Linking series generated at different frequencies

This is a report on our studies of the systematical use of mixed-frequency datasets. We suggest that the use of high-frequency data in forecasting economic aggregates can increase the accuracy of forecasts. The best way of using this information is to build a single model that relates the data of all frequencies, for example, an ARMA model with missing observations. As an application of linking series generated at different frequencies, we show that the use of a monthly industrial production index improves the predictability of the quarterly GNP. Copyright © 2008 John Wiley & Sons, Ltd.

[1]  Helmut Lütkepohl,et al.  Linear aggregation of vector autoregressive moving average processes , 1984 .

[2]  Klaus Wohlrabe,et al.  Makroökonomische Prognosen mit gemischten Frequenzen , 2009 .

[3]  F. Diebold,et al.  Comparing Predictive Accuracy , 1994, Business Cycles.

[4]  Luís Catela Nunes,et al.  Nowcasting quarterly GDP growth in a monthly coincident indicator model , 2005 .

[5]  P. Newbold,et al.  Tests for Forecast Encompassing , 1998 .

[6]  T. Abeysinghe.  Forecasting Singapore's quarterly GDP with monthly external trade , 1998 .

[7]  A. A. Weiss.  Systematic sampling and temporal aggregation in time series models , 1984 .

[8]  E. Philip Howrey.  New Methods for Using Monthly Data to Improve Forecast Accuracy , 1991 .

[9]  D. J. Pedregal,et al.  Should Quarterly Government Finance Statistics Be Used for Fiscal Surveillance in Europe? , 2008, SSRN Electronic Journal.

[10]  Richard H. Jones,et al.  Maximum Likelihood Fitting of ARMA Models to Time Series With Missing Observations , 1980 .

[11]  R. Kohn,et al.  Estimation, Prediction, and Interpolation for ARIMA Models with Missing Data , 1986 .

[12]  Clive W. J. Granger,et al.  Extracting information from mega‐panels and high‐frequency data , 2008 .

[13]  Stephen G. Hall,et al.  Creating high‐frequency national accounts with state‐space modelling: a Monte Carlo experiment , 2001 .

[14]  J. Stock,et al.  A Probability Model of the Coincident Economic Indicators , 1988 .

[15]  Russell P. Robins,et al.  Forecasting quarterly data using monthly information , 1993 .

[16]  James D. Hamilton.  Time Series Analysis , 1994 .

[17]  Andrew Harvey,et al.  Forecasting, Structural Time Series Models and the Kalman Filter , 1990 .