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Changes in Predictive Ability with Mixed Frequency Data

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  • Ana Beatriz Galv�o

    (Queen Mary, University of London)

Abstract

This paper proposes a new regression model - a smooth transition mixed data sampling (STMIDAS) approach - that captures recurrent changes in the ability of a high frequency variable in predicting a low frequency variable. The STMIDAS regression is employed for testing changes in the ability of financial variables in forecasting US output growth. The estimation of the optimal weights for aggregating weekly data inside the quarter improves the measurement of the predictive ability of the yield curve slope for output growth. Allowing for changes in the impact of the short-rate and the stock returns in future growth is decisive for finding in-sample and out-of-sample evidence of their predictive ability at horizons longer than one year.

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Bibliographic Info

Paper provided by Queen Mary, University of London, School of Economics and Finance in its series Working Papers with number 595.

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Date of creation: May 2007
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Handle: RePEc:qmw:qmwecw:wp595

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Keywords: Smooth transition; MIDAS; Predictive ability; Asset prices; Output growth;

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Cited by:
  1. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.

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