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Many factors influence the prices of energy commodities and the value of energy and fuel companies. Among them there are the following factors: economic, social, environmental and political, and recently also the COVID-19 pandemic. The aim of the paper is to examine what the probability and intensity of a decrease in the prices of shares of energy and fuel companies listed on the Warsaw Stock Exchange (Poland) was during the first wave of the pandemic in the first quarter of 2020. The study used the survival analysis methods: the Kaplan-Meier estimator, the test of equality of duration curves and the Cox non-proportional hazards model. The analysis showed that the probability and intensity of price decline of energy and fuel companies in the initial period was the same as that of other companies. The differences become apparent only after 50 days from the established maximum of their value. The risk of price declines in energy and fuel companies increased significantly. This situation was related both to a temporary reduction in demand for energy and fuels, pandemic restrictions introduced in individual countries and the behaviour of stock market investors.

The aim of the research was an assessment of the relative risk of liquidation of a company depending on its age. The research covered economic entities established in Szczecin in the period 1990-2010. The analysis was carried out with the use of a logit model. The risk of company liquidation was examined depending on the entity’s age expressed both in months (continuous variable) and in grouped intervals (year, half-year). In this way, attention was drawn to the benefits of continuous variable coding (rank and 0-1 coding). The research covered companies established during 1990-2010 in total (over 120 thousand) and in time periods resulting from the cyclical character of liquidation of companies (in accordance with the earlier research findings). The research showed that the risk of company liquidation decreases as the company grows older (the use of a continuous variable and a rank variable). On the other hand, the risk of subsequent age groups (using the 0-1 variable) prevents the risk from being monotonous.

The aim of this study was to construct models of trading companies’ lifespan, in individual districts of Zachodniopomorskie Voivodship. The author verified whether the impact of the survival time of trading companies on the survival function in general is the same in individual districts. This may inform potential entrepreneurs’ decisions on whether to set up a trading or other company. The Kaplan‑Meier estimator was calculated and a tests verifying similarities of functions of trading companies within the districts was used. Districts were then divided into groups, according to trading companies’ lifespan. Further on, the functions of the intensity of companies’ liquidation for particular districts were analysed. The rankings of districts were compared in terms of the lifespan of trading companies and businesses in total. In the study, the author used REGON registry, containing data about companies established in Zachodniopomorskie Voivodship in 2009–2011. These entities were observed until the end of 2013. It is something to be considered by both decision makers and entrepreneurs, that the probability of liquidation of a trading company is greater than of any other company. Trading activity is prevailing (the highest percentage of all newly established companies are trading companies), however, trading companies are also most in danger of liquidation. // Celem przeprowadzonych badań była budowa modelu czasu trwania firm handlowych dla poszczególnych powiatów województwa zachodniopomorskiego. Oszacowano estymator Kaplana‑Meiera oraz zastosowano test weryfikujący podobieństwo funkcji firm handlowych w powiatach. Utworzono grupy powiatów. Zbadano funkcję intensywności likwidacji firm w grupach. Porównano uszeregowania powiatów pod względem czasu trwania firm handlowych i firm ogółem. W badaniu wykorzystano dane z rejestru REGON, dotyczące firm powstałych w województwie zachodniopomorskim w latach 2009–2011 (21 powiatów). Obserwacja trwała do końca 2013 roku. Jest to sugestia zarówno dla decydentów, jak i dla przedsiębiorców, że prawdopodobieństwo likwidacji firmy handlowej jest większe niż innych firm. Działalność handlowa jest przeważająca (największy udział w nowych firmach) i najbardziej narażona na likwidację.

The aim of the study was to construct models of firms’ survival duration for individual poviats in the Zachodniopomorskie Voivodeship. The first stage was the calculation of the Kaplan‑Meier estimator and the use of a test for the verification of similarities in the survival function for the analysed poviats. As a result, groups of poviats were created. The next stage of research was the construction of duration tables of the studied firms and an analysis of the intensity function of firms’ liquidation for the poviats. The percentage of firms liquidated after two years of activity in different poviats (stage III) was presented. An analysis of correlation between the percentage of firms liquidated in the analysed period and the number of entities registered per 10 thousand of population in the poviats (stage IV) was also conducted. This study used data from the registry of REGON related to companies established in the Zachodniopomorskie Voivodeship in 2009–2011. These entities were observed till the end of 2013. The study results reveal the differentiation of firm survival models in the poviats of the Zachodniopomorskie Voivodeship. Five groups of poviats were distinguished and characterised.

One of the sustainable development goals (SDG7) is to ensure access to clean and affordable energy, which is related to most other SDGs and plays a crucial role in economic development and human well-being. The aim of the article is to identify factors that enhance and delay one of the most crucial goals of sustainable development, SDG7. The study’s originality lies in the spatiotemporal approach to analysing the impact of selected factors on the development of green energy and increasing its availability. Three groups of potential SDG7 determining factors have been identified: ecological, social and economic. The proposed approach and the use of sensitivity analysis to variables weighting and ranking constructions of EU countries is an innovative aspect of the work and fills the gap in research on SDG7. The study showed that Denmark and Sweden occupy leading positions in the rankings based on the extent of SDG7 implementation. In contrast, Bulgaria, Cyprus and Lithuania occupied one of the last positions. The results of panel-data model estimations showed that in each estimated model, the same “indispensable variables” significantly affect the implementation of SDG7. Among these variables, only the unemployment rate significantly negatively impacted the SDG7 execution. First published online 15 November 2024

Research of firms cohorts, such as human cohorts, are carried out by means of the methods of survival analysis (duration). The paper presents the possibility of using expectancy tables and intensity function (hazard) of firms liquidation. This function may take a typical shape such as shape of a “bathtub” – the intensity of deaths, or the shape of an inverted U – the intensity of firms liquidations.

Research background: As a system of official EU statistics, Intrastat contains data collected by Member States aggregated by Eurostat on the Union?s level in the form of COMEXT database. Country-level data are based on declarations made by businesses dispatching or acquiring goods from other EU Member States. Since the same transaction is declared twice ? as an ICS in one country and at the same time as an ICA in another country by the partner ? the database contains mirror data. Analysis of mirror data lets us assess the quality of public statistics data on international trade. Purpose of the article: The aim of the article is to rank EU Member States according to quality of data on intra-Community trade in goods collected by Intrastat. Foreign trade stimulates economic development on one hand and is the development?s reflection on the other. Thus it is very important that official statistics in this area be of good quality. Analysis of mirror data from partner states in intra-Community trade in goods allows us to claim that not every Member State pro-vides data of satisfactory quality level. Methods: We used the authors? methodology of assessing quality of mirror data. These include data asymmetry indices, both proposed by Eurostat and the authors? own proposals. We have also examined the changes in the above mentioned rankings over time. Findings & Value added: The result of the survey is ordering of EU Member States according to the quality of data on intra-Community trade in goods. The rankings are presented for the period of 2014?2017, during which there were 28 Member States of the EU. Changes in distinct countries? positions were shown as a result of changes in overall quality of statistical data collected in these countries. The research methodology can be used in the process of monitoring data quality of the Intrastat system.

Statistical data on foreign trade are collected in all EU member states separately and then passed on to Eurostat where the data are aggregated. Continuous actions are to ensure that all datasets collected at national level are fully comparable. The aim of the paper is to provide a classification as well as an ordering of CN chapters (2-digit codes) according to the quality of data on intra-Community trade of goods. Data were taken from Eurostat’s COMEXT database. In ordering the chapters, we utilized the distance from the ideal solution with GDM as the distance measure. The study reveals a structure of goods subject to intra-Community trade that is supplementary to the official nomenclature. In addition, we provided CN chapters ordering according to the overall level of irregularities in reported mirror values of ICS and ICA. The results we obtained are of practical value for both researchers and authorities interested in foreign trade.

Adopting the Intrastat system in Poland on its EU‑accession on 1st May, 2004 imposed a new obligation on companies trading goods within the EU. They are obliged to provide information on their intra‑Community trade in the form of monthly declarations. Data on intra‑Community trade from all Member States are collected by Eurostat and disseminated in the form of the Comext database. In public statistics, special attention is being paid to data quality. It is constantly monitored and certain actions are taken to improve it. In order to assess quality of data on intra‑Community trade, the authors have calculated differences between declared values of supplies of goods from Poland as well as foreign acquisitions originating in Poland. The aims of the paper are an analysis of quality of data on Polish intra‑Community trade in goods within Combined Nomenclature chapters as well as creating a ranking of chapters with regard to data accuracy (one of quality dimensions) which we define in terms of divergence between mirror data. Data accuracy was measured with the use of aggregate data quality indices. The ranking of Combined Nomenclature (CN) chapters was presented according to the calculated index value for both intra‑Community supplies of goods (ICS) and intra‑Community acquisitions (ICA). We utilised data on Polish exporters’ transactions from 2017 from the Comext database. In the research results, we indicate those chapters for which large relative discrepancies between mirror data are observed (thus data quality is low). For chapters with low data quality, we present inner structures of discrepancies by country and by CN position. The problem of quality of data on intra‑Community trade is addressed in Poland only in publications of the Central Statistical Office/Statistics Poland. There are no scientific publications on this subject. Therefore, the authors decided to fill this gap and conduct research on sources of information which is the basis for many economic analyses.

The Intrastat system is used for gathering statistical data on trade in goods between the EU Member States. Data from all the Member States are aggregated by Eurostat. Specifics of the data collection process are different in different countries and that is why mirror data (regarding by default the same transactions revealed in statistics of both the acquirer and supplier country) often do not match. The goal of the analysis conducted was to assess the quality of data on intra‑Community trade in goods between the ‘old’ fifteen and the ‘new’ EU Member States as well as to point out these directions that influenced the observed differences in mirror data the most. The paper is a follow‑up of previous research on the quality of foreign trade data.