基于季度预测模型的区域指标预测

Alyona Nelyubina
{"title":"基于季度预测模型的区域指标预测","authors":"Alyona Nelyubina","doi":"10.31477/RJMF.202102.50","DOIUrl":null,"url":null,"abstract":"The paper presents a semi-structural model of a regional economy based on the standard version of the neo-Keynesian model in gaps. The main feature of this tool is its ability to predict regional indicators and model the regional heterogeneity of the national economy. In our model, Russia is divided into two macro-regions: the Central Federal District and the rest of Russia in aggregate. These regions are modelled separately but are interrelated. The benefit of this approach is that it allows us to analyse how shocks in one region are passed along to others, how the regions react to general shocks and what the appropriate monetary policy response should be. The model represents a simple and convenient tool for building macroeconomically consistent forecasts and generating recommendations in the area of monetary policy based on regional specifics.","PeriodicalId":358692,"journal":{"name":"Russian Journal of Money and Finance","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting Regional Indicators Based on the Quarterly Projection Model\",\"authors\":\"Alyona Nelyubina\",\"doi\":\"10.31477/RJMF.202102.50\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a semi-structural model of a regional economy based on the standard version of the neo-Keynesian model in gaps. The main feature of this tool is its ability to predict regional indicators and model the regional heterogeneity of the national economy. In our model, Russia is divided into two macro-regions: the Central Federal District and the rest of Russia in aggregate. These regions are modelled separately but are interrelated. The benefit of this approach is that it allows us to analyse how shocks in one region are passed along to others, how the regions react to general shocks and what the appropriate monetary policy response should be. The model represents a simple and convenient tool for building macroeconomically consistent forecasts and generating recommendations in the area of monetary policy based on regional specifics.\",\"PeriodicalId\":358692,\"journal\":{\"name\":\"Russian Journal of Money and Finance\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Russian Journal of Money and Finance\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31477/RJMF.202102.50\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Russian Journal of Money and Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31477/RJMF.202102.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文在新凯恩斯主义缺口模型的基础上提出了区域经济的半结构模型。该工具的主要特点是能够预测区域指标和模拟国民经济的区域异质性。在我们的模型中,俄罗斯被分为两个宏观区域:中央联邦区和俄罗斯其他地区。这些区域分别建模,但相互关联。这种方法的好处是,它使我们能够分析一个地区的冲击是如何传递给其他地区的,这些地区如何应对总体冲击,以及适当的货币政策应对措施应该是什么。该模型是一种简单方便的工具,用于构建宏观经济一致性预测,并根据区域具体情况在货币政策领域提出建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Forecasting Regional Indicators Based on the Quarterly Projection Model
The paper presents a semi-structural model of a regional economy based on the standard version of the neo-Keynesian model in gaps. The main feature of this tool is its ability to predict regional indicators and model the regional heterogeneity of the national economy. In our model, Russia is divided into two macro-regions: the Central Federal District and the rest of Russia in aggregate. These regions are modelled separately but are interrelated. The benefit of this approach is that it allows us to analyse how shocks in one region are passed along to others, how the regions react to general shocks and what the appropriate monetary policy response should be. The model represents a simple and convenient tool for building macroeconomically consistent forecasts and generating recommendations in the area of monetary policy based on regional specifics.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Dynamic Stochastic General Equilibrium Model with Multiple Trends and Structural Breaks Comparison of Models for Growth-at-Risk Forecasting Modelling the Effects of Unconventional Monetary Policy in a Heterogeneous Monetary Union Forecasting Unemployment in Russia Using Machine Learning Methods A Real-Time Historical Database of Macroeconomic Indicators for Russia
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1