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The aim of the article is to present a non-parametric kernel density estimation method as a tool used for empirical verification of the regional
convergence hypothesis, including convergence of clubs. It is explained how kernel density estimation complements other methods applied to verify the phenomenon of convergence. The empirical part shows an application of the non-parametric density estimation to the analysis of regional convergence of educational achievements of Polish pupils, measured by the average results of the mathematical and natural science part of the lower-secondary school leaving exams on the level of municipalities in years 2002—2013. The results of the analysis indicate the existence of regional convergence of exam results for Polish municipalities. In case of the analysis for three-yearly periods convergence of clubs was observed — the municipalities with lowest exam results constitute a separate club of convergence.

In the last decade, after accession to European Union, Poland has achieved a significant improvement of indicators relating to income on a national level. Polish GDP per capita (in PPP terms) increased from 49% of European Union average in 2004 to 67% in 2013 showing progress in each year (source: Eurostat). Simultaneously an impressive progress was achieved by Polish secondary schools pupils, which is confirmed by international comparisons of educational results (PISA). Empirical analyses of GDP per capita distribution and its dynamics on a regional level in Poland show that the above mentioned progress does not spread out proportionally on all regions and income convergence is not observed. Instead, the relatively fastest growth of initially richest regions (mostly large cities) introduces convergence of clubs which leads to polarization. The purpose of the research is to analyze the relationship between the local convergence of income and educational achievements on a local level in Poland in the period 2003-2013. We aim to verify if and how the convergence processes of these two phenomena are related to each other. The analysis is applied on the level of municipalities (LAU 2, former NUTS 5). Income is measured in terms of per capita revenue in municipality budget from the share in receipts from personal income tax (source of data: Local Data Bank, Polish Central Statistical Office). Educational achievements are measured by the median results of standardized lower-secondary school leaving exams (source of data: Polish Central Examination Board). We introduce a concept of parallel convergence as a way of measurement of the co-relationship between the two phenomena. The evolution of the joint distribution of income and educational achievements is analyzed with the use of a transition matrix generalized for the two-dimensional distributions and with two dimensional kernel density estimates. The analysis shows that in regions with initially highest relative income also initial educational achievements are usually equal to or higher than the average for the whole country. In the regions with relatively lowest initial income the initial distribution of educational achievements does not differ from its distribution for all municipalities. The joint distribution is relatively stable over time. Initial analysis of the dynamics of the joint distribution between 2003 and 2013 shows that for regions with initially lowest income the probability of improving low exam results is lower than the probability of becoming relatively richer. The largest mobility of the joint distribution was observed for the groups with the lowest or low initial income and the highest educational achievements, while highest persistence was found for the groups initially richest with high or the highest educational achievements.

AbstractThere is a growing need to analyze welfare at an intra‐urban level because cities often evince stark divisions. It is therefore important to identify inequalities within them. However, data are hardly available – or very expensive. The purpose of this article is to test whether nonlinear machine learning algorithms provide more accurate predictions of intra‐city well‐being than linear models. In addition, we aim to check if freely available and easily accessible data from Open Street Map offer an alternative to high‐resolution daytime satellite images from Google Maps in accurately predicting well‐being on a local level. Inspired by the Local Human Development Index, we construct a well‐being index based on three dimensions: health, education, and welfare. Potential predictors of well‐being include indicators related to the urbanization rate, access to natural amenities, the transportation system, and access to public transport. Four nonlinear machine learning algorithms (support vector regression with polynomial and radial kernel, random forest, and xgboost) are compared with the linear LASSO approach for the 18 districts of Warsaw, Poland. In addition, we apply innovative tools of explainable artificial intelligence (XAI) to identify the most important predictors of well‐being (measuring model‐agnostic feature importance) and to disclose the shape of relationships between well‐being and its most important predictors. We conclude that the application of nonlinear machine learning algorithms to modeling well‐being not only allows us to reach higher predictive accuracy, but also to better identify and explain the impact of its predictors.

Purpose
The purpose of this study is to explore how individual-level cognitive and organizational-level behavioral factors influence the level of firms' export performance as firms adapt to the challenges of foreign expansion.


Design/methodology/approach
Based on the literature on dynamic capabilities (DCs) and international business, the study introduces a multi-level model of DC to internationalize and test it empirically on a sample of 93 Polish exporting firms using structural equation modeling.


Findings
The results show a strong and positive impact of the "strategy as stretch" managerial mind-set on two behavioral elements, namely, business modeling and partnering capability. Global mind-set has a strong and positive impact on business modeling and learning about foreign markets and a negative but insignificant effect on partnering capability. Only two of the three behavioral elements of the conceptualized DC have significant and positive impacts on export performance. In contrast to the expectations, the direct path coefficient from learning about foreign markets to export performance was found to be positive but insignificant.


Originality/value
This study contributes to the literature by offering a coherent, multi-level framework of DCs. The study goes beyond previous conceptualizations of DCs and considers various individual-level cognitive and organizational-level behavioral elements of DC for the internationalization of exporting firms. In particular, this study shows the interplay between them and their combined impact on export performance.

Polskie społeczeństwo starzeje się i konsekwencje tego procesu już mają wpływ na nasze codzienne życie. Celem tego artykułu jest identyfikacja i określenie kierunku działania czynników, które pozwolą wyjaśnić, dlaczego niektóre gminy starzeją się szybciej od pozostałych. Używając miary autokorelacji przestrzennej (I Morana), a także regresji przestrzennej na danych panelowych, analizujemy charakterystyki polskich gmin w latach 2003–2013. Zmienną zależną w badaniu jest udział w populacji gminy osób starszych (w wieku 70 lat i więcej). Wyniki wskazują na silną autokorelację przestrzenną, co znaczy, że starzenie się populacji w danej gminie jest silnie powiązane z tempem starzenia się w gminach z nią sąsiadujących. W wyjaśnieniu analizowanego zjawiska ważne okazuje się również wiele charakterystyk społeczno‑gospodarczych gminy, w tym sieć transportowa (autostrady i drogi ekspresowe) łącząca gminę z innymi ośrodkami.

AbstractGiven current political concerns with inequality and the sustainable management of natural resources, the issue of the distribution of productive assets in rural areas has become an increasingly important focus of research. Referring to both ample historical evidence and qualitative research, rural sociologists have long postulated that the distribution of economic resources is strongly influenced by the distribution of political power. In this article we support this claim with quantitative analysis. Our focus is on the relationship between land inequality and the attainment of political power by large‐scale farmers in rural Poland. Our findings suggest a strong statistical association between the current level of land inequality and the fact that mayors operate relatively large land holdings themselves. Our results are qualitatively the same no matter whether we measure land inequality as the share of land used by the largest landholders or the land Gini index. They also hold in several robustness checks.

Introduction -- Volatility and its estimation -- Overview of volatility derivatives -- Options delta hedging with no options at all -- Volatility derivatives in portfolio optimization -- Benefits of using volatility futures in investment strategies -- Predictive properties of the volatility term structure -- Conclusions -- List of gures -- List of tables -- Bibliography