Index of the Economic Interaction Effectiveness. between the Natural Monopoly and Regions. I. Math Model

Similar documents
Solutions of Bimatrix Coalitional Games

New Proposed Uniform-Exponential Distribution

Equivalence between Semimartingales and Itô Processes

A Skewed Truncated Cauchy Logistic. Distribution and its Moments

On Stochastic Evaluation of S N Models. Based on Lifetime Distribution

Effect of Administrative Control Procedures to Efficiency of Organization Management

Analysis of Volatility Spillover Effects. Using Trivariate GARCH Model

Option Pricing Model with Stepped Payoff

Applied Mathematical Sciences, Vol. 8, 2014, no. 1, 1-12 HIKARI Ltd,

A New Look at the Final Period Decay of. Homogeneous Isotropic Turbulence

Homomorphism and Cartesian Product of. Fuzzy PS Algebras

Optimization of Integration Model in. Family Takaful

The Moroccan Labour Market in Transition: A Markov Chain Approach

On a Manufacturing Capacity Problem in High-Tech Industry

The differentiated assessment of damage to economy of subjects of the Siberian Federal District from road and transport accident rate

Comparison of Decision-making under Uncertainty Investment Strategies with the Money Market

Budget Setting Strategies for the Company s Divisions

Two hours. To be supplied by the Examinations Office: Mathematical Formula Tables and Statistical Tables THE UNIVERSITY OF MANCHESTER

A Comparison of Univariate Probit and Logit. Models Using Simulation

Class 12. Daniel B. Rowe, Ph.D. Department of Mathematics, Statistics, and Computer Science. Marquette University MATH 1700

Income and Wealth Status of Russian and Tomsk Region s Pensioners

Mechanism of formation of the company optimal capital structure, different from suggested by trade off theory

Econometric Analysis of the Mortgage Loans Dependence on Per Capita Income

Establishment of Risk Evaluation Index System for Third Party Payment in Internet Finance

SAMPLE STANDARD DEVIATION(s) CHART UNDER THE ASSUMPTION OF MODERATENESS AND ITS PERFORMANCE ANALYSIS

BFO Theory Principles and New Opportunities for Company Value and Risk Management

Modern Trends of Interaction of Real and Banking Sectors in Conditions of Modernization Russian Economy

Youngrok Lee and Jaesung Lee

The Golden Age of the Company: (Three Colors of Company's Time)

Optimization of Rescheduling and Economy. Analysis of the Implementation of Kwitang Office. Park Building Construction Project in Jakarta

2. ANALYTICAL TOOLS. E(X) = P i X i = X (2.1) i=1

Class 16. Daniel B. Rowe, Ph.D. Department of Mathematics, Statistics, and Computer Science. Marquette University MATH 1700

Two Hours. Mathematical formula books and statistical tables are to be provided THE UNIVERSITY OF MANCHESTER. 22 January :00 16:00

Inflation in Brusov Filatova Orekhova Theory and in its Perpetuity Limit Modigliani Miller Theory

Valencia. Keywords: Conditional volatility, backpropagation neural network, GARCH in Mean MSC 2000: 91G10, 91G70

EX-POST VERIFICATION OF PREDICTION MODELS OF WAGE DISTRIBUTIONS

Journal of Economics Studies and Research

Hyperidentities in (xx)y xy Graph Algebras of Type (2,0)

A.O. Baranov, V.N. Pavlov

Early Retirement Incentives and Student Achievement. Maria D. Fitzpatrick and Michael F. Lovenheim. Online Appendix

Factor Analysis Aspects of the Enterprise s Operating Leverage

Open Access Asymmetric Dependence Analysis of International Crude Oil Spot and Futures Based on the Time Varying Copula-GARCH

MULTISTAGE PORTFOLIO OPTIMIZATION AS A STOCHASTIC OPTIMAL CONTROL PROBLEM

Stochastic Runge Kutta Methods with the Constant Elasticity of Variance (CEV) Diffusion Model for Pricing Option

Generalising the weak compactness of ω

Time Series Modelling on KLCI. Returns in Malaysia

SOLVENCY AND CAPITAL ALLOCATION

UNBIASED INVESTMENT RISK ASSESSMENT FOR ENERGY GENERATING COMPANIES: RATING APPROACH

Aspects Concerning Modelling of a Risk-Free Investment in the Equity of a Company

An application of Ornstein-Uhlenbeck process to commodity pricing in Thailand

Neural Network Prediction of Stock Price Trend Based on RS with Entropy Discretization

Chapter 2 Uncertainty Analysis and Sampling Techniques

Analysis on the Input-Output Relevancy between China s Financial Industry and Three Major Industries

Probabilistic Analysis of the Economic Impact of Earthquake Prediction Systems

KE2 MCQ Questions. Identify the feasible projects Alpha can select to invest.

Optimal Production-Inventory Policy under Energy Buy-Back Program

Lecture 17 Option pricing in the one-period binomial model.

SOCIAL AND ECONOMIC CONSEQUENCES OF BANKRUPCY OF THE COMPANIES IN UKRAINE

Notes on a Basic Business Problem MATH 104 and MATH 184 Mark Mac Lean (with assistance from Patrick Chan) 2011W

Computing Cost and Accounting Challenges for Octoshell Management System

Optimization Methods in Management Science

Time Observations Time Period, t

About Black-Sholes formula, volatility, implied volatility and math. statistics.

Research Article A Mathematical Model of Communication with Reputational Concerns

Chapter 15: Jump Processes and Incomplete Markets. 1 Jumps as One Explanation of Incomplete Markets

A Study on the Relationship between Monetary Policy Variables and Stock Market

Return Determinants in a Deteriorating Market Sentiment: Evidence from Jordan

Probabilistic models for risk assessment of disasters

Insurance as a factor affecting the effectiveness of the financial mechanism of the governing structures

Research Article Welfare Comparison of Leader-Follower Models in a Mixed Duopoly

PROFITABILITY AND PRODUCTIVITY OF BANK OF INDIA

Examiner s Report. December 2017 Session. Paper 4 Business Economics and Financial Mathematics

Pricing double Parisian options using numerical inversion of Laplace transforms

Computational Independence

Version A. Problem 1. Let X be the continuous random variable defined by the following pdf: 1 x/2 when 0 x 2, f(x) = 0 otherwise.

DM559/DM545 Linear and integer programming

Pricing of a European Call Option Under a Local Volatility Interbank Offered Rate Model

Social and Economic Activity of the Elder Generation in Tomsk Region

Irvine Unified School District

Tax control over legal entities in the Russian Federation Tufetulov A.M. 1, Salmina S.V. 1, Nugaev F.S. 1

How to Measure Herd Behavior on the Credit Market?

Economic Decision Making Using Fuzzy Numbers Shih-Ming Lee, Kuo-Lung Lin, Sushil Gupta. Florida International University Miami, Florida

Chapter 7.2: Large-Sample Confidence Intervals for a Population Mean and Proportion. Instructor: Elvan Ceyhan

ImpactofDefenseExpenditureonEconomicGrowthTimeSeriesEvidencefromPakistan

Impact of Market Concentration on the Growth of Selected Manufacturing industries in India using Mauldon Distribution

Optimization of corrosion protection economics

ESTIMATING THE SIZE OF ROMANIAN SHADOW ECONOMY. A LABOUR APPROACH

FURTHER ASPECTS OF GAMBLING WITH THE KELLY CRITERION. We consider two aspects of gambling with the Kelly criterion. First, we show that for

OPTIMAL PORTFOLIO CONTROL WITH TRADING STRATEGIES OF FINITE

Computing and Graphing Probability Values of Pearson Distributions: A SAS/IML Macro

Predicting the Market

Research Article Portfolio Optimization of Equity Mutual Funds Malaysian Case Study

A micro-analysis-system of a commercial bank based on a value chain

Journal of Science and today's world 2013, volume 2, issue 1, pages: 58-72

P2P-loans, prospects and risks application in the Russian Federation

3.1 Measures of Central Tendency

VARIATIONAL METHODS OF FORMING DEPRECIATION DEDUCTIONS

The Asymptotic Shapley Value for a Simple Market Game

Binomial Mixture of Erlang Distribution

Solutions for practice questions: Chapter 15, Probability Distributions If you find any errors, please let me know at

Transcription:

Applied Mathematical Sciences, Vol. 7, 2013, no. 124, 6181-6185 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/ams.2013.39522 Index of the Economic Interaction Effectiveness between the Natural Monopoly and Regions. I. Math Model Irina Nizovtseva Ural Federal University Office 607, Turgeneva str. 4, Ekaterinburg, Russia, 620075 Nizovtseva.irina@gmail.com Copyright 2013 Irina Nizovtseva. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract In this paper, we proposed option indicator that determines the quality of the interaction regions with natural monopolies. In fact, assessing the effect of the implementation of projects of the program interaction. Evaluation is carried out from the point of view of natural monopoly. Keywords: Natural monopoly, interaction index 1 Introduction Throughout the development of economic science many scientists were dealing with improving the methods of cost-effectiveness analyses of investments into projects. Fairly complete survey of these methods can be found in the researches [1-4]. The proposed in this research effectiveness ratio and the method of its determination are free from this major disadvantage. The effectiveness ratio except financial profitability indexes of the invested project (or a group of interrelated projects) also includes the most important stability factors of the invested enterprise, its reliability and, in addition, it allows considering the extent

6182 Irina Nizovtseva of linkage among the invested project and other projects and regional programs, their influence and interdependence. 2 Elementary model Let s consider the simplest case of the relationships among the sandwich-model (layered model) elements when interaction takes place within the selected elementary tube between two economic entities nodes and, lying on the different functional planes the natural monopoly plane and the other economic entities plane, fig. 1. Fig. 1.An elementary tube. The simplest case. Let s describe a considered situation. The node stimulates the company s development project. Stimulation is carried out by means of intersubjective funds redirection that this region is bound to the node in the form of compensations, for instance, for passenger transfer or for the low-density lines content or for other social-important programs realization. It is obvious that, in particular, the latter can be implemented by the node in order to get an opportunity of participation into the commercial projects involving enterprises of this region. Participation of the node in such projects will seem appropriate only if on the one hand, it meets the requirements of the natural monopoly in this region and, on the other hand, can recover the incurred costs and also bring additional revenue. One form of such participation can be a transmission of enterprise bonds from entity government to the node. These bonds were issued in order to raise funds for the development of production with bonds redemption after time T and one-time payment of loan interest. The volume of such indirect investments is, the lending interest rate is % and the total amount of the refund loan (considering loan interest) is.

Index of the economic interaction effectiveness 6183 3 Economic interaction effectiveness index The economic-mathematical requirements to the definable coefficient k from the point of view of the node (i.e. the natural monopoly) are the following: 1. 01 is the effectiveness ratio normalization; 2. Let is the time of indirect lending. The smaller is, the greater value of the effectiveness ratio k should be. 3. Let is the volume of indirect landing in rubles, - the refund amount (including the interest) after the time of the indirect lending expected by the node, μ is the expected (forecasted) inflation rate (so μ is really refundable funds volume in the current price level). Thus, the revenue from indirect lending of the node is: μ The greater the direct revenue from such redirection is, the greater value of the effectiveness ratio should be. 4. Let is the stability factor of the involved enterprise. The greater the stability factor is, the greater value of the effectiveness ratio should be. 5. Let Δ is the total increase of the produced production volume at the invested enterprise planned in the result of project implementation. Therefore Δ is the increase of the produced production volume at the enterprise per unit of time (for example, per year) expected from the project implementation. Here is the volume of the produced production at the enterprise after project implementation, is the initial volume of the output. The value is the aftereffect, the measure of the expected benefits to the node from the project implementation with the node participation. The greater the measure of the aftereffect is, the greater the effectiveness ratio k should be. 6. Let is the possible guaranteed income from the alternative funds placement required to redirection of funds in a project of the enterprise. 7. Let 01 is a dimensionless coefficient, i.e. the extent of linkage the invested project with other projects and programs of the region. The coefficient of the extent of linkage reflects the extent of the directive influence

6184 Irina Nizovtseva (pressure) to the natural monopoly by the regional authorities insisting on the indirect investment of the node. The method of determination the coefficient of the extent of linkage is the subject of the following researches. It is natural that the greater the coefficient of linkage λ is, the greater the effectiveness coefficient should be. The formula, satisfying all formulated above economic-mathematical requirements, for determination the effectiveness coefficient is proposed below: 1 α Δ 1 α Δ 1 1λ 2 Where is the depth of forecast (range of planning) expressed in the number of the reporting units (periods) of time of the covered perspective. (For instance, 10 years); α is any introduced by us dimensionless coefficient of the extent of importance of the aftereffect from the implementation the project for the node, i.e. the coefficient showing the significance (importance, urgency) that we attach to the aftereffect. For different projects and industrial problems index α can vary in dependence, for example, from the kind of produced production by the enterprise (It is required just deliver production to a consumer or the natural monopoly is interested in this production too, i.e. for the natural monopoly this production is strategically important). α Δ is the total benefit from funds redirection to the project (the node ), i.e. the profit calculated from the standpoint of the node - the natural monopoly. The summation in this formula is made by the number of reporting periods; the stability of the project implementer, i.e. the node. (see, for ex. [1, 5-9]) References [1] S. Vikharev, Comparative vendor score, Applied Mathematical Sciences, 7, 2013, 4949-4952. [2] A. Sheka, Verification and validation of the comparative vendor score, Applied Mathematical Sciences, 7, 2013, 4953-4959. [3] S. Vikharev. Mathematical modeling of development and reconciling cooperation programs between natural monopoly and regional authorities Applied Mathematical Sciences, Vol. 7, 2013, no. 110, 5457-5462. http://dx.doi.org/10.12988/ams.2013.38454

Index of the economic interaction effectiveness 6185 [4] S. Vikharev. Verification of mathematical model of development cooperation programs between natural monopoly and regional authorities. Applied Mathematical Sciences, Vol. 7, 2013, no. 110, 5463-5468. http://dx.doi.org/10.12988/ams.2013.38463 [5] S. Vikharev. Mathematical model of the local stability of the enterprise to its vendors //Applied Mathematical Sciences, Vol. 7, 2013, no. 112, 5553-5558 http://dx.doi.org/10.12988/ams.2013.38465 [6] I. Nizovtseva. The generalized stability indicator of fragment of the network. I. Modeling of the corporate network fragments. Applied Mathematical Sciences, Vol. 7, 2013, no. 113, 5621-5625. http://dx.doi.org/10.12988/ams.2013.38471 [7] I. Nizovtseva. The generalized stability indicator of fragment of the network. II Critical performance event. Applied Mathematical Sciences, Vol. 7, 2013, no. 113, 5627-5632. http://dx.doi.org/10.12988/ams.2013.38472 [8] A. Sheka. The generalized stability indicator of fragment of the network. III Calculating method and experiments. Applied Mathematical Sciences, Vol. 7, 2013, no. 113, 5633-5637. http://dx.doi.org/10.12988/ams.2013.38473 [9] A. Sheka. The generalized stability indicator of fragment of the network. IV Corporate impact degree. Applied Mathematical Sciences, Vol. 7, 2013, no. 113, 5639-5643. http://dx.doi.org/10.12988/ams.2013.38474 Received: September 11, 2013