Abstract: AimMultidimensional unfolding allows representing both columns (e.g. products, services) and rows (e.g. customers) of the preference matrix on the same low-dimensional map (usually it’s a two or three-dimensional map). The main aim of the paper was to propose how to perform unfolding analysis for symbolic objects.MethodologyThe paper describes the possible ways of performing unfolding analysis for symbolic interval-valued data. The external unfolding is described in the details and used in the empirical part of the paper. The data (preferences and dissimilarities) were gathered by using the incomplete method of triads.ResultsThe empirical part presents an application for unfolding symbolic data to evaluate customers’ preferences, where car advertisements are used as the example. The results presented on a two--dimensional perceptual map allowed to discover seven groups of respondents with different preferences; most of them prefer Skoda, Audi, Volkswagen, and Honda advertisements to Toyota and Volvo.Implications and recommendationsThe proposed external approach for symbolic data allows to represent objects as rectangles (on two-dimensional map) or cuboids (in the case of three dimensions). The respondents are represented as points. Further work should focus on creating an algorithm that allows for the presentation of both symbolic objects and preferences expressed by respondents in the form of rectangles or cuboids.Originality/ValueThe paper presents an innovative and previously unpresented external unfolding for symbolic data. Besides that it presents how other unfolding approaches could be adapted for symbolic data. PubDate: Wed, 13 Mar 2024 00:00:00 GMT
Abstract: AimThe paper aims to propose a new estimation method for the Cholesky Multivariate Stochastic Volatility Model based on the iterated filtering algorithm (Ionides et al., 2006, 2015).MethodologyThe iterated filtering method is a frequentist-based technique that through multiple repetitions of the filtering process, provides a sequence of iteratively updated parameter estimates that converge towards the maximum likelihood estimate.ResultsThe effectiveness of the proposed estimation method was shown in an empirical example in which the Cholesky Multivariate Stochastic Volatility Model was used in a study on safe-haven assets of one market index: Standard and Poor’s 500 and three safe-haven candidates: gold, Bitcoin and Ethereum.Implications and recommendations: In further research, the iterating filtering method may be used for more advanced multivariate stochastic volatility models that take into account, for example, the leverage effect (as in Ishihara et al., 2016) and heavy-tailed errors (as in Ishihara and Omori, 2012).Originality/ValueThe main contribution of the paper is the proposition of a new estimation method for the Cholesky Multivariate Stochastic Volatility Model based on iterated filtering algorithm This is one of the few frequentist-based statistical inference methods for multivariate stochastic volatility models. PubDate: Wed, 13 Mar 2024 00:00:00 GMT
Abstract: Research backgroundThe phenomenon of low fertility in Poland is a vital subject of demographic analysis. In recent years, not only have there been changes in procreative and family models, but also in the age structure of society. This is particularly significant in the context of population ageing, which is becoming increasingly evident and brings numerous challenges such as increased burden on healthcare systems, a decrease in the active workforce, and the need to secure adequate retirement funds. Despite the desire to have children, many individuals refrain from making such a decision, and the reasons for this choice are diverse. Therefore, it was essential to conduct an analysis of the factors determining fertility in Poland, considering both the economic and social aspects. Understanding how the economic situation, labour market conditions, and changes in social structure impact on the decision-making process regarding childbearing is essential.Purpose of the paperThe objective of this article was to analyse fertility rates in Poland for the period 2004-2020. The conducted research identified the factors influencing the observed state of low generational replacement and determining their intensity.Methodology/Methods/Data sourcesThe data used in this article were sourced from the Central Statistical Office and covered the years 2004-2020. The study was based on literature concerning demography and econometrics. Three statistical methods were applied in the analysis of fertility in Poland: the Classical Method of Least Squares (CMLS) model, the Fixed Effects (FE) estimator, and the Random Effects (RE) estimator. Fertility analysis was conducted at regional level by dividing Poland into 16 administrative units (voivodeships). A panel model was employed for the analysis, and the results were subjected to Wald, Breusch-Pagan, and Hausman tests to compare the outcomes obtained from different models.FindingsThe results of the analysis indicate that the economic situation and the labour market significantly influence the decision to have children in Poland. The trend of low fertility, although showing some increase, is still characteristic of the country compared to other EU nations. The analysis of the factors determining fertility is vital for understanding the decisions of young generations of Poles regarding parenthood. PubDate: Wed, 13 Mar 2024 00:00:00 GMT
Abstract: AimIn the conducted research, profiles of seasonality in the housing market were determined, which provided an opportunity to answer two fundamental questions: what is the nature of harmonic variation in the seasonality and periodicity of the studied components of the construction process' what parameters of the ARIMA model optimally describe the construction market'MethodologyIn the conducted research, using the X13-ARIMA-SEATS model, seasonal decomposition was carried out in the various stages of the housing construction process.ResultsThe research process conducted to identify seasonal fluctuations in the housing construction market showed that harmonic fluctuation profiles can be identified on an annual basis. An analysis of seasonal fluctuations was carried out for each of the three stages of the housing construction process, while also checking how these profiles function for Poland in general, and for individual investors, and for those building apartments for sale or to rent. The study showed that the market for real estate development activity differs in its seasonal characteristics from that of individual investors.Implications and recommendationsThe conclusions obtained from the research can provide support in the decision-making process, both from a macro and microeconomic perspective. Parameterisation of the occurring fluctuations, and taking them into account in the process of developing a forecast can provide decision-making rationale in the implementation of macroprudential and financial stability policiesOriginality/ValueA novelty is in the demonstration that the residential real estate market in Poland shows different seasonal parameters, divided into the market of individual investors and investors who build apartments for sale or rent. PubDate: Wed, 13 Mar 2024 00:00:00 GMT
Abstract: The aim of this article was to analyse functional data of the number of hospitalised individuals, intensive care patients, positive COVID-19 tests, deaths and convalescents during the second wave of the COVID-19 pandemic in Poland. For this purpose, firstly the author convert data of sixteen voivodeships to smooth functions, and then used the principal component analysis and multiple function-on-function linear regression model to predict the number of hospitalised and intensive care patients due to the COVID-19 infection during the second wave of the pandemic. Finally, the results were compared with those previously obtained for the combined data of the second and third wave of the COVID-19 pandemic in Poland (Hęćka, 2023). PubDate: Mon, 11 Dec 2023 00:00:00 GMT
Abstract: The article considers the problems of young people aged 20-24 on the labour market affected by unemployment in European Union countries. Unemployment is one of the most important economic and social problems, which at the same time constitutes one of the biggest measures characterising the condition of the economy. The diversity of the economic situation in EU countries directly affects young people, an individual group of people entering the labour market and have little or no professional experience. At the same time, they are ready to start work, facing great difficulties in entering the market, influenced by socio-economic as well as demographic factors which directly and indirectly affect employment. Considering the above premise, the aim of the article was to identify the determinants of unemployment of young people aged 20-24 in the EU. The study used data from two years: 2010 and 2020, and applied multiple regression. Statistical data were taken from Eurostat databases. The study allowed to examine the dependence of the influence of individual socioeconomic as well as demographic factors on youth unemployment. The study found that the multivariate regression showed that factors related to young people's participation in education and training (including the NEET rate) relative to labour market status, as well as social inclusion, had a significant impact on the unemployment studied. Over the decade, a decrease was seen in unemployment in most EU member states, in as many as 19 countries, while the remaining eight countries showed an increase. PubDate: Mon, 11 Dec 2023 00:00:00 GMT
Abstract: The primary goal of this research was to estimate the quantile of a conditional distribution using a semi-parametric approach in the presence of randomly missing data, where the predictor variable belongs to a semi-metric space. The authors assumed a single index structure to link the explanatory and response variable. First, a kernel estimator was proposed for the conditional distribution function, assuming that the data were selected from a stationary process with missing data at random (MAR). By imposing certain general conditions, the study established the model’s uniform almost complete consistencies with convergence rates. PubDate: Mon, 11 Dec 2023 00:00:00 GMT
Abstract: The article refers to the topic of the SARS CoV-2 virus pandemic and focuses on the effect of vaccines against this virus. The relation between the administered vaccines and the development of the global pandemic is very pertinent as the problem is being faced by the whole world. The difficulty lies in the fight against the pandemic, which is the cause of the very high death rate due to the virus, and has caused a global economic crisis. Demonstrating patterns and possible anomalies between data on the number of people vaccinated and the course of the disease and the number of deaths is an important factor in raising awareness of the risk of spreading the virus. The methods presented in the second chapter are data agglomeration and the k-means method. The study compared the results obtained in six selected countries from different regions of the world and presented the most important factors influencing the development of the pandemic. The presented methodology was also the basis for a deeper discussion of the factors determining the spread of the virus and can be an introduction to the analysis of time series. At the same time, it enabled the creation of patterns related to the studied phenomenon (for selected countries) defining local factors contributing to the spread of the disease and determining the effectiveness of the vaccines administered in them. The empirical analysis was conducted on the basis of data available in the electronic scientific publication https://ourworldindata.org/. The visualisations were made in the Tableau program, and the cluster analysis was carried out using the Statistica package. PubDate: Tue, 22 Aug 2023 00:00:00 GMT
Abstract: The information society is a product of the intersection of socio-historical-technological contexts, where the development of science and industry has a global reach. The pervasiveness of new information and communication technologies makes it an essential component of a new civilization, affecting every country in varying degrees. Although this techniques approach is grounded in some truth, it neglects other vital aspects that challenge the idea of an information society that prioritizes human needs. The leading nations have achieved this through active research and development, driven by government involvement and the significant contributions of universities. Furthermore, the collaboration of diverse economic, institutional, social, and civic actors has played an essential role in its advancement. However, constructing and promoting an information society transcends infrastructure. It involves political actions that consider the socio-technological nature of this development and its impact on society and other sectors of activity. The objective of this article is twofold. On the one hand, the study analysed the situation of Algeria and its position in relation to other countries regarding the information society, and the other examined the factors that influence the development of the information society in Algeria, trying to identify the most important ones. Finally, the authors proposed a development strategy in this area. The research thesis was formulated as follows: What are the key variables that have an impact on the development of digitalization and the information society in Algeria' Thus, the regulatory frameworks of the most advanced countries are central to the initiatives aimed at its development. To foster the emergence of an information society in Algeria, solidarity must be strengthened, diversity promoted, and the potential of all citizens catalysed. PubDate: Tue, 22 Aug 2023 00:00:00 GMT
Abstract: The Covid-19 pandemic forced an immediate switch from the traditional form of education to a remote one, which caused various problems. Comparative studies conducted among students and academic teachers have shown the complexity of the situation and the ambiguity of assessments concerning the effectiveness of the solutions applied. This article presents an analysis of the results of a survey carried out in Q4 of 2021, using own questionnaire, among students from universities in Poland, Hungary and Greece, and a group of attendees of the Adult Education Centre in Finland (N = 769). The presented area of research embraces students’ experiences of distance learning during the first stage of the Covid-19 pandemic. Descriptive statistics and tests of the equality of means were used to analyse the students’ opinions in order to check for differences in assessments based on the selected metric characteristics of the respondents. Possible differentiation of opinions due to respondent characteristics such as gender or country of study was also searched for. The study results can be used to develop solutions which can be used to improve the quality of distance learning. PubDate: Tue, 22 Aug 2023 00:00:00 GMT
Abstract: This paper attempted using the prospect theory to explain overbidding in first price auctions. The standard outlook in the literature on auctions is that bidders overbid, but the probability weighting functions are nonlinear as in the prospect theory, so they not only tend to underweight the probabilities of winning the auction but also overweight, so that there are overbidders and underbidders. This paper proves that to some extent, non-linear weighting functions do explain overbidding the risk-neutral Nash equilibrium valuation (RNNE). Furthermore, coherent risk measures, such as certainty equivalent and translation invariance, were used to show loss aversion among bidders, and in line with the prospect theory, convexity was also confirmed with sub-additivity, monotonicity and with positive homogeneity. PubDate: Tue, 30 May 2023 00:00:00 GMT
Abstract: The aim of this research was to study a nonparametric estimator of the density and mode function of a scalar response variable given a functional variable, when the observations are i.i.d. This proposed estimator is given by combining Missing At Random (MAR) with the local linear approach. Finally, a comparison study based on simulated data is also provided to illustrate the finite sample performances and the usefulness of the local linear approach with MAR to the presence of even a small proportion of outliers in the data. PubDate: Tue, 30 May 2023 00:00:00 GMT
Abstract: In this research study, the authors obtained the preliminary evaluation of the impact detection of vaccinations against COVID-19 in the EU-27. The empirical basis of the study was the daily number of COVID-19 cases, vaccinations, hospitalisations, and deaths in the EU countries from March 2020 to March 2022. Rules of association were used to identify non-obvious associations between vaccinations against COVID-19 and cases of illness, hospitalisations, and deaths from COVID-19. The obtained results were used to cluster the EU countries by the level of vaccinations against COVID-19, cases of COVID-19, deaths from COVID, and COVID-19 hospitalisations for the EU member states. The K-means clustering method was used for cluster analysis. Hidden dependencies of the number of COVID-19 cases, the number of COVID-19 hospitalisations, and the number of COVID-19 deaths due to the number of vaccinations against COVID-19 by EU countries were revealed. It was established with a high probability that vaccination significantly affects the level of morbidity. For the first time, association rules were obtained, which are preliminary estimates of the relationship between the dynamics of vaccinations against COVID-19 and the dynamics of COVID-19 cases, COVID-19 hospitalisations, and deaths from COVID-19 in the EU. The results can be used to make beneficial decisions, for example, to regulate vaccination policies in individual EU countries, and predict the future consequences of the COVID-19 pandemic. PubDate: Tue, 30 May 2023 00:00:00 GMT
Abstract: The aim of the article is to show the impact of the COVID-19 pandemic on the living situation of large families. The study paid particular attention to the economic and housing problems, as well as the mental condition and challenges related to remote learning. The study was primarily empirical. The article presents the results of quantitative research extended by a catalogue of open questions, together with the results of research conducted by the “Three Plus” Association of Large Families in May 2020. Statistical methods were used to analyse the data. The living conditions (in most of the examined dimensions) of most families with many children deteriorated during the pandemic. The most important problems faced by such families were primarily related to the labour market (employment and running a business), and housing (related to a deterioration of the mental condition of family members). However, the families also indicated closer family relations, caused by forced isolation and slowed-down pace of life (lack of commuting, additional activities, and other activities outside the home). Overall, families with more children, and those living in smaller flats experienced the most difficult situation. PubDate: Wed, 15 Feb 2023 00:00:00 GMT
Abstract: In recent decades, Fuzzy Time Series (FTS) has become a competitive, sometimes complementary, approach to classical time series methods such as that of Box-Jenkins. This study has two different purposes: a theoretical purpose, presenting an overview of the fuzzy logic and fuzzy time series models, and a practical purpose, which is to estimate and forecast monthly international coffee prices during the period 2000-2022. Analysing and forecasting the dynamics of coffee prices is of great interest to producers, consumers, and other market actors in managing and making rational decisions. The findings showed that international coffee prices exhibited significant fluctuations, with large increases and decreases influenced mainly by the level of top-ranked producers. The forecasted results revealed that a decrease in prices during the next six months (Jan 2023 to June 2023) is expected. Based on the results, it is also clear that the FTS models are more flexible and can be applied in forecasting time-series variables. At the same time, volatility and, sometimes, the unexpected swingsin coffee prices continue to draw more criticism and raise different issues regarding the roles of the markets and countries in ensuring food security. PubDate: Wed, 15 Feb 2023 00:00:00 GMT
Abstract: The purpose of the paper was to investigate by the kernel method a nonparametric estimate of the conditional density function of a scalar response variable given a random variable taking values in a separable real Hilbert space when the observations are quasi-associated dependent. Under some general conditions, the authors established the pointwise almost complete consistencies with rates of this estimator. The principal aim is the investigate the convergence rate of the proposed estimator. PubDate: Thu, 10 Nov 2022 00:00:00 GMT
Abstract: This paper expands the considerations of Becker’s and Leibenstein’s family theories with a focus on the additional member of the household (pet/animal) in the analysis of consumption. It is the first analytical approach regarding pet goods consumption with references to microeconomic theories based on Polish data. The study analyses the households’ characteristics that have an impact on expenditure on pet goods. This article used the Polish Household Budget Surveys for 2018. The findings from the logistic regression models suggest that the household’s socio-economic group, place of living, children in household and whether the household rents the flat/accommodation impact on determining the probability of owning a pet among Polish house-holds; analyses of interactions between significant variables were also conducted. However, the human-animal bond could not be included in analysis, which is a limitation, the overall work is pioneering, as it shows the quantitative approach to household economy that highlights the need to elaborate the economic family theories of Becker and Leibenstein by a new family member – a pet. PubDate: Thu, 10 Nov 2022 00:00:00 GMT
Abstract: The article presents an analysis of the results of a survey conducted in 2022 among students and young graduates of three vocational education courses, studying in EU countries (N = 428). The area of research concerns the awareness of competencies sought-after by employers and the self-assessed level of these competencies. The authors used tests of the equality of two means in order to check for differences in assessments according to the respondents’ metric characteristics, and also factor analysis to check for similarities in attitudes towards different types of competencies in the respondents’ assessments. Finding such similarities would allow to use a summative scale and reduce the dimensions. PubDate: Thu, 10 Nov 2022 00:00:00 GMT
Abstract: FDIs are an important part of the ‘bloodstream’ of many countries’ economies, and it would be difficult to overestimate the benefits of FDIs for the states that receive them. The processes of FDI influx and their effects have been the subject of numerous studies and analyses in the fields of both economic theory and empirical research. However, less attention has been paid to the process of divestment, which in many cases may result in adverse changes in the economies of FDI recipient countries. This article proposes that event history analysis methods can be used to study the survival of FDI projects. FDIs are launched at a certain point in time by investors, last for some time, and then can be either terminated or continued. In this context, we may come across complete as well as truncated observations, much like in the analyses of population processes, therefore the use of demographic methods to study the survivability of FDI projects is justified. The purpose of this article was to present specially constructed FDI life tables and to compare the ‘survivability’ patterns of foreign direct investments in selected economic sectors of the Visegrád Group countries. For many years, these countries have enjoyed considerable interest from foreign investors and have often competed with each other for new FDI projects. Therefore, comparing them not only in terms of the processes related to FDI influx, but also in terms of the processes of divestment appears interesting and important to economists, market analysts and the investors themselves. The study used data from the Orbis and Zephyr databases. PubDate: Mon, 12 Sep 2022 00:00:00 GMT
Abstract: This article focuses on the presentation of the forecasting possibilities of bootstrap methods used to predict prices based on time series. The aim of the paper was to examine the quality of the forecasts made with the methods for silver futures contracts. In order to achieve the intended goal, ex-post and ex-ante errors for the forecasts prepared by applying bootstrap methods were analysed. The forecasts were calculated using the daily closing prices of the silver futures contracts for the period from 01/07/2020 to 27/03/2022 The analysis showed that the quality of forecasts for each of the presented methods is at a satisfactory level. Moreover, the forecasts calculated using the bootstrap methods were closer to the real performance of the silver futures contracts than the forecasts obtained using the ARMA model (1,1). In addition, it was shown that the forecasts made with the tapered block bootstrap method are less affected by forecast errors than the other analysed methods. PubDate: Mon, 12 Sep 2022 00:00:00 GMT
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