Improved asymptotic analysis of Gaussian QML estimators in spatial models

This paper presents a fundamentally improved statement on asymptotic behaviour of the well-known Gaussian QML estimator of parameters in high-order mixed regressive/autoregressive spatial model. We generalize the approach previously known in the econometric literature by considerably weakening assumptions on the spatial weight matrix, distribution of the residuals and the parameter space for the spatial autoregressive parameter. As an example application of our new asymptotic analysis we also give a statement on the large sample behaviour of a general fi xed effects design

Labor productivity growth in EU28: Spatial panel analysis

This paper is an attempt to explain variations across EU regions in productivity growth and takes into consideration the important structure of the age-productivity relation of Human Capital. The study is fundamentally based on the theory of Fingleton?s model which analyses the spatial process of productivity growth on the on the foundations of the theory of New Economic Geography. The applied specification links manufacturing productivity growth to the growth of manufacturing output by the means of Verdoorn?s law. The model incorporates productivity-adjusted human capital understood as Total Human Capital Productivity corrected with age structure with the use of productivity as a function of age. Moreover, a new approach to defining the age-productivity curve has been introduced. Based on the previous studies found in the literature the age-productivity function has been interpolated by the means of Radial Basis Function method with thin-plate spline. The age-productivity function allows to describe how the work performance differs over the life period and thus allows for differences in age structure of employees in regions under research. This study covers 261 NUTS 2 regions of EU excluding some French, Portuguese and Spanish regions due to their isolated position and Croatia because of the lack of comparable data. All data used in the empirical part of this study are published by Eurostat and refer to the years 2000-2013. The regional productivity is explained by the quotient of regional GDP and the number of Economically Active Population. The productivity growth is approximated by the exponential change of regional productivity in these years to regional productivity in the year 2000. The regional GDP is expressed in millions of Euro in constant prices (year 2000), where Economically Active Population is in thousands of people 15 years or over. The Human capital is defined by the Employment in Technology and Knowledge-intensive Sectors as a percentage of Economically Active Population. The model has been tested through implemented methodology, namely a spatial panel model with fixed effects. The model presented provides evidence of the importance of increasing returns to scale for regional economic growth, which lead to divergence effects for EU regions. Similar implications can be observed in the case of regionally differentiated human capital. Furthermore, the country fixed effects turned out to be significant. The findings also suggest that productivity in jobs requiring problem solving and learning skills reaches a plateau for the 35-45 age bracket and has its peak around the age of 40. We suggest that the applied approach constitutes an innovation providing additional information hence a deeper analysis of the investigated problem

Spatial Solution to Measure Regional Efficiency — Introducing Spatial Data Envelopment Analysis

When investigating healthcare efficiency at the regional level, the problem of interactions between neighbouring locations arises. The health of the population in a given region is related to the healthcare in other areas through a medical tourism, a limited number of highly specialised institutions, competition between institutions, etc. Ignoring these inter-regional links may result in a systematic bias in the efficiency analysis. Similar issues may hinder any regional studies. Hence, the main purpose of this paper is to introduce a new approach to measuring efficiency in regional studies through spatial data envelopment analysis (SDEA). The paper offers a proper mathematical formulation of the new methodology and highlights differences between classic data envelopment analysis (DEA) and the newly developed method. The motivation for seeking a new solution to the problem of spatially adequate assessment of regional efficiency is derived from the literature review and a discussion of the presented theoretical examples. The classic DEA allows for multidimensional analysis of the performance of homogenous independent decision-making units. However, in regional studies, an area where DEA has gained popularity, the assumption of the isolation of decision-making units seems to be unfounded. In the SDEA approach, the region-specific spatial context is incorporated into the analysis via the W matrix and spatial interactions are reflected in the model through spatially weighted inputs and outputs. Therefore, in our paper, we verify the hypothesis that spatial interactions are an indispensable factor of regional efficiency analysis. A study of healthcare efficiency in European regions is presented as an illustration of the utility of the new methodology. Furthermore, we compare the results of the classic DEA approach with those of the SDEA, which is augmented with the spatial equivalents of inputs and outputs. Our results suggest that classic DEA undervalues regional healthcare efficiency by underestimating the region-specific spatial context.2 Researchers may find the introduced SDEA method useful in all space related fields when investigated phenomenon exhibits spatial autocorrelation. In particular, the new approach may deepen the regional efficiency analysis of innovation, development, logistics, tourism, etc

Spatial Solution to Measure Regional Efficiency — Introducing Spatial Data Envelopment Analysis

When investigating healthcare efficiency at the regional level, the problem of interactions between neighbouring locations arises. The health of the population in a given region is related to the healthcare in other areas through a medical tourism, a limited number of highly specialised institutions, competition between institutions, etc. Ignoring these inter-regional links may result in a systematic bias in the efficiency analysis. Similar issues may hinder any regional studies. Hence, the main purpose of this paper is to introduce a new approach to measuring efficiency in regional studies through spatial data envelopment analysis (SDEA). The paper offers a proper mathematical formulation of the new methodology and highlights differences between classic data envelopment analysis (DEA) and the newly developed method. The motivation for seeking a new solution to the problem of spatially adequate assessment of regional efficiency is derived from the literature review and a discussion of the presented theoretical examples. The classic DEA allows for multidimensional analysis of the performance of homogenous independent decision-making units. However, in regional studies, an area where DEA has gained popularity, the assumption of the isolation of decision-making units seems to be unfounded. In the SDEA approach, the region-specific spatial context is incorporated into the analysis via the W matrix and spatial interactions are reflected in the model through spatially weighted inputs and outputs. Therefore, in our paper, we verify the hypothesis that spatial interactions are an indispensable factor of regional efficiency analysis. A study of healthcare efficiency in European regions is presented as an illustration of the utility of the new methodology. Furthermore, we compare the results of the classic DEA approach with those of the SDEA, which is augmented with the spatial equivalents of inputs and outputs. Our results suggest that classic DEA undervalues regional healthcare efficiency by underestimating the region-specific spatial context.2 Researchers may find the introduced SDEA method useful in all space related fields when investigated phenomenon exhibits spatial autocorrelation. In particular, the new approach may deepen the regional efficiency analysis of innovation, development, logistics, tourism, etc

Online Communities and Online Activities of Politicians – Opinions of Internet Users

: Marketing activity in the field of social media has seemed to be more professional for few years. This communication channel (web 2.0) is established and frequently used on the market of products and services. Social media services are also in progress. They are focused of big data, sale support or profiling offers at an angle of brand fan`s behavior in social media. Collaterally, similar activities in the field of politics appear. The objective of this article is answering the question: what is the attitude of the Internet users to promotion activities like this? It seems to be important from the effective and specific point of view in political communication of social media. Thus, we conducted research described in this text that is going to verify if social media services are the source of knowledge about politics in Poland. What is more, we wanted to check in which way the Internet users find information about politics and what is their level of engagement `around` politicians` online activity.3183201Środkowoeuropejskie Studia Polityczn

Contrastive News and Social Media Linking using BERT for Articles and Tweets across Dual Platforms

X (formerly Twitter) has evolved into a contemporary agora, offering a platform for individuals to express opinions and viewpoints on current events. The majority of the topics discussed on Twitter are directly related to ongoing events, making it an important source for monitoring public discourse. However, linking tweets to specific news presents a significant challenge due to their concise and informal nature. Previous approaches, including topic models, graph-based models, and supervised classifiers, have fallen short in effectively capturing the unique characteristics of tweets and articles. Inspired by the success of the CLIP model in computer vision, which employs contrastive learning to model similarities between images and captions, this paper introduces a contrastive learning approach for training a representation space where linked articles and tweets exhibit proximity. We present our contrastive learning approach, CATBERT (Contrastive Articles Tweets BERT), leveraging pre-trained BERT models. The model is trained and tested on a dataset containing manually labeled English and Polish tweets and articles related to the Russian-Ukrainian war. We evaluate CATBERT's performance against traditional approaches like LDA, and the novel method based on OpenAI embeddings, which has not been previously applied to this task. Our findings indicate that CATBERT demonstrates superior performance in associating tweets with relevant news articles. Furthermore, we demonstrate the performance of the models when applied to finding the main topic -- represented by an article -- of the whole cascade of tweets. In this new task, we report the performance of the different models in dependence on the cascade size

The influence of curcumin additives on the viability of probiotic bacteria, antibacterial activity against pathogenic microorganisms, and quality indicators of low-fat yogurt

Curcumin is a nutraceutical with unique anti-inflammatory, anti-oxidative, and antimicrobial properties. In this study, we aimed to examine the advantages of the use of water dispersible and highly bioavailable form of standardized turmeric extract (Curcuma longa L.)—NOMICU® L-100 (N) in the formulation of probiotic yogurt in comparison with the standard turmeric extract (TE). The antimicrobial activity of both supplements was studied and compared in the context of gram-positive and gram-negative bacteria, yeasts, and fungi. The N maintains the level of Bifidobacterium animalis subsp. lactis BB-2 in yogurt at the recommended level (7–9 log CFU/g) throughout the storage period. NOMICU® L-100 also has a higher inhibitory capacity for the growth of yeast and fungi. The evaluation of quality indicators of yogurt with N and TE at the level of 0.2% proves that yogurt with N has original taste properties. A lower degree of syneresis was noted for yogurt with TE (0.2%), but its sensory properties are unacceptable to the consumer due to the appearance of a bitter taste. In conclusion, based on the obtained results, it has been proven that the use of NOMICU® L-100 (0.2%) in the composition of yogurt provides a product of functional direction with stable quality and safety indicators, which can be stored for at least 28 days

Extremely Preterm Infant Admissions Within the SafeBoosC-III Consortium During the COVID-19 Lockdown

Objective: To evaluate if the number of admitted extremely preterm (EP) infants (born before 28 weeks of gestational age) differed in the neonatal intensive care units (NICUs) of the SafeBoosC-III consortium during the global lockdown when compared to the corresponding time period in 2019. Design: This is a retrospective, observational study. Forty-six out of 79 NICUs (58%) from 17 countries participated. Principal investigators were asked to report the following information: (1) Total number of EP infant admissions to their NICU in the 3 months where the lockdown restrictions were most rigorous during the first phase of the COVID-19 pandemic, (2) Similar EP infant admissions in the corresponding 3 months of 2019, (3) the level of local restrictions during the lockdown period, and (4) the local impact of the COVID-19 lockdown on the everyday life of a pregnant woman. Results: The number of EP infant admissions during the first wave of the COVID-19 pandemic was 428 compared to 457 in the corresponding 3 months in 2019 (−6.6%, 95% CI −18.2 to +7.1%, p = 0.33). There were no statistically significant differences within individual geographic regions and no significant association between the level of lockdown restrictions and difference in the number of EP infant admissions. A post-hoc analysis based on data from the 46 NICUs found a decrease of 10.3%in the total number of NICU admissions (n = 7,499 in 2020 vs. n = 8,362 in 2019). Conclusion: This ad hoc study did not confirm previous reports of a major reduction in the number of extremely pretermbirths during the first phase of the COVID-19 pandemic. Clinical Trial Registration: ClinicalTrial.gov, identifier: NCT04527601 (registered August 26, 2020), https://clinicaltrials.gov/ct2/show/NCT04527601

Metody stochastyczne w ekonometrii przestrzennej – nowoczesna analiza asymptotyczna

W monografii zostały zaprezentowane najnowsze i w dużej mierze autorskie osiągnięcia z zakresu teorii asymptotycznych stochastycznych modeli ekonometrii przestrzennej. Rezultaty pracy naukowej autorów zostały poprzedzone przeglądem klasycznych, choć przedstawionych w nowoczesnym ujęciu, zagadnień ekonometrii przestrzennej. Ważnym elementem omawianej teorii jest nowe Centralne Twierdzenie Graniczne dla form liniowo-kwadratowych .Pozwala ono na przeprowadzanie formalnych dowodów własności granicznych statystyk testowych autokorelacji przestrzennej oraz estymatorów parametrów modeli ekonometrycznych z zależnościami przestrzennymi