ECONOMIC GROWTH MODELING UNDER UNCERTAINTY OF MACROECONOMIC FACTORS: HISTORY REVIEW, PROBLEMS AND PROSPECTS
This article contains a historical overview of main methods dealing with uncertainty in macroeconomic modeling of economic growth in the second half of XX - beginning of XXI century as well as the problems and prospects of its development at the moment. The article highlights five phases of approaches to modeling uncertainty of economic growth. The first stage involves the theory of adaptive expectations developed in the first half of 1950s, while second stage - the simplest formulation of stochastic growth models in the early 1970s. During the third stage (mid 1980s), the real business cycle models were elaborated, in which productivity shocks are considered as random variables; fourth stage covers end of XX - beginning of XXI century when multi-period stochastic models of economic interaction between the closed and the small open economies were developed. The fifth stage includes modern dynamic stochastic general equilibrium models, based on development of RBC-models and the new Keynesian theory. Hypothesis on approximation of unknown or uncertain factors in the economic growth models using stochastic processes is tested; problems of analysis and application of stochastic models for forecasting economic growth are distinguished.