Quality Report on the Dataset: RAF-2
Quality Report on the Dataset: RAF-2 Report on Production, Trade, Stocks, and Storage and Transmission Infrastructure for Crude Oil, Petroleum Products, and Biofuels
Report approval date: December 31, 2025
Responsible person(s): Lidia Nagrodkiewicz, Joanna Matysiak
GENERAL INFORMATION
The report concerns the use of the dataset for the purposes of survey 1.44.11 Liquid and Gaseous Fuels according to the Public Statistics Survey Program (PBSSP) for 2025.
Symbols and names of surveys (PBSSP) for which this dataset is used in a given year: 1.44.03 Specialized Statistical Survey on Fuels and Energy, 1.44.01 Fuel and Energy Balances
Detailed information about the dataset:
The dataset is collected twelve times a year (cumulatively), is mandatory in nature, and is directed to a representatively selected group of population units on a purposefully selected sample. According to PBSSP 2025, data was collected once a month by the 15th day after the month for the period from the beginning of the year to the end of the reporting month and by January 16, 2026, for the period from the beginning of the year to the end of December 2025. The subject scope of the survey covers the following entities of the national economy (regardless of the number of employees): producers of petroleum refining products, licensed entities conducting trade in petroleum refining products and their components (plants and branches), operators or owners of storage and transmission infrastructure for crude oil and fuels
Information on the use of administrative sources for the dataset
Data obtained from the survey is used together with data from sectoral surveys of the Ministry of Energy, surveys conducted by the President of the Central Statistical Office, administrative information systems of the President of the Energy Regulatory Office, KOWR data, the register of producers and traders obliged to create mandatory stocks maintained by the Government Strategic Reserves Agency.
Information about the dataset and its preparation is available in PBSSP 2025
RELEVANCE
Relevance means the degree to which statistical information meets current and potential user needs. It reflects both the scope of statistics produced and the adequacy of methodological solutions applied, including definitions, classifications, and breakdowns, to the expectations of data recipients. The assessment of relevance is made based on the identification and analysis of user groups, determination of their information needs, and verification of the extent to which these needs are met by available statistical products.
Users of the dataset are ministries and central offices, local offices (government and local government administration), entrepreneurs, employers, investors, producer associations, scientific and educational institutions, researchers, students, media - press, radio, television, individuals, internal users. Data users also include foreign institutions, e.g., Eurostat, IEA (International Energy Agency), NATO.
The indicator (rate) of available variables for the dataset (i.e., the ratio of the number of variables provided by respondents based on relevant ESS regulations and/or variable provisions in PBSSP to the number of required variables according to the aforementioned regulations) is: 99%
ACCURACY
Accuracy means the degree of closeness of statistical estimates obtained to the actual value of population parameters. Quality assessment in this area includes analysis of both random errors resulting from the application of sample selection (sampling errors) and non-random errors unrelated to the sampling process, arising at individual stages of survey implementation, including during data collection, processing, and preparation.
Non-sampling errors
Non-random errors occur in all statistical surveys and apply to all variable sets, significantly affecting the interpretation and use of obtained results. Among them, non-response errors are of particular importance, as they can lead to systematic error and simultaneously increase the level of random error in estimates.
Non-response errors occur when no answer is obtained to one or more questions contained in the form or when no information is provided by a given reporting unit. The result of this type of error is a discrepancy between the values of statistics calculated based on available data and the values that would be obtained in case of complete responses.
There are two basic types of non-response errors:
- Unit non-response (subjective non-response error) — a situation in which no data was obtained for a given unit covered by the survey because the unit did not submit a report.
- Item non-response (objective non-response error) — a case when data was collected for a given unit only for some variables covered by the survey, while there are no answers for the remaining information.
For the purposes of the quality report, the phenomenon of non-response is assessed by the unweighted unit response rate, i.e., the ratio of the number of units that responded and are in the result set on the basis of which generalization (calculation of results) is made to the number of units selected for the survey, excluding overcoverage units, i.e., units that are outside the scope of the survey or do not exist in practice (e.g., liquidated units not removed from the frame). For the RAF-2 dataset, the indicator is 0.
TIMELINESS AND PUNCTUALITY
Timeliness of data refers to the time interval between the moment of occurrence of the described phenomenon or event and the moment of making statistical information about it available. Information relevant from the point of view of usefulness to the user.
Punctuality concerns compliance with established publication deadlines and means the difference between the actual date of data dissemination and the date of their planned publication indicated in the official release calendar. Punctuality thus measures the degree of compliance of publication implementation with schedule commitments.
For the RAF-2 dataset Report on Production, Trade, Stocks, and Storage and Transmission Infrastructure for Crude Oil, Petroleum Products, and Biofuels, preliminary results are made available only to bodies conducting survey 1.44.11 Liquid and Gaseous Fuels, while final results are made available to all interested recipients.
In the case of final data, the time interval between the end of the surveyed period and the date of publication of final results for the monthly publication Statistical Information on the Liquid Fuels Market is up to two months. The collected data was made available in accordance with the publication calendar.
ACCESSIBILITY AND CLARITY
Accessibility and clarity refer to the degree to which users can obtain access to statistical data in a simple and user-friendly manner, receive it in the expected form, and in an acceptable time. They also include providing an appropriate resource of accompanying information, in particular metadata, methodological explanations, and information support, which create the necessary context enabling proper interpretation and optimal and effective use of statistics.
Output data obtained from the RAF-2 report Report on Production, Trade, Stocks, and Storage and Transmission Infrastructure for Crude Oil, Petroleum Products, and Biofuels is available in the publication: Statistical Information on the Liquid Fuels Market
https://www.are.waw.pl/badania-statystyczne/wynikowe-informacje-statystyczne#informacja-statystyczna-o-rynku-paliw-cieklych
Data is presented in breakdowns: territorial, temporal, and according to NACE Rev. 2
COMPARABILITY
Comparability refers to the degree to which statistics can be compared between different geographical areas, statistical domains, and reference periods while maintaining interpretive consistency. It assesses the impact of differences in definitions, classifications, measurement methods, and data sources used on the ability to properly compare statistical results over time and space.
In the current edition of the survey, there were no breaks in time series or other changes affecting temporal comparability.
The length of the period for which it is possible to obtain series of comparable statistical data for the above-mentioned example variables of the survey is 252 (the value is given in months).
COHERENCE
Coherence of statistics means the ability of statistical data to be mutually linked and combined with other information sets in a way that enables their comprehensive use in various analyses and applications, both within one statistical domain and between different thematic areas and data sources. Coherence of statistics is its ability to integrate in various ways and for various applications.
Statistical data created on the basis of the RAF-2 dataset Report on Production, Trade, Stocks, and Storage and Transmission Infrastructure for Crude Oil, Petroleum Products, and Biofuels is coherent with other datasets in the scope of annual and short-term surveys, surveys from the same thematic area.
This applies to the following datasets:
- INTRASTAT and EXTRASTAT systems,
- Report on production P-01 and Report on production of products and stocks P-02,
- Balance report on energy carriers and district heating infrastructure G-02b,
- Report on settlement of the transformation process in enterprises producing and processing petroleum refining products RAF-1,
- data from RARS,
- data from KOWR,
- data from URE.