{"title":"趋势通胀和不断变化的通胀动态：贝叶斯 GMM 分析","authors":"Yasufumi Gemma , Takushi Kurozumi , Mototsugu Shintani","doi":"10.1016/j.red.2023.05.003","DOIUrl":null,"url":null,"abstract":"<div><p>Inflation<span> dynamics are investigated by estimating a generalized version of the New Keynesian Phillips curve (NKPC) of Galí and Gertler (1999) using Bayesian GMM. US macroeconomic data suggests that the generalized NKPC (GNKPC) performs best in terms of quasi-marginal likelihood among those considered both during and after the Great Inflation period. The estimated GNKPC indicates that when trend inflation fell after the Great Inflation period, the probability of price change decreased and the GNKPC flattened, which is in line with findings by previous studies.</span></p></div>","PeriodicalId":47890,"journal":{"name":"Review of Economic Dynamics","volume":"51 ","pages":"Pages 506-520"},"PeriodicalIF":2.3000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Trend inflation and evolving inflation dynamics: A Bayesian GMM analysis\",\"authors\":\"Yasufumi Gemma , Takushi Kurozumi , Mototsugu Shintani\",\"doi\":\"10.1016/j.red.2023.05.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Inflation<span> dynamics are investigated by estimating a generalized version of the New Keynesian Phillips curve (NKPC) of Galí and Gertler (1999) using Bayesian GMM. US macroeconomic data suggests that the generalized NKPC (GNKPC) performs best in terms of quasi-marginal likelihood among those considered both during and after the Great Inflation period. The estimated GNKPC indicates that when trend inflation fell after the Great Inflation period, the probability of price change decreased and the GNKPC flattened, which is in line with findings by previous studies.</span></p></div>\",\"PeriodicalId\":47890,\"journal\":{\"name\":\"Review of Economic Dynamics\",\"volume\":\"51 \",\"pages\":\"Pages 506-520\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Review of Economic Dynamics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1094202523000194\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Economic Dynamics","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1094202523000194","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
Trend inflation and evolving inflation dynamics: A Bayesian GMM analysis
Inflation dynamics are investigated by estimating a generalized version of the New Keynesian Phillips curve (NKPC) of Galí and Gertler (1999) using Bayesian GMM. US macroeconomic data suggests that the generalized NKPC (GNKPC) performs best in terms of quasi-marginal likelihood among those considered both during and after the Great Inflation period. The estimated GNKPC indicates that when trend inflation fell after the Great Inflation period, the probability of price change decreased and the GNKPC flattened, which is in line with findings by previous studies.
期刊介绍：
Review of Economic Dynamics publishes meritorious original contributions to dynamic economics. The scope of the journal is intended to be broad and to reflect the view of the Society for Economic Dynamics that the field of economics is unified by the scientific approach to economics. We will publish contributions in any area of economics provided they meet the highest standards of scientific research.
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