Speaker bios
of the 5th Congress of Polish Statistics (Warsaw July 1-3, 2025)
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Speaker bio:
Dr hab. Jan Acedański - ekonomista i statystyk, profesor Uniwersytetu Ekonomicznego w Katowicach, gdzie kieruje Katedrą Metod Statystyczno-Matematycznych w Ekonomii; specjalizuje się w wykorzystaniu metod statystycznych, ekonometrycznych i matematycznych w ekonomii, finansach i zarządzaniu. Autor około 70 opublikowanych prac naukowych, które ukazały się między innymi w takich czasopismach jak Journal of Official Statistics, International Journal of Consumer Studies, Economic Modelling, Applied Economics, The North American Journal of Economics and Finance czy Central European Journal of Economic Modelling and Econometrics. Kierował także grantem NCN SONATA dotyczącym narzędzi modelowania rozkładu majątku w gospodarce polskiej.
Abstract:
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Objective
The paper aims to develop and evaluate, using Polish data, a simple spatiotemporal method for disaggregating annual regional GDP series to quarterly frequency using a smoothing algorithm, and to compare its results with a multivariate regression-based approach that uses auxiliary variables.
Methods
The method assumes that the disaggregated series should exhibit minimal fluctuations while satisfying balancing constraints: regional quarterly sums must match the annual regional data, and the sum of regional quarterly values must equal to the national quarterly figure. The resulting optimization problem is solved via an interior-point algorithm. Its sequential variant requires revising only the most recent disaggregated series when data for a new year become available. A regression model with four benchmarks is used for comparison.
Results
The sequential smoothing method produced quarterly regional GDP growth rates with a level of smoothness comparable to national data while still capturing local variations (e.g. the COVID-19 downturn). A comparison with the one-step version confirmed almost identical results. Against the regression-based approach, average differences in annual growth rates reached up to 0.8 percentage points, with correlation coefficients exceeding 0.87. Forecasting performance analysis indicated that the smoothing method is competitive with regression when series are short or horizons are brief.
Conclusions
The proposed procedure is computationally simple, requires no auxiliary indicators, and can be implemented by statistical offices lacking long, high-quality regional data series. Its sequential variant minimizes historical revisions while maintaining close agreement with regression-based methods. Combining smoothing with a regression-based approach could be considered for further improvement.
Keywords
regional GDP, temporal disaggregation, nowcasting, smoothing algorithm, interior point optimization
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Speaker bio:
Patryk Barszcz - absolwent Uniwersytetu Kardynała Stefana Wyszyńskiego w Warszawie (UKSW), politolog, socjolog, doktor socjologii. Autor rozprawy doktorskiej poświęconej zjawisku samotności wśród młodych dorosłych singli. Zawodowo związany z Głównym Urzędem Statystycznym w Warszawie, gdzie pełni funkcję Eksperta w Departamencie Opracowań Statystycznych i Executive Managera w międzynarodowym czasopiśmie naukowym Statistics in Transition new series. Autor 16 artykułów naukowych. Członek Polskiego Towarzystwa Socjologicznego. Zainteresowania naukowe oscylują wokół zjawiska singlizmu we współczesnym społeczeństwie polskim, samotności, pokolenia Millenialsów, Gniazdowników, młodzieży NEET oraz alternatywnych form nawiązywania relacji międzyludzkich. Numer ORCID: 0000-0002-4025-8255
Abstract:
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Objective
The aim of the presentation during the poster session is to present the position of the Polish scientific journal in the international scientific circulation. The history of the journal, citation indicators in international databases, special issues published in SiTns in recent years and the thematic scope of the quarterly will be presented.
Methods
Presentation of the history of the journal, thematic scope, Special Issues over the years during the poster session during the 5th Congress of Polish Statistics.
Results
Statistics in Transition new series is present in many databases, including Scopus. The journal aspires to join the elite Philadelphia list of scientific journals.
Conclusions
Statistics in Transition new series is a leading Polish scientific journal in the field of statistics. Its presence in many international databases, including primarily Scopus, indicates a very high substantive level of the journal.
Keywords
Statistics in Transition new series, scientific journals
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Speaker bio:
Jacek Białek - is a full professor at the University of Łódź in Poland, where he has been a long-time faculty member in the Department of Statistical Methods. His primary research interests focus on the theory and application of price indices, with particular expertise in the measurement of the Consumer Price Index (CPI) and the Harmonized Index of Consumer Prices (HICP). Additionally, he works at Statistics Poland in the Department of Trade and Services, specializing in the analysis of scanner and web-scraped data. Professor Białek has authored over 100 scientific publications and developed the PriceIndices R package, a tool widely used for analyzing scanner data and calculating price bilateral and multilateral indices. He is also a member of the Editorial Board of the International Journal of Statistics and Probability. For his scientific achievements, Professor Jacek Białek has received numerous prestigious awards, including the Minister's Award, the City of Łódź Award, the "Łódzkie Eureka" distinction, as well as several Rector's Awards from the University of Łódź.
Abstracts:
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Objective
The aim is to investigate if there is an effective yet automatic procedure for detecting downsizing and upsizing? An attempt is made to construct such a procedure in the R environment. Moreover, the aim is to determine the scale of hidden inflation for different food and non-food product groups and the sensitivity of different price index formulas to the phenomenon of over- and under-sizing (disproportionate to its price).
Methods
The study uses IT toosl: R environment and PriceIndices package. The research method is an empirical study using actual scanner data. The data source is a retail chain operating in Poland (cooperating with Statistics Poland).
Results
Both groups of products that do not generate hidden inflation (e.g. bread) and groups of products that are particularly vulnerable to downsizing and upsizing (e.g. yoghurt) are indicated. The results suggest that price index formulas (weighted and unweighted) have different vulnerabilities to hidden inflation (being more or less sensitive to downsizing and upsizing).
Conclusions
Multilateral indices have been shown to be much less sensitive to the phenomena under consideration than bilateral indices. In particular, chained indices (e.g. the Jevons chained index) appear to be particularly susceptible to the phenomenon of hidden inflation. The results in this regard are pioneering in the literature.
Keywords
scanner data, product downsizing, shrinkflation, product upsizing
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Objective
The subject of the study is to present the methodology for estimating changes in taxi service prices in Poland using data collected from the websites of companies and taxi corporations (i.e. using the so-called web-scraping). One of the objectives is also to present the technological and methodological challenges that the statistical office faces when it wants to implement this type of data in the regular production of price indicators. The presented solutions are, among others, the result of activities carried out as part of a project financed by the European Commission.
Methods
The subject of presentation is to present the methodology for estimating changes in taxi service prices in Poland using data collected from the websites of companies and taxi corporations (i.e. using so-called web-scraping). One of the objectives is also to present the technological and methodological challenges that the statistical office faces when it wants to implement this type of data for regular production of price indicators. The presented solutions are, among others, the result of activities carried out as part of a project financed by the European Commission.
Results
As a result of the work carried out, a method for calculating price indices for taxi services in Poland was developed, as well as the tools necessary to collect and gather data from carriers' websites.
Conclusions
The main conclusion from the undertaken action is to implement the methodology for estimating the dynamics of taxi service prices developed under the presented work into the statistical production. It is also recommended to use an automated method for collecting data made available in the public space, which will contribute to an increase in the number of observations of changes in the levels of taxi service prices, as well as to expand the range of service representatives. In addition, solutions and experiences gained in the area of price statistics should be used in other areas of statistical surveys.
Keywords
taxi service prices, stripped data, elementary index, Dutot index
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Objective
The aim of the study is to develop a new price index based on transactional (scanner) data that satisfies both axiomatic requirements (in particular the identity and transitivity tests) and accounts for changes in product quality over time. The authors propose a new index – GEKS-GAQI (Geometric Asynchronous Quality Adjusted Index) – as an extension of the multilateral GEKS indices, which are widely used in inflation measurement based on scanner data.
Methods
An axiomatic and economic approach was applied in constructing the price index. The new GEKS-GAQI index is based on quality-adjusted unit prices and quantities, and uses a geometric averaging method of the sub-indices. The analysis was conducted using real scanner data on milk and coffee sales in Polish supermarkets, provided in the R package “PriceIndices.” In the empirical study, GEKS-GAQI was compared with other indices: GEKS, CCDI, TPD, GEKS-L, GEKS-AQI, GEKS-AQU, and GEKS-GL, both at the barcode (GTIN) level and the COICOP 6 level.
Results
The GEKS-GAQI index satisfies both the transitivity condition and the identity test, making it stand out among other multilateral indices. The analyses showed that the level of data aggregation significantly influences index values. At the COICOP 6 level, index values are more stable than at the GTIN level. Additionally, GEKS-GAQI produced values close to those of the GEKS-GL index, which also meets the identity test. Interesting differences between the multilateral indices under consideration were observed depending on the type of data (milk vs. coffee) and the level of aggregation.
Conclusions
The proposed GEKS-GAQI index provides a methodological and practical contribution to the development of modern inflation measurement methods using scanner data. It stands out from popular indices by combining quality adjustment features with formal properties, making it a promising option. Its use can improve the accuracy of inflation measurement and reduce distortions caused by the so-called chain drift effect. Moreover, GEKS-GAQI bridges the gap between the GEKS approach and the quality-adjusted Geary-Khamis method, opening new possibilities in the field of price statistics.
Keywords
Scanner data, multilateral indices, the GEKS-index
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Speaker bio:
Małgorzata Bogdan is a Professor of Statistics and Head of the Statistics Unit at the University of Wrocław, Poland. She currently serves as Chair of the European Regional Committee of the Bernoulli Society and leads the Commission of Statistics under the Committee of Mathematics at the Polish Academy of Sciences.
She received her PhD from the Wrocław University of Science and Technology and later held a postdoctoral fellowship at the University of Washington, supported by the Foundation for Polish Science. Her international academic experience includes appointments as Visiting Assistant Professor at Purdue University, a Fulbright Scholar at Stanford University, and Professor of Statistics at Lund University, Sweden.
Her research centers on variable selection in high-dimensional settings, Bayesian model selection, and statistical applications in genomics, medicine, finance, and astronomy. In 2020, she received the Hugo Steinhaus Award from the Polish Mathematical Society in recognition of her lifetime contributions to the application of mathematics. In 2024, she was named a Fellow of the Institute of Mathematical Statistics (IMS), acknowledging her influential work in high-dimensional statistics, integration of Bayesian and frequentist approaches, and leadership in international scientific collaboration.
Abstract:
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Objective
Development of a new algorithm for PCGLASSO—a scale-invariant estimator of the high-dimensional partial correlation matrix—and analysis of the properties of both PCGLASSO and the proposed algorithm.
Methods
Theoretical analysis of the properties of PCGLASSO. Derivation of the asymptotic distribution and the condition for the asymptotic recovery of the true structure of the related graphical model. Comparative computer simulations and real data analysis.
Results
The method can recover the hub structures much more efficiently than Graphical LASSO. The proposed algorithm is much more efficient than earlier solutions for PCGLASSO.
Conclusions
The proposed method is effective for uncovering the true structure of network dependencies and has broad applicability, for example in genetics and finance.
Keywords
precision matrix,graphical models,high-dimensional data,sparsity
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Speaker bio:
Dr Justyna Bogołębska - Adiunkt, Wydział Zarządzania, Uniwersytet Łódzki. Specjalizuje się w analizie finansowej przedsiębiorstw, internacjonalizacji działalności gospodarczej oraz zarządzaniu finansami w sektorze MŚP i spółkach giełdowych. Jej zainteresowania badawcze koncentrują się wokół wpływu internacjonalizacji na wyniki finansowe przedsiębiorstw, w szczególności z rynków wschodzących. Autorka publikacji z zakresu finansów przedsiębiorstw, modeli panelowych oraz efektywności strategii ekspansji zagranicznej.
Od 2021 roku prowadzi badania nad zależnością między stopniem internacjonalizacji a rentownością spółek w branży spożywczej oraz przemysłowej. Współpracuje z ośrodkami badawczymi w Polsce i za granicą, uczestnicząc w projektach naukowych i konferencjach międzynarodowych.
W pracy dydaktycznej koncentruje się na rachunkowości zarządczej, analizie sprawozdań finansowych i modelowaniu finansowym.
Abstract:
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Objective
This study aims to assess the financial effects of internationalization in the food industry by comparing exporters and non-exporters (using ROA, ROE and ROS), and by analyzing the impact of internationalization intensity (foreign revenue share) on these metrics. Hypotheses are divided into two sets: basic export status comparison and continuous level of internationalization.
Methods
The study applies fixed-effects panel regression, complemented by Hausman, Breusch-Pagan and robust standard error corrections (Huber-White). The dataset includes over 9,800 firm-year observations from 1998 to 2023. Dependent variables are log-transformed ROA, ROE and ROS, and independent variables include internationalization level, revenue, total assets and market capitalization.
Results
No significant differences in ROA, ROE or ROS were found between exporters and non-exporters. However, a higher level of internationalization significantly reduced ROA and ROS, with ROE remaining statistically unaffected. For ROS, a nonlinear, escalating negative effect was detected.
Conclusions
Internationalization does not automatically improve profitability in the food industry. Negative effects on ROA and ROS may reflect expansion costs, operational complexity and delayed returns. This study challenges common assumptions and contributes robust empirical evidence to the literature on firm internationalization.
Keywords
internationalization, financial performance, food industry, panel data, ROA, ROE, ROS
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Speaker bio:
Krzysztof Borysiak - całym dotychczasowym życiem zawodowym (18 lat) związany jest ze statystyką publiczną. W tym czasie był zaangażowany w różne zadania na każdym poziomie procesu badania, tj. projektowanie zakresu zbieranych danych, gromadzenie i analiza danych, przygotowanie opracowań statystyczny oraz udostępnianiem danych statystycznych, ale również z ich promowaniem oraz budowaniem pozytywnego wizerunku statystyki publicznej.
Do zadań zasługujących na wyróżnienie należą m.in.:
- wieloletnie projektowanie zakresu przekazywanych danych administracyjnych w ramach badań z obszaru gospodarki społecznej;
- udział w przygotowaniu koncepcji pozyskiwania danych z ewidencji stowarzyszeń prowadzonej przez starostwa i urzędy miast na prawach powiatu oraz koordynacja pozyskiwania danych w ramach tego źródła;
- współudział w przygotowaniu publikacji:
- wydawaną cyklicznie co dwa lata od 2008 r. Sektor non-profit Stowarzyszenia, fundacje, społeczne podmioty wyznaniowe, samorząd gospodarczy i zawodowy,
- Współpraca organizacji non-profit z innymi podmiotami (2019, 2017),
- Rola sektora non-profit w dostarczaniu usług społecznych w latach 2014-2016,
- coroczna informacja sygnalna od 2012 r. „Centra integracji społecznej, kluby integracji społecznej, zakłady aktywności zawodowej, warsztaty terapii zajęciowej”;
- koordynacje prac związanych z pozyskaniem danych oraz opracowywaniem wyników z badania 1.04.07 Podmioty nowej gospodarki społecznej: centra integracji społecznej, warsztaty terapii zajęciowej, zakłady aktywności zawodowej;
- wieloletnie opracowanie tablic wynikowych do publikacji i Banku Danych Lokalnych z obszaru gospodarki społecznej;
- udział w pracach rozwojowych:
- w projekcie Usługi integracji społeczno-zawodowej na poziomie NTS 4”.
- w projekcie Zintegrowany system monitorowania sektora ekonomii społecznej;
- udział w promocji badań statystycznych.
Abstract:
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Objective
The aim of this study is to present the role of reintegration units in preventing social exclusion in Poland between 2015 and 2023. These units implement social and professional reintegration services targeted at long-term unemployed individuals, persons with disabilities, people leaving penitentiary institutions, and the homeless. Their operation was strengthened by the Act on social economy of 2022, which defined their status within the social economy sector and assigned them a key role in implementing the objectives of the National Programme for the Development of Social Economy.
Methods
W analizie wykorzystano dane pochodzące wyłącznie ze źródeł administracyjnych: systemów informacyjnych urzędów wojewódzkich, Ministerstwa Rodziny, Pracy i Polityki Społecznej oraz Państwowego Funduszu Rehabilitacji Osób Niepełnosprawnych. Wyniki W 2023 r. działało 1246 jednostek reintegracji społeczno-zawodowej – o 17 mniej niż rok wcześniej, ale o 57 więcej niż w 2015 r. W ciągu 2023 r. z usług reintegracji społeczno-zawodowej skorzystało blisko 49,0 tys. osób zagrożonych wykluczeniem społecznym, tj. o 2,1% więcej niż w 2022 r. W latach 2015-2023 ich liczba wzrosła o 21,6%. Działalność prowa
Results
In 2023, 1,246 units providing social and professional reintegration services were active—17 fewer than in 2022, but 57 more than in 2015. Nearly 49,000 individuals at risk of social exclusion benefited from reintegration services in 2023, representing a 2.1% increase compared to 2022 and a 21.6% increase compared to 2015. Most of the entities focused on activating people with disabilities—733 occupational therapy workshops and 141 vocational activity establishments.
Conclusions
Reintegration units play an important role in preventing social exclusion by supporting individuals at risk of marginalisation in returning to the labour market and active social life. Ongoing monitoring of reintegration units is essential to assess the impact of their services on the economic independence of individuals at risk of social exclusion, which is crucial for effective social policy and sustainable social development.
Keywords
Reintegration units, social exclusion, social and professional reintegration services, social economy
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Speaker bio:
Barbara Cieślik - Mgr ekonomii (SGH), dr nauk ekonomicznych (SGH), adiunkt w Instytucie Rozwoju Gospodarczego Kolegium Analiz Ekonomicznych Szkoły Głównej Handlowej w Warszawie.
Zainteresowania naukowe: Modelowanie sezonowości procesów demograficznych, w szczególności zgonów i urodzeń. Zastosowanie metod ilościowych w ekonomii; szczególnie w ubezpieczeniach, analiza systemów bonus-malus z wykorzystaniem łańcuchów Markowa, modelowanie konkurencji na rynku ubezpieczeń komunikacyjnych, nowe trendy w ubezpieczeniach, w szczególności usage based insurance (pay as you go, pay as you drive, pay how you drive, etc.), wpływ nowych technologii na rynek ubezpieczeń.
Abstract:
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Objective
The purpose of this paper is to analyze seasonal variations in the monthly number of deaths in Poland and selected European countries in the first two decades of the 21st century using the TRAMO / SEATS method. The analyses cover European countries from different geographic regions, characterized by significant differences in the health status and age structure of the population.
Methods
The study used the TRAMO / SEATS method in the JDEMETRA+ software, which is recommended and dedicated by Eurostat for time-series analysis and deseasonalization. The long time series available made possible to examine differences and similarities between countries, as well as to assess the stability of seasonality patterns and their changes over time. Data were obtained from the Eurostat database and Statistics Norway.
Results
The results provide a broad picture of seasonality of deaths in the countries studied. The higher amplitude of the number of deaths and greater susceptibility of the population to seasonal factors in the south than in the north of Europe were confirmed. Decreasing role of seasonality of the death rate, encountered in many studies, was not confirmed. We note differences: the lowest amplitude of fluctuations in the west is in the Netherlands, the highest in Spain and the United Kingdom. In the south, Italy (large and increasing amplitude) and Greece (lowest amplitude, summer extreme) stand out.
Conclusions
The use of the time series decomposition method for analyzing demographic data to extract and fully characterize the pattern of seasonality of death is a novel approach used in this work. The issue of seasonality of death and its measurement addressed in this work is part of not only the growing interest in the scientific community in this issue, but also has great significance for health policy and the identification of necessary strategies in the situation of recurrent epidemics and the challenges posed by environmental factors and cyclically changing weather conditions.
Keywords
seasonality of death, TRAMO / SEATS decomposition, SARIMA models
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Speaker bio:
Zofia Danek - starszy statystyk w Ośrodku Metodologii Badań Ludnościowych w Urzędzie Statystycznym w Poznaniu. Ukończyła studia na kierunku informatyka i ekonometria, obecnie przygotowuje się do obrony pracy dyplomowej. W pracy zawodowej zajmuje się metodologią badań demograficznych, rozwijając kompetencje w zakresie zastosowania nowoczesnych technik analitycznych w statystyce ludnościowej.
Abstract:
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Objective
The aim of this presentation is to introduce capture-recapture methods for population size estimation (dual-system estimation, multiple-system estimation) that account for record linkage errors and their implementation in the {uncounted} package in R. The package is currently being developed at the Population Research Methodology Center in the Statistical Office in Poznań.
Methods
The presented tool includes classical estimators as well as estimators that incorporate record linkage error correction (one-way, symmetric, and asymmetric (Di Consiglio * Tuoto, 2018: Zult et al., 2025)).
Results
The package offers the capability for variance estimation and construction of confidence intervals to assess the quality of the estimates.
Conclusions
As part of the presentation, we will showcase the package in the context of administrative data, with special emphasis on modeling record linkage errors. Examples with simulated data will illustrate the package`s capabilities in various scenarios.
Keywords
capture-recapture, population size estimation, administrative registers, record linkage errors
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Speaker bio:
Czesław Domański - profesor Katedry Metod Statystycznych Uniwersytetu Łódzkiego, honorowy prezes Polskiego Towarzystwa Statystycznego. Do głównych obszarów zainteresowań naukowych należą: konstrukcje testów opartych na teorii serii i statystykach porządkowych, wnioskowania nieparametryczne ("Nieparametryczne testy statystyczne" 1979), nieklasyczne metody wnioskowania statystycznego ("Testy statystyczne", 1990; "Nieklasyczne metody statystyczne (współautor), 2000), statystyczne metody decyzyjne ("Testy statystyczne w procesie podejmowania decyzji", 2014 (współautor), historia polskiej statystyki ("Sylwetki statystyków polskich" 1984 (współautor), "Łódzka statystyka akademicka, 2020 (współautor). Członek kilku towarzystw naukowych i redakcji czasopism statystycznych.
Abstracts:
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Objective
The aim of the paper is to present the participation of Polish statisticians in the process of creating a uniform methodology of statistical research. The foundations of official statistics were created during 10 Statistical Congresses in the years 1853-1885.
Methods
The presentation of the achievements of statisticians is based on an in-depth analysis of the literature on the subject and on the study of documents and source materials.
Results
Starting from the Second Congress, which took place in Paris, Polish statisticians, including August Cieszkowski (1814-1894) took an active part in the event. In 1885, the last congress in this form was held in London, and at the same time the International Statistical Institute was then established. On June 24, 1825, the statute was adopted and the authorities were elected. The first president was Sir W. Rawson. One of the founders of the Institute was Professor Tadeusz Piłat (1844-1923) – director of the National Statistical Office in Lviv. He was the chairman of the MIS committee.
Conclusions
The next ordinary member of the Institute was Józef Kleszczyński (1841-1900), a professor of statistics and administrative law, who in 1885 published in the journal 'Przegląd Polski' an extensive article entitled 'International Statistical Institute', which was the first work devoted to the Institute. In this article, Kleszczyński postulated the establishment of an international statistical institution of an official nature. This postulate was implemented only after World War I.
Keywords
International Statistical Institute, Polish statisticians creating European official statistics
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Objective
The aim of the paper is to present and analyze the development of scientific research and teaching work conducted by statisticians and demographers from Łódź.
Methods
The presentation of the achievements of statisticians and demographers from Łódź is based on an in-depth analysis of the literature on the subject and the study of documents and source materials.
Results
Based on the analyses, it can be stated that the statistical research conducted in Łódz in the interwar period had a significant impact on the development of Polish statistics. In particular, these were works conducted under the supervision of the head of the Department of Statistics of the Łódź City Hall, Edward Rosset, and professor Edward Szturm de Sztrem, which addressed important socio-economic problems of Poland and Łódź, including: 'Alcoholism in the light of statistical researc': 'The political face of the population of the city of Łódź in the light of election research'.
Conclusions
The interwar achievements of Łódź statisticians continued after Poland regained independence within the framework of the University of Łódź, the Łódź branch of the Warsaw School of Economics and the Higher School of Economics. The achievements of the Łódź statistical community, which took place over the last 100 years, contributed to the creation of the Łódź school of statistics and demography.
Keywords
statistical research, development of statistical thought
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Speaker bio:
Dr hab. Mariusz Doszyń, profesor Uniwersytetu Szczecińskiego, specjalizuje się w ekonometrii i statystyce, rynku nieruchomości. Od 2019 roku pełni funkcję kierownika Katedry Ekonometrii i Statystyki w Instytucie Ekonomii i Finansów na Wydziale Ekonomii, Finansów i Zarządzania Uniwersytetu Szczecińskiego.
Jest autorem licznych publikacji naukowych z zakresu statystyki, wyceny nieruchomości, prognozowania i zastosowań ekonometrii. Jego prace ukazywały się m.in. w takich czasopismach, jak The Journal of Real Estate Finance and Economics, Journal of Forecasting, Journal of European Real Estate Research oraz Communications in Statistics: Simulation and Computation.
Od lutego 2024 roku jest zatrudniony jako ekspert w Urzędzie Statystycznym w Szczecinie, w Ośrodku Statystyki Rynku Nieruchomości.
Abstracts:
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Objective
A comprehensive framework identifying and examining the multifaceted problems (technical, governance-related, legal, ethical, economic, operational, socio-cultural) impeding the successful development, deployment and sustained operation of public sector data spaces, and to understand their interdependencies and collective impact is the aim of the presentation.
Methods
The study is based on an extensive review and synthesis of the academic literature, policy documents, government reports and case studies of European public sector data space initiatives. It utilizes a qualitative approach, analyzing documented challenges and lessons learned to build a comprehensive taxonomy and analytical framework of problems.
Results
The key findings reveal a wide spectrum of interconnected problems in building public sector data spaces. These span technical, governance, economic and socio-cultural dimensions, often creating compounding negative impacts.
Conclusions
The research provides a comprehensive taxonomy of the challenges, informing policy and practice for more effective public sector data space implementation. It underscores the need for holistic strategies addressing technical, governance, economic and socio-cultural issues to realize public value, foster innovation and retain citizen trust. A future research agenda is proposed to tackle unresolved problems and guide sustainable development.
Keywords
data spaces, public sector, data governance, European data strategy, digital transformation, data sharing, legal frameworks
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Objective
The aim is to present the possibilities of calculating price indices and rents for commercial real estate (retail, office, warehouse) in Poland.
Methods
The methodology usually takes into account the various types of indices calculated, mainly hedonic: time dummy, rolling time dummy, repricing, average characteristics, imputation, stratification method.
Results
The choice of the method for estimating the index depends on the amount of statistical information available in the database. More extensive databases, which include information such as property characteristics, allow for the calculation of hedonic indices, for example, using the rolling time dummy method.
Conclusions
Improving the quality of rental and commercial property price indices requires obtaining additional sources of data on commercial properties (other than the Property Price Register).
Keywords
price indices, rent indices, commercial real estate, hedonic indices
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Speaker bio:
Dr hab. Hanna Dudek - jest zatrudniona na stanowisku profesora uczelni w Katedrze Ekonometrii i Statystyki Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie, gdzie pełni funkcję kierownika Zakładu Ekonometrii i Inżynierii Finansowej.
Specjalizuje się w zastosowaniach metod statystycznych w badaniach społeczno-ekonomicznych. Jest autorką lub współautorką ponad stu publikacji naukowych, dotyczących m.in. wielowymiarowej analizy ubóstwa oraz ekonometrycznego modelowania różnych form deprywacji materialnej.
W ostatnich latach jej prace koncentrują się na ilościowej analizie poziomu życia, ze szczególnym uwzględnieniem aspektów nierówności społecznych i wykluczenia ekonomicznego.
Aktywnie uczestniczy w konferencjach naukowych poświęconych badaniom poziomu życia i pomiarowi ubóstwa. Jest członkiem Polskiego Towarzystwa Statystycznego.
Abstract:
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Objective
The aim of the paper is to measure the extent of extreme poverty, deprivation, and food poverty in Poland. The central research question is whether the so-called original OECD equivalence scale, used by Statistics Poland (GUS) to estimate extreme poverty and deprivation, is consistent with the scale effects implied by the construction of the subsistence minimum and the social minimum for different household types. In addition, the paper proposes using food expenditure thresholds – adopted in the measurement of extreme poverty and material deprivation – as boundaries for defining food poverty.
Methods
The research focuses on the concepts of the subsistence minimum and the social minimum. To estimate equivalence scales, one-parameter power scales were applied. The analysis is based on anonymised data from the 2023 Household Budget Survey conducted by Statistics Poland.
Results
The findings indicate that the equivalence scale used by Statistics Poland assumes a stronger scale effect than that derived from the subsistence minimum, which leads to differences in the estimated extent of extreme poverty. Indicators of food poverty were also estimated.
Conclusions
The results are of significant importance for improving poverty measurement methods and for informing social policy based on more precise poverty methods.
Keywords
extreme poverty, deprivation, food poverty, equivalence scales, poverty rate
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Speaker bio:
Krzysztof Echaust - jest profesorem Uniwersytetu Ekonomicznego w Poznaniu, gdzie pracuje w Instytucie Informatyki i Ekonomii Ilościowej. Kieruje Katedrą Badań Operacyjnych i Ekonomii Matematycznej. Pełni funkcję redaktora naczelnego czasopisma Przegląd Statystyczny - Statistical Review. Jego zainteresowania naukowe koncentrują się na finansach ilościowych, ekonometrii oraz matematyce finansowej. Autor dwóch monografii, kilku podręczników akademickich oraz kilkudziesięciu artykułów.
Abstract:
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Objective
Safe-haven and hedging instruments are market assets that allow investors to protect their portfolios against losses. A key limitation of most existing research in this topic is the assumption that risk minimization should be the sole criterion in the evaluation of decisions relative to safe-haven and hedging allocation. This perspective fails to capture the real motivations of investors who perceive investments as a trade-off between risk and profit. In contrast to those studies, we propose to verify the hedge or safe-haven property in the prospect theory framework.
Methods
Four of the most often explored assets, i.e., Bitcoin, Ether, Tether and gold, are tested as hedges or safe havens against the G7 and BRICS stock market risk using the cumulative prospect theory framework. We estimate an optimal weight in a hedged portfolio of each candidate for a hedge or safe haven, as well as the effectiveness of the hedge or safe-haven strategy. We introduce the hedging effectiveness measure and show the impact of risk aversion and reference point selection on optimal hedging decisions.
Results
We found that Tether and gold can be useful assets in hedging or safe-haven roles. Bitcoin and Ether cannot increase weighted utility when included in a stock market portfolio. We also compare the results with the minimum variance approach, which is a benchmark for this research. We found that both methods similarly indicate the usefulness of individual assets in a hedge or safe-haven role.
Conclusions
Adopting a behavioral finance approach allows for a deeper understanding of the real motivations behind investors’ decisions regarding the selection of hedging and safe-haven instruments among cryptocurrencies and gold.
Keywords
cryptocurrencies, gold, hedge, safe haven, prospect theory
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Speaker bio:
Iwona Foryś - profesor Uniwersytetu Szczecińskiego w Katedrze Ekonometrii i Statystyki, Instytucie Ekonomii i Finansów. Ekspert w Ośrodku Statystyki Rynku Nieruchomości Urzędu Statystycznego w Szczecinie. Praktyk na rynku nieruchomości, rzeczoznawca majątkowy, doradca i zarządca nieruchomości. Autor licznych publikacji naukowych, współautor projektów wdrożeniowych i grantów badawczych oraz analiz i opinii dla praktyki. Promotor rozpraw doktorskich w obszarze rynku nieruchomości.
Abstract:
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Objective
The aim is to present the possibilities of calculating price indices and rents for commercial real estate (retail, office, warehouse) in Poland.
Methods
The methodology usually takes into account the various types of indices calculated, mainly hedonic: time dummy, rolling time dummy, repricing, average characteristics, imputation, stratification method.
Results
The choice of the method for estimating the index depends on the amount of statistical information available in the database. More extensive databases, which include information such as property characteristics, allow for the calculation of hedonic indices, for example, using the rolling time dummy method.
Conclusions
Improving the quality of rental and commercial property price indices requires obtaining additional sources of data on commercial properties (other than the Property Price Register).
Keywords
price indices, rent indices, commercial real estate, hedonic indices
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Speaker bio:
Konrad Furmańczyk - jest profesorem uczelni na SGGW, pracującym w Katedrze Zastosowań Matematyki w Instytucie Informatyki Technicznej SGGW. Jest też koordynatorem zespołu biostatystycznego w Warszawskim Uniwersytecie Medycznym. Doktorat uzyskał z 2004 roku z nauk matematycznych, w 2017 otrzymał habilitację z nauk matematycznych. Zainteresowania naukowe obejmują statystykę matematyczną, biostatystykę, uczenie maszynowe i statystyczną analizę danych. Jest autorem ponad 80 publikacji naukowych, głównie z listy JCR ze statystyki matematycznej, biostatystyki, zastosowań statystyki w medycynie i innych naukach.
Abstract:
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Objective
The paper will present a graphical model describing the co-occurrence of allergic diseases.
Methods
We present this model in two versions: a generative model that reflects causal relationships and an approximation of the generative model using an ill-specified model that is computationally more efficient and easy to interpret. In both versions of our model, we consider typical symptoms of allergic diseases and additional covariates.
Results
The proposed model was evaluated using data from an epidemiological study on the occurrence of allergic diseases in Poland (www.ecap.pl). The bootstrap and jackknife techniques were used to assess the stability of the proposed model.
Conclusions
Our results show that the ill-specified model is a good approximation of the generative model and helps to predict the prevalence of allergic diseases.
Keywords
Bayesian network, logistic regression
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Speaker bio:
Agnieszka Gajda - geograf. Jest ekspertką ds. systemów informacji przestrzennej (GIS) w Obserwatorium Polityki Miejskiej i Regionalnej Instytutu Rozwoju Miast i Regionów (IRMiR). Specjalizuje się w zastosowaniach GIS do analiz miejskich i regionalnych, zwłaszcza w zakresie dostępności przestrzennej oraz procesów suburbanizacji. Jej działalność badawcza obejmuje również zagadnienia związane z transportem publicznym oraz politykami przestrzennymi. Współautorka publikacji z serii Raporty o stanie polskich miast.
Abstract:
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Objective
For many years, the public debate in Poland has highlighted the issues of urban sprawl and spatial chaos. While various monitoring datasets exist, there is a lack of nationwide, high-resolution spatial statistics. Available land use data often fail to capture the functional aspects of urban areas. The aim of this study is to identify and analyze the functional land use structure of Polish cities using a consistent methodology based on official spatial data, as well as to examine changes between 2017 and 2024.
Methods
The research method is based on the concept of the urban transect. Functional land use analysis was conducted using data from the Land and Building Register (EGiB), with 500 m2 hexagons as the basic unit of analysis. Based on land use structure, the hexagons were classified according to a defined functional typology. To reflect the specific characteristics of Polish cities, two additional categories were introduced: residential development on agricultural land and high-density multifamily housing areas.
Results
The conducted analyses allowed for the identification of the functional and spatial structure of cities, enabling an objective characterization of urban land use and an assessment of its temporal changes. Based on the results, it is possible to broadly identify spatial reserves within cities for potential future development and to indicate the likely directions of urban expansion. The findings also revealed the intensity of uncontrolled and chaotic suburbanization processes.
Conclusions
Due to its high level of automation, ongoing data updates, and relatively easy access, the proposed research method offers a viable alternative to traditional studies of the functional and spatial structure of cities. The resulting data – accurate yet standardized and generalized – effectively reflect changes occurring in urban space, making them a valuable source for analyzing the evolution of spatial structure over any selected time period.
Keywords
urban space, LULC, EGiB, GIS
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Speaker bio:
Eugeniusz Gatnar - profesor nauk ekonomicznych. Obecnie kieruje Katedrą Analiz Gospodarczych i Finansowych na Wydziale Finansów na Uniwersytecie Ekonomicznym w Katowicach. Jest autorem ok. 170 prac naukowych, w tym 5 monografii.
Od czterech kadencji jest z wyboru członkiem Komitetu Statystyki i Ekonometrii PAN. W latach 2007-2015 był członkiem Rady Statystyki. W latach 2020-2024 był przewodniczącym Naukowej Rady Statystycznej. Od roku 2023 jest członkiem Komisji Metodologicznej GUS.
W latach 2007-2010 był doradcą Prezesa Narodowego Banku Polskiego, następnie w latach 2010-2015 był członkiem Zarządu NBP, i członkiem Rady Polityki Pieniężnej w kadencji 2016-2022.
Abstract:
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Objective
The aim of the study is to identify the strength of the statistical base's impact on the value of the current CPI inflation index
Methods
The study is based on indicator analysis, time series analysis, R package, Statistics Poland database, NBP dataset.
Results
The reasearch results indicate a decomposition of the inflation rate to assess the statistical base effect.
Conclusions
The statistical base affects the value of inflation rates and should be taken into account when interpreting inflation rates for monetary policy purposes.
Keywords
inflation, CPI, statistical base, monetary policy
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Speaker bio:
Professor Elżbieta Gołata is a demographer and statistician. Since 2020, she has chaired the Committee on Demographic Studies of the Polish Academy of Sciences, of which she has been a member since 2003. In 2024, she was appointed Deputy Chairwoman of the Government Population Council, having participated in its work since 2020.
From 2016 to 2024, she served as Vice-Rector for Research and International Relations at the Poznań University of Economics and Business. She is also a member of the Committee on Statistics and Econometrics of the Polish Academy of Sciences (2015-2018, 2024-2027). Since 2014, she has served on both the Scientific Statistical Council at the President of Statistics Poland (GUS) and the Main Council of the Polish Statistical Association.
Her scientific interests focus on demographic change, spatial aspects of social statistics, and the assessment of statistical data quality. She pays particular attention to population size and structure estimates, censuses, population ageing, and labour market analysis. She is the author of numerous scientific publications, articles, and books.
Abstract:
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Objective
The main objective of the paper is to present the economic activity of population 50 and over in the context of the decision to retire in Poland compared to other European Union countries. The study presents the differences in the age at which retirement begins and the share of people receiving benefits. The analysis includes the main reason for ceasing work upon retirement, as well as the main reason for continuing to work upon retirement or returning to the labour market.
Methods
In the study, multidimensional statistical and comparative analysis methods were used. Using demographic analysis methods, changes in life expectancy and age structures were also presented, as well as the consequences for potential labour force resources and the dependancy ratio. The study used Eurostat data, in particular from the 'Pension and labour market participation' module conducted in 2023 as part of the European Labour Force Survey. In addition, data from Statistics Poland and OECD were used.
Results
The results of the study indicate that despite the increase in economic activity observed in recent years, the retirement age in Poland is among the lowest in Europe. The participation of people receiving benefits in the labour market has increased – 11.6% of people aged 50-74 who receive a pension continue to work. On the other hand, over 75% of retirees aged 60-64 remain outside the labour market. This applies to 94% of women and 33% of men. After retiring at the age of 65-69, the share of men outside the labour market increases to over 97%.
Conclusions
The demographic conditions of shrinking labour resources and changes in the age structure indicate the need to develop incentives for longer economic activity.
Keywords
pension, economic activity of population 50+
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Speaker bio:
Tomasz Górecki - jest profesorem w Zakładzie Statystyki Matematycznej i Analizy Danych Wydziału Matematyki i Informatyki, Uniwersytetu im. Adama Mickiewicza w Poznaniu. Jego główne zainteresowania badawcze dotyczą metod sztucznej inteligencji, uczenia maszynowego i analizy szeregów czasowych oraz ich zastosowań. Posiada wieloletnie doświadczenie we współpracy z przemysłem, m.in. Allegro, Lidl i Samsung, gdzie pracował m.in. nad systemami prognozującymi popyt i zapasy, nad inteligentnymi systemami głosowymi oraz systemami rekomendacyjnymi. Ponadto od lat współpracuje ze specjalistami w innych dziedzinach nauki m.in. ekonomii, chemii, geografii czy transportu łącząc praktykę z teorią. Jest autorem przeszło 100 prac naukowych i 3 opracowań książkowych.
Abstract:
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Objective
The study aims to develop and compare advanced regression models, including novel variants of random forests, for functional data. We examine whether methods combining functional data analysis with random forests better capture complex relationships in the data than traditional statistical approaches.
Methods
Classical linear regression, functional regression, principal component analysis, and random forests were applied. Two new models were introduced: the Functional Random Forest (FRF), which incorporates functional analysis at the sample level, and the Full Functional Random Forest (FFRF), which performs functional analysis at the tree split level.
Results
The new functional models, FRF and FFRF, more effectively capture complex relationships in functional data than standard random forests and linear regression. Functional models also achieve good performance, particularly in specific applications.
Conclusions
Functional random forests (FRF and FFRF) offer an innovative approach to modeling functional data by combining the strength of random forests with functional data analysis. The study introduces new methods to statistics that can enhance data analysis in natural and technical sciences, inspiring further research on hybrid models.
Keywords
random forest, functional data analysis, principal components analysis
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Speaker bio:
Małgorzata Górka, MA - Head of the Kujawsko-Pomorskie Regional Research Centre at the Statistical Office in Bydgoszcz. With 18 years of experience in public statistics, she specialises in statistical communication, education, and publishing. At the conference, she presented a talk titled Challenges and Opportunities of Effective Communication of Labour Market Statistics
Abstract:
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Objective
In an era of information overload, statistical data must compete for attention with emotions, narratives and... memes. So how do we effectively talk about the labour market in a language that not only conveys the complexity of the phenomena, but also reaches the audience?
Methods
This presentation is a journey through the world of numbers, charts and statistical interpretation – in search of ways to make statistics not ‘dry’ but attention-grabbing and understandable. I will talk about the challenges of data communication: from misinterpretations to oversimplifications. But also about opportunities – new tools, visualisations and data storytelling techniques.
Results
Effective communication of statistics is not just a matter of form – it is the foundation for better decisions, policies and actions in the labour market.
Conclusions
For the presentation of activities, I will use materials and activities prepared by the Statistical Office in Bydgoszcz to promote the results of the Survey on Employment in the National Economy and the Survey on the Distribution of Wages and Salaries in the National Economy, but also various forms of media communication of the data made available.
Keywords
labour market, statistical data, data communication, data visualisation, data interpretation, data user, communication challenges, data presentation tools
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Speaker bio:
Krzysztof Jajuga - Profesor nauk ekonomicznych, wykładowca Uniwersytetu Ekonomicznego we Wrocławiu, Politechniki Warszawskiej, Uniwersytetu Ekonomicznego w Krakowie, oraz uczelni za granicą: (m.in. USA, Chiny). Doktor honoris causa Uniwersytetu Ekonomicznego w Krakowie, Akademii WSB w Dąbrowie Górniczej. Dorobek naukowy z finansów, zarządzania ryzykiem, nieruchomości, nowych technologii oraz statystyki i ekonometrii. Prezydent światowego towarzystwa naukowego z obszaru analizy danych - International Federation of Classification Societies. Przewodniczący Komitetu Nauk o Finansach Polskiej Akademii Nauk. Prezes CFA Society Poland. Członek Rady Doradczej Association of Business Service Leaders. Współpracuje z wieloma podmiotami. Autor ekspertyz i opinii, również na potrzeby procesów sądowych.
Abstract:
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Objective
The aim of the study is to provide a description of the actions that statisticians should take in order to, on the one hand, more fully utilize the potential of statistical inference in the era of big data and AI and, on the other hand, to make statistics users more aware of the inherent elements of uncertainty present in statistical inference.
Methods
The method used is a critical analysis of the literature and research studies that contain elements of statistical inference. A creative reflection on the practice of statistical research in the context of the groundbreaking work of Ronald Fisher Statistical Methods for Research Workers” published in 1925 was also mentioned.
Results
Discussions on the dilemmas related to the category of statistical significance held in the scientific community worldwide is a consequence of the incomplete consideration of model assumptions in the practice of statistical inference and of assigning a decisive significance to a single sample study in the context of the universal goals of scientific research.
Conclusions
With respect to the practice of testing statistical hypotheses, we postulate the use of the the Bayesian approach as complementary to the classical approach inextricably linked to Ronald Fisher.
Keywords
statistical inference, uncertainty, model assumptions, big data, scientific research
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Speaker bio:
dr Jarosław Janecki - adiunkt w Szkole Głównej Handlowej w Warszawie, Katedrze Ekonomii Stosowanej. W latach 1994-2006 pracował w Ministerstwie Finansów, następnie w latach 2006-2019 w banku Societe Generale oraz w latach 2020-2025 w Głównym Urzędzie Statystycznym w Warszawie. W swoich badaniach koncentruje się na zagadnieniach dotyczących bankowości centralnej, rynków finansowych oraz niepewności w gospodarce.
Abstract:
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Objective
The aim of the study is to assess the level of uncertainty of different groups of respondents in relation to the answers given to the questions included in the survey.
Methods
The study used the Dempster-Shafer method, in which unlike Bayesian theory, instead of specific probabilities, the degree of conviction is assigned to the answers given. This allows for the assessment of the respondents' uncertainty in relation to a given question. The source of the data are the results of survey research conducted by DG ECFIN.
Results
The results of the conducted analysis allow for the identification of discrepancies in the degree of uncertainty of the answers given in periods of generally increased uncertainty.
Conclusions
The applied method allows for a better understanding of the cognitive structure among the surveyed entities. It can supplement the description of the results of the survey research conducted.
Keywords
uncertainty, survey research, probability
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Speaker bio:
Paweł Janukowicz - doktor nauk społecznych w dyscyplinie ekonomia i finanse, członek Towarzystwa Ekonomistów Polskich (TEP), pracownik samorządowy. Posiada wieloletnie doświadczenie zawodowe w administracji samorządowej w obszarze polityki regionalnej, rynku pracy i rozwoju regionalnego. Specjalizuje się w analizie procesów społeczno-gospodarczych, regionalnych aspektach rozwoju i konkurencyjności, a także oddziaływania funduszy unijnych na rozwój społeczno-gospodarczy polskich regionów.
Abstract:
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Objective
The aim of the analysis is to assess the impact of European Union funds under the 2014–2020 cohesion policy on the level of innovativeness in Polish voivodships. The main research question is: does the intensity of EU support in the area of R&D translate into an increase in regional innovation capacity, or is the effectiveness of this policy primarily dependent on local absorption conditions?
Methods
The analysis is based on data from the Ministry of Funds and Regional Policy concerning the value and structure of funding agreements related to R&D activities, supplemented by innovation indicators from the European Commission’s Regional Innovation Scoreboard and statistical data from Statistics Poland (GUS) for the 16 Polish voivodships. The study employs correlation analysis methods to identify relationships between the level of support and innovation outcomes at the regional level. The results are also presented in the form of graphical visualizations.
Results
Between 2014 and 2020, the largest share of EU funding was allocated to enterprises, which had a particularly strong impact on regions with a higher capacity to generate innovation, such as Mazowieckie, Małopolskie, and Pomorskie. In the eastern regions, despite the use of EU funds, challenges remain in fully realizing their innovation potential, in part due to limited demand for innovation and lower levels of development. The effectiveness of innovation funds therefore depends not only on their scale but also on the ability of regional markets to absorb and implement project outcomes.
Conclusions
Impact of EU funds varies across regions. A key limitation remains the low capacity of many regions to implement innovations. The effectiveness of the funds does not depend on their amount, but on market conditions that determine the real possibility of translating projects into economic outcomes. The analysis contributes to the literature on regional development policy by highlighting the need to design policies based not only on the allocation of funds, but also on the actual capacity to use them effectively within the economy.
Keywords
regional innovativeness, EU funds, cohesion policy, regional development
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Speaker bio:
Alina Jędrzejczak - jest kierownikiem Katedry Metod Statystycznych na Wydziale Ekonomiczno-Socjologicznym Uniwersytetu Łódzkiego. Jednocześnie pełni funkcję eksperta w Ośrodku Statystyki Matematycznej Urzędu Statystycznego w Łodzi. Jest również kierownikiem programu European Master in Officail Statistics (EMOS) na Uniwersytecie Łódzkim. Jej główne obszary zainteresowań to rozkłady dochodów, pomiar i dekompozycja nierówności dochodowych oraz metody szacowania parametrów dla małych obszarów. Obecnie jest członkiem rad redakcyjnych: Statistica & Applicazioni, Statistics in Transition i Acta Universitatis Lodziensis Folia Oeconomica. W 2025 roku otrzymała tytuł profesora nauk społecznych w dyscyplinie ekonomia i finanse.
Abstract:
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Objective
The aim of the paper is to present and analyze the development of scientific research and teaching work conducted by statisticians and demographers from Łódź.
Methods
The presentation of the achievements of statisticians and demographers from Łódź is based on an in-depth analysis of the literature on the subject and the study of documents and source materials.
Results
Based on the analyses, it can be stated that the statistical research conducted in Łódz in the interwar period had a significant impact on the development of Polish statistics. In particular, these were works conducted under the supervision of the head of the Department of Statistics of the Łódź City Hall, Edward Rosset, and professor Edward Szturm de Sztrem, which addressed important socio-economic problems of Poland and Łódź, including: 'Alcoholism in the light of statistical researc': 'The political face of the population of the city of Łódź in the light of election research'.
Conclusions
The interwar achievements of Łódź statisticians continued after Poland regained independence within the framework of the University of Łódź, the Łódź branch of the Warsaw School of Economics and the Higher School of Economics. The achievements of the Łódź statistical community, which took place over the last 100 years, contributed to the creation of the Łódź school of statistics and demography.
Keywords
statistical research, development of statistical thought
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Speaker bio:
Tomasz Józefowski - doktor nauk społecznych w dyscyplinie ekonomia i finanse; pełni funkcję kierownika Ośrodka Statystyki Małych Obszarów w Urzędzie Statystycznym w Poznaniu, a także pracuje jako asystent w Katedrze Statystyki w Instytucie Informatyki i Ekonomii Ilościowej na Uniwersytecie Ekonomicznym w Poznaniu. Jego główne zainteresowania zawodowe i naukowe koncentrują się na estymacji dla małych obszarów oraz metodach kontroli ujawniania danych. Aktywnie uczestniczy w pracach zespołu do spraw metod kontroli ujawniania danych statystycznych w Głównym Urzędzie Statystycznym. Jest także członkiem grupy eksperckiej do spraw metodologii w zakresie metod kontroli ujawniania danych w Eurostacie.
Abstract:
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Objective
In this presentation, we will recall the basic assumptions of the Statistical Disclosure Control algorithm prepared for the needs of the Geostatistical Portal of Statistics Poland, one of the basic and most comprehensive channels for sharing and analyzing Polish official statistics data. We will present the assumptions and the scheme of the optimal data protection process and indicate the basic problems related to the practical implementation and the possibilities of solving them.
Methods
In the research, we use an algorithm written in SAS and R using the sdcMicro package of the R environment, its application and parameterization.
Results
We will discuss the effects of applying the algorithm and correcting the obtained disturbances in order to maintain the definitional consistency of the provided data and the summation of appropriate values.
Conclusions
We will point out the usefulness of the algorithm and outline the most important challenges facing official statistics in this area – both methodological (differential privacy, generating synthetic data) and organizational (e.g. access to data for scientific purposes).
Keywords
Statistical Disclosure Control, Geostatistical Portal, perturbative methods, synthetic data
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Speaker bio:
Małgorzata Just - pracuje na stanowisku adiunkta w Katedrze Finansów i Rachunkowości na Wydziale Ekonomicznym Uniwersytetu Przyrodniczego w Poznaniu. Jest autorką kilkudziesięciu artykułów naukowych z ekonomii i finansów. Jej zainteresowania naukowe obejmują ekonometrię finansową, inwestycje i zarządzanie ryzykiem, w szczególności modelowanie zmienności i zależność na rynkach finansowych i towarowych w warunkach zdarzeń ekstremalnych.
Abstract:
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Objective
Safe-haven and hedging instruments are market assets that allow investors to protect their portfolios against losses. A key limitation of most existing research in this topic is the assumption that risk minimization should be the sole criterion in the evaluation of decisions relative to safe-haven and hedging allocation. This perspective fails to capture the real motivations of investors who perceive investments as a trade-off between risk and profit. In contrast to those studies, we propose to verify the hedge or safe-haven property in the prospect theory framework.
Methods
Four of the most often explored assets, i.e., Bitcoin, Ether, Tether and gold, are tested as hedges or safe havens against the G7 and BRICS stock market risk using the cumulative prospect theory framework. We estimate an optimal weight in a hedged portfolio of each candidate for a hedge or safe haven, as well as the effectiveness of the hedge or safe-haven strategy. We introduce the hedging effectiveness measure and show the impact of risk aversion and reference point selection on optimal hedging decisions.
Results
We found that Tether and gold can be useful assets in hedging or safe-haven roles. Bitcoin and Ether cannot increase weighted utility when included in a stock market portfolio. We also compare the results with the minimum variance approach, which is a benchmark for this research. We found that both methods similarly indicate the usefulness of individual assets in a hedge or safe-haven role.
Conclusions
Adopting a behavioral finance approach allows for a deeper understanding of the real motivations behind investors’ decisions regarding the selection of hedging and safe-haven instruments among cryptocurrencies and gold.
Keywords
cryptocurrencies, gold, hedge, safe haven, prospect theory
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Speaker bio:
Sławomir Kalinowski - doktor habilitowany nauk ekonomicznych, profesor w Instytucie Rozwoju Wsi i Rolnictwa Polskiej Akademii Nauk. Kierownik Zakładu Ekonomii Wsi. Sekretarz Rady Naukowej IRWiR PAN. Członek Komitetu Nauk o Pracy i Polityce Społecznej PAN. Wiceprzewodniczący Sekcji Młodych KNoPiPS PAN. Członek zespołów redakcyjnych kwartalników Wieś i Rolnictwo oraz Zagadnienia Ekonomiki Rolnej. Zainteresowania badawcze koncentrują się wokół problematyki ubóstwa i poziomu życia na wsi, ekonomii dobrobytu, niepewności dochodów, koncepcji smart villages, a także prekaryzacji ludności wiejskiej. Autor ponad 140 publikacji naukowych, w tym monografii "Ubóstwo ubogich. Obszary deprywacji potrzeb beneficjentów pomocy społecznej" (2024, wsp. Aleksandra Łuczak, Oskar Szczygieł), "Koncepcja smart villages. Przykłady z Polski" (2021, wsp. Łukasz Komorowski i Anna Rosa), "Moja sytuacja w okresie koronawirusa" (2021), "Poziom życia ludności wiejskiej o niepewnych dochodach" (2015), Ubóstwo ludności wiejskiej województwa wielkopolskiego (2007). Wiceprezes zarządu Fundacji Badań Wiejsko-Miejskich RURall, członek Rady Fundacji ROLL-na. W latach 2009-2015 sekretarz Międzyśrodowiskowej Grupy Badawczej "Margines Społeczny Poznania". Ekspert Polskiego Towarzystwa Polityki Społecznej oraz członek Poznańskiego Towarzystwa Przyjaciół Nauk. Prywatnie folklorysta i choreograf tańca ludowego. Strona domowa www.skalin.pl.
Abstract:
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Objective
The analysis of differences between poverty measures is mainly based on income levels or indicators of material deprivation. Their comparison has consequences, such as differences in assessing the scale of the problem. The research has two goals: methodological and practical. The methodological goal is to present a methodological concept for studying poverty as a barometer that will inform in advance about changes in the situation of the population. The practical goal is to apply this methodology to study poverty in territorial units in Poland.
Methods
Our research focuses on a multidimensional approach based on multi-criteria decision-making methods that consider various aspects of poverty, such as health, education, housing conditions, and access to services. We use data from the Local Data Bank of Statistics Poland, which allows us to obtain accurate and up-to-date information. We aim for the research to be repeatable, enabling the monitoring of changes over time and the adaptation of social policies to dynamically changing conditions. Additionally, we identify the time of exiting or deeper falling into poverty of territorial units.
Results
This analysis represents the essence and extension of research on the diagnosis of poverty and social exclusion in the Mazowieckie Voivodeship from 2012 to 2023. The findings emphasize the need for an integrated approach to identifying poverty, one that considers various indicators influencing poverty.
Conclusions
An integrated multidimensional approach to identifying poverty, which considers various indicators, is crucial for effectively monitoring and adapting social intervention strategies. The research emphasizes the need to consider different aspects of poverty in social policies, which allows for a more comprehensive understanding of the problem and better adaptation of interventions to the actual needs of impoverished individuals.
Keywords
poverty, objective measures, social policy, multidimensional approaches
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Speaker bio:
Dorota Kałuża-Kopias - adiunkt w Katedrze Demografii na Wydziale Ekonomiczno-Socjologicznym Uniwersytetu Łódzkiego. Specjalizuje się w badaniach nad migracjami ludności w kontekście rynku pracy oraz starzenia się ludności. Członkini Rady Programowej Centrum Studiów Migracyjnych UŁ oraz współpracowniczka Komitetu Badań nad Migracjami PAN, w zakresie migracji wewnętrznych i badań regionalnych. Członkini Polskiego Towarzystwa Statystycznego.
Abstract:
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Objective
Identification of further residence plans of Ukrainian citizens residing in the Łódź and Silesian voivodeships, i.e. in voivodeships with a diversified economic context.
Methods
A logistic regression model was used to analyze the further residence plans of Ukrainians in the Łódź and Silesian regions. The explanatory variables included, among others, those illustrating the situation of immigrants on the labor market, knowledge of the Polish language, their satisfaction with selected areas of life (financial, housing situation) and the type of support received. The main source of data is a survey conducted among Ukrainians living in the Łódź and Silesian voivodeships in the fall of 2024. The tool used was an online survey - in total, the survey covered 680 Ukrainians.
Results
The results obtained indicate significant differentiation in terms of further residence plans, both among migrants who arrived before and after the war, as well as between the analysed voivodeships. The results of the analysis indicate, among other things, that knowledge of Polish increases the probability of declaring a desire to stay in Poland, especially in the case of war refugees. People who declared satisfaction with their financial situation expressed over 1.6 times greater willingness to stay in the Łódź region, and 1.4 times greater in the Silesia region.
Conclusions
The conducted study makes it possible to estimate the number of Ukrainians who are willing to stay permanently in selected regions and the factors that increase the chance of staying in the region they currently live in.
Keywords
Ukrainians, labor market, Lodz Voivodeship, Silesian Voivodeship
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Speaker bio:
Dr inż. Oleksij Kelebaj - asystent w Katedrze Rynków Finansowych Uniwersytetu Ekonomicznego w Krakowie. Jego działalność naukowa koncentruje się na zagadnieniach z zakresu ekonomii matematycznej oraz modelowaniu matematycznym procesów wzrostu gospodarczego. Prowadzi badania nad analizą zróżnicowania rozwoju gospodarczego i społecznego na poziomie regionalnym i lokalnym. Specjalizuje się w ilościowych metodach badawczych wykorzystywanych w analizie danych makroekonomicznych.
Abstract:
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Objective
The aim of the paper is a statistical analysis of the impact of the lagged unemployment rate and GDP growth rates on the unemployment rate in regions of the Czech Republic and Slovakia. In their study, the authors attempt to answer the following questions: Do changes in regional GDP significantly influence changes in unemployment rates at the regional level in the Czech Republic and Slovakia? Were the effects of the 2008 financial crisis and the COVID-19 pandemic noticeable in both countries? Did the previous unemployment rate in both countries have a significant impact on its subsequent level?
Methods
The study is based on descriptive statistics, unemployment rate growth equation, the Ordinary Least Squares (OLS) method, Generalized Method of Moments (GMM) and Fixed effects.
Results
Prague recorded the highest GDP level during the analyzed period. The capital also exhibited the lowest average unemployment rate. Bratislava stood out significantly from the other regions in terms of GDP. The lowest average unemployment rates were also recorded in Bratislava. In both the unemployment growth equation estimated using OLS and GMM (with some exceptions), for Czech and Slovak regions, the previous unemployment level had a statistically significant impact on its growth. The GDP growth rate in Slovak and Czech regions generally reduced the increases in the unemployment rate.
Conclusions
The results of the conducted analyses provide a solid foundation for formulating practical recommendations in the field of regional and economic policy. The conclusions drawn from the comparison of Czech and Slovak regions can serve as a basis for developing more precise tools to support regional labor markets, especially in areas where unemployment is of a structural nature. The methods used in the article can also be applied beyond the borders of the Czech Republic and Slovakia, as the described statistical and econometric techniques maintain their universality in a comparative context.
Keywords
descriptive statistics, econometrics, mathematical economics, regional development, unemployment
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Speaker bio:
Błażej Kochański jest adiunktem w Katedrze Statystyki i Ekonometrii na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej i ekspertem ds. ryzyka bankowego. Pracował dla banków w Polsce i Europie jako specjalista ds. ryzyka, kierownik ds. planowania i analiz, członek zarządu ds. ryzyka, członek rady nadzorczej i konsultant ds. zarządzania. Zbudował liczne modele predykcyjne wspomagające zarządzanie ryzykiem, z sukcesem zarządzał portfelami kredytowymi, opracował skuteczne strategie zarządzania ryzykiem klientów detalicznych. Po dołączeniu do świata akademickiego jest gotowy dzielić się swoim doświadczeniem, wiedzą i intuicjami poprzez współpracę ekspercką, dydaktykę i publikacje naukowe.
Abstract:
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Objective
Statistics is often perceived by students as a difficult, abstract and rather unpleasant subject. The aim of the activities I will discuss in this presentation was to increase student engagement and improve the understanding of key statistical concepts through the use of active learning methods.
Methods
As part of a statistics course for students of economic analytics, a range of activities inspired by English-language educational literature was implemented (including Gelman & Nolan, 2017: Schaeffer et al., 1996). Everyday objects (a tape measure, kitchen scale, beach ball, candies, and dice), simulation games, and playful elements (such as creating memes) were used to illustrate both basic and advanced tools of probabilistic modeling and methods of statistical inference.
Results
The introduction of these activities increased student interest in the subject and made it easier to grasp difficult topics. Although the final exam remained challenging, 90% of students passed it on the first attempt. The course was also rated more highly than in previous editions.
Conclusions
Using active learning methods based on simple props and interactive forms of work can significantly improve the effectiveness of teaching statistics. This approach allows students to gain a deeper understanding of the material and enables the instructor to observe genuine engagement and those “aha!” moments during class. Effective and well-organized collaboration among academic instructors, including the sharing of proven teaching strategies, contributes to improved teaching quality, increased student engagement, and the broader popularization of statistics.
Keywords
statistics education, active learning, teaching innovations
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Speaker bio:
Dr Bernard Kokczyński - ukończył studia magisterskie z zakresu Finansów i Rachunkowości (2019) na Uniwersytecie Łódzkim. Obronił na Uniwersytecie Łódzkim pracę doktorską w 2025 roku.
Specjalizuje się w analizie danych, pomiarze ryzyka kredytowego oraz konstrukcji modeli predykcji bankructwa przedsiębiorstw. W 2018 r. został laureatem nagrody Prezesa Bankowego Funduszu Gwarancyjnego za najlepszą pracę licencjacką pt. "Analiza cech kredytobiorców nieterminowo spłacających zobowiązania", napisaną pod kierunkiem prof. dr hab. Doroty Witkowskiej.
Doświadczenie zawodowe zdobywał jako menedżer placówki bankowej (Alior Bank), prowadząc zespół sprzedażowy. Prowadził działalność gospodarczą z zakresu pośrednictwa finansowego i budował zespół doradców ubezpieczeniowych (PZU Życie S.A.). Obecnie odpowiada za pomiar ryzyka rynkowego i kredytowego w Volia Energy Contracting Poland, a także prowadzi zajęcia dydaktyczne w Akademii Piotrkowskiej w Piotrkowie Trybunalskim z zakresu bankowości, analizy finansowej, finansów przedsiębiorstw oraz metod ilościowych.
Abstract:
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Objective
The purpose of the empirical study presented in the paper is to compare linear discriminant models constructed on the basis of diagnostic variables selected using different techniques for their selection, and to indicate which bankruptcy prediction model proved to be the best from the point of view of the multivariate evaluation of model accuracy.
Methods
The study applied a quantitative approach using discriminant analysis to identify companies at risk of bankruptcy. The effectiveness of the models was evaluated using Wilks` lambda statistic, AUC values and classification accuracy of the models. A number of methods were used to select discriminating variables: arbitrary selection of variables based on the literature and using GPT Chat (version 3.5), one-way analysis of variance (ANOVA) and stepwise forward selection, Hellwig`s method of selecting diagnostic variables, t-statistics, backward stepwise method. The source of the data was the EMIS
Results
Eight discriminant models based on different methods of selecting diagnostic variables were evaluated. The highest classification efficiency (both in the learning and test sample) was achieved by model D, built using a two-step method (significance test of mean differences + progressive selection). Models F (based on isolated variables selected by the Hellwig method) and H (backward method) also had high classification efficiency. In contrast, the worst results were obtained by model A, based on arbitrary selection of variables. AUC indices for most models (except for model A) exceeded the val
Conclusions
The results of the study indicate that appropriate independent variable selection techniques play an important role in the process of building discriminant models. The study also makes an important methodological contribution, challenging the common belief that Wilks` lambda statistic is highly useful in assessing the quality of classification models. The results show that the analysis of classification performance should be the main point of reference when evaluating discriminatory models.
Keywords
diagnostic variable selection, linear discriminant function, bankruptcy prediction, Euclidean distance
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Speaker bio:
Mgr Ewelina Konarska-Michalczyk - Urząd Statystyczny w Szczecinie, Zachodniopomorski Ośrodek Badań Regionalnych, Koordynator ds. CSR, dostępności i edukacji.
Abstract:
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Objective
The presentation aims to show how modern AI-based technologies can support organizations in internal and external communications, with a particular focus on activities in the areas of accessibility, HR and employee psychological support. The paper will discuss the existing technological solutions, their practical applications, as well as potential ethical and organizational challenges associated with their implementation.
Methods
The presentation will present the practical application of AI in the areas identified in the research objective. Possible technologies, benefits and risks will be discussed, as well as stages and an implementation scenario. The aspect of ethics in AI implementation will be addressed. Examples of the use of appropriate prompts to facilitate the use of AI resources will be mentioned.
Results
In the era of digital transformation, institutions and business units face the challenge of adapting to the requirements and expectations of external as well as internal audiences. Also, statistical offices, in order to meet the requirements and remain competitive, should and even are obliged to keep up with the intensity of technological change, while keeping in mind the sensitivity of audiences, especially from groups with special needs.
Conclusions
Mimo wielu korzyści płynących z korzystania z dostępnych narzędzi AI, należy mieć jednocześnie na uwadze fakt, iż technologie te wiążą się z ryzykiem naruszenia prywatności, nieprzejrzystością algorytmów oraz ograniczonym zaufaniem użytkowników. Konieczne jest więc etyczne i odpowiedzialne podejście do ich projektowania i wdrażania.
Keywords
AI, employee mental health support, HR, accessibility
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Speaker bio:
Katarzyna Kopczewska - dr hab. nauk ekonomicznych, profesor Uniwersytetu Warszawskiego na Wydziale Nauk Ekonomicznych (WNE UW) w Katedrze Data Science. W latach 2012-2020 prodziekan WNE UW, w kadencji 2020-2024 Senator UW, stypendystka University of Glasgow. Od 2020 Członek Naukowej Rady Statystycznej przy Prezesie GUS, w 2023 nagrodzona przez Prezesa GUS Odznaką Honorową za Zasługi dla Statystyki Rzeczypospolitej Polskiej.
W pracy badawczej zajmuje się modelowaniem geo-przestrzennym i rozwijaniem metod ilościowych, w szczególności statystyki i ekonometrii przestrzennej oraz przestrzennego uczenia maszynowego. Działa na rzecz otwartego oprogramowania obliczeniowego R - jako dydaktyk i autorka książek wydanych w Polsce i zagranicą. Ekspert w zakresie danych gospodarczo-społecznych, kierownik w grantach NCN i Horyzont 2020. W środowisku międzynarodowym aktywnie działa w sieci naukowej regionalistów European Regional Science Association, stale publikuje w czołowych międzynarodowych czasopismach i wydawnictwach naukowych oraz pełni rolę redaktora.
Abstracts:
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Objective
This paper addresses the conceptual and practical challenges of applying artificial intelligence (AI) and spatial machine learning (SML) in regional science. The goal is to clarify how SML differs from more general applications of AI in the spatial context, and to demonstrate their value for solving real-world location-based problems. We argue that AI offers a novel analytical framework that complements traditional methods and leads to more accurate, data-driven policy and business recommendations.
Methods
Our approach combines spatial machine learning (SML) with an interactive AI-based application designed to support decision-making. We use data on business entities in Poland, enriched with detailed spatial characteristics of their environment. SML algorithms are employed to detect spatial patterns and predict optimal business locations. These results are then embedded into the AI app, which enables users, such as policymakers and entrepreneurs, to explore scenarios and receive recommendations tailored to specific regional contexts.
Results
Our results show that spatial machine learning (SML) offers strong predictive performance in identifying optimal business locations. However, AI extends beyond prediction, enabling the generation of strategic recommendations for both business and policy. This distinction is crucial: while SML identifies patterns in spatial data, AI provides a broader decision-making framework by integrating predictions with contextual reasoning and actionable outputs. This combination supports more informed regional planning and business choices.
Conclusions
This work contributes to the emerging literature on AI in regional science by offering clear definitions and practical examples that distinguish spatial ML from broader AI applications. The proposed model serves both researchers and practitioners by demonstrating how AI can support location-based decision-making. Our findings highlight the need for a better integration of spatial thinking into AI workflows, ultimately improving regional policy design and business strategies.
Keywords
Artificial Intelligence, spatial machine learning, regional science, business location, spatial data
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Objective
The aim of the presentation is to present an original QDC (Quick Density Clustering) algorithm, which is used to divide point data into groups according to spatial density. This is a new solution that complements the existing tools for spatial quantitative modelling, based on spatial machine learning methods.
Methods
The algorithm is based on a highly intuitive design that exploits the characteristics of varied spatial density. Points located close to each other can be easily extracted because the sum of distances to the k nearest neighbours is low, while the number of neighbours within a certain radius is high. Conversely, points from low-density areas have a high sum of distances to the k nearest neighbours, while the number of neighbours within a certain radius is low. These two features clearly characterise areas with low and high density.
Results
Dividing these two spatial variables (normalised) using the k-means algorithm into k groups allows geo-localised points to be divided into groups with similar spatial density in a simple and quick manner. The application of the QDC algorithm to data on human activity – the location of residents (data from the census) and the location of companies (data from REGON) – will be presented. Relative spatial densities will be compared based on data rasters and in relation to the road and settlement networks downloaded from Open Street Map.
Conclusions
The QDC algorithm is an interesting methodological innovation that has many applications in monitoring social mobility dynamics. It is a sampling-resistant solution that is also easily adaptable to streaming (the constantly growing) data.
Keywords
spatial density clustering, geolocated point data, spatial machine learning
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Objective
This study addresses the question of whether technological relationships are asymmetric, and how certain technologies act as drivers of innovation within regional clusters. The main objective is to develop a methodological framework that captures directional (asymmetric) relationships between technologies, with the aim of identifying those that function as catalysts in regional innovation systems.
Methods
The research uses an unsupervised machine learning approach combining two techniques: DBSCAN (density-based spatial clustering) to group patents into spatial clusters, association rule mining (a priori algorithm) to uncover asymmetric co-occurrence patterns between technology types over time. The dataset includes UK patent applications filed between 1980 and 2015, sourced from UKIPO and PATSTAT. Each patent is geocoded using inventor coordinates and classified by technology type (high-tech vs. low-tech), and grouped into 5-year time intervals.
Results
The study showed that: technologies are asymmetrically related, high-tech patents are influencing low-tech more, compared to the opposite, and H04Q (selecting), H04N (pictorial communication e.g. television), H04M (telephonic communication) and H04L (transmission of digital information, e.g. telegraphic communication) affect each other very frequently,forming a 'technological cluster'.
Conclusions
This study contributes to regional science and innovation studies by providing a novel methodological framework for detecting asymmetric technological relationships. It challenges the common assumption of symmetry in relatedness measures and offers practical tools for identifying catalyst technologies that may support regional diversification strategies. The method is generalizable and can be applied to any spatio-temporal dataset with classification variables, making it valuable for broader applications in policy analysis, technology forecasting and economic geography.
Keywords
asymmetric technological relatedness, patent clustering, regional innovation, catalyst technologies, spatio-temporal analysis
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Speaker bio:
Tomasz Kopczewski - prowadzi działalność dydaktyczną i badawczą w Katedrze Data Science Wydziału Nauk Ekonomicznych Uniwersytetu Warszawskiego. Specjalizuje się w mikroekonomii, ekonomii eksperymentalnej i metodach ilościowych. W swojej pracy skupia się na opracowywaniu i wdrażaniu nowych metod nauczania oraz przekazywania wiedzy ekonomicznej - działalność tę określa mianem "inżynierii wiedzy". Jest autorem metody dydaktycznej "Know Thyself", łączącej ekonomię eksperymentalną, narzędzia Data Science, symulacje Monte Carlo oraz elementy fizyki, filozofii i etyki. Integrując podejścia ortodoksyjne i heterodoksyjne, tworzy spójny program dydaktyczno-badawczy, inspirowany humanistyczną wizją ekonomii Vernona Smitha oraz koncepcją racjonalności ekologicznej. Obecnie jego prace badawcze koncentrują się na: (i) roli czasu i procesów nieergodycznych w teorii ekonomicznej, (ii) uwzględnianiu dylematów etycznych w modelach mikroekonomicznych głównego nurtu, (iii) analizie mechanizmów powstawania i rozprzestrzeniania się wiedzy zbiorowej oraz jej wpływu na decyzje ekonomiczne.
Abstract:
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Objective
The aim of this paper is to present the original educational method 'Know thyself', which employs statistics to develop students’ research competencies and self-awareness. The research question investigates economics students` awareness of the fake data problem and examines how effectively they detect and interpret manipulated data within practical and ethical contexts.
Methods
A didactic experiment replicating canonical research on randomness perception was conducted. Students generated fictional accounting datasets subsequently analyzed using Benford’s law. Additionally, a survey assessed students’ awareness of fake data, their previous experiences, and strategies for handling data manipulation.
Results
Findings revealed students` limited proficiency in identifying fake data, confirming the importance of developing analytical and critical competencies. Simultaneously, increased student engagement was observed when exercises highlighted real-world consequences of misinformation and ethical dilemmas associated with data reliability.
Conclusions
The results indicate the necessity of integrating data verification and ethical responsibility topics into curricula. The 'Know thyself' method enriches statistical education by incorporating philosophical and ethical aspects, enabling students to critically evaluate data and their own decisions, thus contributing significantly to the didactic literature and educational practice in economics.
Keywords
Know thyself method, fake data, Benford’s law, teaching microeconomics, ethics in statistics
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Speaker bio:
Krzysztof Kosiński, PhD in Natural Sciences in the field of Biology, university lecturer, and Director of the Department of Agriculture and Environment at the Podkarpackie Voivodeship Office. Author of numerous scientific publications. In his free time, he is an enthusiast of livestock breeding.
Abstract:
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Objective
The study aim to determine the influence of wolves on the actual decline in the cattle population in the Podkarpacie region in relation to other factors.
Methods
The research is conducted on the basis of tables of conflict situations kept by the communes in which conflicts between wolves and humans are most visible.
Results
Behaviour patterns of wolves are derived in the long-term, as well as the elements that significantly influence the worsening of the decline in the cattle population in Podkarpacie are determined.
Conclusions
Wolves are species that, when given the choice between obtaining food in the wild forests or obtaining animals kept on farms, chose the latter. There may be many reasons, including the lack of game that they hunt in the forests.
Keywords
wolf, Subcarpathia, ruminants, population decline
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Speaker bio:
Dr hab. Dariusz Kotlewski, prof. SGH - absolwent Szkoły Głównej Handlowej w Warszawie na kierunku Stosunki Międzynarodowe. Doktorat obronił w 2014 r. w dyscyplinie ekonomia i finanse. Stopień doktora habilitowanego otrzymał w lutym 2024 r., a od października 2024 r. jest profesorem SGH.
Pracował przez ponad 5 lat w Stowarzyszeniu Elektryków Polskich (SEP) zajmując się sprawami międzynarodowymi. Obecnie od ponad 10 lat pracuje w Głównym Urzędzie Statystycznym (GUS), w Departamencie Studiów Makroekonomicznych i Finansów, gdzie zajmuje się badaniami makroekonomicznymi gospodarki, w tym szczególnie rachunkowością wzrostu gospodarczego. Jego najważniejszym osiągnięciem jest opracowanie metodologii oraz implementacja rachunku produktywności KLEMS w polskiej statystyce.
Zainteresowania naukowe obejmują głównie zagadnienia związane z rachunkowością wzrostu gospodarczego, ze szczególnym uwzględnieniem jej przestrzennego wymiaru, tj. dystrybucji regionalnej wzrostu gospodarczego, w tym jego dekompozycji czynnikowej i sektorowej. Oprócz studiów czysto makroekonomicznych, badania naukowe wiążą się z szeroko rozumianą regionalistyką, obejmującą sektor elektroenergetyczny, infrastrukturę transportową, rynek nieruchomości, rozwój miast i regionów, funkcjonowanie przestrzenne sektorów PKD w świetle rachunku KLEMS.
Abstract:
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Objective
The aim of the paper is to present how the initiative of performing KLEMS productivity accounting by Polish voivodships was achieved, and to demonstrate its viability and usefulness. This includes the explanation of the basic methodology, the presentation of the necessary methodological extensions, the demonstration of the effectiveness of the applied methodology in the form of published results, and some examples of specific applications of final data.
Methods
The basic methodology relies on the idea of economic growth decomposition in the form of KLEMS growth accounting (otherwise called KLEMS productivity accounting) adapted to Polish data availability. A trans log production function is being used in calculations not only at the aggregate level but also at industry level. The special achievement of Polish KLEMS initiative is to develop a methodology for decompositions at regional level, i.e. at industry level and by voivodship at the same time. Data for the research have been provided by Statistics Poland’s units.
Results
The results of the calculations have been published on Statistics Poland’s site. They allow to study economic growth at regional level (by voivodship) and by industry. Labour, capital and multifactor productivity contributions (and their sub-contributions) to growth can be observed at the level of these aggregations, allowing for ample economic analyses of which the possibilities are yet to be explored.
Conclusions
The numerous possible applications include the possibility to study and compare not only economic growth and the contributions to it at the aggregate but also at regional level thus allowing to observe the effectiveness of regional economic policy at different NACE activity aggregations. The specific use can consist of studying specialisations, including smart specialisations of different regions. A specific industry example will be provided as a demonstration.
Keywords
KLEMS, productivity, economic growth, growth decomposition
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Speaker bio:
Dr Agnieszka Kozera - adiunkt w Katedrze Finansów i Rachunkowości Wydziału Ekonomicznego Uniwersytetu Przyrodniczego w Poznaniu. Jej badania koncentrują się głównie na roli inwestycji gmin, współfinansowanych ze środków Unii Europejskiej, w zakresie rozwoju gospodarki niskoemisyjnej. Szczególną uwagę poświęca analizie zróżnicowania tej aktywności inwestycyjnej w układzie typów administracyjnych gmin i przestrzennym oraz identyfikacji jej uwarunkowań społeczno-ekonomicznych, finansowych i środowiskowych. Bada również czynniki i bariery wpływające na przebieg transformacji energetycznej na poziomie lokalnym. W analizach wykorzystuje różnorodne metody ilościowe, w tym metody statystyczne, taksonomiczne i ekonometryczne. Autorka ponad 90 oryginalnych prac twórczych, w tym ponad 60 publikacji naukowych opublikowanych po uzyskaniu stopnia doktora. Członkini Polskiego Towarzystwa Statystycznego, Polskiego Towarzystwa Ekonomicznego, Polskiego Stowarzyszenia Ekonomistów Środowiska i Zasobów Naturalnych oraz Stowarzyszenia Ekonomistów Rolnictwa i Agrobiznesu.Abstract:
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Objective
In the face of escalating climate challenges and the urgent need for energy transformation, municipalities play a crucial role in implementing sustainable development policies. They undertake investment activities aimed at developing a low-carbon economy, the spatial distribution of which may exhibit significant spatial correlations. The objective of this study was to identify and assess the phenomenon of spatial autocorrelation in municipal investments related to the development of a low-carbon economy in the Greater Poland Voivodship, co-financed by European Union funds. The research aimed
Methods
The study was based on data obtained from the Local Data Bank of Statistics Poland (GUS) and databases of the Ministry of Funds and Regional Policy. To assess the spatial autocorrelation of municipal investments in the low-carbon economy, global and local measures of spatial autocorrelation were applied. The calculations were conducted in the R environment.
Results
The results revealed a spatial concentration of the intensity of municipal investments in the low-carbon economy across the Greater Poland Voivodship. The identified clusters of municipalities with high and low levels of implemented low-carbon projects confirm that functional urban areas may play a significant role as poles of intensification for this type of investment.
Conclusions
This study offers a new perspective in the literature on local sustainable development by integrating the analysis of low-carbon investments with a spatial approach. It demonstrates that the distribution of climate-oriented actions at the municipal level is not random but may be shaped by territorial dependencies and functional structures. Consequently, the research contributes to a deeper understanding of the spatial diffusion of the energy transition at the local level and enables the identification of territorial mechanisms that support or hinder the development of a low-carbon economy. The
Keywords
low-carbon economy, municipal investments, spatial autocorrelation, global Moran’s I, local Moran statistics, spatial analysis
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Speaker bio:
Prof. Partha Lahiri is Professor and Director of the Joint Program in Survey Methodology (JPSM) and Professor of Department of Mathematics at the University of Maryland College Park (UMD), and an Adjunct Research Professor of the Institute of Social Research, University of Michigan, Ann Arbor. Prior to joining UMD, prof. Lahiri was the Milton Mohr Professor of Statistics at the University of Nebraska-Lincoln. His research interests include survey statistics, Bayesian statistics, data integration, and small-area estimation. He published over 80 papers in peer-reviewed journals, delivered 17 plenary/keynote speeches and over 80 invited talks in professional meetings worldwide. Over the years, prof. Lahiri served on the editorial board of several international journals, including the Journal of the American Statistical Association, Statistics in Transition New Series, and Survey Methodology. He served on several advisory committees, including the U.S. Census Advisory committee and U.S. National Academy panel and served as consultant for international organizations such as the United Nations and the World Bank.
Prof. Lahiri is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. He received the 2021 SAE Award at the 63rd World Statistics Congress Satellite Meeting on Small Area Estimation in recognition of lifetime contributions to small area estimation research. More recently, Prof. Lahiri was awarded the Neyman Medal at a joint session of the 3rd Congress of Polish Statistics and 2022 International Association of Official Statistics (IAOS) held in Krakow, Poland, for outstanding contributions to the development of statistical sciences.
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Speaker bio:
Joanna Landmesser-Rusek - is a university professor in the Department of Econometrics and Statistics at the Institute of Economics and Finance of the Warsaw University of Life Sciences. She received her Ph.D. in economics in 2002 and her habilitation degree in 2014 (also in the discipline of economics). The habilitation procedure was conducted on the basis of the monograph entitled "The use of methods of duration analysis to study the economic activity of the population in Poland". Her research interests focus on microeconometric modeling (survival analysis, counterfactual scenario analysis, income inequality decomposition, multidimensional poverty) and network analysis for financial markets. Within the latter, she studies the topological properties of currency networks. She has published 91 articles in scientific journals and 4 monographs.
Abstract:
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Objective
Forecasting exchange rates is a key issue in finance and economics. The purpose of the conducted study was to evaluate the effectiveness of graph neural networks (GNNs) in forecasting and classifying returns for exchange rates, with a special focus on the structural relationship between currencies.
Methods
The analysis included time series of returns for 15 major world currencies over the 2022-2024 period. The structure of the network was determined based on correlations between returns, using minimum spanning trees (MST), in which nodes represented individual currencies and edges reflected the interdependencies between them. Forecasting and classification of returns for exchange rates was performed using convolutional graph networks (GCNs). The results were compared with benchmark models using ex-post forecast errors (RMSE, MAE) and measures of classification accuracy (Acc).
Results
Traditional models, such as ARMA, for example, analyze time series independently, ignoring the interconnectedness between currencies. However, exchange rates form a dynamic network of relationships that can be effectively modeled using GNNs. The constructed graph networks took into account the structural relationships between currencies. Both the GCN and LSTM-GCN models outperformed traditional statistical methods in terms of prediction and classification quality. The analysis of embeddings of nodes made it possible to identify the most influential currencies shaping the market structure.
Conclusions
The growing interest in GNNs in financial data analysis in recent years suggests their potential superiority over classical statistical methods. The results obtained confirmed this, and the built predictive graph neural network models can support investors and financial institutions in decision-making and risk management.
Keywords
graph neural networks, exchange rates
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Speaker bio:
Dr Paweł Lańduch - doktor nauk społecznych w dyscyplinie ekonomia i finanse. Specjalizuje się w badaniach statystycznych przedsiębiorstw, szczególnie w imputacji danych. Ostatnio zajmował się także kwestią kontroli ujawniania danych (czyli ochrony wrażliwych informacji statystycznych przed ich rozpoznaniem przez osoby niepowołane w oparciu o udostępniane dane wynikowe). Pracownik Urzędu Statystycznego w Poznaniu Ośrodka Statystyki Krótkookresowej Działu Metodologii i Programowania.
Abstract:
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Objective
The aim of the study is to examine the application of non-random data sources in business statistics.
Methods
The study uses the simulation method on the basis of a superpopulation model built from the frame and dataset of a real business survey.
Results
The study shows a comparison of the accuracy of the used estimators with the unbiased Horvitz-Thompson estimator.
Conclusions
Estimators using mass estimation are feasible in terms of the acceptable levels of accuracy compared to the representative method.
Keywords
mass imputation
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Speaker bio:
Professor Ronald D. Lee holds a Ph.D. in Economics from Harvard University. He spent a postdoctoral year at the National Institute of Demographic Studies (INED, France). After teaching for eight years at the University of Michigan, he joined Demography at Berkeley in 1979, with a joint appointment in Economics. He currently holds the Edward G. and Nancy S. Jordan Endowed Chair in Economics.
Professor Lee is also the Director of the Center on the Economics and Demography of Aging at Berkeley. Professor Lee is an elected member of the National Academy of Sciences, the American Association for the Advancement of Science, the American Academy of Arts and Sciences, and a Corresponding member of the British Academy. His other honors include Presidency of the Population Association of America and its Mindel C. Sheps Award for research in Mathematical Demography, and the Irene B. Taeuber Award for outstanding contributions in the field of demography. He also has chaired the population and social science study section for NIH and the National Academy of Sciences Committee on Population and has served on the National Advisory Committee on Aging. He is currently on the National Advisory Committee on Child Health and Human Development.
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Speaker bio:
Dr hab. Cecylia Leszczyńska – Uniwersytet Warszawski, Wydział Nauk Ekonomicznych, Katedra Historii Gospodarczej.
Zajmuję się historią gospodarczą XIX i XX wieku, specjalizuję się w badaniach historii polskiej bankowości centralnej i systemów monetarnych, wzrostu gospodarczego Polski i jego przestrzennego zróżnicowania, historii migracji, statystyki historycznej. Uczestniczyłam w ostatnich latach w projektach badawczych dotyczących: statystyki historycznej Polski (prowadzony przez GUS), społeczeństwa Drugiej Rzeczypospolitej (prowadzony przez Instytut Historii PAN), wzrostu gospodarczego ziem polskich w okresie 1870-1910 (prowadzony przez Katedrę Historii Gospodarczej WNE UW). Jestem autorką/współautorką około 100 publikacji w wymienionych wyżej dziedzinach. Do najważniejszych opublikowanych w ostatnich latach zaliczam:
- Leszczyńska C., Bukowski M., Koryś P., Tymiński M., Wolf N., 2019, Urbanization and GDP per capita: new data and results for the Polish lands, 1790-1910, “Historical Methods: A Journal of Quantitative and Interdisciplinary History”, no. 4, s. 213-227.
- Leszczyńska C., 2019, Polish Emigration Abroad: Regional Structure and Streams of Emigration in the Years 1870–1914 and 1918–1939, “Poland’s Demographic Past/Przeszłość Demograficzna Polski”, s. 177-207.
- Leszczyńska C., Bukowski M., Koryś P., Tymiński M., Wolf N., 2018, Wzrost gospodarczy ziem polskich w okresie pierwszej globalizacji (1870-1910), „Ekonomista” 2018, nr 1, s. 127-153.
- Leszczyńska C., Bukowski M., Koryś P., Tymiński M., 2017, Rozwój regionalny ziem polskich pod zaborami. Porównanie poziomu produktu brutto per capita na dzisiejszych terenach Polski na przełomie XIX i XX wieku (wyniki pierwszych estymacji), „Roczniki Dziejów Społecznych i Gospodarczych”, s. 163-197.
- Leszczyńska C., 2016, Level of living of Polish citizens in the interwar period, and its diversification, “Roczniki Dziejów Społecznych i Gospodarczych” , s. 95-122.
- Leszczyńska, 2013, Polska polityka pieniężna i walutowa w latach 1924-1936. W systemie Gold Exchange Standard, Wydawnictwa Uniwersytetu Warszawskiego, Warszawa, ss. 410.
- Leszczyńska C., 2013, Wirtschaftsgeschichte in Polen. Forschungsstand, „Historie. Jahrbuch des Zentrum für Historische Forschung Berlin der Polnischen Akademie der Wissenschaften“, Folge 6, s. 91-120.
- Leszczyńska C., 2013, The Determinants of Foreign Banking Activity in Poland during the Interwar Period, [in:] Foreign Financial Institutions and National Financial Systems. Studies in Banking and Financial History, ed. M. Aspey et al, The European Association for Banking and Financial History (EABH) e.V., Frankfurt a.M., s. 163-202.
- Leszczyńska C., Kuklo C., Łukasiewicz J., 2014, Polska w Europie/Poland in Europe, GUS Warszawa, ss. 605.
- Leszczyńska C., 2018, Polska 1918-2018, GUS Warszawa, ss. 365.
Abstract:
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Objective
The research problem focuses on the subject matter and thematic scope of Polish censuses in the 19th and 20th century (until 1988). The role of international models and standards in the construction of national censuses is described, as well as the importance of international statistical congresses, statistical agencies operating under the League of Nations (in the interwar period), the United Nations (in the second half of the 20th century) and the International Statistical Institute. The scope of the censuses and their role as a source of information for social and demographic research.
Methods
The study is based on a comparative analysis of international and national census documentation and forms from the 19th and 20th century. The subject matter and scope of the studied demographic and social issues, the continuity and discontinuity of certain groups of issues and the problem of the repetition of the scope of information were all reconstructed. In addition, the challenges associated with the organisation of censuses (personal censuses, administrative censuses, population registration based on various sources, etc.) were presented.
Results
Censuses began to be conducted in some European countries in the second half of the 18th century, and became a cyclical event in the 19th century. In the second half of the 19th century, censuses gained attributes of the universality, being conducted on a single day, directly and respondents being identified individually. International statistical institutions played an important role in the development of census procedures and standards. A set of common questions concerning demographic and social issues became one of the basic features of censuses in the 20th century.
Conclusions
Censuses constitute one of the most valuable sources for historical studies of demographics, levels of education, the living conditions of the population, its occupational structure and sources of income of societies. The thematic scope and set of census questions evolved under the influence of national and international standards, leading to the comparability of data in dynamic and spatial terms. Due to the fact that censuses were conducted at the level of the smallest administrative units, they also showed societies in different regional cross-sections.
Keywords
history of statistics, Polish censuses in the 19th and 20th century, historical demographics, statistical sources
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Speaker bio:
Bożena Łazowska (1958 - ), dr historii, bibliograf, wieloletni dyrektor Centralnej Biblioteki Statystycznej im. Stefana Szulca (2004-2023), od 2008 r. członek Zespołu "Historia Polski w liczbach" działającego w Głównym Urzędzie Statystycznym. Od 2011 r. członek Polskiego Towarzystwa Statystycznego, w latach 2014-2019 członek Sądu Koleżeńskiego Rady Głównej PTS, od 2019 r. zastępca przewodniczącego Oddziału Warszawskiego PTS i członek Rady Głównej Polskiego Towarzystwa Statystycznego. Pełni funkcję sekretarza Sekcji Naukowej Stowarzyszenia Bibliotekarzy Polskich. Autorka ponad 120 prac naukowych z zakresu historii, statystyki, demografii i informacji naukowej. Ważniejsze publikacje: Bibliografia wydawnictw poufnych i służbowych GUS 1950-1988, t.1-2 (Warszawa 1998-2000), Działalność badawcza Głównego Urzędu Statystycznego w okresie II Rzeczypospolitej (Warszawa 2015), Centralna Biblioteka Statystyczna 1918-2018 (Warszawa 2018).
Abstract:
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Objective
The aim of the paper is to present, on the basis of all currently available archival source data and historical studies, the situation of the Polish industry in the General Government in the years 1939-1945.
Methods
The study uses historical analysis based on the available printed and archival sources.
Results
the work has a pioneering character
Conclusions
the first time in the literature the topic was taken up
Keywords
history of statistics, World War II, General Government, industry
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Speaker bio:
Aleksandra Łuczak - jest profesorem Uniwersytetu Przyrodniczego w Poznaniu i pracuje w Katedrze Finansów i Rachunkowości na Wydziale Ekonomicznym. Jej główne zainteresowania badawcze koncentrują się na wielokryterialnych metodach ilościowych i ich zastosowaniach w ekonomii i finansach. Interesuje się metodami taksonomicznymi i metodami podejmowania decyzji, szczególnie ich zastosowaniami w rozwiązywaniu problemów związanych z planowaniem rozwoju lokalnego i regionalnego. W ostatnich latach zajmuje się również badaniami nad metodami pomiaru obiektywnego i subiektywnego ubóstwa jako zjawiska wielowymiarowego. Jest autorką i współautorką ponad 100 publikacji naukowych, a także członkiem Polskiego Towarzystwa Statystycznego oraz zespołów redakcyjnych czasopism "Przegląd Statystyczny" i "Journal of Agribusiness and Rural Development".
Abstracts:
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Objective
The analysis of differences between poverty measures is mainly based on income levels or indicators of material deprivation. Their comparison has consequences, such as differences in assessing the scale of the problem. The research has two goals: methodological and practical. The methodological goal is to present a methodological concept for studying poverty as a barometer that will inform in advance about changes in the situation of the population. The practical goal is to apply this methodology to study poverty in territorial units in Poland.
Methods
Our research focuses on a multidimensional approach based on multi-criteria decision-making methods that consider various aspects of poverty, such as health, education, housing conditions, and access to services. We use data from the Local Data Bank of Statistics Poland, which allows us to obtain accurate and up-to-date information. We aim for the research to be repeatable, enabling the monitoring of changes over time and the adaptation of social policies to dynamically changing conditions. Additionally, we identify the time of exiting or deeper falling into poverty of territorial units.
Results
This analysis represents the essence and extension of research on the diagnosis of poverty and social exclusion in the Mazowieckie Voivodeship from 2012 to 2023. The findings emphasize the need for an integrated approach to identifying poverty, one that considers various indicators influencing poverty.
Conclusions
An integrated multidimensional approach to identifying poverty, which considers various indicators, is crucial for effectively monitoring and adapting social intervention strategies. The research emphasizes the need to consider different aspects of poverty in social policies, which allows for a more comprehensive understanding of the problem and better adaptation of interventions to the actual needs of impoverished individuals.
Keywords
poverty, objective measures, social policy, multidimensional approaches
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Objective
This study examines the influence of the Human Development Index (HDI) on Sustainable Development (SD) in EU countries by analysing the relationship between HDI and a new Sustainable Development Index (SDI), highlighting regional disparities and policy implications.
Methods
Using 18 Eurostat indicators from 2021, the SDI is constructed via the TOPSIS method. Bilinear ordering visualizes EU countries’ SDI and HDI scores. Spearman’s rank correlation analyses their relationship, with data normalized using zero unitarization and winsorization to handle outliers.
Results
The SDI ranges from 0.270 (Romania) to 0.709 (Denmark). HDI varies from 0.795 (Bulgaria) to 0.948 (Denmark). Northern / Western EU countries (e.g., Denmark, Sweden) score higher in both, while Eastern / Southern countries (e.g., Romania, Bulgaria) lag. Spearman’s correlation (r=0.852) shows a strong link.
Conclusions
The strong SDI-HDI correlation underscores their alignment. Northern / Western EU countries excel in both, while Eastern / Southern ones need targeted strategies. Policymakers can use these insights to balance human and sustainable development, enhancing EU-wide outcomes.
Keywords
Sustainable Development, Human Development, TOPSIS, Bilinear Ordering, EU
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Speaker bio:
Dr Bartosz Łukaszewski - Uniwersytet Papieski Jana Pawła II w Krakowie, socjolog, wykładowca, analityk, ekspert i pracownik naukowy Instytutu Statystyki Kościoła Katolickiego, Prezes Zarządu Fundacji "Naszym Dzieciom" w Warszawie, koordynator projektów badawczych z zakresu metod ilościowych, a także metod mieszanych, ekspert PKA w dyscyplinie nauki socjologiczne.
Abstract:
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Objective
The aim of this paper, as well as the research project being carried out, is to present verification of the links between the characteristics of Internet use among Polish youth (the most popular content, dominant social media, time spent on the Internet, etc.) and subjective (declared, perceived) general health status. The cognitive impulse for the research project carried out in the panel perspective was the progression of broadband Internet in 2014, then – around 2016 and 2017 – the so-called smartphone revolution, and currently the expansion of AI mechanisms.
Methods
The project has been carried out for 10 years, last year a study was carried out verifying the potential impact of interactional strain resulting from the frequency of using the Internet on the decrease in the perceived state of health (N=315), the results of which were presented at the 4th KSP. This year, the study covered over 500 people (youth, young adults, purposeful selection), using correlation, determination mechanisms and a linear regression model, while maintaining the main research assumptions, adding to the tool a component regarding pornographic content and a sense of anxiety.
Results
In 2024, a statistically significant correlation was noted between the so-called ”social online mirror” and lowered self-esteem (r=-0.303). The meta-analysis of ESS 11 data (linear regression models) shows that high frequency of Internet use affects the decrease in subjective general health in 12% (r=-0.347, p?0.001) in Polish society and as much as 48% among young people (r=-0.694, r-squared=0.48, p?0.001). At the same time, interactional strain was found among young people resulting from a number of different network activities.
Conclusions
The research results are the basis for the implementation of broadly understood public policy for youth, as well as detailed preventive programs in terms of reducing the risk of addiction to all mechanisms of the network society that determine the reduction of subjective general health. The significance of the project is therefore purely ”applied” (implementative), and the post-research conclusions and their validity imply the construction of models of cross-sectoral activities to reduce the risk of long-term consequences of the virtualization of the lifestyle of contemporary youth.
Keywords
subjective general health, Internet use, Polish youth, Polish society, anxiety
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Speaker bio:
Marta Marszałek - Assistant Professor at the SGH Warsaw School of Economics, Institute of Statistics and Demography. Analyst and expert collaborating with Statistics Poland (GUS) in the field of social statistics and satellite accounts. Author of the first and subsequent editions of the Household Production Satellite Account and co-author of the Social Economy Satellite Account for Poland. Her research interests and professional experience focus on: domestic unpaid work, non-market household production, the care economy, generational economics, time transfers, satellite accounts, the measurement of gender inequalities, care work, and the future of work.
Abstract:
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Objective
This paper addresses the growing relevance of unpaid household and care work in the context of increasing demand for care services due to demographic and labour market changes.
Methods
To valuing unpaid work the replacement cost method (input method) using market wage rates was applied. This method assumes that the input is the time spent on specific domestic tasks and activities. Time-use data were drawn from the 2023 Time Use Survey, and hourly wage rates by occupation were used to estimate the monetary value of household work. Selected macroeconomic aggregates from national accounts relating to the household sector were then incorporated into the valuation of non-market household production. A Household Production Satellite Account for Poland 2023 was compiled.
Results
The valuation revealed that unpaid household work accounted for approximately 90% of non-market household production in 2023 (compared to 78% in 2013). The gross value added of non-market household production represented approximately 40.4% in relation to Poland’s GDP in 2023. Given its significant scale, this form of production should not be excluded from official public statistics. It can be presented through a satellite account of household production as a complementary data source alongside national accounts, offering insights into the real contribution of households to the economy.
Conclusions
The substantial size of unpaid work and non-market household production confirms the contribution of households to both the care economy and the informal economy. It also allows for meaningful comparison with GDP. The Satellite Account of Household Production fills an important gap in the system of social and economic statistics by estimating the non-market contribution of households. Alongside national accounts, it serves as a valuable source of information on time transfers and household resources.
Keywords
care work, informal economy, unpaid work, gender equality, household production satellite account, time use survey
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Speaker bio:
Łukasz Matoga - doktor nauk społecznych w dyscyplinie geografia społeczno-ekonomiczna i gospodarka przestrzenna, zawodowo związany z Urzędem Statystycznym w Krakowie, w którym odpowiada za organizację badań statystycznych w zakresie zdrowia i ochrony zdrowia. Brał udział w licznych projektach naukowo-badawczych poświęconych rozwojowi turystyki oraz lecznictwa uzdrowiskowego w różnych kontekstach przestrzennych, środowiskowych i funkcjonalnych. Ostatnio interesuje go problematyka efektywności, dostępności i jakości systemu ochrony zdrowia, zwłaszcza opieki psychiatrycznej nad dziećmi i młodzieżą. Pasjonat podróży, nowoczesnych technologii i mocnego espresso.
Abstract:
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Objective
Primary health care (PHC) is the cornerstone of the health care system and plays a key role in ensuring the availability of medical services, the coordination of patient care and the implementation of preventive measures. The aim of the presentation is to illustrate the importance of the PHC by analysing selected statistical data on e.g. consultations in the PHC, quality of services as assessed by patients, accessibility to outpatient health services and reasons for abandoning appointments with primary care physicians, as well as the staff resources of family medicine specialists.
Methods
The paper is based on the results of a nationwide statistical survey on the activities of medical facilities and the use of health care services in households. They provide information on the number of consultations provided in PHC departments and infirmaries by age group of outpatients, an assessment of the course of visits to the primary care physicians or main reasons for unmet needs for medical examination or treatment.
Results
The data collected show that in 2023, there was an average of almost five consultations per capita provided to outpatients in the PHC, and about 3% of household members did not use the services of a primary care physicians, despite the need.
Conclusions
The PHC is the most accessible form of health care, so it is important to emphasise the need for further investment in its development, especially in the context of the observed ageing population. The PHC provides the first line of contact between the patient and the health system, leading to early detection and treatment of diseases, resulting in improved population health, system efficiency and reduced medical expenditure in the long term.
Keywords
primary health care, health care system, PHC, health care statistics, an outpatient department and infirmaries of the primary health care
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Speaker bio:
Adrianna Mermela Starszy Statystyk w Ośrodku Metodologii Badań Ludnościowych Urzędu Statystycznego w Poznaniu, absolwentka kierunku Informatyka i Ekonometria w specjalności Analityka Gospodarcza Uniwersytetu Ekonomicznego w Poznaniu (2025). W ramach swojej pracy zawodowej zajmuje się statystyką opartą na rejestrach, metodologią spisów powszechnych oraz estymacją liczby ludności na podstawie danych administracyjnych.
Abstract:
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Objective
The aim of this presentation is to introduce capture-recapture methods for population size estimation (dual-system estimation, multiple-system estimation) that account for record linkage errors and their implementation in the {uncounted} package in R. The package is currently being developed at the Population Research Methodology Center in the Statistical Office in Poznań.
Methods
The presented tool includes classical estimators as well as estimators that incorporate record linkage error correction (one-way, symmetric, and asymmetric (Di Consiglio * Tuoto, 2018: Zult et al., 2025)).
Results
The package offers the capability for variance estimation and construction of confidence intervals to assess the quality of the estimates.
Conclusions
As part of the presentation, we will showcase the package in the context of administrative data, with special emphasis on modeling record linkage errors. Examples with simulated data will illustrate the package`s capabilities in various scenarios.
Keywords
capture-recapture, population size estimation, administrative registers, record linkage errors
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Speaker bio:
Izabela Miechowicz - dr nauk medycznych, adiunkt w Katedrze Informatyki i Statystyki Uniwersytetu Medycznego w Poznaniu, współautor 139 artykułów naukowych, rozdziałów w monografiach i streszczeń konferencyjnych, członek Polskiej Grupy Narodowej Międzynarodowego Towarzystwa Biostatystyki Klinicznej i Polskiego Towarzystwa Statystycznego.
Abstract:
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Objective
The aim of the study was to develop and evaluate the U-smile method, designed to visualize and quantitatively assess the usefulness of new predictors in binary classification models, with particular emphasis on scenarios involving imbalanced data.
Methods
The U-smile method – comprising U-smile plots and the BA (Absolute Change), RB (Relative Change), and I (Net Reclassification Index) coefficients – was used to analyze the impact of new predictors in binary classification models. The study was conducted using real-world data from the Heart Disease dataset and simulated data, incorporating various class imbalance scenarios.
Results
The U-smile method effectively identifies and visualizes the contribution of new predictors to classification improvement, even under data imbalance conditions. The introduction of a three-level approach and the use of the I coefficient as a weighting factor in BA and RB plots enhance the interpretability of results.
Conclusions
The U-smile method provides a valuable tool for assessing the usefulness of new predictors in binary classification models, especially when data are imbalanced. Its application can support variable selection processes and improve the interpretability of predictive models across various fields, such as medicine or social sciences.
Keywords
binary classification, U-smile method, ROC curve, likelihood-ratio test, imbalanced data
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Speaker bio:
Dr Grzegorz Migut- doktor nauk o zarządzaniu i jakości, analityk i wykładowca z ponad 20-letnim doświadczeniem. Łączy działalność naukową, dydaktyczną i praktyczną. Specjalizuje się w zastosowaniach data science w procesach decyzyjnych, modelowaniu zachowań klientów oraz modelach uczenia maszynowego. Autor książki "Tworzenie skutecznych modeli Data Mining na przykładzie prognozowania migracji klientów". Dyrektor działu technicznego StatSoft Polska. Prowadzi zajęcia na Wydziale Informatyki Akademii Górniczo-Hutniczej oraz współpracuje dydaktycznie z czołowymi uczelniami w Polsce.
Abstract:
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Objective
The aim of the study is to identify and evaluate the influence of key factors (TIVHE) on the quality of customer retention classification models and to compare the effectiveness of econometric and advanced machine learning methods.
Methods
The study is simulation-based aligned with the CRISP-DM methodology using a complex customer retention dataset. The influence of five factor groups was analyzed across logistic regression, decision trees, neural networks and ensemble models.
Results
The findings of the study show what follows: predictor transformation was most beneficial for logistic regression, feature engineering and hyperparameter tuning improved all models, segmentation helped interpretable models but harmed black-box methods, and aggregation improved predictions for all except logistic regression.
Conclusions
Effective model development requires aligning the TIVHE strategy with the nature of the algorithm used. The results underscore the need for a flexible modeling approach, offering guidance for enhancing model performance.
Keywords
machine learning, data mining, hyperparameter optimization, classification models, customer retention models, model ensembles
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Speaker bio:
Andrzej Młodak - doktor habilitowany nauk ekonomicznych, konsultant w Ośrodku Statystyki Małych Obszarów Urzędu Statystycznego w Poznaniu. Jest również profesorem w Międzywydziałowym Zakładzie Matematyki i Statystyki Uniwersytetu Kaliskiego im. Prezydenta Stanisława Wojciechowskiego w Kaliszu. W pracy naukowej zajmuje się wielowymiarową analizą danych, kontrolą ujawniania danych, statystyką regionalną, ekonomią matematyczną i edukacją statystyczną. Zastępca redaktora naczelnego czasopisma "Wiadomości Statystyczne. The Polish Statistician" oraz Associate Editor periodyku "Statistics in Transition - new series". Długoletni członek Polskiego Towarzystwa Statystycznego oraz Kaliskiego Towarzystwa Przyjaciół Nauk (zasiada we władzach obu organizacji).
Abstract:
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Objective
In this presentation, we will recall the basic assumptions of the Statistical Disclosure Control algorithm prepared for the needs of the Geostatistical Portal of Statistics Poland, one of the basic and most comprehensive channels for sharing and analyzing Polish official statistics data. We will present the assumptions and the scheme of the optimal data protection process and indicate the basic problems related to the practical implementation and the possibilities of solving them.
Methods
In the research, we use an algorithm written in SAS and R using the sdcMicro package of the R environment, its application and parameterization.
Results
We will discuss the effects of applying the algorithm and correcting the obtained disturbances in order to maintain the definitional consistency of the provided data and the summation of appropriate values.
Conclusions
We will point out the usefulness of the algorithm and outline the most important challenges facing official statistics in this area – both methodological (differential privacy, generating synthetic data) and organizational (e.g. access to data for scientific purposes).
Keywords
Statistical Disclosure Control, Geostatistical Portal, perturbative methods, synthetic data
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Speaker bio:
Karolina Mroczyńska
dr inż. adiunkt, Instytut Matematyki, Uniwersytet Kazimierza Wielkiego w Bydgoszczy, dr nauk matematycznych (2009 - UMK), informatyk (UKW - 2014)
prowadzone badania: algebra, analizy statystyczne, zastosowania matematyki, dydaktyka matematyki i informatyki, pedagogika specjalna
autor grantów edukacyjnych m.in. MNiSW: Bydgoskie Impresje Matematyczne, Etiudy matematyczne dla ósmoklasistów,
medal KEN, nagrody indywidualne Rektora za działalność dydaktyczną
Abstract:
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Objective
Statistical education is of great importance in the modern world: it influences both the worldview and the decisions a young person makes. School is the first environment where students learn about statistics and its importance theoretically and practically, and not only during mathematics lessons. The aim of the study is to present examination tasks from the last 10 years, where statistical knowledge and skills proved crucial to their solution.
Methods
The presentation is based on an analysis of examination papers, analysis of sources and publications, as well as interviews.
Results
The analysis of examination papers in science and social science subjects shows the universality and functionality of statistics.
Conclusions
The importance of disseminating statistical knowledge and skills is not always emphasized in the school setting. It is worth emphasizing, however, that the Statistical Olympiad organized by Statistics Poland and the Polish Statistical Association, which will have its 10th edition in 2025/2026, is enjoying increasing interest and emphasizes the importance and significance of statistics for young people.
Keywords
mathematical statistics, statistical education, universality and functionality of statistics, Statistical Olympiad
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Speaker bio:
Paweł Murawski, Departament Innowacji, Główny Urząd Statystyczny
Analityk danych z 16-letnim doświadczeniem w statystyce publicznej. Specjalizuje się w przetwarzaniu i analizie danych ze źródeł administracyjnych, integracji danych oraz ocenie ich jakości. Brał udział w realizacji dwóch spisów powszechnych w latach 2011 i 2021. Uczestniczył w licznych projektach krajowych i międzynarodowych, których celem było zwiększenie efektywności wykorzystania danych administracyjnych, poprawa jakości danych statystycznych oraz rozwój infrastruktury informacyjnej statystyki publicznej. Współtwórca nowatorskich rozwiązań analitycznych i technologicznych, w tym metod udostępniania danych na poziomie siatki przestrzennej (grid), które znacząco poszerzyły zakres i użyteczność danych dostępnych dla użytkowników zewnętrznych
Abstract:
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Objective
The aim of the presentation is to show the results of an experimental study on the spatial analysis of the effects of the flood in Poland in September 2024 and the applicability of the developed method to monitor the effects of natural disasters.
Methods
Remote sensing data, geospatial data and administrative data were used for the study. The survey consisted of 3 stages. In the first, the extent of flood-affected areas was determined on the basis of satellite imagery from the Copernicus programme (Sentinel 2). In the second stage, address points were assigned to the delineated flood zone extents (source: National Population and Housing Census 2021), and then data on persons and buildings from the integrated administrative database ('List of Persons for Experimental Study') were assigned to the address points.
Results
Linking data from such a variety of sources made it possible to obtain, for the areas actually affected by the floods, information such as the population and its demographic characteristics, employed persons, economic entities, farms, buildings and their age, and others. For the purpose of performing spatial analyses, the data were aggregated to the municipality, census area and district. The talk will present the main conclusions of these analyses and detailed statistics for several of the most affected municipalities.
Conclusions
The developed data integration method is a complex process, in which the main goal at each stage is to ensure high data quality (including coherence and comparability). At the same time, it provides great opportunities to prepare, in a relatively quick way, spatial analyses of the extent and effects of floods, as well as other types of natural disasters.
Keywords
Earth Observation methods, remote sensing, geospatial data, administrative data, flood
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Speaker bio:
Agnieszka Nocko - kierownik ośrodka w Ośrodku Statystyki Budownictwa Urzędu Statystycznego w Lublinie. W pracy zawodowej zajmuję się przygotowaniem i realizacją badań statystycznych z zakresu statystyki budownictwa. Zainteresowania badawcze rozwijane w ramach pracy zawodowej koncentrują się na zagadnieniach związanych z problematyką suburbanizacji, rozwojem budownictwa w szczególności na terenach miejskich obszarów funkcjonalnych.
Abstract:
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Objective
The Statistical Office in Lublin, as part of the implementation of tasks related to the acquisition of administrative data, has cooperated with the General Office of Building Control (GUNB) on the SOPAB system under development. The purpose of the presentation is to introduce SOPAB as a future source of construction data. The innovative solutions used in the newly-created registry will improve data quality. Considering the information resource of SOPAB, its creation will provide opportunities to obtain a wider set of data in the future than at present, and this in turn will create new opportunities for analytical and publication work.
Methods
No statistical methods will be used. The presentation is intended to introduce the SOPAB administrative system.
Results
Currently, consultation work is underway on the implementation of the assumptions of the system between the GUNB`s project task contractor, Poznan Institute of Technology, and the SO in Lublin. Their purpose is to ensure methodological consistency and completeness of the data to be obtained, necessary for official statistics to carry out the tasks included in the Statistical survey program of official statistics (PBSSP) and international obligations. SOPAB will contribute to reducing workload, eliminate the manual process of filling out statistical forms improving the quality and detail of the data collected, and streamline the process of obtai
Conclusions
In the future, the SOPAB system will become a source of administrative data in the field of building permits and tangible effects of construction. Ultimately, the expanded System will include solutions and tools for the complete development of results in the field of construction, the preparation of which will significantly reduce the workload and time consumption They will therefore serve both cooperating institutions and, consequently, the whole society.
Keywords
administrative data, construction statistics, digitalization, construction process
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Speaker bio:
Dagmara Oprych-Franków - związana ze statystyką publiczną od 2003 roku. W latach 2009-2021 kierownik Ośrodka Statystyki Cen w Urzędzie Statystycznym w Opolu. Od 2021 roku pracuje w Departamencie Handlu i Usług Głównego Urzędu Statystycznego na stanowisku konsultanta w Wydziale Cen Konsumpcyjnych. Odpowiada za prowadzenie analiz próby do badań cen konsumpcyjnych w zakresie wybranych grup towarów i usług na potrzeby wskaźników CPI, HICP oraz OOH. Zajmuje się także analizą cen detalicznych w kontekście wyżej wymienionych wskaźników. Uczestniczy w pracach grup roboczych, seminariach i konferencjach poświęconych statystyce cen, organizowanych przez Eurostat i inne instytucje międzynarodowe.
Abstract:
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Objective
The aim is to investigate if there is an effective yet automatic procedure for detecting downsizing and upsizing? An attempt is made to construct such a procedure in the R environment. Moreover, the aim is to determine the scale of hidden inflation for different food and non-food product groups and the sensitivity of different price index formulas to the phenomenon of over- and under-sizing (disproportionate to its price).
Methods
The study uses IT toosl: R environment and PriceIndices package. The research method is an empirical study using actual scanner data. The data source is a retail chain operating in Poland (cooperating with Statistics Poland).
Results
Both groups of products that do not generate hidden inflation (e.g. bread) and groups of products that are particularly vulnerable to downsizing and upsizing (e.g. yoghurt) are indicated. The results suggest that price index formulas (weighted and unweighted) have different vulnerabilities to hidden inflation (being more or less sensitive to downsizing and upsizing).
Conclusions
Multilateral indices have been shown to be much less sensitive to the phenomena under consideration than bilateral indices. In particular, chained indices (e.g. the Jevons chained index) appear to be particularly susceptible to the phenomenon of hidden inflation. The results in this regard are pioneering in the literature.
Keywords
scanner data, product downsizing, shrinkflation, product upsizing
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Speaker bio:
Janusz Pappelbon - zastępca dyrektora Urzędu Statystycznego w Olsztynie, jest absolwentem Uniwersytetu Mikołaja Kopernika w Toruniu. Ukończył studia w zakresie planowania i zagospodarowania przestrzennego. Za swoją pracę dyplomową otrzymał wyróżnienie Polskiego Towarzystwa Geograficznego w ogólnopolskim konkursie prac magisterskich. W latach 2014-2018 odbył studia doktoranckie w dziedzinie nauk ekonomicznych w Szkole Głównej Handlowej w Warszawie. Urzędnik służby cywilnej.
Pracę w Urzędzie Statystycznym w Olsztynie rozpoczął w 2000 roku wykonując zadania o charakterze informatycznym. Odpowiadał m.in. za zasilanie internetowej bazy Demografia. W 2004 roku został kierownikiem Wydziału Statystyki Gospodarczej. Od 2007 roku pełni funkcję zastępcy dyrektora.
Do jego obowiązków należy przede wszystkim koordynowanie prac związanych z realizacją badań dotyczących sytuacji demograficznej w Polsce (urodzenia, zgony, małżeństwa, rozwody i migracje). Od 2008 roku bierze udział w obradach grup roboczych prowadzonych przez Eurostat, zajmujących się metodologią statystyki zgonów oraz spisów ludności. W latach 2010-2018 uczestniczył w projekcie Uniwersytetu w Minnesocie, którego efektem było opracowanie zestawu prób mikrodanych z Narodowych Spisów Powszechnych przeprowadzonych w latach 1978-2011. Od 2020 roku współpracuje z Ministerstwem Zdrowia oraz Ministerstwem Spraw Wewnętrznych i Administracji w zakresie wdrożenia w Polsce elektronicznej karty zgonu. Pod jego kierunkiem powstał prototyp Atlasu Demograficznego Polski wydanego przez GUS w 2017 roku.
Jego zainteresowania zawodowe skupiają się głównie na poprawie jakości badań statystycznych z zakresu demografii oraz na analizie procesów demograficznych w Polsce.
Abstract:
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Objective
In the recent years, there has been a dynamic, steadily deepening decline in the population of Poland. This process is shaped primarily by natural increase, which has remained negative since 2013. A record high natural decline was observed in the past 2024, when 156.7 thousand more people died than were born (a decline of 41 people per 10 thousand population). The aim of this paper is to present the most important demographic factors influencing unfavorable trends in mortality and birth rates.
Methods
The source of the data are the results of demographic surveys conducted by the Statistics Poland – collected by the Statistical Office in Olsztyn. The characteristics of population reproduction processes were characterized by the following coefficients: demographic dynamics, natural increase and fertility. The observed trends in the intensity of births and deaths were referred primarily to the transformations in the population structure by age. Various forms of graphic presentation were used to visualize the analysis results, such as: cartograms, age pyramids and charts.
Results
The dynamic decline in the number of births (apart from the procreative behaviors of the population) is influenced by the decreasing number of women of reproductive age, especially those aged 20-35. In the case of deaths, the greatest impact on their intensity is the increasing percentage of people aged 65 and over in the total population (the ongoing process of ageing of population). Additionally, in 2020 and 2021, the covid-19 pandemic had a particular impact on the rapid increase in the number of deaths. Analyses also showed clear spatial differentiation in terms of vital statistics.
Conclusions
The observed demographic processes may significantly affect all areas of socio-economic life in Poland. The demographic forecast indicates that the current trends regarding natural decrease and ageing of population will deepen.
Keywords
natural increase, depopulation, vital statistics, ageing of population
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Speaker bio:
Karolina Piech - pracuje w Instytucie Rozwoju Miast i Regionów, gdzie specjalizuje się w analizach przemian demograficznych oraz kształtowania przestrzeni miejskiej. W swoich badaniach szczególną uwagę poświęca koncepcji miasta zwartego, zgłębiając sposoby jego klasyfikacji oraz modele rozwoju sprzyjające zrównoważonej urbanizacji.
Abstract:
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Objective
For many years, the public debate in Poland has highlighted the issues of urban sprawl and spatial chaos. While various monitoring datasets exist, there is a lack of nationwide, high-resolution spatial statistics. Available land use data often fail to capture the functional aspects of urban areas. The aim of this study is to identify and analyze the functional land use structure of Polish cities using a consistent methodology based on official spatial data, as well as to examine changes between 2017 and 2024.
Methods
The research method is based on the concept of the urban transect. Functional land use analysis was conducted using data from the Land and Building Register (EGiB), with 500 m2 hexagons as the basic unit of analysis. Based on land use structure, the hexagons were classified according to a defined functional typology. To reflect the specific characteristics of Polish cities, two additional categories were introduced: residential development on agricultural land and high-density multifamily housing areas.
Results
The conducted analyses allowed for the identification of the functional and spatial structure of cities, enabling an objective characterization of urban land use and an assessment of its temporal changes. Based on the results, it is possible to broadly identify spatial reserves within cities for potential future development and to indicate the likely directions of urban expansion. The findings also revealed the intensity of uncontrolled and chaotic suburbanization processes.
Conclusions
Due to its high level of automation, ongoing data updates, and relatively easy access, the proposed research method offers a viable alternative to traditional studies of the functional and spatial structure of cities. The resulting data – accurate yet standardized and generalized – effectively reflect changes occurring in urban space, making them a valuable source for analyzing the evolution of spatial structure over any selected time period.
Keywords
urban space, LULC, EGiB, GIS
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Speaker bio:
Dr hab. Michał Bernard Pietrzak - jest Profesorem Uczelni na Wydziale Zarządzania i Ekonomii Politechniki Gdańskiej. Jest doświadczonym ekonometrykiem specjalizującym się w stosowaniu metod ilościowych, ze szczególnym uwzględnieniem metod wielowymiarowej analizy porównawczej, ekonometrii finansowej oraz ekonometrii przestrzennej oraz metod badań marketingowych. Podejmowane przez niego problemy badawcze związane są z dziedzinami ekonomii, zarządzania i finansów. Bieżące badania naukowe dotyczą regionalnych analiz dotyczących rozwoju wybranych przestrzennych zjawisk ekonomicznych oraz analiz przebiegu procesów transformacji energetycznej, ze szczególnym uwzględnieniem rynku energii odnawialnej. Profesor Pietrzak opublikował wyniki badań w ponad 100 artykułów indeksowanych w bazie Web of Science Core Collection.
Abstract:
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Objective
One of the key problems in the development of world economies is the implementation of sustainable development goals. Some of the goals are focused on environmental factors mainly related to industrial operation and fossil fuel consumption. The concept of energy efficiency, which assumes the achievement of both carbon emission reductions and sustainable economic growth, can be used to evaluate the Sustainable Development Goals. The purpose of this study is to assess energy efficiency in European Union member states.
Methods
One approach to studying energy efficiency is to analyze energy intensity, defined as energy consumption per unit of output (usually gross domestic product). This approach is criticized for ignoring the structure of the economy and environmental conditions, thus assuming that economic output is the only determinant. Another approach is the DEA (Data Envelopment Analysis) method, a non-parametric linear programming method for measuring the efficiency of multiple decision-making units.
Results
The application of the DEA model assumed the following input variables: GDP, renewable energy, country area or population. The analysis also used the determinants of CO2 emissions: energy intensity, energy structure, carbon intensity and economic activity. As a result of the research, the potential of individual member states to reduce carbon emissions was determined and they were ranked by this criterion.
Conclusions
Ranking EU member countries by the criterion of energy efficiency made it possible to identify countries that are leaders in terms of reducing CO2 emissions and countries that need to intensify their efforts to improve the effectiveness of environmental policy.
Keywords
energy efficiency, CO2 emissions, Sustainable Development Goals, DEA, EU member states
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Speaker bio:
Piotr Płuciennik - pracuje na stanowisku profesorskim w Zakładzie Statystyki Matematycznej I Analizy Danych na Wydziale Matematyki i Informatyki. Naukowo zajmuje się badaniem zależności na rynkach finansowych za pomocą modeli ekonometrycznych. W ostatnich latach przewodnim tematem jego badań stały się spółki i indeksy spółek społecznie odpowiedzialnych.
Abstract:
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Objective
The study aimed to assess the impact of ESG scores on the market risk of companies listed in the S&P 500 index. Specifically, it examined the influence of ESG performance on market risk both across the entire index and within selected sectors, including Financials, Health Care, Industrials and Information Technology.
Methods
In the first step, the GARCH-type models were fitted to the daily rates of return of 482 S&P 500 companies. Based on the GARCH-type models, we determined the dynamic Value-at-Risk (VaR) for each company. In the next step, the relationship between the VaR and the companies' ESG scores was identified for each day of the analyzed period. There were estimated dependence measures of 5%-VaR and 1%-VaR with companies' ESG scores. Considering that the relationship between VaR and companies' ESG scores may be non-linear, the analysis included not only the Pearson correlation coefficient, but also the S
Results
All dependence measures oscillate near zero during all the analyzed periods. The lower bound of confidence intervals is slightly above zero only in a few days in February 2022 and October 2023 – the beginning of the war in Ukraine and the beginning of the Israel-Hamas conflict. The effect is minimal and fleeting. Similar results were obtained for the companies from the Financials, Health Care, Industrials and Information Technology sectors. A more evident positive correlation between ESG scores and VaR is observed in the Industrial sector.
Conclusions
The conducted analysis confirmed a statistically significant correlation between Value-at-Risk and ESG scores exclusively for companies in the Industrials sector of the S&P 500 index. This finding suggests that, within this sector, lower market risk is meaningfully associated with higher ESG scores. One possible explanation is that companies in the Industrials sector may demonstrate greater commitment to environmental responsibility, social impact and corporate governance, which may be positively perceived by the market.
Keywords
GARCH models, ESG, S&P500 index
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Speaker bio:
Mgr Anna Połeć - doktorantka w Szkole Doktorskiej Nauk Społecznych Uniwersytetu Jagiellońskiego w Krakowie, w dyscyplinie Ekonomia i Finanse. Absolwentka studiów magisterskich z matematyki na Wydziale Matematyki i Informatyki Uniwersytetu Jagiellońskiego w specjalizacji Matematyka Stosowana. Tematem rozprawy doktorskiej jest "Zastosowanie funkcji specjalnych w rozwiązywaniu modeli wzrostu gospodarczego". W swoich badaniach koncentruje się na zagadnieniach z zakresu ekonomii matematycznej oraz modelowaniu matematycznym procesów wzrostu gospodarczego, ze szczególnym naciskiem na wykorzystanie zaawansowanych narzędzi matematycznych. Obszarem specjalizacji jest analiza modeli z czasem ciągłym, które nie posiadają elementarnego rozwiązania. Bierze ponadto udział w badaniach nad analizą zróżnicowania rozwoju gospodarczego i społecznego na poziomie regionalnym i lokalnym.
Abstracts:
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Objective
The aim of the study is to construct a macroeconomic model describing the impact of armaments on the dynamics of basic macroeconomic variables in the economy.
Methods
The model uses elements of the theory of differential equations and numerical methods,
Results
The model allows for simulations of military production growth paths mimicking the arms race process, for example during the Cold War between the USA and the USSR or between North and South Korea.
Conclusions
The model can be extended as a multi-equation econometric model, and the estimates of its parameters can describe actually functioning economies.
Keywords
Solow model, arms race, differential equations, numerical methods
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Objective
The aim of the paper is a statistical analysis of the impact of the lagged unemployment rate and GDP growth rates on the unemployment rate in regions of the Czech Republic and Slovakia. In their study, the authors attempt to answer the following questions: Do changes in regional GDP significantly influence changes in unemployment rates at the regional level in the Czech Republic and Slovakia? Were the effects of the 2008 financial crisis and the COVID-19 pandemic noticeable in both countries? Did the previous unemployment rate in both countries have a significant impact on its subsequent level?
Methods
The study is based on descriptive statistics, unemployment rate growth equation, the Ordinary Least Squares (OLS) method, Generalized Method of Moments (GMM) and Fixed effects.
Results
Prague recorded the highest GDP level during the analyzed period. The capital also exhibited the lowest average unemployment rate. Bratislava stood out significantly from the other regions in terms of GDP. The lowest average unemployment rates were also recorded in Bratislava. In both the unemployment growth equation estimated using OLS and GMM (with some exceptions), for Czech and Slovak regions, the previous unemployment level had a statistically significant impact on its growth. The GDP growth rate in Slovak and Czech regions generally reduced the increases in the unemployment rate.
Conclusions
The results of the conducted analyses provide a solid foundation for formulating practical recommendations in the field of regional and economic policy. The conclusions drawn from the comparison of Czech and Slovak regions can serve as a basis for developing more precise tools to support regional labor markets, especially in areas where unemployment is of a structural nature. The methods used in the article can also be applied beyond the borders of the Czech Republic and Slovakia, as the described statistical and econometric techniques maintain their universality in a comparative context.
Keywords
descriptive statistics, econometrics, mathematical economics, regional development, unemployment
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Speaker bio:
Radmila Roszkowska - absolwentka Uniwersytetu Warszawskiego oraz stypendystka Europejskiej Akademii Dyplomacji. Jako Naczelnik Wydziału Standardów Klasyfikacyjnych w Głównym Urzędzie Statystycznym bierze udział w pracach nad tworzeniem standardów klasyfikacyjnych w ramach Grup Roboczych i Zadaniowych Eurostatu oraz opracowuje krajowe standardy klasyfikacyjne, zgodne ze standardami międzynarodowymi wprowadzanymi aktami prawnymi lub zalecanymi do stosowania przez UE i ONZ. Opracowała wraz z zespołem Polską Klasyfikację Działalności PKD 2025, natomiast obecnie skupia się na nowelizacji Polskiej Klasyfikacji Wyrobów i Usług.
Abstract:
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Objective
The aim of the study is to present an analysis of the activities carried out to develop PKD 2025 and the promotion of the classification in order to encourage domestic users to independently re-register their PKD activity codes in official registers, including REGON, KRS and CEiDG.
Methods
The study shows the statistics and analysis of the impact of the wide-ranging national consultations on the PCAs in the new classification. The changes introduced, in particular regarding the divisions of the current groupings, should be duly justified (for example, turnover or a significant estimated market share).
Results
As a result of meetings organized by Statistics Poland and promotion of changes to the PKD 2007 in the years 2022-2024, 71 institutions, chambers, business associations, government administration units and the UAS applied. The largest group of entities that submitted proposals for changes to the classification were institutes, chambers and associations of entrepreneurs. As part of a broad consultation on the amendment to the PKD 2007, 173 proposals for changes to the classification were collected. In addition, as part of the legislative process, further changes and new c
Conclusions
Classification of PKD activities is a classification with a wide application, used, among others, for reporting, registration and economic analysis purposes. For these reasons, it is important that it reflects the changing reality, i.e. it takes into account new technologies, new activities emerging on the market, new categories of service activities.
Keywords
PKD 2025, PKD amendment, new PKD, classifications
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Speaker bio:
Tomasz Sekuła na co dzień zarządza licznymi procesami, w tym m.in.: prowadzeniem badań statystycznych, przetwarzaniem danych z administracyjnych źródeł danych, a także analizą danych statystycznych. Posiada wieloletnie doświadczenie w projektowaniu metodologii badawczych dla organizacji non-profit. Jest autorem publikacji opisujących potencjał społeczno-ekonomiczny podmiotów ekonomii społecznej, role sektora w świadczeniu usług społecznych. Uczestniczył w przygotowaniu rachunku satelitarnego ekonomii społecznej dla Polski 2018. W zakresie jego doświadczenia zawodowego znajduje się również opiniowanie metodologii monitorowania rozwoju podmiotów ekonomii społecznej na poziomie krajowym i regionalnym.
Ukończył studia na Uniwersytecie Jagiellońskim na kierunkach politologia i prawo.
Abstract:
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Objective
The aim of this study is to present the role of reintegration units in preventing social exclusion in Poland between 2015 and 2023. These units implement social and professional reintegration services targeted at long-term unemployed individuals, persons with disabilities, people leaving penitentiary institutions, and the homeless. Their operation was strengthened by the Act on social economy of 2022, which defined their status within the social economy sector and assigned them a key role in implementing the objectives of the National Programme for the Development of Social Economy.
Methods
W analizie wykorzystano dane pochodzące wyłącznie ze źródeł administracyjnych: systemów informacyjnych urzędów wojewódzkich, Ministerstwa Rodziny, Pracy i Polityki Społecznej oraz Państwowego Funduszu Rehabilitacji Osób Niepełnosprawnych. Wyniki W 2023 r. działało 1246 jednostek reintegracji społeczno-zawodowej – o 17 mniej niż rok wcześniej, ale o 57 więcej niż w 2015 r. W ciągu 2023 r. z usług reintegracji społeczno-zawodowej skorzystało blisko 49,0 tys. osób zagrożonych wykluczeniem społecznym, tj. o 2,1% więcej niż w 2022 r. W latach 2015-2023 ich liczba wzrosła o 21,6%. Działalność prowa
Results
In 2023, 1,246 units providing social and professional reintegration services were active—17 fewer than in 2022, but 57 more than in 2015. Nearly 49,000 individuals at risk of social exclusion benefited from reintegration services in 2023, representing a 2.1% increase compared to 2022 and a 21.6% increase compared to 2015. Most of the entities focused on activating people with disabilities—733 occupational therapy workshops and 141 vocational activity establishments.
Conclusions
Reintegration units play an important role in preventing social exclusion by supporting individuals at risk of marginalisation in returning to the labour market and active social life. Ongoing monitoring of reintegration units is essential to assess the impact of their services on the economic independence of individuals at risk of social exclusion, which is crucial for effective social policy and sustainable social development.
Keywords
Reintegration units, social exclusion, social and professional reintegration services, social economy
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Speaker bio:
Magdalena Skalik, Departament Innowacji, Główny Urząd Statystyczny
Magdalena Skalik jest głównym specjalistą w Departamencie Innowacji w Głównym Urzędzie Statystycznym. Posiada wieloletnie doświadczenie w realizacji badań statystycznych, pracach metodologicznych i koncepcyjnych ze szczególnym uwzględnieniem obszaru badań regionalnych i przestrzennych. Obecnie zajmuje się m.in. analizą danych przestrzennych oraz wdrażaniem metod teledetekcyjnych do statystyki publicznej. Jej zainteresowania badawcze skupione są wokół obszaru nowych źródeł danych oraz nowych metod analiz.
Abstract:
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Objective
The aim of the presentation is to show the results of an experimental study on the spatial analysis of the effects of the flood in Poland in September 2024 and the applicability of the developed method to monitor the effects of natural disasters.
Methods
Remote sensing data, geospatial data and administrative data were used for the study. The survey consisted of 3 stages. In the first, the extent of flood-affected areas was determined on the basis of satellite imagery from the Copernicus programme (Sentinel 2). In the second stage, address points were assigned to the delineated flood zone extents (source: National Population and Housing Census 2021), and then data on persons and buildings from the integrated administrative database ('List of Persons for Experimental Study') were assigned to the address points.
Results
Linking data from such a variety of sources made it possible to obtain, for the areas actually affected by the floods, information such as the population and its demographic characteristics, employed persons, economic entities, farms, buildings and their age, and others. For the purpose of performing spatial analyses, the data were aggregated to the municipality, census area and district. The talk will present the main conclusions of these analyses and detailed statistics for several of the most affected municipalities.
Conclusions
The developed data integration method is a complex process, in which the main goal at each stage is to ensure high data quality (including coherence and comparability). At the same time, it provides great opportunities to prepare, in a relatively quick way, spatial analyses of the extent and effects of floods, as well as other types of natural disasters.
Keywords
Earth Observation methods, remote sensing, geospatial data, administrative data, flood
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Speaker bio:
Tymoteusz Strojny - statystyk zatrudniony w Ośrodku Metodologii Badań Ludnościowych Urzędu Statystycznego w Poznaniu. Ukończył studia licencjackie z informatyki i ekonometrii na Uniwersytecie Ekonomicznym w Poznaniu. Zawodowo koncentruje się na metodologii integracji danych
Abstract:
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Objective
Development and release of a universal, error-tolerant tool (package) for record blocking that minimizes the number of comparisons in entity resolution procedures without sacrificing matching accuracy, especially under conditions of missing identifiers and low data quality.
Methods
Approximate Nearest Neighbours, Graph indexing, record blocking
Results
Development of a package that provides high recall while achieving a high reduction of pairs required for comparison.
Conclusions
The package is a tool suitable for use in integrating data from administrative registers for the purpose of population size estimation. A scientific article describing the proposed method is currently under review in the journal SoftwareX.
Keywords
record linkage, deduplication, approximate nearest neighbours, official statistics
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Speaker bio:
Prof. dr hab. Mirosław Szreder - jest profesorem nauk ekonomicznych (od 2005 r.), specjalizującym się w rozwoju i zastosowaniach metod statystyki matematycznej w problematyce ekonomicznej i społecznej. Dużą popularność zdobyły dwa wydania książki autorstwa M. Szredera pt. "Metody i techniki sondażowych badań opinii" (PWE, 2004 i 2010). Jest ponadto autorem ponad 200 innych prac naukowych, a także wielu tekstów popularyzujących statystykę, m.in. w dzienniku "Rzeczpospolita", w tygodnikach "Polityka" i "Tygodnik Powszechny", a także w "Biuletynie Polskiego Towarzystwa Ekonomicznego".
W latach 2002-2008 oraz 2016-2024 pełnił funkcję Dziekana Wydziału Zarządzania Uniwersytetu Gdańskiego. W latach 2012-2016 był w Uniwersytecie Gdańskim Prorektorem ds. rozwoju i finansów. Od kilkunastu lat jest członkiem Komitetu Statystyki i Ekonometrii PAN, a obecnie także przewodniczącym Naukowej Rady Statystycznej na kadencję 2025-2029.
Abstract:
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Objective
The aim of the study is to provide a description of the actions that statisticians should take in order to, on the one hand, more fully utilize the potential of statistical inference in the era of big data and AI and, on the other hand, to make statistics users more aware of the inherent elements of uncertainty present in statistical inference.
Methods
The method used is a critical analysis of the literature and research studies that contain elements of statistical inference. A creative reflection on the practice of statistical research in the context of the groundbreaking work of Ronald Fisher Statistical Methods for Research Workers” published in 1925 was also mentioned.
Results
Discussions on the dilemmas related to the category of statistical significance held in the scientific community worldwide is a consequence of the incomplete consideration of model assumptions in the practice of statistical inference and of assigning a decisive significance to a single sample study in the context of the universal goals of scientific research.
Conclusions
With respect to the practice of testing statistical hypotheses, we postulate the use of the the Bayesian approach as complementary to the classical approach inextricably linked to Ronald Fisher.
Keywords
statistical inference, uncertainty, model assumptions, big data, scientific research
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Speaker bio:
Jolanta Szutkowska - jest mgr ekonomii. Ukończyła Wydział Ekonomiczno-Społeczny w Szkole Głównej Planowania i Statystyki - obecnie Szkoła Główna Handlowa w Warszawie oraz podyplomowe Studium dotyczące funkcjonowania Unii Europejskiej w Krajowej Szkole Administracji Publicznej. To osoba o wszechstronnych zainteresowaniach i spojrzeniu interdyscyplinarnym na zagadnienia statystyki publicznej co wynika z jej bogatego doświadczenia zawodowego. Podczas rozwoju kariery zawodowej w służbie statystycznej zajmowała się rozwojowymi i innowacyjnymi zagadnieniami z zakresu: statystyki kosztów pracy i wynagrodzeń, metodologii i jakości badań statystycznych a obecnie jako Naczelnik Wydziału Rozwoju i Innowacji odpowiada za działania rozwojowe i wizerunkowe w statystyce handlu i usług. Była członkiem różnych grup roboczych i zadaniowych Eurostatu i ONZ. Jest autorką wielu artykułów opublikowanych w Wiadomościach Statystycznych, które popularyzują wiedzę o statystyce publicznej, w tym artykułu futurologicznego przedstawiającego wizję rozwoju statystyki publicznej za 100 lat. Czas wolny wypełnia jej kontakt z naturą, książki, parapsychologia oraz numerologia.
Abstract:
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Objective
Artificial Intelligence enters into official statistics. However, it is not a miraculous invention that makes every work immediately perfect. To cooperate with AI, you need to have expert knowledge in the given field of statistics, have a vision, the ability to write prompts, algorytms and know how to combine them synergistically to obtain measurable effects and avoid the traps of AI hallucinations. How to do this is the subject of the paper.
Methods
The methodology of the approach to work with AI was based on the principles, methods and techniques presented in the publication 'Modern technologies and new data sources in inflation measurement' from 2022, edited by Jacek Białek, Mieczyslaw Klopotek and Tomasz Panek. The paper presents practical issues related to the use of AI techniques in inflation measurement, with attention paid to the occurrence of certain barriers and limitations affecting the quality of statistical processes and obtained statistical data.
Results
The paper discusses the challenges that exist in the area of trade and services. It defines what AI is and how it can help in the conducting of statistical surveys. It presents the advantages and disadvantages of AI application when using scanned data and scrapped data in measuring CPI/HICP inflation. Among the factors influencing the quality of work with AI, attention was paid to, among others, the role of critical thinking and its importance in achieving statistical goals.
Conclusions
Thanks to AI, we can use the data potential in a more optimal way from a diverse sources ecosystem. However, the key issue is always the relevance of these data to the construction of strategies or state policies.Therefore, each result that we obtain from the work with AI must be assessed by a statistician in terms of its consistency with methodological and qualitative requirements of the standards of official statistics.Such a rational approach can protect us from production of artificial results by AI that we are unable to interpret on the basis of available statistical knowledge.
Keywords
Artificial Intelligence, machine learning, data scanning, data scraping, critical thinking
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Speaker bio:
mgr Magdalena Święcka - pracownik GUS od ponad 20 lat, główny specjalista w Departamencie Studiów Makroekonomicznych i Finansów. Absolwentka kierunku Metody Ilościowe i Systemy Informacyjne SGH (2002 r.) oraz studiów podyplomowych Rachunkowości i Finanse Przedsiębiorstwa SGH (2003 r.). Posiada doświadczenie zawodowe w zakresie badania koniunktury gospodarczej oraz obsługi grantów w tym zakresie ze środków Komisji Europejskiej. Współautorka publikacji "Co warto wiedzieć o koniunkturze gospodarczej?" (2024 r.)
Abstract:
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Objective
The paper presents methodological aspects of BTS, its development as well as use of data for additional analyses and applications. Additional elements include the impact of war in Ukraine on the situation of enterprises in Poland and rapid structural diagnosis of macroeconomic processes at micro level (Mic-Mac). Moreover, the results of additional work using data from the survey will also be presented (output gap, employment gap, but also business cycle indicator or analysis of business cycles for the main economies of the world and the EU, included in the annual Macroeconomic Report).
Methods
Additional sets of questions are included in the standard BTS. Initially, they concerned the COVID-19 pandemic, then this issue was replaced by questions concerning the war in Ukraine. Currently, the additional module includes questions on basic macroeconomic processes: investments, labour market, price developments, which provide – rare in official statistics – behavioural aspects of companies` decision-making. With the use of data from the survey as well as those in the field of business climate analyses, additional elements used in other studies and analyses are also developed.
Results
Data gathered from these BTS extensions provide – together with the results of a standard part of the survey – information on the current assessments of the impact of the war in Ukraine on business activities as well as up-to-date key economic issues. The first results were presented within a few days after the survey was carried out in very detailed cross-sections.
Conclusions
Due to its scale, subject matter and level of detail, the survey along with its developmental elements are a source of quick information on the consequences of emergency situations, selected aspects of business activity or key macroeconomic processes from the company`s perspective. The survey results allow the provision of additional analytical information on important phenomena including the cyclical position of the economy, output gap or labour hoarding. Further developments are planned, which will gradually transform the survey into a comprehensive tool for multidimensional economic diagnostics.
Keywords
business tendency, factors limiting activity, output gap
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Speaker bio:
Michał Taracha - asystent badawczy w Instytucie Statystyki i Demografii Kolegium Analiz Ekonomicznych Szkoły Głównej Handlowej (SGH) w Warszawie. Doktorant Szkoły Doktorskiej SGH w Warszawie w dyscyplinie ekonomia i finanse w zakresie ekonomii. Absolwent studiów magisterskich w SGH w Warszawie na kierunku metody ilościowe w ekonomii i systemy informacyjne ze specjalnością modelowanie ekonometryczne w biznesie.
Jego publikacje i zainteresowania badawcze obejmują ekonometryczną analizę konsekwencji społecznych pandemii COVID-19, takich jak problem wykluczenia społecznego, zmian jakości życia czy też zmian sytuacji finansowej. Jego prace są ponadto skoncentrowane na kwestiach powiązanych z rynkiem pracy (m.in. elastyczności zatrudnienia i politykach rynku pracy), dzietnością, a także na analizie rezyliencji na poziomie regionalnym przy wykorzystaniu metod ekonometrii przestrzennej.
Członek zespołu w projektach grantowych finansowanych ze środków Komisji Europejskiej oraz Ministerstwa Rodziny, Pracy i Polityki Społecznej:
- "FutuRes - Towards a Resilient Future of Europe" (2023-obecnie);
- "Non intended health, economic and social effects of the COVID - 19 epidemic control decisions: Lessons from SHARE (SHARE-COVID19)" (2021-2024);
- "Wsparcie realizacji badań panelowych osób w wieku 50 lat i więcej w międzynarodowym projekcie Survey of Health, Ageing and Retirement in Europe (SHARE)" (2021-2022).
Uczestnik projektów badawczych:
- "Wpływ wahań cyklicznych na dystrybucję dobrobytu i szczęścia" (projekt finansowany przez Narodowe Centrum Nauki);
- "Trends and determinants of extending working life" (projekt finansowany w ramach grantu RID LEAD);
- "Indeksu Zdrowych Miast" - w ramach czterech edycji jako przedstawiciel obszaru "Infrastruktura" (projekt organizowany m.in. przez grupę LuxMed, o patronacie m.in. Ministerstwa Zdrowia i Ministerstwa Sportu i Turystyki);
- Zintegrowana Platforma Analityczna (projekt finansowany przez Ministerstwo Cyfryzacji).
Finalista międzynarodowego konkursu ekonometrycznego dla studentów i doktorantów "Econometric Game 2024" organizowanego przez Uniwersytet w Amsterdamie. Uczestnik I edycji Programu Młody Naukowiec SGH (2019-2020). Autor 13 publikacji naukowych (opublikowanych m.in. w ramach Springer Nature) i aktywny uczestnik 13 międzynarodowych konferencji naukowych (27. edycji Nordic Congress of Geronbtology, 30. International Population Conference lub 59. edycji ERSA Congress). Od 2022 roku sekretarz czasopisma naukowego "ASK: Research and Methods" wydawanego przez Ohio State University we współpracy z Instytutem Filozofii i Socjologii Polskiej Akademii Nauk. W latach 2019-2020 przewodniczący Studenckiego Koła Naukowego Geografii Ekonomicznej i Badań Regionalnych SGH w Warszawie.
Abstract:
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Objective
Studies on resilience in developmental psychology, demography, sociology and economics show that current adaptability in the face of shocks depends on factors experienced across life stages. This study aims to assess how the optimality of life trajectories (calculated for ages 20–50) affects quality-of-life changes during the pandemic among people aged 50+, compared to the influence of other socio-demographic characteristics.
Methods
Firstly, the Needleman–Wunsch algorithm was used to perform the sequence analysis. Each sequence contained yearly elements representing one of the 33 socio-economic situations from SHARE Wave 7. Secondly, the results of sequence analysis were treated as a predictor of changes in life quality during the pandemic (change in the CASP index between the period of 2015–2017 and 2022), using multilevel logit models and partially proportional odds models with clustered standard errors.
Results
Belonging to the quintile group characterised with the most financially optimal life paths was associated with a 7.3-percentage-point lower risk of quality-of-life decline during the pandemic, compared to the least optimal group. The effect of a one-standard-deviation change in life trajectory alignment was 4-5 times lower than a one-standard-deviation change in loneliness or depression levels (measured with a short R-UCLA scale and the EURO-D scale). This effect was similar to the one-standard-deviation change in education level.
Conclusions
The effect of favourable life trajectories aligns with the notion of resilience and relates to the literature on developmental psychology (Waters and Sroufe, 1983). The Needleman-Wunsch algorithm has been used in social sciences since the 1980s and more recently in research based on the SHARE data. This study stands out by the thorough computation of substitution costs between sequence elements, with a substitution cost matrix based on dissimilarities between respondent groups calculated using a modified Gower metric.
Keywords
SHARE, resilience, sequence analysis, COVID-19, multilevel analysis
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Speaker bio:
Tomasz Tokarski - Katedra Ekonomii Matematycznej Uniwersytetu Jagiellońskiego (kierownik).
Zainteresowania: ekonomia matematyczna, teoria wzrostu gospodarczego. Promotor 9 doktoratów.
Abstract:
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Objective
The aim of the study is to construct a macroeconomic model describing the impact of armaments on the dynamics of basic macroeconomic variables in the economy.
Methods
The model uses elements of the theory of differential equations and numerical methods,
Results
The model allows for simulations of military production growth paths mimicking the arms race process, for example during the Cold War between the USA and the USSR or between North and South Korea.
Conclusions
The model can be extended as a multi-equation econometric model, and the estimates of its parameters can describe actually functioning economies.
Keywords
Solow model, arms race, differential equations, numerical methods
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Speaker bio:
Michał Urbas - socjolog, doktor nauk społecznych. Zawodowo związany z Urzędem Statystycznym w Krakowie. Pracuje w Ośrodku Statystyki Zdrowia i Ochrony Zdrowia, gdzie zajmuje się badaniem działalności leczniczej zakładów lecznictwa uzdrowiskowego oraz stacjonarnych zakładów rehabilitacji leczniczej. Interesuje się procesami zachodzącymi we współczesnym społeczeństwie, w szczególności zmianami demograficznymi i starzeniem się ludności. Z pasją śledzi rozwój lecznictwa uzdrowiskowego, jako dopełnienia procesu leczenia i trwałego elementu turystki uzdrowiskowej.
Abstract:
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Objective
Primary health care (PHC) is the cornerstone of the health care system and plays a key role in ensuring the availability of medical services, the coordination of patient care and the implementation of preventive measures. The aim of the presentation is to illustrate the importance of the PHC by analysing selected statistical data on e.g. consultations in the PHC, quality of services as assessed by patients, accessibility to outpatient health services and reasons for abandoning appointments with primary care physicians, as well as the staff resources of family medicine specialists.
Methods
The paper is based on the results of a nationwide statistical survey on the activities of medical facilities and the use of health care services in households. They provide information on the number of consultations provided in PHC departments and infirmaries by age group of outpatients, an assessment of the course of visits to the primary care physicians or main reasons for unmet needs for medical examination or treatment.
Results
The data collected show that in 2023, there was an average of almost five consultations per capita provided to outpatients in the PHC, and about 3% of household members did not use the services of a primary care physicians, despite the need.
Conclusions
The PHC is the most accessible form of health care, so it is important to emphasise the need for further investment in its development, especially in the context of the observed ageing population. The PHC provides the first line of contact between the patient and the health system, leading to early detection and treatment of diseases, resulting in improved population health, system efficiency and reduced medical expenditure in the long term.
Keywords
primary health care, health care system, PHC, health care statistics, an outpatient department and infirmaries of the primary health care
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Speaker bio:
Dr inż. Katarzyna Widera ukończyła studia magisterskie Matematyka na Wydziale Matematyki, Fizyki i Chemii Uniwersytetu Opolskiego oraz studia inżynierskie Zarządzanie i marketing w Instytucie Zarzadzania Politechniki Opolskiej. Stopień doktora nauk ekonomicznych o specjalności statystyka i ekonometria uzyskała na Wydziale Zarządzania Uniwersytetu Ekonomicznego w Katowicach. Jest nauczycielem akademickim związanym z Politechniką Opolską. Obecnie jest kierownikiem Katedry Ekonomii, Finansów, Badań Regionalnych oraz Metod Ilościowych na Wydziale Ekonomii i Zarządzania. Prowadzi zajęcia z matematyki (w ekonomii i zarządzaniu), ekonometrii, statystyki opisowej, wnioskowania statystycznego oraz podstaw metodologii badań. Promotor prac licencjackich i magisterskich.
W latach 2012 - 2016 z mianowania Ministra Kultury i Dziedzictwa Narodowego pełniła funkcję dyrektora instytucji naukowo - badawczej PIN - Instytutu Śląskiego w Opolu.
Od 2019 roku jest konsultantem w Urzędzie Statystycznym w Opolu, najpierw w Ośrodku Badań Regionalnych, potem w Ośrodku Statystyki Cen, a obecnie w Dziale Inżynierii Danych. Współautorka zeszytu metodologicznego pn. Indeksy cen eksportu i importu, opracowanego wraz Głównym Urzędem Statystycznym.
Członek komitetu redakcyjnego czasopisma naukowego Journal of Sustainable Mining i recenzent statystyczny w czasopiśmie Economics & Sociology. Autor i współautor licznych artykułów naukowych, w tym w Scientific Report i Wiley. W pracy naukowej zajmuje się zastosowaniem metod ilościowych w zrównoważonym energetycznie zarządzaniu regionem w aspekcie środowiskowym.
Abstract:
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Objective
The purpose of the study is to define a representative based on the available data. Validation of the transaction data set from selected travel agencies and indication of the characteristics of the representative are the stages of the analysis. They are the starting point for calculating the price index for tourism.
Methods
The source data comes from the administrators. The challenge in this study is the verification of the transactional data set. It results from the non-uniform characteristics of information about products / offers obtained from data providers. The characteristics of individual offers differ in the number of categories and specifications. The high variability of the product offer over time results from the nature of the data, which is characterized by seasonality over a period of one year. The problem is also the lack of data in the time series – seasonality for a given offer.
Results
The statistical analysis carried out, both with the use of statistical tests and an attempt to build and estimate the hedonic model, made it possible to indicate potential representatives for the calculation of the price index.
Conclusions
When setting the threshold of importance for the weights from the data providers, it is possible to indicate a representative associated with a group of tourist offers for the discussed direction or destination. Preliminary calculations of the price index of tourist services indicate a high volatility of its value.
Keywords
price index, weight for offer, weight for representative, destination, hedonic
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Speaker bio:
Robert Wieczorkowski received his PhD degree in mathematics from Institute of Mathematics, Warsaw University of Technology, Poland, in 1995. Currently, he is a consultant at Department for Innovation, Statistics Poland. His main areas of interest include: application of survey sampling theory in social, business and agricultural surveys, computational statistics and application of numerical methods in socio-economic studies. Dr Robert Wieczorkowski is an co-author of many methodological publications published by Statistics Poland.
Abstract:
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Objective
Item count techniques (ICTs) are statistical methods of indirect questioning that are broadly used by applied researchers in surveys with sensitive questions. These techniques require the use of some control variable while the variable under study is not directly observable. The aim of the paper is to examine the robustness of various item count models against some assumption violations.
Methods
To analyze the problem of robustness of item count models we conduct a comprehensive Monte Carlo simulation study. We introduce different violations in data distribution and examine the consequences for the efficiency of the estimation of the sensitive population proportion.
Results
For small departures from the idealized theoretical distribution of the control variable, estimators obtained by ML formulas via the EM numerical algorithm are still either more efficient or equally efficient as MM estimators in all considered cases (despite the fact that MM estimators do not depend on the distribution of the control variable in item count models). For moderate departures from the theoretical distribution of the control variable, in most cases the results are similar but there are several exceptions.
Conclusions
The parametric approach broadly used in ICTs to address the latent variable has many advantages in terms of estimation. However, it also introduces some problems regarding theoretical assumptions about the distribution of the control variable. We have analyzed the robustness of various item count models against departures from these theoretical assumptions. The presented analysis is of special importance for further applications of item count models.
Keywords
sensitive questions, item count techniques, latent variable, robustness, EM algorithm
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Speaker bio:
Dr hab. Barbara Więckowska - matematyk, statystyk i nauczyciel akademicki związany z Uniwersytetem Medycznym im. Karola Marcinkowskiego w Poznaniu. Pełni funkcję adiunkta w Katedrze Informatyki i Statystyki, gdzie pracuje od 2004 roku. Jest absolwentką matematyki na Uniwersytecie Adama Mickiewicza w Poznaniu. Stopień doktora oraz doktora habilitowanego uzyskała na Uniwersytecie Medycznym w Poznaniu. Aktywnie działa zarówno w sferze akademickiej, jak i wdrożeniowej. Pomysłodawczyni i współautorka oprogramowania PQStat (od 2010 r.) - narzędzia do obliczeń statystycznych, wykorzystywanego przez większość polskich uczelni i instytutów naukowych. Popularyzatorka statystyki - prowadzi kanał PQStat na YouTube upowszechniając wiedzę z zakresu analizy danych. Autorka metody U-smile (Explainable Machine Learning) - do wizualizacji rezultatów działania binarnych modeli uczenia maszynowego
Abstracts:
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Objective
The aim of this presentation is to introduce the U-smile Likelihood Evaluation method (U-smile rLR), which allows for assessing the predictive usefulness of a variable in binary classification without the need to define a decision threshold. The method separately evaluates prediction quality for events and non-events, offering more interpretable insights than classical approaches.
Methods
The U-smile method is based on the decomposition of the relative Likelihood Ratio (rLR) and its visualization using U-smile plots. It enables the identification of variables with asymmetric predictive impact across classes and assessment of their predictive strength. The method was applied to the Heart Disease dataset, with random (non-informative) variables used as a reference.
Results
The analysis showed that variables with high rLR values produce distinct 'smiles' on U-smile plots, which are easy to interpret visually. The plots allowed us to determine which group (event or non-event) contributed to the statistical significance of the Likelihood Ratio test. The findings were consistent with those based on ROC curves. The method proved robust against non-informative random variables and predictive asymmetry.
Conclusions
U-smile is an effective, threshold-free method for evaluating predictive variables that complements ROC and calibration plots. It provides a graphical and statistical assessment of predictive strength and class asymmetry, in line with Explainable ML principles. Its intuitive visual format facilitates result communication, even to non-technical stakeholders.
Keywords
binary classification, rLR, U-smile, predictive model evaluation, model interpretability
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Objective
The aim of the study was to develop and evaluate the U-smile method, designed to visualize and quantitatively assess the usefulness of new predictors in binary classification models, with particular emphasis on scenarios involving imbalanced data.
Methods
The U-smile method – comprising U-smile plots and the BA (Absolute Change), RB (Relative Change), and I (Net Reclassification Index) coefficients – was used to analyze the impact of new predictors in binary classification models. The study was conducted using real-world data from the Heart Disease dataset and simulated data, incorporating various class imbalance scenarios.
Results
The U-smile method effectively identifies and visualizes the contribution of new predictors to classification improvement, even under data imbalance conditions. The introduction of a three-level approach and the use of the I coefficient as a weighting factor in BA and RB plots enhance the interpretability of results.
Conclusions
The U-smile method provides a valuable tool for assessing the usefulness of new predictors in binary classification models, especially when data are imbalanced. Its application can support variable selection processes and improve the interpretability of predictive models across various fields, such as medicine or social sciences.
Keywords
binary classification, U-smile method, ROC curve, likelihood-ratio test, imbalanced data
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Speaker bio:
Prof. dr hab. Dorota Witkowska - jest absolwentką Wydziału Ekonomiczno-Socjologicznego UŁ (kierunek: Informatyka i cybernetyka ekonomiczna), który ukończyła w 1980 r. W 1985 r. obroniła na Uniwersytecie Łódzkim pracę doktorską, w 1993 r. uzyskała stopień doktora habilitowanego nauk ekonomicznych (ekonometria), a w 2003 r. otrzymała tytuł naukowy profesora nauk ekonomicznych.
Po studiach, realizując swoje zainteresowania badawcze, podjęła pracę w Instytucie Ekonometrii i Statystyki Uniwersytetu Łódzkiego, od 1992 r. była zatrudniona w Instytucie Zarządzania Politechniki Łódzkiej, w latach 2004 - 2014 w Katedrze Ekonometrii i Statystyki Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie, a poczynając od 2014 r. do chwili obecnej pracuje w Katedrze Zarządzania Finansami Przedsiębiorstwa Uniwersytetu Łódzkiego.
W latach 1985-86 i 1996 była stypendystką Fulbrighta w Princeton University i Pennsylvania University (USA). W 2012 r. była wykładowcą w Georg August University w Getyndze (Niemcy), a w 2013 r. realizowała swoje badania w tym uniwersytecie w ramach stypendium DAADu. W latach 2015 - 2020 r. była visiting professor w Shanghai Finance University, Shanghai Lixin Univesity of Accounting and Finance w Szanghaju i Shandong University of Finance and Economics w Jinanie (Chiny), a od 2019 r. pełni podobną funkcję w University of Johannesburg (RPA).
W czasie 45-letniej pracy naukowej opublikowała ponad 300 opracowań naukowych w kraju i za granicą, w tym ponad 30 monografii i podręczników akademickich.
Abstract:
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Objective
The purpose of the empirical study presented in the paper is to compare linear discriminant models constructed on the basis of diagnostic variables selected using different techniques for their selection, and to indicate which bankruptcy prediction model proved to be the best from the point of view of the multivariate evaluation of model accuracy.
Methods
The study applied a quantitative approach using discriminant analysis to identify companies at risk of bankruptcy. The effectiveness of the models was evaluated using Wilks` lambda statistic, AUC values and classification accuracy of the models. A number of methods were used to select discriminating variables: arbitrary selection of variables based on the literature and using GPT Chat (version 3.5), one-way analysis of variance (ANOVA) and stepwise forward selection, Hellwig`s method of selecting diagnostic variables, t-statistics, backward stepwise method. The source of the data was the EMIS
Results
Eight discriminant models based on different methods of selecting diagnostic variables were evaluated. The highest classification efficiency (both in the learning and test sample) was achieved by model D, built using a two-step method (significance test of mean differences + progressive selection). Models F (based on isolated variables selected by the Hellwig method) and H (backward method) also had high classification efficiency. In contrast, the worst results were obtained by model A, based on arbitrary selection of variables. AUC indices for most models (except for model A) exceeded the val
Conclusions
The results of the study indicate that appropriate independent variable selection techniques play an important role in the process of building discriminant models. The study also makes an important methodological contribution, challenging the common belief that Wilks` lambda statistic is highly useful in assessing the quality of classification models. The results show that the analysis of classification performance should be the main point of reference when evaluating discriminatory models.
Keywords
diagnostic variable selection, linear discriminant function, bankruptcy prediction, Euclidean distance
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Speaker bio:
Anna Wójcik is currently employed in the Statistical Office in Rzeszów. Academically, she is affiliated with the Faculty of Economics and Finance at the University of Rzeszów, where she has begun work on her doctoral dissertation in the area of information asymmetry in the labor market.
She has experience working with students at the University of Rzeszów (2016-2018), where she provided career counseling at the Career Services Office and was involved in the management of an academic journal. She also has experience as a career advisor in projects aimed at the activation of individuals at risk of social exclusion.
She has collaborated with the Development Foundation "Dobre Życie" ("Good Life"), conducting development workshops for youth and performing analyses and evaluations of projects funded by national and European sources. Between 2012 and 2015, she conducted university-level courses in pedagogy, general didactics, drama, and knowledge management at the University of Rzeszów.
Abstract:
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Objective
The purpose of the presentation is to highlight the information asymmetries present in the Polish labor market and their potential impact on the difficulty of choosing a career development path.
Methods
To analyze the supply side of the labor market, a pilot survey was conducted among students of a technical high school in Rzeszów regarding their career choices. For the analysis of the demand side of the labor market, web scraping was applied to two job offer portals along with text mining techniques.
Results
The pilot study showed that, in most cases, young people do not know what profession they want to pursue in the future. They primarily acquire knowledge about the labor market on their own or through conversations with their parents. A comparison of job offer portals revealed that the image of the labor market varies significantly between platforms.
Conclusions
The Polish education system lacks a coordinated and well-thought-out system for guiding career development. The abundance and diversity of available labor market information do not make this task easier. A modern career counselor must adopt new techniques for collecting and integrating data in order to obtain a coherent and comprehensive picture of the labor market and to perform their profession reliably.
Keywords
labor market, career counseling, web scraping, text mining
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Speaker bio:
Sebastian Wójcik, PhD in Mathematics. Head of the Mathematical Statistics Division at the Statistical Office in Rzeszów, Statistics Poland, and lecturer at the University of Rzeszów. His research interests include statistics, machine learning, functional equations and inequalities.
Abstracts:
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Objective
The purpose of the presentation is to highlight the information asymmetries present in the Polish labor market and their potential impact on the difficulty of choosing a career development path.
Methods
To analyze the supply side of the labor market, a pilot survey was conducted among students of a technical high school in Rzeszów regarding their career choices. For the analysis of the demand side of the labor market, web scraping was applied to two job offer portals along with text mining techniques.
Results
The pilot study showed that, in most cases, young people do not know what profession they want to pursue in the future. They primarily acquire knowledge about the labor market on their own or through conversations with their parents. A comparison of job offer portals revealed that the image of the labor market varies significantly between platforms.
Conclusions
The Polish education system lacks a coordinated and well-thought-out system for guiding career development. The abundance and diversity of available labor market information do not make this task easier. A modern career counselor must adopt new techniques for collecting and integrating data in order to obtain a coherent and comprehensive picture of the labor market and to perform their profession reliably.
Keywords
labor market, career counseling, web scraping, text mining
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Objective
The study aim to determine the influence of wolves on the actual decline in the cattle population in the Podkarpacie region in relation to other factors.
Methods
The research is conducted on the basis of tables of conflict situations kept by the communes in which conflicts between wolves and humans are most visible.
Results
Behaviour patterns of wolves are derived in the long-term, as well as the elements that significantly influence the worsening of the decline in the cattle population in Podkarpacie are determined.
Conclusions
Wolves are species that, when given the choice between obtaining food in the wild forests or obtaining animals kept on farms, chose the latter. There may be many reasons, including the lack of game that they hunt in the forests.
Keywords
wolf, Subcarpathia, ruminants, population decline
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Speaker bio:
Dorota Wyszkowska, dr hab., prof. UwB, zastępca dyrektora Urzędu Statystycznego w Białymstoku, pracownik Uniwersytetu w Białymstoku (Wydziału Ekonomii i Finansów, Katedry Finansów), autorka lub współautorka blisko 100 publikacji dotyczących finansów samorządowych, funduszy europejskich, zielonych finansów, jakości życia i gospodarki senioralnej, autorka lub współautorka prac badawczych na rzecz Banku Światowego, jednostek samorządu terytorialnego, organizacji pozarządowych.
Abstract:
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Objective
In many local government financial supply systems, shares in state taxes are an important source of revenue. Although they do not have taxing power over them, they are counted among the fiscally efficient sources of revenue for local government units (LGUs). Therefore, it is reasonable to consider the evaluation of this source of revenu for territorial self-government units, particularly in light of the legal changes that took effect in Poland on 1 January 2025. This presentation aims to determine the level of diversity among Polish communes in terms of their income from PIT participation and
Methods
Descriptive statistical measures and graphical presentation methods will be employed to evaluate the level of diversification of the analysed source of revenue for territorial self-government units. Conversely, econometric modelling will be employed to identify the determinants of fiscal efficiency. The data used in the analysis comes from the Ministry of Finance's resources and official statistics (Local Data Bank). The Statistical Geoportal will be used to prepare the presentation.
Results
Although shares in the PIT are quite significantly differentiated spatially, they constitute a fiscally significant source of revenue for territorial self-government units. Small rural municipalities (predominantly agricultural) receive significantly less revenue from PIT than urban municipalities or cities with county rights. According to the simulation, the changes introduced on 01.01.2025 will lead to a reduction in these disparities, although some units will still require significant subsidies under the existing income equalisation schemes.
Conclusions
The results presented here can be used to evaluate the fiscal efficiency of the analysed revenue source of LGUs. They may also provide a basis for further in-depth analyses of the importance of this source of revenue in shaping the financial self-reliance of LGUs.
Keywords
tax sharing, LGU's own revenue, financial self-reliance, fiscal efficiency determinants of PIT share
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Speaker bio:
Bohdan Wyżnikiewicz - dr nauk ekonomicznych (UW 1984), publicysta i komentator gospodarczy, były prezes GUS i doradca prezesów GUS, prezes Instytutu Prognoz i Analiz Gospodarczych Fundacja Naukowa (IPAG), członek Naukowej Rady Statystycznej i Komisji Metodologicznej GUS, członek Komitetu Prognoz PAN. Pracował w Europejskiej Komisji Gospodarczej ONZ. Był ekspertem Banku Światowego i członkiem komitetu doradczego CEIES w Eurostacie oraz członkiem organów doradczych kilku ministerstw i GPW. Wykładowca akademicki. Autor ponad 200 publikacji naukowych i dwóch książek.
Abstracts:
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Objective
The aim of the paper is an attempt to outline the evolution of the income distribution of Poles in the period from the Second Polish Republic to the present day. Particular attention is paid to changes in the concentration of income, the synthetic indicator of income inequality, the indication of the income gap and not the level or value of income.
Methods
Sources of income information for the period up to the end of World War II, mostly non-statistical, are scattered and fragmentary. A method based on the analogy of income distribution in countries with a social and economic situation similar to Polish will be used. Data for the period of the People`s Republic of Poland are incomplete. Using the stylized facts approach, the likely magnitude of Gini`s income concentration indicator will be estimated. The periods of analysis include the interwar period, the German occupation, the People`s Republic of Poland and the Third Polish Republic.
Results
In each of the separate periods of the analysis, income inequality evolved for different reasons and the spatial differentiation of income is still influenced to some extent by the effects of partitions. The log-normal distribution, i.e. the natural shape of the income distribution, accompanied the market economy in the interwar period and after 1989. Between 1939 and 1989, the natural distribution of income was distorted.
Conclusions
As expected, the distribution of Poles` incomes over the past 100 years has largely depended on the economic system and significant historical upheavals, such as World War II, the change of state borders and population movements, the continuation and overthrow of the centrally planning system.
Keywords
income distribution, concentration of income. income inequality, income gap
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Objective
The aim of the paper is to draw attention to the non-existence of a separate code of professional ethics in force in Polish official statistics. Relying on international practices, i.e. standards and aspects of statistical ethics contained in the European Union`s Code of Statistical Practices and the Fundamental Principles of Official Statistics of the United Nations, seem to be insufficient. They are also not properly separated.
Methods
The methods used are based on the analysis of the content of the Code of Statistical Practices of the European Union and the Fundamental Principles of Official Statistics of the United Nations in terms of distinguishing the elements of these documents that relate to the issue of ethical principles in official statistics. Additionally, a critical analysis is conducted, aimed at pointing out certain deficits in international standards of ethics in statistics.
Results
The analysis will include a review of the practical application of basic ethical principles in official statistics. Cases of conscious or unconscious violation or circumvention of ethical principles will be cited. The risks associated with the possibility of violating these rules will be discussed. The consequences of the lack of a sense of public importance of statistical information by its creators – as a public good – for its recipients will be indicated.
Conclusions
The conclusion of the paper is the postulate to start a discussion and then work on the creation of a code of professional ethics in official statistics in Poland. Following the example of the practice and experience of several countries, I believe that the right place to develop the postulated code may be a team of independent experts or the Polish Statistical Association.
Keywords
ethics in official statistics, codes of professional ethics
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Speaker bio:
Grzegorz Zabiegły - główny specjalista z 25-letnim stażem w Ośrodku Statystyki Gospodarki Mieszkaniowej i Komunalnej w Urzędzie Statystycznym w Lublinie. Uczestnik projektów z zakresu gospodarki mieszkaniowej: "SMUP - System Monitorowania Usług Publicznych", "Pozyskanie nowych wskaźników z zakresu planowania przestrzennego i budownictwa mieszkaniowego przydatnych do oceny dostępności i jakości usług publicznych". Współautor opracowań i publikacji z zakresu gospodarki mieszkaniowej i infrastruktury komunalnej.
Abstract:
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Objective
The presentation shows the results of the work on the Building and Dwelling Database.
Methods
Data from the 2021 Population and Housing Census, data from the NOBC system (Address identification system for streets, properties, buildings and dwellings), survey B-07 – reports on residential buildings and residential units in non-residential buildings (put into use) and Attrition were used to create the database.
Results
The use of data from administrative sources and non-statistical distributed systems for statistical purposes will contribute to broadening the scope of studies and analyses carried out in the field of housing and municipal management.
Conclusions
The Building and Housing Database will comply with the EU requirements for European statistics on population and housing (ESOP) and will form the basis for building and housing censuses. Combining data from different sources will allow the creation of new, richer datasets, more fully describing the phenomena under study and enabling analysis of relationships between information that is available in separate sources.
Keywords
Housing stocks
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Speaker bio:
Dr Mariola Zalewska - jest ekspertem w dziedzinie zarządzania oraz zrównoważonego rozwoju, pracownikiem Wydziału Zarządzania Uniwersytetu Warszawskiego. Ukończyła Wydział Matematyki, Informatyki i Mechaniki Uniwersytetu Warszawskiego oraz Hautes Études Commerciales Paris.
W UW współtworzyła dwa programy studiów magisterskich:
Sustainable Development oraz Erasmus Mundus Joint Master Global Environment and
Development, znacząco rozszerzając ofertę edukacyjną UW w obszarze zrównoważonego rozwoju.
Od 2020 roku aktywnie uczestniczy w Sojuszu 4EU+, reprezentując Uniwersytet Warszawski w międzynarodowych inicjatywach akademickich. Jest także członkiem Zespołu Roboczego ds. Społecznej Odpowiedzialności Uczelni w Ministerstwie Funduszy i Polityki Regionalnej oraz Zespołu ds. Edukacji Klimatycznej w Ministerstwie Edukacji, gdzie współpracuje nad wdrażaniem treści o zrównoważonym rozwoju i klimacie w polskim systemie edukacji.
Dr Zalewska prowadzi badania nad zrównoważonym rozwojem i efektywnym wykorzystaniem zasobów, koncentrując się na pomiarze i monitorowaniu wskaźników zrównoważonego rozwoju.
Jej prace obejmują zarówno budowanie strategii, jak i ocenę wpływu działalności gospodarczej na środowisko. Szczególną uwagę poświęca opracowywaniu modeli zarządzania, analizie gospodarki o obiegu zamkniętym oraz ocenie efektywności wdrażanych polityk i innowacji w zakresie zrównoważonego rozwoju.
Abstract:
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Objective
The purpose of the study was to determine perceptions, experiences and attitudes towards sustainability micro-statements in academia, and to explore their potential as a tool to support education.
Methods
The study was exploratory in nature. Its goal was to understand the perception and potential of micro-statements as a tool to support sustainability education in academia. The online questionnaire targeted students at public universities in Poland.
Results
Respondents showed moderate familiarity with microcredentials, but at the same time high interest in their teaching potential, especially in the context of flexible learning and rapid response to labor market needs. The majority of respondents considered microcredentials to be an important or very important tool to support the development of competencies in social justice, green finance and the circular economy. The data collected also confirms the importance of interdisciplinarity, active teaching methods and cross-sector cooperation (university-business-administration).
Conclusions
Micro-credentials are seen as a valuable tool for education and communication, especially in the field of sustainability. They increase student engagement and help align competencies with labor market requirements. However, the implementation of microcredentials requires better staff preparation and integration with university programs. Universities should support their development, taking into account various forms of teaching and cooperation with the external environment.
Keywords
microcredentials, sustainable development, higher education, students
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Speaker bio:
Dr inż. Agnieszka Zgierska - Główny Urząd Statystyczny, Departament Badań Społecznych i Rynku Pracy, dyrektor.
Redaktor tematyczny czasopisma GUS i PTS "Wiadomości Statystyczne. The Polish Statistician"
Zainteresowania naukowe: rynek pracy i wynagrodzenia, demografia, prognozy demograficzne i prognozowanie zasobów pracy, dochody i warunki życia, ekonomika rolnictwa, przygotowanie i realizacja badań statystycznych, w tym badań ankietowych, spisy powszechne, doskonalenie jakości badań statystycznych.
Abstract:
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Objective
The aim is to present the work in progress at the UNECE forum and to promote the discussed topic of work quality (from the employee`s point of view).
Methods
The study is based on an expert method of labor market statisticians.
Results
The effect of the research is a discussion on the developed list of indicators measuring the quality of work.
Conclusions
A list of indicators for measuring the quality of work has been developed.
Keywords
quality of employment measurement
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Speaker bio:
Marcin Związek ukończył studia inżynierskie na wydziale Matematyki, Fizyki i Informatyki Uniwersytetu Opolskiego. Obecnie kierownik Działu Inżynierii Danych w Urzędzie Statystycznym w Opolu. Wcześniej pracował jako programista w Wydziale Informatyki tego urzędu.
Abstract:
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Objective
The purpose of the study is to define a representative based on the available data. Validation of the transaction data set from selected travel agencies and indication of the characteristics of the representative are the stages of the analysis. They are the starting point for calculating the price index for tourism.
Methods
The source data comes from the administrators. The challenge in this study is the verification of the transactional data set. It results from the non-uniform characteristics of information about products / offers obtained from data providers. The characteristics of individual offers differ in the number of categories and specifications. The high variability of the product offer over time results from the nature of the data, which is characterized by seasonality over a period of one year. The problem is also the lack of data in the time series – seasonality for a given offer.
Results
The statistical analysis carried out, both with the use of statistical tests and an attempt to build and estimate the hedonic model, made it possible to indicate potential representatives for the calculation of the price index.
Conclusions
When setting the threshold of importance for the weights from the data providers, it is possible to indicate a representative associated with a group of tourist offers for the discussed direction or destination. Preliminary calculations of the price index of tourist services indicate a high volatility of its value.
Keywords
price index, weight for offer, weight for representative, destination, hedonic
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