CHANGES IN THE INCOMES AND EXPENDITURES OF HOUSEHOLDS IN POLAND AND THEIR REGIONAL RELATIONS

The article assesses the financial situation of households in 2000-2019 in prospect of changes of incomes and expenditures in Poland. It has been assumed, as a point of reference, that dispersionof the analysed processes is dependent on geographical area– therefore regional scale was applied. To the analysis and comparison the data from the researches on households budgetsperformed by GUS were used. Adopting simultaneously an econometric approach (considering the time (years 2000-2019) as independent, explanatory variable) analytical trend functions wereestimated. A retrospective analysis of the incomes and expenditures of the population of Poland indicates the growing trends. Regional comparative analysis of households allows to drawconclusions that level of economic condition is very diversified.

Is the European Union Making Progress on Energy Decarbonisation While Moving towards Sustainable Development?

Three-quarters of global greenhouse gas emissions come from burning fossil fuels for energy. To confront climate change, the world must move away from fossil fuels and decarbonise its energy systems. In the light of European Union documents, decarbonisation signifies the elimination of CO2 emissions on account of their harmfulness to the environment. The European Union is planning that by 2030, these emissions will be 40% lower in comparison to 1990. A fundamental query arises here: do the achievements of EU countries give cause for optimism in this regard? The aim of the study is an attempt to determine the tendency of changes concerning energy decarbonisation as well as to distinguish typological groups of bodies (EU countries) with similar dynamics in the researched phenomenon. Trend functions and the distance matrices of the growth rate of the researched phenomenon were used for the dynamic classification. The conducted research confirmed that EU countries indicate spatial differentiation in terms of CO2 emissions. It is related to the general socio-economic development of countries, their level of industrialisation, the quality of their natural environment, their degree of urbanisation, etc. The most favourable situation, in terms of the analysed phenomenon, i.e., the largest average decrease in CO2 per capita in the analysed period, was characteristic of Ireland, Greece, and Cyprus. On the other hand, an adverse situation relating to an increase in the indicator occurred in five EU countries, specifically in Luxembourg and Lithuania.

The Stochastic Modified Lundqvist-Korf Diffusion Process: Statistical and Computational Aspects and Application to Modeling of the CO2 Emission in Morocco

The main goal of this paper is to study the possibility of using a stochastic non-homogeneous (without exogenous factors) diffusion process to model the evolution of CO2 emissions in Morocco and concretely using a new process, in which the trend function is proportional to the modified Lundqvist-Korf growth curve. First, the main characteristics of the process are studied, then we establish a computational statistical methodology based on the maximum likelihood estimation method and the trend functions. When we are estimating the parameters of the process, a non-linear equation is obtained and the simulated annealing method is proposed to solve it after bounding the parametric space by a stagewise procedure. Also, to validate this methodology, we include the results obtained from several examples of simulation. Finally, the process and the methodology established are applied to real data corresponding to the evolution of CO2 emissions in Morocco.

Stochastic Diffusion Process Based on Generalized Brody Curve: Application to Real Data

A new stochastic diffusion process based on Generalized Brody curve is proposed. Such a process can be considered as an extension of the nonhomogeneous lognormal diffusion process. From the corresponding Itô’s stochastic differential equation (SDE), firstly we establish the probabilistic characteristics of the studied process, such as the solution to the SDE, the probability transition density function and their distribution, the moments function, in particular the conditional and non-conditional trend functions. Secondly, we treat the parameters estimation problem by using the maximum likelihood method in basis of the discrete sampling, thus we obtain nonlinear equations that can be solved by metaheuristic optimization algorithms such as simulated annealing and variable search neighborhood. Finally, we perform a simulation studies and we apply the model to the data of life expectancy at birth in Morocco.

A Stochastic Lomax Diffusion Process: Statistical Inference and Application

In this paper, we discuss a new stochastic diffusion process in which the trend function is proportional to the Lomax density function. This distribution arises naturally in the studies of the frequency of extremely rare events. We first consider the probabilistic characteristics of the proposed model, including its analytic expression as the unique solution to a stochastic differential equation, the transition probability density function together with the conditional and unconditional trend functions. Then, we present a method to address the problem of parameter estimation using maximum likelihood with discrete sampling. This estimation requires the solution of a non-linear equation, which is achieved via the simulated annealing method. Finally, we apply the proposed model to a real-world example concerning adolescent fertility rate in Morocco.

Constrained multi-fidelity surrogate framework using Bayesian optimization with non-intrusive reduced-order basis

This article addresses the problem of constrained derivative-free optimization in a multi-fidelity (or variable-complexity) framework using Bayesian optimization techniques. It is assumed that the objective and constraints involved in the optimization problem can be evaluated using either an accurate but time-consuming computer program or a fast lower-fidelity one. In this setting, the aim is to solve the optimization problem using as few calls to the high-fidelity program as possible. To this end, it is proposed to use Gaussian process models with trend functions built from the projection of low-fidelity solutions on a reduced-order basis synthesized from scarce high-fidelity snapshots. A study on the ability of such models to accurately represent the objective and the constraints and a comparison of two improvement-based infill strategies are performed on a representative benchmark test case.

ENVIRONMENTAL EXPENSES IN MUNICIPAL BUDGETS IN POLAND IN THE CONTEXT OF ASPIRING TO BECOMING A SMART, SUSTAINABLE CITY

Environmental protection is one of the key priorities of sustainable development. Nowadays, in contemporary economies and organizations it is also the basic component of development strategies. Unfortunately, its real implementation is associated with significant financial expenses and long-term payback period and as a result - in fact - it often becomes only the basic component of media and marketing strategies. Therefore, the main aim of this article is to analyse the scope and changes of environmental expenses in the municipal budgets in Poland as one of the conditions for becoming a smart community or smart city. The research includes financial statistics of 2,477 municipal communities in Poland from the period of 2003-2018 and the research questions are: 1) What were the tendencies in the environmental expenses, their level and their share in the municipal budgets for the analysed period, and (2) how could these tendencies be identified in the context of creating a smart community or smart city? The used methodology is based on budget statistical data from 2003-2018 and includes structure and dynamics indices as well as trend functions.

Stochastic Brennan–Schwartz Diffusion Process: Statistical Computation and Application

In this paper, we study the one-dimensional homogeneous stochastic Brennan–Schwartz diffusion process. This model is a generalization of the homogeneous lognormal diffusion process. What is more, it is used in various contexts of financial mathematics, for example in deriving a numerical model for convertible bond prices. In this work, we obtain the probabilistic characteristics of the process such as the analytical expression, the trend functions (conditional and non-conditional), and the stationary distribution of the model. We also establish a methodology for the estimation of the parameters in the process: First, we estimate the drift parameters by the maximum likelihood approach, with continuous sampling. Then, we estimate the diffusion coefficient by a numerical approximation. Finally, to evaluate the capability of this process for modeling real data, we applied the stochastic Brennan–Schwartz diffusion process to study the evolution of electricity net consumption in Morocco.

A novel improvement of Kriging surrogate model

Purpose This paper aims to introduce a method based on the optimizer of the particle swarm optimization (PSO) algorithm to improve the efficiency of a Kriging surrogate model. Design/methodology/approach PSO was first used to identify the best group of trend functions and to optimize the correlation parameter thereafter. Findings The Kriging surrogate model was used to resolve the fuselage optimization of an unmanned helicopter. Practical implications The optimization results indicated that an appropriate PSO scheme can improve the efficiency of the Kriging surrogate model. Originality/value Both the STANDARD PSO and the original PSO algorithms were chosen to show the effect of PSO on a Kriging surrogate model.