Monitoring of a condition of economic systems on the basis of the analysis of dynamics of entropy

1. Monitoring of a condition of economic systems on the basis of the analysis of dynamics of entropy A.N. Tyrsin1, O.V. Vorfolomeeva2 1 – ScienceandEngineeringCenter «ReliabilityandResourceofLargeSystemsandMachines», UralBranch, RussianAcademyofSciences, Ekaterinburg 2 – Chelyabinsk Stat University, Chelyabinsk

2. Entropy role in difficult, open systems Prigogine I.: Bifurcation– turning point in system development: choice from several new conditions; bifurcations are provoked by change of the operating parameter of system, entropy increase. Overcoming of a point of bifurcation is accompanied by decrease in entropy, self-organization. KlimontovichU.L.: There is "a norm of a randomness"(entropy level) for normal functioning of system; deviations from norm mean "illness". If "treatment" approaches a condition of open system to norm, self-organization process takes place. -------------------------------------------------------------------- Entropy characterizes system functioning.

3. S -multidimensional random variable If the random vector Y has a multidimensional normal distributionthen

4. Entropy - probabilistic model Y2 Y3 Y1 Y5 Y4 System and its components: The Entropy - probabilistic model allows to allocate elements of difficult system and communication between them as separate variables H(Y2) H(Y1) H(Y3) H(Y5) H(Y4) growth points

5. Statement 1. Let X1, X2 - two continuous random variables with the finite variances, defined on the all numerical axis and described by one-type distributions. Then 12, 22, 1, 2 – variances and parameters of scale of random variables X1 и X2.

6. Example 1. 1) For normally distributed randomvariables X1andX2 with variances 12 and22the difference of entropiesis equal 2) For exponential distributed random variables X1andX2 with scale parameters1, 2 the difference of entropiesis equal 3) Let's consider random variablesX1andX2, distributed under the lognormalny law with parameters of scale, and form parameter s. Entropy for the lognormalny law with scale parameters  andformsis equalTaking into account that dispersion is equal, receive

7. Statement 2. Let we have two systems of continuous random variables and Then the difference of joint entropies of system of random variables is equal

8. where the coefficients of determination of the corresponding dependences

9. Denoting we will present the system as where ,  it is the increments of entropy at the expense of changes of dispersions and correlations of random variables .

10.  There are following ideas in economics that are underlay in the practical application of entropy-dynamic model:  • Hypothesis : The behavior of system can be considered as stochastic  • Formation of system of signs by means of the factorial analysis • Monitoring of a condition of system in dynamics (analysis of change of entropy) The analysis of entropy-dynamic model in economics

11. Example2.Let's consider the list of macroeconomic indicators from the section "Main Socio-economic Indexes of the Russian Federation" annually published by the State committee on statistics of the Russian Federation of collections "Russia in Figures" from 2000 to 2011. • It was established on the basis of the factorial analysis that the initial system can be represented in the form of three factors (main components) which are explained by 93,2% of all variation of initial signs. Factor: Y1 – national wealth, factorY2 – deficiency (surplus) of the budget taking into account a rate of national currency and unemployment rate in the country, factorY3 – price index of producers of the industry.

12. Then, let's carry out the comparative analysis of behavior of a macro system in two periods (before 2005 and after) on the basis of the analysis if entropy of a random vector. Then we will receive This result can testify to deterioration of macroeconomic indicators in the second period integrally, caused by the economic crisis in comparison with the fact that the first period was characterized by the growth of economic development of the country.

13. The analysis of change of each of a component shows that the growth of entropy of a randomness was affected mostly by the second element of the system (Y2) and on the increase in entropy of self-organization - weakening of the interaction between components Y1 and Y2.

14. Entropy modeling of dynamics of stochastic system is offered. In it's basis there is a representation of the system in the form of the random vector. Each of vector's components presents a continuous random variable. This approach allows solving problems of monitoring of the condition of stochastic systems in economics. • Entropy - dynamic model doesn't show quantitative change of studied parameters, but gives deeper assessment of influence of this change. For example, if it is known that any average value of a quantitative index went down, then with the help entropy – dynamic the dynamic model could answer whether this decrease was uniform and organized or not. • Entropy-dynamic model investigates the system fully. Results can be received both on separate elements of the system, and on the whole system that is almost impossible to analyze at a quantitative assessment of indicators of system. Conclusions: