Artificial Neural Networks in Inflation Forecasting at the Meso-Level
Irina Astrakhantseva, Anna Kutuzova, Roman Astrakhantsev
Abstract
The aim of the article is to analyze inflation factors and their influence on the consumer price index in the regions. The article discusses the existing mathematical models for the forecasting of the regional inflation rate as an important national measure. Advantages, disadvantages and application fields of these models are presented. The appropriateness of recurrent neural network use for regional inflation forecasting is demonstrated. The article describes the process of neural network architecture creation, its training, inflation parameter forecasting.
Topics & Concepts
Inflation (cosmology)Artificial neural networkIndex (typography)Computer scienceConsumer price index (South Africa)Measure (data warehouse)Inflation rateEconomic forecastingEconometricsProcess (computing)Price indexEconomicsArtificial intelligenceMacroeconomicsInterest rateData miningMonetary policyWorld Wide WebOperating systemPhysicsTheoretical physicsEnergy Load and Power ForecastingMonetary Policy and Economic ImpactStock Market Forecasting Methods