Comparing pre-war and forced Ukrainian migrants in Poland: Challenges for the labour market and prospects for integration

Before full-scale war broke out in 2022, over 1 million Ukrainians resided legally in Poland. Within weeks of Russia's aggression, around 1.5 million new Ukrainian forced migrants had arrived, many of whom remain in Poland. As of September 2023, 970,000 Ukrainian refugees were still in Poland, where they enjoyed temporary protection status. This paper analyses data from a 2022 survey of both forcibly displaced and pre-war Ukrainian migrants with the aim of establishing what measures are needed to facilitate the economic integration of the former group. The two cohorts differ in terms of gender, age, family status, ways of seeking employment, employment situation and aspirations. Although 66 per cent of respondents had completed tertiary education, only 30 per cent of the forcibly displaced group had Polish-language skills. The paper recommends strategies for the provision of language education along with solutions to enable the labour market participation of this group and otherwise support their integration.     

Multi-couple reflecting team: preliminary report

The aim of therapeutic help in marital crisis is to break the vicious circle of mutual hurtful accusations. The method that the authors present below involves a group of couples working within a closed cycle of meetings. In the course of successive group meetings, the various couples act as reflecting teams (RTs) for each other. This achieves two objectives: the couple recounting their crisis receives nonthreatening feedback, which helps them to implement positive changes and break out of the self-perpetuating destructive interaction. In addition, the couples acting as the RT learn nonjudgmental, nontheorizing and affirmative communication.     

Extreme ranking analysis in robust ordinal regression

We extend the principle of robust ordinal regression with an analysis of extreme ranking results. In our proposal, we consider the whole set of instances of a preference model that is compatible with preference information provided by the DM. We refer to both, the well-known UTA^GMS method, which builds the set of general additive value functions compatible with DM's preferences, and newly introduced in this paper PROMETHEE^GKS, which constructs the set of compatible outranking models via robust ordinal regression. Then, we consider all complete rankings that follow the use of the compatible preference models, and we determine the best and the worst attained ranks for each alternative. In this way, we are able to assess its position in an overall ranking, and not only in terms of pairwise comparisons, as it is the case in original robust ordinal regression methods. Additionally, we analyze the ranges of possible comprehensive scores (values or net outranking flows). We also discuss extensions of the presented approach on other multiple criteria problems than ranking. Finally, we show how the presented methodology can be applied in practical decision support, reporting results of three illustrative studies.     

Beyond Markowitz with multiple criteria decision aiding

The paper is about portfolio selection in a non-Markowitz way, involving uncertainty modeling in terms of a series of meaningful quantiles of probabilistic distributions. Considering the quantiles as evaluation criteria of the portfolios leads to a multiobjective optimization problem which needs to be solved using a Multiple Criteria Decision Aiding (MCDA) method. The primary method we propose for solving this problem is an Interactive Multiobjective Optimization (IMO) method based on so-called Dominance-based Rough Set Approach (DRSA). IMO-DRSA is composed of two phases: computation phase, and dialogue phase. In the computation phase, a sample of feasible portfolio solutions is calculated and presented to the Decision Maker (DM). In the dialogue phase, the DM indicates portfolio solutions which are relatively attractive in a given sample; this binary classification of sample portfolios into ‘good’ and ‘others’ is an input preference information to be analyzed using DRSA; DRSA is producing decision rules relating conditions on particular quantiles with the qualification of supporting portfolios as ‘good’; a rule that best fits the current DM’s preferences is chosen to constrain the previous multiobjective optimization in order to compute a new sample in the next computation phase; in this way, the computation phase yields a new sample including better portfolios, and the procedure loops a necessary number of times to end with the most preferred portfolio. We compare IMO-DRSA with two representative MCDA methods based on traditional preference models: value function (UTA method) and outranking relation (ELECTRE IS method). The comparison, which is of methodological nature, is illustrated by a didactic example.     

Who gets to look nice and who gets to play? Effects of child gender on household expenditures

We examine the relationship between a child’s gender and family expenditure using data from the Polish Household Budget Survey. Having a first-born daughter as compared with a first-born son increases the level of household expenditures on child and adult female clothing, and it reduces spending on games, toys and hobbies. This could be a reflection of a pure gender bias on behalf of the parents or a reflection of gender complementarities between parents’ and children’s expenditures. We find no robust evidence on gender differences in educational investment, measured by kindergarten expenditure. The analysed expenditure patterns suggest a so-far unexamined role of gender in child development. Parents in Poland seem to pay more attention to how girls look and favour boys with respect to activities and play, which could have consequences in adult life and contribute to sustaining gender inequalities and stereotypes.     

Asymptotic behaviour of proportions of observations in random regions determined by central order statistics from stationary processes

In this paper, we show that proportions of observations that fall into a random region determined by a given Borel set and a central order statistic converge almost surely, provided that the corresponding population quantile is unique. We also describe three types of possible asymptotic behaviour of these proportions in the case of non-unique population quantile. As an application of our findings we establish limiting properties of numbers of ties with a central order statistics in a discrete sample. Our results are derived not only for independent and identically distributed observations but more generally for strictly stationary and ergodic sequences of random variables.     

Comparison of the effectiveness of forecasts obtained by means of selected probability functions with respect to forecast error distributions

The forecasting of sales in a company is one of the crucial challenges that must be faced. Nowadays, there is a large spectrum of methods that enable making reliable forecasts. However, sometimes the nature of time series excludes many well-known and widely used forecasting methods (e.g., econometric models). Therefore, the authors decided to forecast on the basis of a seasonally adjusted median of selected probability distributions. The obtained forecasts were verified by means of distributions of the Theil U² coefficient and unbiasedness coefficient.     

A simulation study of the Bennett test and Miller test for coefficients of variation

In the article, properties of the Bennett test and Miller test are analyzed. Assuming that the sample size is the same for each sample and considering the null hypothesis that the coefficients of variation for k populations are equal against the hypothesis that k ? 1 coefficients of variation are the same but differ from the coefficient of variation for the kth population, the empirical significance level and the power of the test are studied. Moreover, the dependence of the test statistic and the power of the test on the ratio of coefficients of variation are considered. The analyses are performed on simulated data.     

The middling mobile: finding place in the liquid city

The middling mobile, differentiated by their modest and unsure mobility, are a vast of bulk of people who intend or expect to move on. As they travel, they tread differing intensities of rhythm and social embeddedness felt to be chaotic, constraining, liberating, or comforting. Owing to their aspirations to ‘get out’ of a rhythmic life, or to move somewhere familiar, the middling mobile use movement and rootedness to navigate and manage everyday life in the liquid city. My analysis offers a holistic exposition of a life that flows between mobility/immobility and rhythmic/arrhythmic forms, and the transitions between them.