Forecasting with real-time macroeconomic data: The ragged-edge problem and revisions

Kees E. Bouwman; Jan P.A.M. Jacobs

doi:10.1016/j.jmacro.2011.04.002

Forecasting with real-time macroeconomic data: The ragged-edge problem and revisions

Kees E. Bouwman^*, Jan P.A.M. Jacobs

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

Real-time macroeconomic data are typically incomplete for today and the immediate past ('ragged edge') and subject to revision. To enable more timely forecasts the recent missing data have to be imputed. The paper presents a state-space model that can deal with publication lags and data revisions. The framework is applied to the US leading index. We conclude that including even a simple model of data revisions improves the accuracy of the imputations and that the univariate imputation method in levels adopted by The Conference Board can be improved upon.

Original language	English
Pages (from-to)	784-792
Number of pages	9
Journal	Journal of Macroeconomics
Volume	33
Issue number	4
DOIs	https://doi.org/10.1016/j.jmacro.2011.04.002
Publication status	Published - Dec 2011

Access to Document

10.1016/j.jmacro.2011.04.002

Cite this

@article{b3e19dbba3064db29fce42138943f8df,

title = "Forecasting with real-time macroeconomic data: The ragged-edge problem and revisions",

abstract = "Real-time macroeconomic data are typically incomplete for today and the immediate past ('ragged edge') and subject to revision. To enable more timely forecasts the recent missing data have to be imputed. The paper presents a state-space model that can deal with publication lags and data revisions. The framework is applied to the US leading index. We conclude that including even a simple model of data revisions improves the accuracy of the imputations and that the univariate imputation method in levels adopted by The Conference Board can be improved upon.",

keywords = "Data imputations, Data revisions, Kalman filter, Leading index, Publication lags, State space models",

author = "Bouwman, {Kees E.} and Jacobs, {Jan P.A.M.}",

year = "2011",

month = dec,

doi = "10.1016/j.jmacro.2011.04.002",

language = "English",

volume = "33",

pages = "784--792",

journal = "Journal of Macroeconomics",

issn = "0164-0704",

publisher = "Elsevier B.V.",

number = "4",

}

TY - JOUR

T1 - Forecasting with real-time macroeconomic data

T2 - The ragged-edge problem and revisions

AU - Bouwman, Kees E.

AU - Jacobs, Jan P.A.M.

PY - 2011/12

Y1 - 2011/12

N2 - Real-time macroeconomic data are typically incomplete for today and the immediate past ('ragged edge') and subject to revision. To enable more timely forecasts the recent missing data have to be imputed. The paper presents a state-space model that can deal with publication lags and data revisions. The framework is applied to the US leading index. We conclude that including even a simple model of data revisions improves the accuracy of the imputations and that the univariate imputation method in levels adopted by The Conference Board can be improved upon.

AB - Real-time macroeconomic data are typically incomplete for today and the immediate past ('ragged edge') and subject to revision. To enable more timely forecasts the recent missing data have to be imputed. The paper presents a state-space model that can deal with publication lags and data revisions. The framework is applied to the US leading index. We conclude that including even a simple model of data revisions improves the accuracy of the imputations and that the univariate imputation method in levels adopted by The Conference Board can be improved upon.

KW - Data imputations

KW - Data revisions

KW - Kalman filter

KW - Leading index

KW - Publication lags

KW - State space models

UR - http://www.scopus.com/inward/record.url?scp=80755189363&partnerID=8YFLogxK

U2 - 10.1016/j.jmacro.2011.04.002

DO - 10.1016/j.jmacro.2011.04.002

M3 - Article

SN - 0164-0704

VL - 33

SP - 784

EP - 792

JO - Journal of Macroeconomics

JF - Journal of Macroeconomics

IS - 4

ER -

Forecasting with real-time macroeconomic data: The ragged-edge problem and revisions

Abstract

Access to Document

Other files and links

Fingerprint

Cite this