Affiliations: School of Finance and Statistics, Hunan University, Changsha, Hunan, China
Correspondence:
[*]
Corresponding author. Haoyang Tan, School of Finance and Statistics, Hunan University, Changsha, Hunan, China. E-mail: tlltjay@protonmail.com.
Abstract: The heterogeneity of inflation expectations, especially the residents’ inflation expectations, has a great influence on controlling the actual inflation rate and the effective implementation of my country’s monetary policy. In the process of monetary policy formulation, the monetary authorities need to pay more attention to the heterogeneous expectations among microeconomic individuals. This paper introduces the genetic algorithm, a new artificial intelligence method, to analyze the demand for the heterogeneity of inflation expectations and explains the basic steps to use it and how to apply it to explain problems in economics. Moreover, this paper uses a genetic algorithm-based generation overlap model to simulate the dynamic evolution of inflation heterogeneity among residents and the equilibrium selection process of price levels in a wide search space. The results of the simulation experiment show that it is of practical significance to use genetic algorithms to simulate the dynamic process of the heterogeneity of residents’ inflation expectations.
Keywords: Genetic algorithm, inflation, simulation experiment, data mining, heterogeneity
