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Forecasting macroeconomy based on the term structure of credit spreads: evidence from China

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  • Rongxi Zhou
  • Xianliang Wang
  • Guanqun Tong

Abstract

This article establishes an original methodology to forecast macroeconomy based on the term structure of credit spreads. It combines the traditional Svensson model with genetic algorithms to obtain the interest rate term structures of government bonds and corporate bonds and calculates credit spreads as their differences. And this article defines three factors of the term structure of credit spreads: level, slope and curvature. Based on these three factors and several macroeconomic variables, VAR models are developed and tested to forecast macroeconomic variables. The empirical results confirm that VAR models can predict the changes of China's macroeconomy well, which indicates that the term structure of credit spreads contains information of future changes of macroeconomic variables. We believe this result has significant implications for macroeconomy policy-makers.

Suggested Citation

  • Rongxi Zhou & Xianliang Wang & Guanqun Tong, 2013. "Forecasting macroeconomy based on the term structure of credit spreads: evidence from China," Applied Economics Letters, Taylor & Francis Journals, vol. 20(15), pages 1363-1367, October.
  • Handle: RePEc:taf:apeclt:v:20:y:2013:i:15:p:1363-1367
    DOI: 10.1080/13504851.2013.806778
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    Cited by:

    1. Johanna Garnitz & Robert Lehmann & Klaus Wohlrabe, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," CESifo Working Paper Series 7691, CESifo Group Munich.
    2. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2017. "Forecasting GDP all over the World: Evidence from Comprehensive Survey Data," MPRA Paper 81772, University Library of Munich, Germany.

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