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Modeling of Expectations in the Systems with Heterogeneous Agents in the Presence of Shadow Economy

Author:

Leonid A. Serkov and Dmitry B. Yelizarov

Abstract:

The paper investigates the influence of an informal sector of economy on the dynamic stochastic general equilibrium models (DSGE–models) with heterogeneous agents using the algorithm of formation of expectations associated with agent learning by trial and error. The authors study a neoclassical DSGE–model with two sectors of economy, namely legal and shadow ones, exposed to aggregate productivity shocks. The model describes an economy with incomplete markets, aggregate uncertainty and an infinite number of heterogeneous economic agents (households and firms). The source of heterogeneity is idiosyncratic shocks of the agents’ revenues. The authors test the parameters of the model on the statistics on the Russian economy and compare the constructed model with a similar one with representative agents. They prove that the quality of the developed model is higher than the quality of the models with representative agents. Finally, the authors examine the impact of the factors of informal sector on the volatility of variables in the model.

Keywords: shadow economy; heterogeneous agents; expectations; learning by trial and error.

For citation:

Serkov L.A., Yelizarov D.B. Modelirovanie ozhidaniy v sistemakh s geterogennymi agentami pri nalichii tenevogo sektora ekonomiki [Modeling of expectations in the systems with heterogeneous agents in the presence of shadow economy]. Izvestiya Uralskogo gosudarstvennogo ekonomicheskogo universiteta – Journal of the Ural State University of Economics, 2017, no. 2 (70), pp. 17–26.