Testing for Differences in Survey-Based Density Expectations: a Compositional Data Approach

Dovern J, Glas A, Kenny G (2024)

Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2024

Journal

Journal of Applied Econometrics Wiley-Blackwell

Journal Issue: forthcoming

Abstract

We propose to treat survey-based density expectations as compositional data when testing either for heterogeneity in density forecasts across different groups of agents or for changes over time. Monte Carlo simulations show that the proposed test has more power relative to both a bootstrap approach based on the KLIC and an approach which involves multiple testing for differences of individual parts of the density. In addition, the test is computationally much faster than the KLIC-based one, which relies on simulations, and allows for comparisons across multiple groups. Using density expectations from the ECB Survey of Professional Forecasters and the U.S.~Survey of Consumer Expectations, we show the usefulness of the test in detecting possible changes in density expectations over time and across different types of forecasters.

Authors with CRIS profile

Jonas Dovern Lehrstuhl für Statistik und Ökonometrie Alexander Glas Lehrstuhl für Statistik und Ökonometrie

Involved external institutions

Die Europäische Zentralbank / European Central Bank (EZB / ECB) DE Germany (DE)

How to cite

APA:

Dovern, J., Glas, A., & Kenny, G. (2024). Testing for Differences in Survey-Based Density Expectations: a Compositional Data Approach. Journal of Applied Econometrics, forthcoming.

MLA:

Dovern, Jonas, Alexander Glas, and Geoff Kenny. "Testing for Differences in Survey-Based Density Expectations: a Compositional Data Approach." Journal of Applied Econometrics forthcoming (2024).

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