Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

Results found: 10

first rewind previous Page / 1 next fast forward last

Search results

help Sort By:

help Limit search:
first rewind previous Page / 1 next fast forward last
1
Publication available in full text mode
Content available

Błogosławieństwo organów – wczoraj i dziś

100%
Baran P.
Pro Musica Sacra
|
2019
|
vol. 17
EN
The article presents the practice of blessing an organ pipe in the roman rite of thecatholic church. The author enlightens the blessings of the instrument in the liturgical lifeof the church, so that he can move on examine the various forms of blessing the organ,contained in the rituals. The history of the emergence of the ritual in the context of thelatest Vatican Council is also shown. Ending, the author presents a new form of the blessing,which is used in the archdiocese of Kraków in the last few years.
PL
Artykuł prezentuje praktykę błogosławieństwa organów w rycie rzymskim Kościoła katolickiego. Autor przybliża początki obecności organów w życiu liturgicznym Kościoła, by przejść następnie do analizy poszczególnych wersji błogosławieństwa organów obecnych w rytuałach. Przedstawiona jest również historia powstania tego obrzędu w kontekście ostatniej reformy soborowej. Na końcu autor prezentuje zupełnie nową formę błogosławienia organów, która od kilku lat jest używana na terenie archidiecezji krakowskiej.
2
Publication available in full text mode
Content available

Quality of INTRASTAT DATA. Comparison Between the ‘Old’ and the ‘New’ EU Member States

63%
Markowicz I., Baran P.
Acta Universitatis Lodziensis. Folia Oeconomica
|
2019
|
vol. 2
|
issue 341
69-80
PL
W systemie INTRASTAT zbierane są dane statystyczne dotyczące wymiany towarowej między krajami UE. Eurostat agreguje dane pochodzące z poszczególnych państw członkowskich. Specyfika procesu pozyskiwania danych różni się w poszczególnych krajach, w związku z czym dane lustrzane (dotyczące w założeniu tych samych transakcji, odnotowanych w statystyce kraju wywozu i kraju przywozu) często się nie pokrywają. Celem przeprowadzonych analiz była ocena jakości danych o wewnątrzunijnej wymianie towarowej krajów „starej” piętnastki i „nowych” członków UE ze wskazaniem, które kierunki w największym stopniu wpłynęły na występowanie obserwowanych różnic w danych lustrzanych. Artykuł jest kontynuacją badań jakości danych dotyczących handlu zagranicznego.
EN
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.
3
Publication available in full text mode
Content available

Analiza rozbieżności danych lustrzanych dotyczących masy towarów w statystykach handlu wewnątrzunijnego

63%
Markowicz I., Baran P.
Wiadomości Statystyczne. The Polish Statistician
|
2020
|
vol. 65
|
issue 8
27-38
EN
In the research carried out to date by the authors of the article, the assessment of the quality of mirror data in the exchange of goods between European Union (EU) countries was based on the value of goods. A similar approach is applied by many researchers. The aim of the research discussed in the article is to assess the quality of data relating to intra-EU trade based on not only the value, but also on the quantity of goods. The analysis of discrepancies in data relating to trade between EU countries, with a particular emphasis on Poland, was based on selected research methods known from literature. Both the value-based and the quantitative approach constitute the authors' contribution to the development of research methodology. Data quality indicators were proposed and data pertaining to the weight of goods were used. Information on trade in goods between EU countries in 2017 obtained from Eurostat's Comext database was analysed. The research relating to the dynamics also covered the years 2005, 2008, 2011, and 2014. The results of the analysis demonstrated that the total share of export of goods from Poland to a given country within the EU is different for data expressed in value (value of goods) and in quantity (weight of goods). Therefore, both approaches should be applied in the study of the quality of mirror data.
PL
W badaniach prowadzonych dotychczas przez autorów artykułu ocena jakości danych lustrzanych w wymianie towarowej między krajami Unii Europejskiej (UE) opierała się na wartości towarów. Analogiczne podejście stosuje wielu badaczy. Celem badania omawianego w artykule jest ocena jakości danych dotyczących obrotu wewnątrzunijnego na podstawie nie tylko wartości, lecz także ilości towarów. W analizie rozbieżności danych w handlu między krajami UE, ze szczególnym uwzględnieniem Polski, wzorowano się na wybranych metodach badania znanych z literatury przedmiotu. Podejście zarówno wartościowe, jak i ilościowe stanowi wkład własny autorów w metodykę badawczą. Zaproponowano wskaźniki jakości danych oraz wykorzystano dane dotyczące masy towarów. Analizie poddano informacje na temat obrotu towarowego między krajami unijnymi w 2017 r. pochodzące z bazy Eurostatu Comext. Badanie dynamiki obejmowało również lata: 2005, 2008, 2011 i 2014. Wyniki analizy pokazały, że ogółem udział wywozu z Polski towarów do danego kraju na obszarze UE jest różny dla danych wyrażonych wartościowo (wartość towarów) i ilościowo (masa towarów). W badaniu jakości danych lustrzanych należy zatem stosować oba podejścia.
4
Publication available in full text mode
Content available

Intra-community trade asymmetries-based clustering and linear ordering of combined nomenclature chapters using Generalized Distance Measure (GDM)

63%
Markowicz I., Baran P.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2019
|
issue vol. 23 no. 3
50-58
EN
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.
5
Publication available in full text mode
Content available

Jakość danych statystycznych dotyczących obrotów towarowych między krajami Unii Europejskiej

63%
Markowicz I., Baran P.
Wiadomości Statystyczne. The Polish Statistician
|
2019
|
vol. 64
|
issue 1
7-19
EN
The objective of presented analysis is to assess quality of data on foreign trade within the Union. Data from Eurostat’s COMEXT database was used. The differences between declared export quantities of foods from a given country and data on imports from this country to other member states gathered by Eurostat have been analyzed. These differences partly result from the adopted statistical thresholds and reflect the quality of the collected data. The authors have compared EU member states based on convergence of data on dispatches and arrivals of goods from each country. Using data discrepancy measures member states were ranked with regard to statistical data quality, which is an innovation in foreign trade research.
PL
Celem przedstawionego w artykule badania jest ocena jakości danych dotyczących handlu zagranicznego wewnątrz Unii Europejskiej (UE). W badaniu wykorzystano dane za 2017 r. pochodzące z bazy Comext, udostępnianej przez Eurostat. Zbadano różnice między deklarowanymi wartościami wywozu towarów z danego kraju a danymi o przywozie z tego kraju do innych krajów UE. Różnice te częściowo wynikają z przyjętych progów statystycznych i odzwierciedlają jakość zgromadzonych danych. Kraje unijne porównano także pod względem zbieżności danych o wywozie i przywozie towarów z poszczególnych krajów. Wykorzystując miary rozbieżności danych, uszeregowano kraje pod względem poziomu jakości danych statystycznych, co stanowi element innowacyjny w badaniach handlu zagranicznego.
6
Publication available in full text mode
Content available

Jakość danych dotyczących wewnątrzunijnej wymiany towarowej

63%
Markowicz I., Baran P.
Wiadomości Statystyczne. The Polish Statistician
|
2019
|
vol. 64
|
issue 6
5-15
EN
Official statistics on trade in goods between EU member states are collected on country-level and then aggregated by Eurostat. Methodology of data collecting differs slightly between member states (e.g. various statistical thresholds and coverage), including differences in exchange rates as well as undeclared or late-declared transactions, errors in classification of goods and other mistakes. It often involves incomparability of mirror data (nominally concerning the same transactions recorded in statistics of both dispatcher and receiver countries). A huge part of these differences can be explained with the variable quality of data resources in the Eurostat database. In the study data quality on intra-EU trade in goods for 2017 was compared between Poland and neighbouring EU countries, i.e.: Germany, Czech Republic, Slovakia, Lithuania, and other Baltic states – Latvia and Estonia. The additional aim was to indicate the directions having the greatest influence on the observed differences in mirror data. The results of the study indicate that the declarations made in Estonia affect the poor quality of data on trade in goods between the countries mentioned above to the greatest extent.
PL
Dane statystyki publicznej dotyczące wymiany towarowej między krajami Unii Europejskiej (UE) gromadzone są na poziomie krajowym, a następnie agregowane przez Eurostat. Metodyka zbierania danych różni się w pewnym zakresie w poszczególnych krajach członkowskich (np. różne są progi statystyczne i poziom pokrycia), a do tego występują różnice kursowe, transakcje niezgłoszone, opóźnione zgłoszenia, błędy klasyfikacji towarowej i inne. Powoduje to, że dane lustrzane, dotyczące w założeniu tych samych transakcji odnotowanych w statystyce kraju wywozu i kraju przywozu, są często nieporównywalne. Znaczną część rozbieżności można tłumaczyć zróżnicowaną jakością zbiorów danych zasilających bazę Eurostatu. Celem przedstawionego w artykule badania jest porównanie jakości danych za 2017 r. o wewnątrzunijnej wymianie towarowej Polski i sąsiednich krajów UE: Niemiec, Czech, Słowacji i Litwy oraz pozostałych krajów bałtyckich – Łotwy i Estonii. Dodatkowym celem jest wskazanie, które kierunki w największym stopniu wpłynęły na występowanie różnic w danych lustrzanych. Wyniki przeprowadzonej analizy wskazują, że najczęściej wpływ na niską jakość danych dotyczących wymiany towarowej między badanymi krajami mają deklaracje składane w Estonii.
7
Publication available in full text mode
Content available

ICA and ICS-based rankings of EU countries according to quality of mirror data on intra-Community trade in goods in the years 2014-2017

63%
Markowicz I., Baran P.
Oeconomia Copernicana
|
2019
|
vol. 10
|
issue 1
55-68
EN
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.
8
Publication available in full text mode
Content available

A Ranking of Combined Nomenclature Chapters According to Quality of Data on Intra‑Community Trade in Goods of Polish Businesses

63%
Markowicz I., Baran P.
Acta Universitatis Lodziensis. Folia Oeconomica
|
2019
|
vol. 4
|
issue 343
195-209
PL
Wprowadzenie w Polsce systemu INTRASTAT wraz z wejściem naszego kraju do Unii Europejskiej 1 kwietnia 2004 roku spowodowało nałożenie na podmioty prowadzące obrót towarowy z innymi państwami członkowskimi UE obowiązku przekazywania informacji o zrealizowanych przez nie obrotach. Dane o handlu wewnątrzwspólnotowym z poszczególnych krajów gromadzone są przez Eurostat i udostępniane w postaci bazy Comext. W celu określenia jakości danych o wewnątrzwspólnotowej wymianie towarowej zbadano różnice między deklarowanymi wartościami wywozu towarów z Polski i przywozu z Polski do pozostałych krajów unijnych. Celem artykułu jest analiza jakości danych o polskim handlu wewnątrzunijnym w podziale na działy nomenklatury scalonej CN oraz utworzenie rankingu działów pod względem jakości danych, rozumianej jako rozbieżność między danymi lustrzanymi. Pomiaru jakości danych dokonano z wykorzystaniem zagregowanych wskaźników rozbieżności. Zaprezentowano ranking działów według wyznaczonych wartości wskaźników, osobno dla wewnątrzwspólnotowych dostaw towarów (WDT) i wewnątrzwspólnotowych nabyć towarów (WNT). Wykorzystano dane z bazy Comext dotyczące transakcji wewnątrzwspólnotowych polskich eksporterów w 2017 roku. Efektem przeprowadzonego badania było wskazanie działów o największych względnych rozbieżnościach między danymi lustrzanymi (najniższej jakości danych). W działach o najniższej jakości wskazano wewnętrzną strukturę rozbieżności według krajów oraz pozycji klasyfikacji towarowej. Problem jakości danych dotyczących handlu wewnątrzwspólnotowego jest poruszany w Polsce jedynie w publikacjach GUS‑u. Brak jest prac naukowych w tym zakresie. Dlatego też autorzy postanowili wypełnić tę lukę i prowadzić badania nad źródłami informacji, które są podstawą wielu analiz gospodarczych.
EN
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.
9
Publication available in full text mode
Content available

A new method for calculating mirror data asymmetry in international trade

63%
Markowicz I., Baran P.
Oeconomia Copernicana
|
2020
|
vol. 11
|
issue 4
637-656
EN
Research background: Some statistics are of a bilateral nature. This is how foreign trade data is organized. They are recorded both in the supplier and recipient countries, hence they are called mirror data. The data recorded at both trading partner countries are not the same for different reasons. Such differences between data on the same groups of transactions are often referred to as the asymmetry of mirror data. The information about the value of the flows of goods are of great importance in economic analyses and therefore their quality is particularly important. Purpose of the article: The aim of this paper is to present a new measure of data asymmetry - the aggregated quantity index with value-based weights. Methods: The proposed measure combines the quantity and the value of turn-over in individual trade relations. Such a measure makes it possible to eliminate basic deficiencies in value-based measures, while considering the specificity of trade in individual countries. The proposed measure of data asymmetry was confronted with several measures present in the literature and previously used by the Authors. The numerical example uses Comext data on intra-Community trade in 2017 provided by Eurostat. Findings & Value added: The proposed measure performs better than all the previously used data asymmetry indices. It is to some extent immune to exchange rate differences and inconsistencies resulting from the inclusion of transport and insurance costs in the value of goods. In addition, it gives lower weights to unimportant trade directions than other data asymmetry indices. Since the new index has proved to be better than the measures previously used, it is worth applying to those trade relations where the data are not de-rived from customs documents, but from declarations made by businesses, as in the case of intra-Community trade.
10
Publication available in full text mode
Content available

Mirror data asymmetry in international trade by commodity group: the case of intra-Community trade

63%
Markowicz I., Baran P.
Oeconomia Copernicana
|
2021
|
vol. 12
|
issue 4
889-905
EN
Research background: Transactions in international trade of goods are recorded in two sources, on the side of the seller's country and on the side of the buyer's country. The confrontation of such data makes it possible to measure their quality. An inconsistency between the data is called mirror data asymmetry. Purpose of the article: The aim of the paper is to adapt the methods developed by the Authors to study mirror data asymmetry to commodity group markets examination. The quality of data on trade within specific commodity groups (CN chapters) in intra-Community trade was compared. The data were aggregated by country. The indicators used allow for the indication of commodity groups with high mirror data compatibility and those with data asymmetry between intra-Community supplies (ICS) and acquisitions (ICA). Moreover, the commodity groups for which the value-based and quantity-based approaches give different results have been identified. Methods: Based on the literature on the subject and their own research, the Authors have developed a group of methods for studying the asymmetry of mirror data. The proposed indicator formulas are based on various data aggregation approaches. The research used data on intra-Community supplies and acquisitions of goods broken down into 97 chapters of the Combined Nomenclature (CN). Differences between the ICS and ICA in particular commodity groups were aggregated for all pairs of EU countries. The data comes from the Comext database, provided by Eurostat. Findings & value added: The results of the analysis are rankings of the Combined Nomenclature (CN) chapters by the quality of data on ICS and ICA. Lists of CN chapters have been created for discrepancies both in value and weight of goods. Thus, areas of necessary intensification of the work of public statistics services to improve data reliability were identified.
first rewind previous Page / 1 next fast forward last
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.