The article aims at ascertaining the relationship between indicators affecting the green economic growth of the Eurozone countries. Despite extensive research, scientists have not yet found a clear answer as to whether economic growth and climate change mitigation can be aligned. Another important aspect of the study was to investigate the possible effect of environmental policies on macroeconomic variables such as GDP, investment, employment, and trade. The authors of the article applied the PVAR econometric model to measure the impact of energy consumption, CO2 emissions, and some of the macroeconomic indicators on GDP growth in 19 countries of the Eurozone for years 2000–2016.
Based on the results, we cannot yet state explicitly that economic growth in the Eurozone countries has been decoupled from climate change mitigation; however, green transition is on the right track.
This paper reviews the binomial and trinomial option pricing models and their convergence to the Black-Scholes model result. These models are generalized for the European and American options. The trinomial models are said to be more accurate than the binomial when fewer steps are modelled. These models are widely used for the usual vanilla option types, European or American options, that respectively can be exercised only at the expiration date and at any time before the expiration date. The results are supportive of the conventional wisdom that trinomial option pricing models such as the Kamrad-Ritchken model and the Boyle model are converging faster than the binomial models. When binomial models are compared in terms of convergence, the most efficient model is the Jarrow-Rudd model. This paper concludes that improved binomial models such as the Haahtela model are converging faster to the BS model result. After some trials, binomial distribution follows log-normal distribution assumed by the Black-Scholes model.
The purpose of this paper is to attempt to classify risk which can be observed when one deals with data from the metals market. Usually the general definition of risk includes two dimensions. The first one is the probability of occurrence and the second one are the associated consequences of a set of hazardous scenarios. In this research the authors try to add a new dimension: the source of risk, which can be defined in terms of the level of turnover (volatility of volume) and price (volatility of returns). One can categorize risks in terms of multidimensional ranking based on a comparative evaluation of the consequences, probability, and source of a given risk. Another dimension is the chosen risk measures, in the meaning of the risk model. In risk analysis, some selected quantile risk measures were proposed: VaR, Expected Shortfall, Median Shortfall and GlueVaR. The empirical part presents a multidimensional risk analysis of the metal market.
The purpose of the article is to assess selected large cities in Poland as senior-friendly. Using the municipal population forecast for 2017-2030 published in 2017, together with the available database, own analyses were made for selected cities in Poland. Additionally for the description of ‘senior-friendly’ cities, it was assumed that the starting point is the WHO definition, which indicated four main criteria determining whether a given city can be considered to be friendly to the elderly. In a city friendly to seniors, the principles, services, environment and structures built up support the active ageing process and avail it for the residents. For the purposes of the research, taking into account the above objectives and based on published sources, a descriptive model was created. The study assessed selected Polish cities as senior-friendly cities, using the robust taxonomic approach.
A new causal simulation model of economic development was created, which comprehensively in detail and fully reflects various types of legal and shadow economic activities and their interrelations.
The model is used to forecast the whole (legal and shadow) country’s economy up to 2022.
The dynamics of shadow and legal indicators are different.
The biggest and most important difference is about exports and imports. Official statistics give a negative balance of the Ukrainian foreign trade of Ukraine in 2019-22. However, total export, determined by the model, considerably exceeds imports, so actually we expect a surplus.
This is very important for the National Bank: its policy based on the official (legal) negative balance of Ukraine foreign trade should be one (throw foreign currency reserves into the market or to devalue the hryvnia), but with the actual balance that includes shadow flows and is positive, - contrary one (to buy currency on the market or to revalue the national currency).
Our model calculates how the production volumes of all types of goods and services should change to ensure that supply and demand are balanced. These numbers can serve a reference for manufacturers.
We suggested that the relevant Ukrainian authorities take an active position in the implementation of the developed forecast for the economic development of Ukraine: measuring actual rates of changes in the production of these types of goods during the year, they provide recommendations to producers to increase or decrease their production.
Categorical data analysis is a statistical method that can be successfully applied in different scientific areas, such as: social, medical, psychological and political sciences. Classification and segmentation are statistical methods that usually have been used for large quantitative datasets to identify segments in the data, however if applied for categorical data for contingency tables, one may arrive at impressive results as well. This paper presents the use of classification and segmentation methods for categorical data in a contingency table based on real data from Central Statistics on the number of university positions in Polish voivodeships. The authors compare the results of different approaches and provide graphical results using advanced visualization tools, perceptual map (biplot) and dendrogram. Comparative analysis provides information on corresponding categories of academic positions in different voivodeships. All calculations are conducted in R.
Classification models enable optimal actions to be taken at every stage of the customer’s lifecycle. A circumstance affecting both the model building process and the assessment of their discriminatory power is the unbalanced distribution of the dichotomous dependent variable. The article focuses on the question of reliable assessment of the goodness of fit. The first part of the article reviews the measures of predictive power and then assesses the impact of the distribution of the dependent variable on the selected measures of goodness of fit. As a result, the high sensitivity of a number of measures such as lift, accuracy (ACC), or F-Score was observed. The sensitivity of MCC and Kappa Cohen’s measurements was also observed. Sensitivity (SENS) and specificity (SPEC), Youden’s index and measures based on ROC curves showed no such sensitivity. The conclusions obtained may allow the avoidance of misjudging the predictive power of models built for both learning and business practice.
The aim of this paper is to bring together some of the foundational and recent literature interlinking corporate governance and the leadership role of the board of directors. Strategic leadership is widely assumed to be a responsibility that defaults to the Chief Executive Officers (CEOs). However, in practice, what most CEOs do is strategic management rather than strategic leadership. While strategic management does share key aspects of strategic leadership CEOs are expected to prioritize the managerial side over the leadership side. This is just one of the situations in which the board-room assumes the leadership role. This paper discusses how boards of directors conduct the process of strategic leadership in their organizations. In recent years there has been an increasing interest among scholars to understand how boards strategize from a behavioral point of view. This growing interest has resulted in the development of various typologies regarding boards’ involvement in the strategic leadership processes.
Problems associated with environmental pollution concern most large Polish cities. They are mainly caused by transport, municipal waste, emissions from the housing sector and from factories, particularly burdensome for the environment. Based on data related to the state and the protection of the natural environment and road transport, the author attempted to divide Polish cities with county (‘powiat’) rights into groups with different environmental features. Discriminatory analysis was used for the division. The highest average value of the discriminatory function was shown by the group with the most favourable environmental and social conditions. In subsequent groups, the environmental pollution grew more and more. In turn, classification functions of discriminatory analysis allowed for the assignment of individual cities to selected groups. Discriminatory analysis could therefore be used as a support tool for examining the state of the environment and environmental protection in cities with county rights. The goal of the work is to identify the diversity of environmental and communication conditions in Polish cities with county (‘powiat’) rights.
In the article an attempt is made to identify the quality of credit exposure determinants of banks in European Union countries that were characterized by a high level of impaired loans at the end of 2017 (Bulgaria, Croatia, Cyprus, Italy, Ireland, Greece, Portugal). Using the static panel-based approach the non-performing loan (NPL) determinants for the period from 2011 to 2017 were analyzed. The results showed that the high level of NPLs can be explained mainly by both macroeconomic and microeconomic factors. In particular, it has been shown that in the surveyed countries supervisory authorities should pay special attention to smaller banks with high dynamics of new loans and a low return on assets due to the fact that these entities are characterized by a higher NPL ratio. A higher level of NPL is also affected by a high concentration of the banking sector and higher interest rates on newly granted loans. As a result of research it was also shown that the majority of NPL determinants are the same in all types of banks, regardless of the business model and the scope of banking supervision. The differences were noticeable in characteristics regarding the housing market as well as the profitability of operations and lending dynamics of the analyzed entities.