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Nonlinear Models Used to Analyze the Relation between Inflation and Unemployment

Many mathematical models have been developed in the last years in order to analyze economic phenomena and processes. Some of these models are optimization models, static or dynamic, while others are developed specially to study the evolution of economic phenomena. The topic of this paper is forecasting with nonlinear models. A few well-known nonlinear models are introduced, and their properties are discussed. The variety of nonlinear relationships is important both from the perspective of estimation and from the precision of forecasts in the medium and especially long term. Most nonlinear forecasting methods and all methods based on neural networks lead to predictions that have a better quality than the forecasts obtained by linear methods. The last section of this paper contains a detailed study of the relationship between inflation and unemployment and a numerical application with numerical data from Romania.