Seasonal Adjustment Without Revisions

Abeln, Barend; Jacobs, Jan

doi:10.1007/978-3-031-22845-2

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Aruoba et al (2013) consider the problem from a forecast combination perspective, assuming "news" errors and imposing priors to address identification, while Aruoba et al (2016) consider alternative identifying assumptions and propose the addition of an instrumental variable. Almuzara et al (2021) investigate a dynamic factor model (DFM) with cointegration restrictions while Anesti et al (2022) propose a mixed-frequency release-augmented DFM. See Jacobs et al (2022) for details.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Employment reconciliation and nowcasting

Goto

Jacobs

Sinclair

et al. 2023

J of Applied Econometrics

View full text Add to dashboard Cite

SummaryWe construct a latent employment estimate for the United States, which both reconciles the information from separate payroll and household surveys and incorporates the preliminary data revision process of the payroll data. We find that our reconciled latent employment series looks somewhat different than the initial release of payroll employment and is closer to the fully revised data that is benchmarked to a near census of employment. A real‐time exercise, however, suggests that the reconciled employment estimate is remarkably similar to the initial release of payroll employment with near zero weight on the household survey information.

show abstract

Section: Introductionmentioning

confidence: 99%

“…However, its performance during crises is strange. For details, seeAbeln and Jacobs (2023).4 Our modeling framework allows for l different releases of x t . There is nothing that requires these l releases to be consecutive, but they need to be in order.…”

mentioning

confidence: 99%

Employment reconciliation and nowcasting

Goto

Jacobs

Sinclair

et al. 2023

J of Applied Econometrics

View full text Add to dashboard Cite

show abstract

Multivariate Trend‐Cycle‐Seasonal Decompositions with Correlated Innovations*

Tian,

Jacobs,

Osborn

2024

Oxf Bull Econ Stat

View full text Add to dashboard Cite

Multivariate analysis can help to focus on important phenomena, including trend and cyclical movements, but any economic information in seasonality is typically ignored. The present paper aims to more fully exploit time series information through a multivariate unobserved component model for quarterly data that exhibits seasonality together with cross‐variable component correlations. We show that economic restrictions, including common trends, common cycles and common seasonals can aid identification. The approach is illustrated using Italian GDP and consumption data.

show abstract

Seasonal Adjustment Without Revisions

Cited by 2 publications

References 0 publications

Employment reconciliation and nowcasting

Employment reconciliation and nowcasting

Multivariate Trend‐Cycle‐Seasonal Decompositions with Correlated Innovations*

Contact Info

Product

Resources

About