A Version of a Dynamic Stochastic General Equilibrium Model for an Open Economy

Baluta, Victor Ivanovich; Шульц, Д Н

doi:10.1134/s207004822004002x

Cited by 2 publications

(1 citation statement)

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“…where θ is a parameter reflecting the propensity of the population to diversify the consumer basket; δ is a parameter that takes into account the share of imports in the consumer basket and the ratio of prices for imported goods to the cost of the consumer basket [53] (pp. 362-364), [54] (p. 121).…”

Section: Relationship Between Regionsmentioning

confidence: 99%

Constructing a Region DSGE Model with Institutional Features of Territorial Development

2022

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The growing importance of regional units in national economies gives rise to the objective need to improve the tools of spatial management. The construction of realistic development scenarios and forecasts is possible on the basis of the DSGE models’ tools. At the same time, models of a similar class that describe socio-economic processes at the level of the regional economy are practically not represented in modern studies. The purpose of the paper is to build a model of the regional economy based on DSGE tools. A feature of the proposed model is the consideration of spatial features through budget expenditures on the digitalization of such areas as healthcare and education. The high importance of these costs became evident during the COVID-19 crisis, when the consequences of underfunding IT costs in education and healthcare led to slowing economic growth. We have allocated health and education expenses in the standard budget limit of the regional government. On the basis of the developed model, response functions for shocks of exogenous variables for 20 periods were built. The result of the simulation is the response functions of endogenous variables in response to the fading growth in the share of spending on human capital in the region, as well as the obtained values of elasticities for a single change in shocks.

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Section: Relationship Between Regionsmentioning

confidence: 99%