The article deals with the evaluation of the economic performance of domestic enterprises under foreign control, especially by subjects from Eastern European countries currently involved in the war conflict in Ukraine, through several key indicators monitored by Inward Foreign Affiliates Statistics (IFATS) and compiled by the Czech Statistical Office (CZSO). The war conflict in Ukraine raises, among other, questions about the effects of sanctions against aggressor countries. IFATS could serve as one possible source for evaluation of their impact with new data coming in the future. In the article, selected data from the IFATS database will be compared for the economy as a whole and according to the specific prevailing economic activities as well. Although the contribution of enterprises controlled by subjects from both aggressor countries and Ukraine to the Czech economy is quite marginal, the latter ones are among the most represented in terms of their number that is still growing. However, their economic importance grows much slower.

In the run-up to launching the «Next Generation EU» large-scale recovery plan aimed at overcoming the Covid-19 pandemic consequences it becomes important to analyse the pre-Covid development problems, including those in the field of education. The purpose of this work is to study the dynamics of inequality in educational achievements and opportunities in the Visegrad Group countries based on the PISA data from 2003–2018 period. The results obtained by our research team suggest that Hungary has the highest level of inequality of opportunity among the Visegrad Group countries, followed by Slovakia. Meanwhile, individual factors contributing to the overall level of inequality of opportunity have both features common to all countries and unique features.

The pace of change in contemporary reality creates a need for fresh data to diagnose the impact of this change on the labour market. Opportunities to meet these expectations are provided by data resources collected in registers and administrative systems directly or indirectly related to employment. Experimental work carried out on the adaptation of data from these sources for statistical purposes shows that, for instance, data on employed persons calculated on the basis of the resources of the Social Insurance Institution (ZUS) and the Agricultural Social Insurance Fund (KRUS) allow analyses to be carried out taking into account, i.a., the generations. Currently, there are four generations on the labour market in Poland: the Baby Boomers, X, Y and Z, which differ in terms of their value system, motivation to work, expectations and loyalty to employers.

In changing context of the present-day world, trade openness has a crucial role to play in economic development of different countries. Besides other factors, institutional quality plays a vibrant role in achieving a high growth rate. The objective of the present study is to understand how institutional quality influences economic growth and trade openness in India. To achieve the objectives of the study, Autoregressive Distributed Lag bound testing approach has been used. The findings show that there exists long-run relationship between the variables used in this study. From the findings, it can be concluded that total trade has a negative impact, whereas export enhances economic growth in the country. The results also show that improvement in institutional quality has a positive impact on economic growth. Thus the findings suggest that the country needs to adopt policies that can improve the quality of institutions and can enhance the formation of physical and human capital.

Brazil does not have an official real estate price index yet. A 2011 presidential decree stipulated for the Brazilian Institute of Geography and Statistics (IBGE) the assignment to create and spread a real estate price index for Brazil. In this paper, we test some different hedonic model methods to estimate quarterly price indices for apartments in Belo Horizonte, Brazil, from January 2005 to December 2015. Our goals are: i) to measure and compare the different hedonic methods; ii) to present some results that will contribute to the discussion about the development of an official real estate price index in Brazil. The empirical results corroborate the idea of intense apartment prices valuation in Belo Horizonte, mainly between 2007 and 2011, when the annual price index growth remained above 20%. These results cast light on the potential use of both hedonic methods and administrative data base to construct an official real estate price index for Brazil.

The South Asian Association for Regional Cooperation (SAARC) region is an important player in the world agriculture trade. They have vast potential to strengthen their position in global agricultural trade due to theregion's opportunities to increase agricultural production combined with growing global demand. To discover the SAARC potential of agricultural trade patterns, the present paper examines the determinants of bilateral agricultural exports from 2000 to 2019. The gravity model was estimated by employing the Poisson Pseudo Maximum Likelihood (PMML) technique, including zero trade flows for panel data. The results confirm the positive and significant impact of exporter gross domestic product (GDP), importer GDP, Broder, common language, South Asian Free Trade Area (SAFTA), and India-Sri Lanka Free Trade Agreement (ISFTA) on bilateral agricultural trade inthe SAARC region. On the other hand, distance and development levels significantly negatively impact bilateral agricultural trade. Lastly, the study showed an insignificant impact of the bilateral exchange rate.

The k-Nearest Neighbour method is a popular nonparametric technique for solving classification and regression problems without having to make potentially restrictive a priori assumptions about the functional form of the statistical relationship under investigation. The purpose of this paper was to demonstrate that the scope of this method can be extended in a way that enables the simultaneous consideration of continuous, ordered discrete, and unordered discrete explanatory variables. An exemplary application to a publicly available dataset demonstrated the feasibility of the proposed approach.

This note reviews a direct least squares estimation of a state space model and highlights its advantages over the standard Kalman filter in some applications. Although there is a close relationship between these two concepts, dual understanding of the estimation problem seems to be little appreciated by the mainstream econometric literature as well as applied researchers. Due to computational and theoretical advancements, the least squares estimation of a state space model has become a viable alternative in many fields, showing great potential in solving otherwise difficult problems. This note gathers and discusses some possible applications to illustrate the point and contribute to their wider use in practice.

One of the common challenges in actuarial mathematics is finding a model for the number of claims and claim severity. We focus on one of the suggested models, namely, on the Schröter family of discrete probability distributions. Furthermore, we introduce a simple and easy-to-compute parameter estimate for this family of distributions, which can be used especially as initial values in optimization algorithms that are needed to compute other estimates.