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Euroconference2014 Budapest Conference Papers

Predictability of Term Spread for Economic Activity with Liquidity Premium Theory

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ABSTRACT

In this article, we explore the predictive content of the term spread based on the liquidity premium theory. We decompose the contribution of the spread into the effect of expected future changes in short rates and the effect of the term premium. We also examine whether the predictive power of the term spread for real economic activity can be enhanced by such a decomposition. The basic finding is that both the expectations effect and the term premium effect are relevant for predicting economic fluctuations. In particular, we find that the decomposition might lead to a better prediction for the business-cycle turning points than the usual term spread.

JEL Classification:

Acknowledgments

We thank the editor and two anonymous referees for helpful comments and/or discussions on earlier drafts.

Funding

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2013S1A3A2053586).

Notes

1. Due to data availability, however, the 1-year government bond and the 3-month monetary stabilization bond yield rates span from February 2000 and September 2006, respectively.

2. In order to save space, the regression results for selected lags are presented in this table. A detailed set of table is available from the authors upon request.

3. We have also examined the term spreads (K5–K1), (T2–T1), and (T2–T03). However, as the results are similar to those discussed in the previous section, they are not reported in this article.

4. Further details of the regression results on other cases are suppressed in this article, which are available from the authors upon request. A detailed set of tables is also available in a working paper version.

5. Further details of the regression results are available in a working paper version of this article.

Additional information

Funding

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2013S1A3A2053586).

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