Forecasting the Monthly US Inflation Rate

Seminar paper from the year 2023 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 1.0, University of Munster, language: English, abstract: This paper sets out to forecast the US monthly inflation rate using various statistical models and the FRED-MD database, which contains monthly observations on 127 macroeconomic variables from 1959 to 2022. Forecasting (expected) inflation rates is essential for the plans of private individuals and firms as well as governments' and central banks' policy decisions. In particular, this paper tests the accuracy of various univariate time series models, time series models with exogenous regressors, and Machine Learning models in a pseudo-out-of-sample experiment. An AR(1) model will serve as the benchmark to which the performance of the other models is compared. The exogenous regressors are selected by theory and by correlation with the target variable. Finally, the paper considers how a combination of models can increase the accuracy of their forecasts.