APPLICATION OF STOCHASTIC DIFFERENTIAL EQUATIONS IN POPULATION GROWTH

Abstract

Population is a key macroeconomic indicator which plays an important role in decision making, social security and economic growth. So it is important to predict the dynamics of population using various mathematical models. Population is described as a function of time usually by dynamic models based on differential equations. The most common practical methods are component, exponential and logistic models. On the other hand, the population growth can be considered as stochastic variables since a number of population depends on social and economic policies, political stability and so on. In this work, we first examine the existing population models such as exponential and logistic model. Then we consider the corresponding stochastic models for population growth, compare these methods using Monte Carlo simulation and predict the dynamics of Mongolian population up to 2035 year by the methods.