Specialization of entrepreneurs in the production of goods and the provision of services in modern economies

The study of the sectoral characteristics of early-stage entrepreneurial activity is one of the topical issues in modern research. The aim of the study is to assess the existing level of specialization of nascent entrepreneurs in modern national economies. The source of information for the analysis of the industry specialization of nascent entrepreneurs was the data provided in the Global Entrepreneurship Monitor project. The research methodology involved economics modeling with normal density function. The result of the computational experiment is the assessment of the indicator values characterizing the involvement of nascent entrepreneurs in the production and service sectors of national economies. A comparative analysis of the values of indicators for Russia and the foreign countries was carried out. It has been proved that nascent entrepreneurs in the countries under consideration are on average 4 times more likely to start activities in the service sector than in the commodity producing sector.

Solving the one-warehouse N-retailers problem with stochastic demand: An inter-ratio policies approach

In this paper, we consider a two-echelon supply chain in which one warehouse provides a single product to N retailers, using integer-ratio policies. Deterministic version of the problem has been widely studied. However, this assumption can lead to inaccurate and ineffective decisions. In this research, we tackle the stochastic version of two-echelon inventory system by designing an extension of a well-known heuristic. This research considers customer demands as following a normal density function. A set of 240 random instances was generated and used in evaluating both the deterministic and stochastic solution approaches. Due to the nature of the objective function, evaluation was carried out via Monte Carlo simulation. For variable demand settings, computational experiments shows that: i) the use of average demand to define the inventory policy implies an underestimation of the total cost and ii) the newly proposed method offers cost savings.

Accumulated (integrated) interest and the square root process

Purpose The purpose of this study is to determine distributional properties of the accumulated rate of interest when the instantaneous rate of interest evolves in terms of the Cox et al. (1985) square root process. Design/methodology/approach The law of iterated (or double) expectations is used to determine the mean and variance of the accumulated rate of interest on a cash management (or loan) account when interest accumulates at the instantaneous rates of interest implied by the square root process. Findings This study demonstrates how the accumulated rate of interest does not satisfy the strong mixing conditions necessary for convergence in distribution to the normal density function. Originality/value This study has strong educational value in determining distributional properties of the accumulated rate of interest when the instantaneous rate of interest evolves in terms of the Cox et al. (1985) square root process and demonstrating how the accumulated rate of interest does not satisfy the strong mixing conditions necessary for convergence in distribution to the normal density function.

Location-scale matching for approximate quasi-order sampling

Quasi-orders are reflexive and transitive binary relations and have many applications. Examples are the dependencies of mastery among the problems of a psychological test, or methods such as item tree or Boolean analysis that mine for quasi-orders in empirical data. Data mining techniques are typically tested based on simulation studies with unbiased samples of randomly generated quasi-orders. In this paper, we develop techniques for the approximately representative sampling of quasi-orders. Polynomial regression curves are fitted for the mean and standard deviation of quasi-order size as a function of item number. The resulting regression graphs are seen to be quadratic and linear functions, respectively. The extrapolated values for the mean and standard deviation are used to propose two quasi-order sampling techniques. The discrete method matches these location and scale measures with a transformed discrete distribution directly obtained from the sample. The continuous method uses the normal density function with matched expectation and variance. The quasi-orders are constructed according to the biased randomized doubly inductive construction, however they are resampled to become approximately representative following the matched discrete and continuous distributions. In simulations, we investigate the usefulness of these methods. The location-scale matching approach can cope with very large item sets. Close to representative samples of random quasi-orders are constructed for item numbers up to n = 400.

On the normal moments distributions and its characterizations

Normal moment distribution is a family of elliptical density, the density which depends on the shape parameter \(\alpha\), such that when \(\alpha=0\), it corresponds to the normal density function. Several properties of this class of density function and characterizations are established.

Point-Symmetric Multivariate Density Function and Its Decomposition

For aT-variate density function, the present paper defines the point-symmetry, quasi-point-symmetry of orderk(<T), and the marginal point-symmetry of orderkand gives the theorem that the density function isT-variate point-symmetric if and only if it is quasi-point-symmetric and marginal point-symmetric of orderk. The theorem is illustrated for the multivariate normal density function.

GARCHSK Based Risk Assessment in Electric Power Industry

The restructuring/deregulation in electric power industry has heightened the importance of risk assessment. A model to estimate value-at-risk via GARCHSK specification is proposed, in which the seasonalities, heteroscedasticities, skewnesses, kurtosises and relationship to system loads are jointly addressed. The impacts of probability distribution assumption for innovations on value-at-risk estimate validation are analyzed for three distributions: normal, student-t and Gram-Charlier series expansion of the normal density function. The numerical example shows that the proposed model performs better in predicting one-period-ahead VaR.

On generalized measures of entropy and dependence

Various authors have studied extensions of Shannon’s entropy but their inferential properties and applications in applied sciences have not invited proper attention from researchers. In the present paper we explore the motivation and implication of using various classes of the generalized entropies and conditional entropies. We evaluate β-class and (α, β)-class entropies for multivariate normal density function. We also obtain the measures of dependence in terms of the classes of generalized entropies.