Accuracy and reliability
Contact infoPrices and Consumption, Economic Statistics
André Pedersen Ystehede
+45 39 17 31 63
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The sample is selected using a top down approach, i.e. the businesses with the largest turnover are selected for the sample to achieve the highest coverage possible with as few reporting units as possible. As the sample is not selected randomly the sample error cannot estimated, however, overall the index i assessed to be of high quality. Only final statistics are published.
The statistics is currently based on around 2.000 reported prices each year, which makes up around 40 per cent of the number of completed one-family houses each year. The prices are reported from a small number of businesses specialized in building turn-key one-family houses. The businesses are selected using a top-down approach, i.e. the businesses with the largest turnover are selected for the sample to achieve the highest coverage possible with as few reporting units as possible. The prices from these businesses, thus, represent all newly completed one-family houses, regardless of whether they are standard houses or one of kind. In spite of this, the accuracy is assessed to be acceptable, as the calculation of the index is performed using a hedonic regression approach. The information needed to differentiate between standard and one of a kind houses are not available, thus, a mix of prices on standard houses and one of a kind houses could add some error to the statistics. Non-response is minimal and is not regarded as a significant source of error. It is assessed that the price development of the sample is representative of the price development in the population. Errors can furthermore arise from errors in the reported prices and from errors in the administrative data. Data is thoroughly examined for these types of errors before they are included in the calculations.
The sample is selected top-down to achieve as high turnover coverage as possible. The sample is therefore not a random sample and it is not possible to estimate the overall size of the sampling error.
The statistics is based on 30 to 40 percent of the completed one-family houses i Denmark, which is assessed to be a sufficient market coverage. Over-coverage is is avoided by only including houses of the correct type which have been completed within the relevant period of time.
When the construction companies report prices and the associated addresses on newly completed one-family houses errors may occur. Therefore, the reported prices are checked thoroughly and the information is compared to the Danish Buildings and Dwellings Register (BBR). Furthermore, error may occur in the BBR, however, this type of error is expected to have very little influence on the statistics. A small number of the reported prices for a given period will not included in the calculations if the associated information cannot be found in the BBR. Besides from this, no issues with non-response have occured.
The price development is calculated using hedonic regression which implies some assumptions with regards to which characteristics influence the price of the construction of a one-family house. The characteristics used in the calculation are the following: · Floor area · Roof · Number of rooms · Number of bathrooms · Number of floors · Geography · Construction company Information on quality (eg. marble vs. ceramic tiles) cannot be obtained from the administrative registers, and thus, to get this information it must be reported from the construction companies. This would, however, place an unfair burden on the businesses, which is why the information is not included in the calculations. This introduces risk of error, as a price development might be driven by changes in quality. However, it is expected that the quality of houses built in two consecutive quarters will have the same quality on average.
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.
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.
An overall quality assessment rests upon a combination of coverage, number reporting businesses and prices in the sample and he quality of the collected prices and the price methods used. The sample is selected in order to cover as large a share of the turnover in the industry as possible. Since the statistics was established in 2015, prices for 30 to 40 per cent of the completed one-family houses each year. The coverage varies according to the combined market share of the reporting companies that has been increasing throughout the time period. Prices are matched with information from the Buildings and Dwellings Register, e.g. floor area, number of bathrooms and roofing materials. This information is used in the calculation of the index using a hedonic regression - a method recommended by Eurostat for calculating price indices for heterogeneous products/services. The quality is monitored continuously and efforts are put in where the quality can be improved. The quality work e.g. consists of supplementing the sample.
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