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

27695 Bouwman; J.P.A.M. Jacobs

doi:10.1016/j.jmacro.2011.04.002

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

27695 Bouwman, J.P.A.M. Jacobs

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

8 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. (C) 2011 Elsevier Inc. All rights reserved.

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

Keywords

Data revisions
Publication lags
Data imputations
Leading index
State space models
Kalman filter
FACTOR MODEL
GDP
TESTS

Access to Document

10.1016/j.jmacro.2011.04.002

Handle.net

Persistent link

Embargoed Document

Forecasting with real-time macroeconomic data The ragged-edge problem
Final publisher's version, 218 KB
Request copy

Cite this

@article{f27f00d594314a8893f2c095fa2b7829,

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. (C) 2011 Elsevier Inc. All rights reserved.",

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

author = "27695 Bouwman and J.P.A.M. Jacobs",

year = "2011",

month = dec,

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

language = "English",

volume = "33",

pages = "784--792",

journal = "Journal of Macroeconomics",

publisher = "ELSEVIER SCIENCE BV",

number = "4",

}

TY - JOUR

T1 - Forecasting with real-time macroeconomic data

T2 - The ragged-edge problem and revisions

AU - Bouwman, 27695

AU - Jacobs, J.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. (C) 2011 Elsevier Inc. All rights reserved.

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. (C) 2011 Elsevier Inc. All rights reserved.

KW - Data revisions

KW - Publication lags

KW - Data imputations

KW - Leading index

KW - State space models

KW - Kalman filter

KW - FACTOR MODEL

KW - GDP

KW - TESTS

U2 - 10.1016/j.jmacro.2011.04.002

DO - 10.1016/j.jmacro.2011.04.002

M3 - Article

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

Keywords

Access to Document

Handle.net

Embargoed Document

Fingerprint

Cite this