Prediction of the Netherlands' money stock

Butter, F.A.G. den; Gevel, F.J.J.S. Van de

doi:10.1007/bf01460320

“…In that sense it corroborates with results from other studies that combination of forecasts may be useful to enhance the forecasting performance (see e.g. Den Butter and Van de Gevel (1989), Den Butter and Van Dijken 1997)). …”

Section: Discussionsupporting

confidence: 90%

Beating the random walk: a performance assessment of long-term interest rate forecasts

Butter

¹

,

Jansen²

2013

Applied Financial Economics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. (0)10 408 9031 Most TI discussion papers can be downloaded at http://www.tinbergen.nl. Terms of use: Documents in This version 27 October 2008Beating the random walk: a performance assessment of longterm interest rate forecasts Frank A.G. den Butter and Pieter W. Jansen * Abstract This paper assesses the performance of a number of long-term interest rate forecast approaches, namely time series models, structural economic models, expert forecasts and combinations thereof. The predictive performance of these approaches is compared using out of sample forecast errors, where a random walk forecast acts as benchmark. It is found that for five major OECD countries, namely United States, Germany, United Kingdom, The Netherlands and Japan, the other forecasting approaches do not outperform the random walk, or a somewhat more sophisticated time series model, on a 3 month forecast horizon. On a 12 month forecast horizon the random walk model can be outperformed by a model that combines economic data and expert forecasts. Here several methods of combination are considered: equal weights, optimized weights and weights based on forecast error. It appears that the additional information contents of the structural models and expert knowledge is only relevant for forecasting 12 months ahead.

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Butter

¹

,

Dijken

²

1997

Open Economies Review

5

0

View full text Add to dashboard Cite

Beating the Random Walk: A Performance Assessment of Long-Term Interest Rate Forecasts

Butter

¹

,

Jansen²

2008

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. (0)10 408 9031 Most TI discussion papers can be downloaded at http://www.tinbergen.nl. Terms of use: Documents in This version 27 October 2008Beating the random walk: a performance assessment of longterm interest rate forecasts Frank A.G. den Butter and Pieter W. Jansen * Abstract This paper assesses the performance of a number of long-term interest rate forecast approaches, namely time series models, structural economic models, expert forecasts and combinations thereof. The predictive performance of these approaches is compared using out of sample forecast errors, where a random walk forecast acts as benchmark. It is found that for five major OECD countries, namely United States, Germany, United Kingdom, The Netherlands and Japan, the other forecasting approaches do not outperform the random walk, or a somewhat more sophisticated time series model, on a 3 month forecast horizon. On a 12 month forecast horizon the random walk model can be outperformed by a model that combines economic data and expert forecasts. Here several methods of combination are considered: equal weights, optimized weights and weights based on forecast error. It appears that the additional information contents of the structural models and expert knowledge is only relevant for forecasting 12 months ahead.

show abstract

Prediction of the Netherlands' money stock

Abstract: Amsterdam, respectively. This study was completed when the first author was at the Nederlandsche Bank. We gratefully acknowledge the useful comments of a referee on a previous version of this article.

Cited by 3 publications

References 23 publications

Beating the random walk: a performance assessment of long-term interest rate forecasts

Beating the random walk: a performance assessment of long-term interest rate forecasts

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Beating the Random Walk: A Performance Assessment of Long-Term Interest Rate Forecasts

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