Accuracy and reliability

Overall accuracy

The accuracy of PPPs increases with the level of aggregation. This means that the PPP (and thus also the PLI, real expenditure and volume index per capita) at GDP level will be more reliable, or precise, than the PPP for final household consumption or gross capital formation. Similarly, the PPP for final household consumption will be more reliable than the PPP for "food and non-alcoholic beverages", or "clothing and footwear", the latter two being sub-aggregates of final household consumption.

An important source of uncertainty is the selection of goods and services, which are not equally representative of all countries included in the international comparisons. Consumption is composed differently in the various countries, and there is therefore a potential conflict between representativeness and comparability.

The input data into the PPP compilation process comes from several sources, specifically, from special PPP price surveys and from national accounts. This makes it impossible to calculate any meaningful, numerical measure of error margins for PPPs. However, there is general agreement that PPPs, PLIs and other PPP-based indicators are not intended to establish a strict ranking of countries. The degree of uncertainty associated with the basic price and expenditure data, and the methods used for compiling PPPs, may produce errors that influence the ranking of countries, particularly when countries are clustered around a very narrow range of outcomes. PPPs and PPP-based indicators thus provide an indication of the relative order of magnitude of one country in relation to other countries in the comparison. As outlined above, this is more so at a low level of aggregation than in the case of, for instance, GDP or GDP per capita.

Sampling error

In the price surveys, the most important source of statistical margins of sampling errors is the range of goods and services, which are not equally representative of all countries included in the international comparisons. The composition of consumption expenditure differs among countries, and this gives rise to potential conflicts between representativeness and data comparability.

Non-sampling error

For some areas, such as the health sector, it is particularly difficult to provide comparable information. The healthcare sector is structured differently in the various countries and there are no pure market prices for these services, which constitutes an additional source of uncertainty.

In the consumer goods price surveys, measurement errors can occur due to non-compliance with the strict definition of the products in the product sample, for instance with regard to package sizes or quality parameters. While the validation process aims at eliminating these errors by carefully comparing the price material provided by each country and evaluating its plausibility, some of these errors can be hard to identify, especially those related to quality. Similar problems can occur in other surveys as well, like the annual survey on compensation of public sector employees. Here, the problem stems from the heterogeneity of data sources across countries.

While non-response from one particular statistical unit can usually be easily overcome by replacing that unit, and normally has a very limited impact at the level of the published categories anyway, a special problem does occur where no prices are available for a given product in one or more countries. In these cases, a price relative is imputed on the basis of the price relatives for other products. If a country does not report prices for any sample product in a given basic heading, the gaps are typically filled using the PPP of either a "similar", or of a hierarchical, basic heading.

Quality management

Statistics Denmark follows the recommendations on organisation and management of quality given in the Code of Practice for European Statistics (CoP) and the implementation guidelines given in the Quality Assurance Framework of the European Statistical System (QAF). A Working Group on Quality and a central quality assurance function have been established to continuously carry through control of products and processes.

Quality assurance

Statistics Denmark follows the principles in the Code of Practice for European Statistics (CoP) and uses the Quality Assurance Framework of the European Statistical System (QAF) for the implementation of the principles. This involves continuous decentralized and central control of products and processes based on documentation following international standards. The central quality assurance function reports to the Working Group on Quality. Reports include suggestions for improvement that are assessed, decided and subsequently implemented.

Quality assessment

The data complies well with the PPP Regulation. Data are in general of good quality and the resulting PPPs are plausible.

Data revision - policy

Statistics Denmark revises published figures in accordance with the Revision Policy for Statistics Denmark. The common procedures and principles of the Revision Policy are for some statistics supplemented by a specific revision practice.

Data revision practice

There are only minor differences between provisional and final figures. Following the calculation of the final PPPs for a given reference year, PPPs are no longer revised. However, in order to maintain the highest possible degree of coherence with national accounts, the entire time series of PPPs is rescaled to the latest national accounts aggregates twice a year, in June and December, and the database updated accordingly.