马尔可夫切换MIDAS模型在GDP及其组成部分临近预测中的应用

Q3 Economics, Econometrics and Finance Applied Econometrics Pub Date : 2023-01-01 DOI:10.22394/1993-7601-2023-70-122-143

I. Stankevich

{"title":"马尔可夫切换MIDAS模型在GDP及其组成部分临近预测中的应用","authors":"I. Stankevich","doi":"10.22394/1993-7601-2023-70-122-143","DOIUrl":null,"url":null,"abstract":"The paper investigates the application of Markov‐Switching MIDAS (Mixed Data Sampling) models to nowcasting of Russian GDP and its components. Different methods to get the resulting nowcast based on nowcasts under different regimes are proposed: weighted by regime probabilities, most probable regime, and perfectly predicted regime nowcasts. The model obtained is compared with standard econometric nowcasting models. Among all the models tested, Markov‐Switching MIDAS model with perfectly predicted regime yields the best results for most of the series analyzed. MS MIDAS models without perfect regime foresight also perform better than standard MIDAS models and MFBVAR models for most of the series analyzed.","PeriodicalId":8045,"journal":{"name":"Applied Econometrics","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of Markov-Switching MIDAS models to nowcasting of GDP and its components\",\"authors\":\"I. Stankevich\",\"doi\":\"10.22394/1993-7601-2023-70-122-143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper investigates the application of Markov‐Switching MIDAS (Mixed Data Sampling) models to nowcasting of Russian GDP and its components. Different methods to get the resulting nowcast based on nowcasts under different regimes are proposed: weighted by regime probabilities, most probable regime, and perfectly predicted regime nowcasts. The model obtained is compared with standard econometric nowcasting models. Among all the models tested, Markov‐Switching MIDAS model with perfectly predicted regime yields the best results for most of the series analyzed. MS MIDAS models without perfect regime foresight also perform better than standard MIDAS models and MFBVAR models for most of the series analyzed.\",\"PeriodicalId\":8045,\"journal\":{\"name\":\"Applied Econometrics\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Econometrics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22394/1993-7601-2023-70-122-143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Econometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22394/1993-7601-2023-70-122-143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}

引用次数: 0

摘要

本文研究了马尔可夫切换混合数据抽样(MIDAS)模型在俄罗斯GDP及其组成部分的临近预测中的应用。提出了基于不同状态下的临近预报得到临近预报结果的方法:按状态概率加权、最可能状态加权和完美预测状态临近预报。所得模型与标准的计量临近预报模型进行了比较。在所有测试的模型中，具有完美预测状态的马尔可夫切换MIDAS模型对大多数分析序列产生了最好的结果。在分析的大多数序列中，没有完善制度预见的MS MIDAS模型也比标准MIDAS模型和MFBVAR模型表现更好。

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

微信好友朋友圈 QQ好友复制链接

本刊更多论文

Application of Markov-Switching MIDAS models to nowcasting of GDP and its components

The paper investigates the application of Markov‐Switching MIDAS (Mixed Data Sampling) models to nowcasting of Russian GDP and its components. Different methods to get the resulting nowcast based on nowcasts under different regimes are proposed: weighted by regime probabilities, most probable regime, and perfectly predicted regime nowcasts. The model obtained is compared with standard econometric nowcasting models. Among all the models tested, Markov‐Switching MIDAS model with perfectly predicted regime yields the best results for most of the series analyzed. MS MIDAS models without perfect regime foresight also perform better than standard MIDAS models and MFBVAR models for most of the series analyzed.

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

Applied Econometrics Economics, Econometrics and Finance-Economics, Econometrics and Finance (miscellaneous)

CiteScore

0.70

自引率

0.00%

发文量

期刊介绍： The Journal of Applied Econometrics is an international journal published bi-monthly, plus 1 additional issue (total 7 issues). It aims to publish articles of high quality dealing with the application of existing as well as new econometric techniques to a wide variety of problems in economics and related subjects, covering topics in measurement, estimation, testing, forecasting, and policy analysis. The emphasis is on the careful and rigorous application of econometric techniques and the appropriate interpretation of the results. The economic content of the articles is stressed. A special feature of the Journal is its emphasis on the replicability of results by other researchers. To achieve this aim, authors are expected to make available a complete set of the data used as well as any specialised computer programs employed through a readily accessible medium, preferably in a machine-readable form. The use of microcomputers in applied research and transferability of data is emphasised. The Journal also features occasional sections of short papers re-evaluating previously published papers. The intention of the Journal of Applied Econometrics is to provide an outlet for innovative, quantitative research in economics which cuts across areas of specialisation, involves transferable techniques, and is easily replicable by other researchers. Contributions that introduce statistical methods that are applicable to a variety of economic problems are actively encouraged. The Journal also aims to publish review and survey articles that make recent developments in the field of theoretical and applied econometrics more readily accessible to applied economists in general.