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Constructing a dynamic financial conditions indexes by TVP-FAVAR model

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  • Shaoping Wang
  • Fan Xu
  • Sanpan Chen

Abstract

A factor augmented vector autoregressive models with time-varying coefficients and stochastic volatility is used to constructing financial conditions index to explore the link between composite index of financial indicators and future inflation. Time variation in the models’ parameters allows for the weights attached to each financial variable in the index to evolve over time. A monthly data of Chinese CPI and a wide range of macroeconomic variables are adopted to construct FCI and the experiment result shows its good forecasting performance to inflation.

Suggested Citation

  • Shaoping Wang & Fan Xu & Sanpan Chen, 2018. "Constructing a dynamic financial conditions indexes by TVP-FAVAR model," Applied Economics Letters, Taylor & Francis Journals, vol. 25(3), pages 183-186, February.
    • Handle: RePEc:taf:apeclt:v:25:y:2018:i:3:p:183-186
    DOI: 10.1080/13504851.2017.1307929
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    References listed on IDEAS

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    1. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    2. Koop, Gary & Korobilis, Dimitris, 2014. "A new index of financial conditions," European Economic Review, Elsevier, vol. 71(C), pages 101-116.
    3. Esteban Gómez & Andrés Murcia & Nancy Zamudio, 2011. "Financial Conditions Index: Early and Leading Indicator for Colombia," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 29(66), pages 174-220, December.
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    Cited by:

    1. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.

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