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Bayesian dynamic stochastic general equilibrium model of Kazakhstan

Authors: Shults D.N.;

Bayesian dynamic stochastic general equilibrium model of Kazakhstan

Abstract

The article presents dynamic stochastic general equilibrium model of Kazakhstan and its parameters estimation by Bayesian methods. A feature of DSGE-approach is the use of the neo-Keynesian microeconomic foundation, which allows describing the behavior of key economic actors and taking into account the main market failures (imperfect markets and sticky prices). In addition, DSGE-models are based on the theory of rational expectations. The model is a system of 15 linearized equations for key macroeconomic indicators of the main economic sectors: households, enterprises, the National Bank, and the external sector. The model describes the economy in the short term (excluding investments in fixed assets), in the inflation targeting mode with a floating exchange rate. Parameters were evaluated by Bayesian methods. The advantage of this approach is the possibility to estimate parameters on short time series due to the use of prior information. This is important in the conditions of structural changes. Scenario calculations were performed on the estimated parameters for aggregate factor productivity shocks and aggregate demand shocks, for prices shock and for an increase in external interest rates. The results can be used for the development of monetary policy and optimization of its parameters. The results can also be used as a foundation for building applied QPM models.

Keywords

Accounting. Bookkeeping, Economics as a science, HF5601-5689, dynamic stochastic general equilibrium models, HG1-9999, inflation targeting., Marketing. Distribution of products, HF5410-5417.5, HB71-74, Finance, bayesian estimation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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