Survey-based forecast distributions for Euro Area growth and inflation: ensembles versus histograms

Krüger, Fabian

doi:10.1007/s00181-017-1228-3

Cited by 14 publications

(6 citation statements)

References 30 publications

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“…In these cases, forecasters overstate their ex ante uncertainty compared to the squared forecast errors and should, on average, reduce the variance of their histogram close to the target. Overall, these results square with similar evidence documented in Söderlind (2003, 2006) and Clements (2014Clements ( , 2018 for the FED-SPF and in Kenny et al (2014), Krüger (2017), andCasey (2021) for the ECB-SPF. In particular, our findings support the result of Clements (2014) that the ex ante uncertainty of SPF participants exceeds ex post uncertainty at short forecast horizons.…”

Section: Analysis Of Variance Misalignmentsupporting

confidence: 90%

Uncertainty measures from partially rounded probabilistic forecast surveys

Glas

Hartmann

2022

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Although survey‐based point predictions have been found to outperform successful forecasting models, corresponding variance forecasts are frequently diagnosed as heavily distorted. Professional forecasters who report inconspicuously low ex ante variances often produce squared forecast errors that are much larger on average. In this paper, we document the novel stylized fact that this variance misalignment is related to the rounding behavior of survey participants. Rounding may reflect the fact that some survey participants employ a rather judgmental approach to forecasting as opposed to using a formal model. We use the distinct numerical accuracies of panelists' reported probabilities as a way to propose several alternative and easily implementable corrections that (i) can be carried out in real time, that is, before outcomes are observed, and (ii) deliver a significantly improved match between ex ante and ex post forecast uncertainty. According to our estimates, uncertainty about inflation, output growth and unemployment in the U.S. and the Euro area is higher after correcting for the rounding effect. The increase in the share of nonrounded responses in recent years also helps to understand the trajectory of survey‐based average uncertainty during the years since the financial and sovereign debt crisis.

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Section: Analysis Of Variance Misalignmentsupporting

confidence: 90%

Uncertainty measures from partially rounded probabilistic forecast surveys

Glas

Hartmann

2022

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“…Many have sought -see Clements & Galvão (2017) and references therein -to compare model-based probability densities (or moments thereof) to the bin forecasts. Echoing our findings, Krüger (2017) reports similar forecast performances between histograms and distributions constructed from survey errors for the ECB's SPF. Recently, Bassetti et al (2022) Cakmakli & Demircan (2022) improve nowcasts from a factor model of US GDP by adding measurement equations for mean and variance factors that reflect the cross-sectional average and variance (i.e., disagreement) of individual SPF point forecasts.…”

Section: Introductionsupporting

confidence: 82%

What is the predictive value of SPF point and density forecasts?

Clark

Ganics

Mertens

2022

Working Paper (Federal Reserve Bank of Cleveland)

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This paper presents a new approach to combining the information in point and density forecasts from the Survey of Professional Forecasters (SPF) and assesses the incremental value of the density forecasts. Our starting point is a model, developed in companion work, that constructs quarterly term structures of expectations and uncertainty from SPF point forecasts for quarterly fixed horizons and annual fixed events. We then employ entropic tilting to bring the density forecast information contained in the SPF’s probability bins to bear on the model estimates. In a novel application of entropic tilting, we let the resulting predictive densities exactly replicate the SPF’s probability bins. Our empirical analysis of SPF forecasts of GDP growth and inflation shows that tilting to the SPF’s probability bins can visibly affect our model-based predictive distributions. Yet in historical evaluations, tilting does not offer consistent benefits to forecast accuracy relative to the model-based densities that are centered on the SPF’s point forecasts and reflect the historical behavior of SPF forecast errors. That said, there can be periods in which tilting to the bin information helps forecast accuracy. Replication files are available at https://github.com/elmarmertens/ClarkGanicsMertensSPFfancharts

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“…We do not focus on these findings because they are not directly related to the analysis of the variance misalignment. 25…”

Section: Differences In Forecast Errorsmentioning

confidence: 99%

Uncertainty Measures from Partially Rounded Probabilistic Forecast Surveys

Glas¹,

Hartmann²

2020

SSRN Journal

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Although survey-based point predictions have been found to outperform successful forecasting models, corresponding variance forecasts are frequently diagnosed as heavily distorted. Forecasters who report inconspicuously low ex-ante variances often produce squared forecast errors that are much larger on average. In this paper, we document the novel stylized fact that this variance misalignment is related to the rounding behavior of survey participants. Rounding may reflect the fact that some survey participants employ a rather judgmental approach to forecasting as opposed to using a formal model. We use the distinct numerical accuracies of panelists' reported probabilities as a means to propose several alternative and easily implementable corrections that i) can be carried out in real time, i.e., before outcomes are observed, and ii) deliver a significantly improved match between ex-ante and ex-post forecast uncertainty. According to our estimates, uncertainty about inflation, output growth and unemployment in the U.S. and the Euro area is higher after correcting for the rounding effect. The increase in the share of non-rounded responses in recent years also helps to understand the trajectory of survey-based average uncertainty during the years since the financial and sovereign debt crisis.

show abstract

Survey-based forecast distributions for Euro Area growth and inflation: ensembles versus histograms

Cited by 14 publications

References 30 publications

Uncertainty measures from partially rounded probabilistic forecast surveys

Uncertainty measures from partially rounded probabilistic forecast surveys

What is the predictive value of SPF point and density forecasts?

Uncertainty Measures from Partially Rounded Probabilistic Forecast Surveys

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