{"title":"Using a Wage–Price-Setting Model to Forecast US Inflation","authors":"Nguyen Duc Do","doi":"10.1002/for.3210","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>This study modifies a wage–price-setting (WPS) model to forecast US inflation over 1- to 3-year horizons, based on the assumption that firms use a rule of thumb to set prices after settling a wage agreement. The out-of-sample forecast results show that productivity growth is a powerful predictor of inflation, in the sense that during the 1990Q1–2023Q4 period, the modified WPS model improved upon some univariate benchmark models and multivariate models such as the Phillips curve, term spread, and wage-inflation models. From the early 2000s to the prepandemic period, forecast accuracy was improved by combining productivity growth with anchored inflation expectations. Interestingly, during this period, forecasts derived from the WPS model with constant-inflation expectations were found to slightly outperform Greenbook forecasts in forecasting quarter-over-quarter inflation from two- to four-quarter horizons.</p>\n </div>","PeriodicalId":47835,"journal":{"name":"Journal of Forecasting","volume":"44 2","pages":"803-832"},"PeriodicalIF":3.4000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forecasting","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/for.3210","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
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Abstract
This study modifies a wage–price-setting (WPS) model to forecast US inflation over 1- to 3-year horizons, based on the assumption that firms use a rule of thumb to set prices after settling a wage agreement. The out-of-sample forecast results show that productivity growth is a powerful predictor of inflation, in the sense that during the 1990Q1–2023Q4 period, the modified WPS model improved upon some univariate benchmark models and multivariate models such as the Phillips curve, term spread, and wage-inflation models. From the early 2000s to the prepandemic period, forecast accuracy was improved by combining productivity growth with anchored inflation expectations. Interestingly, during this period, forecasts derived from the WPS model with constant-inflation expectations were found to slightly outperform Greenbook forecasts in forecasting quarter-over-quarter inflation from two- to four-quarter horizons.
期刊介绍：
The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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