Analysis of heterogeneity of inflation expectation based on genetic algorithm and time series model

被引:0
作者
Tan, Haoyang [1 ]
Zhang, Qiang [1 ]
机构
[1] Hunan Univ, Sch Finance & Stat, Changsha, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Genetic algorithm; inflation; simulation experiment; data mining; heterogeneity; UNCERTAINTY; DYNAMICS; PRICE;
D O I
10.3233/JIFS-189487
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:6481 / 6491
页数:11
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