Precision-Based Sampling for State Space Models that Have No Measurement Error

Mertens, Elmar

doi:10.2139/ssrn.4572669

SSRN Journal

2023

DOI: 10.2139/ssrn.4572669

|View full text |Cite

Precision-Based Sampling for State Space Models that Have No Measurement Error

Elmar Mertens

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Publication Types

Select...

Other1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Constructing fan charts from the ragged edge of SPF forecasts

Clark

Ganics

Mertens

2022

Working Paper (Federal Reserve Bank of Cleveland)

View full text Add to dashboard Cite

We develop a model that permits the estimation of a term structure of both expectations and forecast uncertainty for application to professional forecasts such as the Survey of Professional Forecasters (SPF). Our approach exactly replicates a given data set of predictions from the SPF (or a similar forecast source) without measurement error. Our model captures fixed horizon and fixed-event forecasts, and can accommodate changes in the maximal forecast horizon available from the SPF. The model casts a decomposition of multi-period forecast errors into a sequence of forecast updates that may be partially unobserved, resulting in a multivariate unobserved components model. In our empirical analysis, we provide quarterly term structures of expectations and uncertainty bands. Our preferred specification features stochastic volatility in forecast updates, which improves forecast performance and yields model estimates of forecast uncertainty that vary over time. We conclude by constructing SPF-based fan charts for calendar-year forecasts like those published by the Federal Reserve.

show abstract

Constructing fan charts from the ragged edge of SPF forecasts

Clark

Ganics

Mertens

2022

Working Paper (Federal Reserve Bank of Cleveland)

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Precision-Based Sampling for State Space Models that Have No Measurement Error

Cited by 1 publication

References 27 publications

Constructing fan charts from the ragged edge of SPF forecasts

Constructing fan charts from the ragged edge of SPF forecasts

Contact Info

Product

Resources

About