Constructing a Region DSGE Model with Institutional Features of Territorial Development

Dubrovskaya, Julia; Шульц, Д Н; Kozonogova, Elena

doi:10.3390/computation10070105

Cited by 4 publications

(3 citation statements)

References 43 publications

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“…The empirical analysis of economic growth is associated with three problems: variable selection, connected with different economic growth theories; parameter heterogeneity, determined according to different levels of the development of countries; and cross-sectional dependence, caused by latent general shocks, spatial features and interactions [42,43].…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling the Spatial Effects of Digital Data Economy on Regional Economic Growth: SAR, SEM and SAC Models

Varlamova

Кадочникова

2023

Mathematics

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The potential for the development of digital data and their infrastructure creates new opportunities for economic growth. The purpose of this study was to develop an approach to identify a set of indicators to quantify the data economy and model its impact on economic growth. The cumulative index and Gini coefficient indicated differentiation and disparity in the digital data infrastructure of 85 regions for 2016–2021. In the presence of a positive spatial correlation, digital development does not indicate clear spatial clubs. Selected according to the calculation of Lagrange multipliers and likelihood ratios, panel econometric models with spatial lags, using SAR, SEM and SAC, showed a short-term negative effect and a long-term positive effect of the digital data economy on economic growth, confirmed by the calculation of marginal effects. During the pandemic, the data economy had a positive impact on regional economic growth. The positive spatial effect of interactions between regions detected by the models in the framework of economic growth indicates the synergistic nature of digitalization. The main conclusions of this study provide evidence-based support for the digital transformation of regions and can help create information infrastructure and accumulate human capital to eliminate disparities in the digital development of regions.

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Section: Literature Reviewmentioning

confidence: 99%

Modeling the Spatial Effects of Digital Data Economy on Regional Economic Growth: SAR, SEM and SAC Models

Varlamova

Кадочникова

2023

Mathematics

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“…Furthermore, the shock of environmental expenditures in a local area can well explain the volatility of social investment and real output in China, but shocks of environmental expenditures in external regions had little contribution to the volatility of investment and production in local areas. Dubrovskaya et al (2022) also presents an extended version of the dynamic stochastic general equilibrium model for the conditions of the regional economy. Interaction modeling was carried out between the two regions.…”

Section: Review Of the Literaturementioning

confidence: 99%

Measuring national policy impacts in a region: SAMBA+REG

Penna,

Osterno,

Barreto

et al. 2023

Estud. Econ.

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This article presents an empirical methodology for analyzing the propagation of aggregate shocks across regions. While focusing on the specific case of Brazil and Ceará, the proposed methodology can be easily adapted to examine other regions as well. We develop a dynamic model, termed SAMBA+REG, which complements the Central Bank of Brazil’s dynamic stochastic general equilibrium model (SAMBA) by incorporating regional elements. This theoretical framework allows us to explore how aggregate shocks impact a specific region. We conduct simulations using fiscal and monetary shocks and the results align with the existing literature. SAMBA+REG not only facilitates the evaluation of the effects of central government economic policies on a regional economy, but also offers insights into various strategies for state governments to respond effectively to these policies.

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“…In recent decades, theoretical contributions to macroeconomics have mainly been based on dynamic stochastic general equilibrium models (DSGE models) with rational expectations, where a representative agent is able to understand the complexity of the underlying mathematical model [1][2][3]. The advantage of these models is, firstly, that they have microeconomic justifications, that is, it is assumed that consumers maximize the expected discounted sum of utility function values, and producers maximize their profits in dynamics.…”

Section: Introductionmentioning

confidence: 99%

The Specific Behavior of Economic Agents with Heterogeneous Expectations in the New Keynesian Model with Rigid Prices and Wages

Serkov

Krasnykh

2023

Mathematics

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The purpose and scientific novelty of this work is to analyze the changes and features of economic agents’ behavior when incorporating wage rigidity into a new Keynesian model under cognitive constraints of agents. The working hypothesis is the assumption that the forecasting of the output gap, inflation of prices and wages occurs with the help of fundamentalist and extrapolation rules. The first rule is based on forecasting the variables under study on the basis of their stationary values. The second rule is based on extrapolation of the latest available data on inflation and the output gap. The weight shares of agents applying these heuristic rules change endogenously, which is the source of endogenous waves of optimism and pessimism. An analysis of the impulse responses of interest rate and technology shocks suggests that a more flexible economy (an economy with flexible wages and rigid prices) is less prone to a spike in the economic cycle caused by waves of optimism and pessimism than a more rigid economy (an economy with rigid prices and wages) due to the inability of agents to respond immediately to exogenous disturbances in rigid conditions. Thus, these shocks cause wave effects in the economy, i.e., cyclical movements, i.e., a rigid economy will be more prone to booms and busts caused by alternating optimism and pessimism than a flexible economy. The model with an imperfect labor market is characterized by an increased concentration of vital forces at the values of 0 and 1, as well as in the mid-distribution compared to the base model. This feature provides a key explanation for the abnormal dynamics of the evolution of variables in this model. It is concluded that the difference between the degree of optimism and pessimism in the base model and in the model with rigid wages and prices is the full trust of agents in the central bank in targeting wage inflation in the absence of the stabilization of this inflation by the bank.

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Constructing a Region DSGE Model with Institutional Features of Territorial Development

Cited by 4 publications

References 43 publications

Modeling the Spatial Effects of Digital Data Economy on Regional Economic Growth: SAR, SEM and SAC Models

Modeling the Spatial Effects of Digital Data Economy on Regional Economic Growth: SAR, SEM and SAC Models

Measuring national policy impacts in a region: SAMBA+REG

The Specific Behavior of Economic Agents with Heterogeneous Expectations in the New Keynesian Model with Rigid Prices and Wages

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