{"title":"Short-term inflation projections model and its assessment in Latvia","authors":"Andrejs Bessonovs, O. Krasnopjorovs","doi":"10.1080/1406099X.2021.2003997","DOIUrl":null,"url":null,"abstract":"ABSTRACT This paper builds a short-term inflation projections (STIP) model for Latvia. The model is designed to forecast highly disaggregated consumer prices using cointegrated ARDL approach of [Pesaran, M., & Shin, Y. (1998). An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis. Econometric Society Monographs, 31, 371–413.]. We assess the forecast accuracy of STIP model using out-of-sample forecast exercise and show that our model outperforms both aggregated and disaggregated AR(1) benchmarks. Across inflation components, the forecast accuracy gains are 20–30% forecasting 3 months ahead and 15–55% forecasting 12 months ahead.","PeriodicalId":43756,"journal":{"name":"Baltic Journal of Economics","volume":"21 1","pages":"184 - 204"},"PeriodicalIF":1.2000,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Baltic Journal of Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1080/1406099X.2021.2003997","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT This paper builds a short-term inflation projections (STIP) model for Latvia. The model is designed to forecast highly disaggregated consumer prices using cointegrated ARDL approach of [Pesaran, M., & Shin, Y. (1998). An Autoregressive Distributed Lag Modelling Approach to Cointegration Analysis. Econometric Society Monographs, 31, 371–413.]. We assess the forecast accuracy of STIP model using out-of-sample forecast exercise and show that our model outperforms both aggregated and disaggregated AR(1) benchmarks. Across inflation components, the forecast accuracy gains are 20–30% forecasting 3 months ahead and 15–55% forecasting 12 months ahead.