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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. Garnitz, Johanna & Lehmann, Robert & Wohlrabe, Klaus, 2019. "Forecasting GDP all over the world using leading indicators based on comprehensive survey data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 51(54), pages 5802-5816.
    2. Qin Zhang & He Ni & Hao Xu, 2023. "Forecasting models for the Chinese macroeconomy in a data‐rich environment: Evidence from large dimensional approximate factor models with mixed‐frequency data," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 719-767, March.
    3. Chris Heaton & Natalia Ponomareva & Qin Zhang, 2020. "Forecasting models for the Chinese macroeconomy: the simpler the better?," Empirical Economics, Springer, vol. 58(1), pages 139-167, January.

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