Forecasting inflation: The use of dynamic factor analysis and nonlinear combinations

Author:

Hall Stephen G.123,Tavlas George S.24ORCID,Wang Yongli5ORCID

Affiliation:

1. Leicester University Leicester UK

2. Bank of Greece Athens Greece

3. Pretoria University Pretoria South Africa

4. Hoover Institution Stanford University Stanford California USA

5. Birmingham University Birmingham UK

Abstract

AbstractThis paper considers the problem of forecasting inflation in the United States, the euro area, and the United Kingdom in the presence of possible structural breaks and changing parameters. We examine a range of moving window techniques that have been proposed in the literature. We extend previous works by considering factor models using principal components and dynamic factors. We then consider the use of forecast combinations with time‐varying weights. Our basic finding is that moving windows do not produce a clear benefit to forecasting. Time‐varying combination of forecasts does produce a substantial improvement in forecasting accuracy.

Publisher

Wiley

Subject

Management Science and Operations Research,Statistics, Probability and Uncertainty,Strategy and Management,Computer Science Applications,Modeling and Simulation,Economics and Econometrics

Reference28 articles.

1. Arnold M.(2022 September 5).ECB makes Hawkish shift as inflation surge shreds faith in models. Financial Times.

2. Arnold M. Smith C. &Giles C.(2022 June 29).Central Bank chiefs call end to era of low rates and moderate inflation. Financial Times.

3. Estimating and Testing Linear Models with Multiple Structural Changes

4. Trending time-varying coefficient time series models with serially correlated errors

5. Intercept corrections and structural change

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