting).

The objective of pure price indexes is to measure price change over time to constant quality. This is achieved by re-pricing an identical basket of products each period and ensuring the basket of products is unaffected by quality and quantity changes. This is often referred to as pricing to constant quality and an important element of the day-to-day role of price statisticians.

The concept of quality is based on the notion of utility to the purchaser. Quality change is measured by reference to the expected value of the changes to the purchaser. While it is not always possible to achieve this in practice, it is the principal guideline in making decisions concerning quality change.

In economic theory it is generally assumed that whenever a difference in price is found between products which appear to be physically identical, there must be some other factor, such as location, timing, conditions of sale etc., which is introducing a difference in quality. Otherwise it can be argued that the difference does not exist, as rational purchasers would always buy the lower priced products and no sales would take place at the higher price.

However, underlying the economic theory are some strong assumptions which rarely hold true in the marketplace. The key assumption behind “different price means different quality” is that purchasers have
perfect information and that they are free to choose between products offered at different prices.

In most markets, purchasers do not have perfect information about existing price differences and may therefore inadvertently buy at higher prices. While it is true that most purchasers will search out lower prices, costs are incurred in the process. The lack of information about price differences may result in search costs being greater than price differences, in which case rational purchasers may be prepared to accept the risk that they are not in fact buying at the lowest price. The existence of this imperfect information in the marketplace is evident from the number of situations where buyers or sellers negotiate over prices.

Even when purchasers are well informed, in practice they are not always free to choose the price at which they purchase. This situation arises because of price discrimination, whereby the seller is in a position to charge different prices to different categories of purchasers (for products that are otherwise identical). Price discrimination is a common practice in the marketplace as it enables sellers to increase revenues and profits.

Complicating this observation is the difficulty that arises when purchasers can resell amongst themselves (that is, purchasers that buy at the lowest price can resell products to other purchasers). Under such circumstances price discrimination is less likely to occur. While this circumstance can occur for the sale of most products, this situation rarely arises for services, since it is usually impossible to resell services. Price discrimination is frequently practised in many of the transportation and business service industries for this very reason. Therefore, when different prices are charged to different purchasers it is essential to establish whether there are in fact any quality differences associated with the lower prices.

The applicability of the underlying economic theory is tested when differences in price arise because there is insufficient supply. Such a situation typically occurs when there are two parallel markets. For example, there may be a primary domestic market and a secondary market for imports. If the quantities available in the domestic market are limited, there may be excess demand so that supplies may be imported. As a result, the price on the secondary market will tend to be higher. It is also possible that products from the secondary market are not only more expensive but of different quality.

Therefore, prices statisticians are faced with a contrast between theory and practice: theory indicates that a difference in price means a difference in quality, but a difference in price may also arise due to lack of information, price discrimination by customer type, supply constraints and/or the existence of parallel markets. Thus, the existence of different prices does not always reflect corresponding differences in the qualities of the products.

The term ‘quality’ embraces all those characteristics in a product that the purchaser values or from which it derives utility. Therefore, the problem is to identify those characteristics that purchasers value, to make an estimate of the value of those characteristics and to measure the change in those characteristics embodied in the product so that their effect can be removed when calculating price movements. When used in this context, ‘quality’ encompasses all attributes of a product, including quantity.

Sets of products are available in the marketplace with physical characteristics which differ from each other. For example, potatoes may be old or new, red or white, washed or unwashed, loose or prepacked. Loose unwashed Russet Burbank potatoes (used for French fries) are a different quality of potato to washed, prepacked Atlantic potatoes (used for crisps).

When sets of products are sufficiently similar to be considered the same generic type of product (such as a potato), but have sufficiently different characteristics that make them distinguishable from each other from an economic viewpoint, the products are said to possess different qualities.

Not all differences in quality are attributable to differences in physical characteristics of products. Products with identical physical characteristics delivered to different locations, or at different times, are considered to have quality differences. Purchasers situated in one location frequently have different marginal utility from that of purchasers in other locations; hence, different locations may result in different qualities.

Identical products provided at different times of the day (or year) must be treated as different qualities. An example of such a quality difference occurs with the supply of electricity. Electricity provided at peak times is considered to be of a higher quality than that provided at off peak; the very fact of a peak time shows that purchasers of electricity attach greater utility to the provision of electricity at these times.

Quality differences may also be determined by a range of other non-physical attributes. Quality may be determined by conditions of sale, presence of free after sales service, guarantees for durable products, inclusion of delivery, methods for payment, and so forth.

Frequently the precise product priced in one period is no longer available in the next period because either there has been some change in the characteristics of the product or else something new has taken its place. For price index purposes it is necessary to devise techniques to identify quality differences and eliminate their effect on prices from the calculations of price change for inclusion in the index.

The objective of pure price indexes is to measure price change over time to constant quality. This is achieved by re-pricing an identical product or service each period and ensuring the product or service is unaffected by quality and quantity changes. The dynamic nature of products and services, where differentiating and improving quality of products and services is a key element, pricing to constant quality cannot be achieved without the application of quality adjustments. A failure to price to constant quality would result in a pure price index that reflected price change and quality change.

Adjusting for quality prevents distorted price statistics that can occur from unsuitable quality adjustments or incorrect application. Biases can arise from the inability to account for changes in quality over time.

Quality adjustments create conceptual and practical challenges, the importance of correct procedures ensure that price statistics measure pure price change.

The importance of pricing to constant quality is evident when the primary purpose of the Producer and International Trade Price Indexes is to support the calculation of volume measures in the Australian National Accounts and Balance of Payments. Pricing to constant quality results in the quality change being correctly reflected in the volume measures when deflation of current price estimates occurs.

The real world of economic transactions is ever changing and dynamic. Frequently the product priced in one period is no longer available in the next period because either there has been some change in the characteristics or something new has taken its place. Specific varieties of products regularly appear then disappear. New products can appear because of advances in technology, making the production of these new products possible.

Failure to account for quality changes would introduce a bias into the price index. Thus, if the qualities of products being compared are not identical, there are effectively two options:

• to adjust the observed price of the old quality for the change in quality which has taken place (referred to as a quality adjustment) or
• to treat the two qualities as if they were two separate products and obtain their prices in the periods in which they were not collected.

The problem facing price statisticians is isolating and quantifying the direct effects of changes in the quality on products they are pricing in the fixed basket, to achieve an index of pure price change. However, the ABS has several options for quality adjustment available for index managers and further information on the methods are available below.

Quality adjustment is defined as making a change in the price or price movement that accounts for the change in quality that affects the utility of the product.

In compiling the Producer and International Trade Price Indexes, five situations and treatment methods are clearly defined when a product changes:

• Overlapping sales - where there is at least one period when both qualities are on sale in the market at the same time
• Non-overlapping sales - where one quality is replaced by another of different quality, but the two qualities have not been available in the market at the same time
• Component approach - where there are some changes in the composition of a particular quality
• Hedonics - where the different qualities are assumed to be functions of certain measurable characteristics or
• Not directly comparable - where qualities are different, but no information exists to allow an explicit quality adjustment to be made.

Overlapping sales arise where a particular product being priced is no longer available in the market place from one period to the next, but there is another similar product that has been, and continues to be, available in the same market as the initial product and is expected to be a substitute once it is discontinued.

In this situation, provided the two products were sold side by side for some time in the same market and both were sold in reasonable quantities, the approach is to collect prices for both products at the one date and to assume that the difference in prices represents the difference in quality between the two. The assumption is that the market has adequate knowledge of the qualities and prices of each product and that the difference in price is regarded by them as a reasonable measure of the difference in quality. The second product is then substituted for the first using the technique of splicing price series, as illustrated below:

Example: consider two harvesters for sale. Harvester A is for sale in period 0 and period 1. Harvester B is for sale in period 1 and period 2. The two harvesters are both for sale during period 1, in which case there is an overlap of the two products. The products are considered to be of different qualities.

The price movement reflected in the index from period 0 to period 1 is the movement in the price of Harvester A (6.3%). The price movement from period 1 to period 2 is based on Harvester B (3.2%), which will be priced in subsequent periods to replace Harvester A. The difference in price between Harvester A and Harvester B has been eliminated through the process of splicing the new price series to the old price series.

An equally applicable interpretation of this process is to consider the comparison of prices between period 1 and period 2. In period 1, Harvester A is priced at $85,000. In period 2, Harvester B is priced at $98,000, and this is interpreted as:

• a quality change of $10,000, from $85,000 to $95,000
• a price change of $95,000 to $98,000.

In some cases, even with overlapping sales, simple splicing of the price of the new specification to the existing price series is not a satisfactory way of eliminating changes in quality. This situation occurs, for example, when the price of a new model reflects not only the extent of modifications but also a degree of price change, upwards or downwards, for reasons quite distinct from these modifications. In these circumstances, a simple splicing of the old and new prices would eliminate the elements of pure price change as well as the elements of change in quality. In such cases, it is necessary to assess the degree of pure price change involved and to ensure that this is reflected in the price series after splicing.

Where two qualities are not sold in the marketplace at the same time, it is necessary to implement indirect methods of quantifying the change in quality. This circumstance arises frequently for durable products, such as motor vehicles, white goods, home entertainment products and so forth, where producers cease all production of the superseded model when a new model is introduced. In these cases, it is necessary to estimate the relative prices of the old and new models, had they been sold in the market at the same time. The estimated relative prices then give an indication of the measure of the relative qualities.

In many circumstances the difference between the old and new products is a matter of size or dimensions. For example, an 80g jar of instant coffee is replaced with a 100g jar. In such cases the difference in price is readily determined by considering the per unit price; in the case of instant coffee, the change in price per gram would yield the quality adjusted price change¹. 

This process is equivalent to considering the difference in size as a difference in quality, and then explicitly pricing this difference. In the case of the coffee jar, the process would be to determine the price of the extra 20g. This value would then indicate the quality change between the smaller and the larger jar. In practice, this value of the quality difference is used to quality adjust the previous period price, such that the products in both the current period and the previous period are of the same quality.

These data may be interpreted as:

• a quality change of $1.05, from $4.20 to $5.25, representing the addition of an extra 20g of coffee; and
• a price change of $-0.25, being the fall from $5.25 to $5.00.

The method used to adjust for changes in the composition of a quality is to identify the quality difference and place a value on that difference. Frequently the composition of a particular product changes because of the use of different materials or the addition or deletion of particular features.

An example would be a change in the wool/synthetic mix of a yarn. In such cases, the technique used to estimate the value to the user of the quality change involves ascertaining the additional cost (or saving) to the manufacturer and examining the prices of broadly comparable products (e.g. yarns containing various proportions of pure wool and synthetic fibres).

Sometimes the modified product differs markedly from the previously priced product. An example of such changes occurs with the change in model for a particular make of motor vehicle. This type of quality change requires the collection of a considerable amount of information and, in some cases, subjective judgement is required to estimate a monetary value by which to adjust the price. The first step is to obtain a full picture of the differences between the old and new models. This is done by:

• obtaining detailed information from the manufacturer or industry associations, such as design and engineering reports
• examining published tests and other comments on the new model in trade publications, magazines, etc.
• physically examining the new model and questioning producers about the nature of the changes.

Having identified the precise differences between the models, the next step is to determine which of these differences represents changes in quality and to estimate the monetary value of each change. Some changes are relatively simple to quantify. Continuing the car example, changing the type of tyres on the new model when both types of tyres are sold separately in the market is readily assessable since the value of the quality change can be assessed as the difference in the selling prices of the tyres.

Other changes require more detailed examination. If we consider motor vehicles again, a new model car may have leather covered seats while the old model has cloth covered seats, in which case the factors that would be considered are:

• the unit cost to the manufacturer of the change
• whether the leather covered seats have been previously available as an option and, if so, what was the price and did a significant number of buyers purchase the option at that time
• the change in comfort and durability of the seats.

When faced with measuring prices for products which undergo rapid quality change, international best practice is to develop hedonic price indexes when suitable source data are available. This is the approach being advocated by international agencies such as the Organisation for Economic Co-operation and Development³, the International Labour Organization and the International Monetary Fund.

A hedonic price index is any price index that utilises, in some manner, a hedonic function. In broad terms, a hedonic function identifies the relationship between the prices of different varieties of a product, such as differing models of personal computers, and the characteristics within them. By comparing prices and features of various computers, a hedonic regression model assigns values to each of the particular features that are identified as price determining (for example, processor speed, memory, disk capacity etc.).

Personal computers are an area of rapid technological change. Products available in the marketplace change frequently as new features are added and existing features improve. For example, the rapid change in hard disk size, random access memory, and clock speed of desktop personal computers is well documented. A further issue is that older models quickly become redundant. The net result of these changes is that over any two periods there are both new products and discontinued products, with the result that comparing like with like becomes difficult. This is of particular concern when it is observed that improved features on later models do not always result in a price rise, or a commensurate price rise that would be observed if the components were bought separately (again, a bigger hard disk drive is an example). The quality adjustment problem is applicable to all price indexes, not just those for personal computers. However, traditional approaches to solving this problem (for example, matched model approaches, explicit quality adjustments, or component level pricing, amongst others) are inadequate for these sorts of products.

The Producer Price Indexes use a form of hedonic index known as the 'consecutive two period chained time dummy double imputation hedonic price index' for use in price indexes for personal computers. This process sees a matched model price index applied for personal computers sold between consecutive periods, combined with a consecutive-period time dummy price index (this is produced by using regression techniques) to measure price changes for both discontinued and newly introduced products.

The double imputation method can best be thought of as a traditional matched model index with an explicit adjustment applied because of both the departure of superseded models and the introduction of new models. A key deficiency of the basic matched model approach is that it makes no provision for systematically including the effects of price and quality changes in models available in the marketplace, and determines price change by only considering those models which appear in the market in both periods of interest. In other words, any improvement in quality associated with the introduction of a new model will not be measured if only matched models are priced.

The double imputation price index counters this deficiency by implicitly imputing price movements for both superseded models and newly introduced models. This is where the term 'double imputation' arises. A hedonic regression model is run on the dataset each period and from this, a price factor is determined for each characteristic of the computer. Whilst this gives the ability to calculate the price for each specification, what is actually used in the imputation, is the time dummy variable. The time dummy variable is representative of the price change between the two periods taking into account the different characteristics of the computer. This is combined with the matched model index to create the double imputation index which will reflect the movement of the whole sample. The index is then considered representative of all transactions, since recently superseded models and new models are included in the determination of price change, in addition to products common to both periods.

Further, the implicit imputation process at the core of this technique uses a hedonic function to adjust for changes in the characteristics of both the new and superseded models; that is, the prices imputed are adjusted for quality change, and hence the resulting index measures pure price change.

The process utilises price data from Australian vendors of personal computers, and so is not only representative of the Australian marketplace but also avoids issues with both exchange rate fluctuations and arbitrarily lagging prices to take account of shipping times etc. The double imputation index uses a hedonic function based on characteristics of personal computers sold in the Australian marketplace, using prices in Australian dollars, and so furthermore does not rely on the restrictive assumptions underlying a universal hedonic function.

Any movements in the double imputation index can be decomposed into the movement due to changes in prices of the matched sample, and the movement due to changes in other products in the marketplace. Movements in the index can be explained in terms of changes in list prices of existing products and changes in quality of new products, and so the resulting measures are easily explainable to users.

Despite the efforts to quantify explicitly differences in quality, circumstances occasionally arise where insufficient information exists to value the differences between two models of a product. In such cases it is still necessary to make a quality adjustment to allow comparison of prices. In the absence of any other information, the strategy employed in the Producer and International Trade Price Indexes is to consider the problem in two parts:

1. If the old model had existed in the current period, how much would the price have changed between the current and previous period?
2. What would the price have been in the current period?

If no other information is available, the quarterly movement in the price of the old model needs to be estimated from the price movements of similar products. In this manner the price movement problem is directly comparable to the imputation and temporarily missing price observations problem described in the Producer and International Trade Price Indexes Calculation in practice section.

Once the price movement has been determined, an estimate of the current period price for the old model can be made by working forwards from the observed previous period price. The new model is then introduced in the subsequent period (with a back price), and any difference at that time between the estimated price for the old model and the (observed) previous period price for the new model is due to the difference in qualities between the two models.

This approach is only used in circumstances where other efforts at quality adjustment have been exhausted, since excessive use would introduce bias into the price indexes. Such biases arise because of the assumptions underlying the application of this technique.

1. Prices for new models move the same as prices for other models - the use of the not directly comparable technique has an implicit assumption that the new model has the same price movement as other models. It is known across some industries that prices are increased when new models are introduced (as a means of increasing revenues and profits), in which case use of this mechanism would result in a downward bias for these types of products.
2. Prices change for reasons other than the introduction of new models - a more severe consequence of the prices move the same assumption occurs for those products where the only price movement occurs when models are changed. In this case, prices for continuing models remain static from period to period. The introduction of a new model would always result in an imputed (estimated) price change of zero - meaning that the index would never change. This may also be interpreted as all differences in observed price being solely attributable to quality change.

The incorporation of new products into an index, results in high quality indexes because it ensures they have a representative sample. New products exhibit different pricing behaviours to established products. Excluding them will result in biasing of the indexes.

The production or importation of a new product causes particular difficulties in compiling indexes and these difficulties arise because:

• new products are difficult to identify when using a fixed basket; in particular, difficulties arise when differentiating new products from improvements to existing products
• measuring price changes for new products has its own range of issues
• incorporating a new product into a fixed basket index requires index restructuring, measurement of value data for the new product and reweighting of the existing index structure.

The key question in identifying new products is differentiating new products from existing products whose quality has changed. A practical definition of a new product is that the new product cannot be effectively linked to an existing product as a continuation of an existing resource base and service flow. For example, the VCR was a completely new product when it was introduced in the 1970s because nothing like it had existed before. On the other hand, the DVD recorder replaced the VCR when it was introduced.

Identifying new products requires regular assessment of the marketplace, involving ongoing liaison with producers, regulatory authorities, and industry associations. The ABS approach this problem using several different methods.

For the International Trade Price Indexes, new products are identified through the analysis of data from the Australian Border Force, and International Merchandise Trade Statistics. These data are particularly useful since they not only highlight the emergence of new products but also the value of sales and purchases, indicating the importance of any new product.

The Producer Price Indexes use a variety of different instruments to detect the emergence of new products. First, questions regarding new products are asked each period in the Survey of Producer Prices. Second, regular contact is made with providers outside the quarterly cycle to assess specifically potential changes in production. Finally, a program of personal visits is made to providers and industry associations.

After a new product is identified, its price for two consecutive periods needs to be determined before it is included in the price index. This requirement ensures that a quarterly price movement can be associated with the new product. Such a requirement means that back prices are sometimes used, where the price in a previous period is supplied in a later period. In all circumstances, it is necessary for the product to have existed in the marketplace sufficiently long enough for a price movement to be determined. Of further concern is that an individual new product will almost certainly represent other such products sold in the marketplace, in which case it is necessary that any such initial price movement is representative of the entire market (for the new product).

A new product, by its very nature, does not belong to the fixed basket of a price index and must be introduced at some point after its arrival in the marketplace. As described above, the bias associated with new products is exacerbated through delays in introducing it into the price index. Yet a new product can only be introduced when both sufficient value data for the product exists and when the price index is reviewed.

Value data (either revenue or expenditure depending upon the nature of the price index) are essential for incorporating any product into a price index. Introducing a new product will also have an impact on the revenue (or expenditure) of other products in the marketplace. Consequently, value data are required for not only the new product but also for other products in the price basket. The introduction of a new product results in a value aggregate (and therefore a weight) being attached to the new product, and a change in the value aggregates of other products in the basket.

As the economy evolves and industries emerge and change, the ABS regularly reviews the scope and composition of its Producer and International Trade Price Indexes. This process is known as an ‘index review’ and can result in changes being required to existing price indexes, and to implement these changes, three steps must be undertaken to effectively update the series without compromising the quality of the price index:

• A link period must be chosen
• Value data must be price updated to the link period
• The newly weighted index chained onto the existing price index.

This process can apply to changes to an exist index series, or when a new elementary aggregate (or any other component) is introduced into a price index structure.

The link period is the designated time period where the index is calculated on both an old and new weighting basis. The link period is based on availability and timing of data, internal resource constraints, economic behaviour and should not coincide with changes to tax legislation or other significant regulatory amendments.

It is generally up to the index manager to identify an appropriate link period to implement a change to the index series, however, in practice the June quarter is the preferred period as it allows direct comparison of complete financial years without having to account for the link. 

Weights are price updated to account for price changes between the weight reference period and the link period. Weighting data usually comes from an annual data source, and in some cases can span more than one year. The link period, however, is always chosen to be a single quarter, and is always a period subsequent to the weight reference period. Although only observed in aggregate, the value data can be considered as being composed of the product of prices and quantities from the weight reference period. For inclusion in the index, these data will be expressed in terms of quantities from the weight reference period and prices from the link period.

Price updating value data is achieved by multiplying the weighting data by the proportional price change between the weight period and the link period. This updating occurs at the elementary aggregate level, with the resulting upper level value aggregates determined by aggregating the price updated components along the index structure.

The proportional price change between the weight period and the link period is determined by the ratio of the price indexes for the two periods; here the price indexes are on the existing index structure. In the usual case where the weighting reference period is longer than a quarter, the price index for the weight period is determined as the average of the quarterly price indexes that the weighting period spans. The ratio is the link period index divided by the averaged weight period index.

The resulting link period value aggregate is then expressed in terms of prices from the link period and quantities from the weight reference period.

In period 3, prices and quantities are returned to their index reference period values and in period 4 the index reference period prices and quantities are shuffled between items. The period 3 situation is sometimes described as time reversal and the period 4 situation as price bouncing.

The index number under direct estimation returns to 100.0 when prices and quantities of each item return to their index reference period levels; however, the chained index numbers do not.

This situation poses a quandary for prices statisticians when using a fixed weighted index. There are obvious attractions in frequent chaining; however, chaining in a fixed weighted index may lead to biased estimates. This can occur if there is seasonality or cycles in the price, and chaining coincides with the top or bottom of each cycle. For this reason, it is generally accepted that indexes should not be chained at intervals less than annual.

The Australian Bureau of Statistics changes the index reference period (a process known as re-referencing) for its suite of price indexes from time to time, but not frequently. This is because frequently changing the index reference period is inconvenient for users, particularly those who use price indexes for contract escalation, as it rebases the index reference period back to 100.0. Additionally, the process of re-referencing can result in the loss of precision for historic data, especially for time series with a significant historical timeseries.

Re-referencing in practice

The conversion of an index series from one index reference period to another involves calculating a conversion factor using the ratio between the two series of index numbers. The derived conversion factor is applied to the historical series to create a new historical series on the new reference period.

For example:

In this example, an update to the index reference period of an index series is required to be made from an index reference period of 1998-99 = 100.0 to 2011-12 = 100.0 (see Table 3.9 below).

The average value of the price index series from the index reference period of 1998-99 is (150.2 + 150.7 + 151.1 + 152.2)/4 = 151.1. (rounded to one decimal place).

A conversion factor is then derived by diving the rounded average value by 100 (100.0/151.1) to produce the value of 0.6620.

The March quarter 2011 index number for the new index reference period of 2011-12 = 100.0 would be the value of the current March quarter 2011 index value (147.0) multiplied by the derived conversion factor (0.6620), which would be 97.3 (147.0×0.6620).

A similar process would be used to reconvert the data back from the 2011-12 index reference period to the 1998-99 index reference period.

For example:

If the December quarter value for 2012 of a price index was 103.6 which, when multiplied by the conversion factor of 1.511 (151.1/100.0), would give an index number of 156.5 on the index reference period of 1998-99 = 100.0.

It should be noted that a different conversion factor will apply for each index. There is no universal conversion factor for all Producer and International Trade Price Indexes.

Please note that re-referencing should not be confused with reweighting. Re-referencing does not change the relative movements between periods. However, reweighting involves introducing new weights and recalculating the aggregate index for each period which will affect the relative movements between periods.

As stated above, the process of re-referencing can have an impact on the precision of long-term historical time-series. This issue arises as a result of the ABS rounding and storing published price indexes to one decimal place.

Published percentage changes to index numbers are calculated from the rounded index numbers. A consequence of re-referencing price indexes can be that period-to-period percentage changes may differ to those previously published due to rounding of the re-referenced values. These differences do not constitute a revision.

As re-referencing is conducted to account for substitution in the marketplace, the evolution of pricing methods and the emergence of new products. Re-referencing is not performed frequently as changing the index reference period is problematic for users, particularly those who use the Producer and International Trade Price for contract escalation.

The ABS last re-referenced the Producer and International Trade Price Indexes in the September quarter 2012 with the index reference period of the 2011-12 Financial Year = 100.0 

The Import Price Index and Export Price Index employ the use of exchange rates where the contractual currencies of transactions are recorded in currencies other than Australian dollars. While a proportion of Australia’s international trade is conducted in Australian dollars, those that are traded in foreign currencies require conversion to Australian dollars. Hence changes in the relative value of the Australian dollar against overseas currencies (in particular, the major trading currencies such as the United States dollar, Japanese yen, Pound sterling and Euro) has a direct impact on the price of  products purchased or sold in foreign currencies. That is, when the Australian dollar appreciates, it buys more foreign currency, and the price of the product in Australian dollars falls. Conversely, when the Australian Dollar depreciates, it buys less foreign currency and price of the product in Australian dollars rises.

Example:

Consider a transaction undertaken in US dollars.  Assume that the transaction is $200 USD in both September and December.

If the exchange rate in September is 0.75 (that is, 1 Australian dollar buys 0.75 US dollars, or 75 US cents), the $200 USD transaction equates to:

AUD price = USD price / (USD per AUD exchange rate)

                 = $200 USD / (0.75 USD per 1 AUD)

                 = $266.67 AUD

If the exchange rate in December is 0.80 (that is, 1 Australian dollar buys 0.80 US dollars, or 80 US cents), then we say that the "dollar has appreciated", and the $200 USD transaction equates to:

AUD price = USD price / (USD per AUD exchange rate)

                 = $200 USD / (0.80 USD per 1 AUD)

                 = $250.00 AUD

The Australian dollar price has fallen from $266.67 to $250, or a fall of 6.25%