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A UK financial conditions index using targeted data reduction: forecasting and structural identification

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  • Kapetanios, G
  • Price, SG
  • Young, G

Abstract

A financial conditions index(FCI)is designed to summarise the state of financial markets. We construct two with UK data. The first is the first principal component(PC)of a set of financial indicators. The second comes from a new approach taking information from a large set of macroeconomic variables weighted by the joint covariance with a subset of the financial indicators (a set of spreads), using multivariate partial least squares, again using the first factor. The resulting FCIs are broadly similar. They both have some forecasting power for monthly GDP in a quasi-real-time recursive evaluation from 2011-2014 and outperform an FCI produced by Goldman Sachs. A second factor, that may be interpreted as a monetary conditions index, adds further forecast power, while third factors have a mixed effect on performance. The FCIs are used to improve identification of credit supply shocks in an SVAR. The main effects relative to an SVAR excluding an FCI of the (adverse) credit shock IRFs are to make the positive impact on inflation more precise and to reveal an increased positive impact on spreads.

Suggested Citation

  • Kapetanios, G & Price, SG & Young, G, 2017. "A UK financial conditions index using targeted data reduction: forecasting and structural identification," Essex Finance Centre Working Papers 20328, University of Essex, Essex Business School.
    • Handle: RePEc:esy:uefcwp:20328
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    Cited by:

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    3. Luke Hartigan & Michelle Wright, 2023. "Monitoring Financial Conditions and Downside Risk to Economic Activity in Australia," The Economic Record, The Economic Society of Australia, vol. 99(325), pages 253-287, June.
    4. Somnath Chatterjee & Ching‐Wai (Jeremy) Chiu & Thibaut Duprey & Sinem Hacıoğlu‐Hoke, 2022. "Systemic Financial Stress and Macroeconomic Amplifications in the United Kingdom," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(2), pages 380-400, April.
    5. Duo Qin & Sophie van Huellen & Qing Chao Wang & Thanos Moraitis, 2022. "Algorithmic Modelling of Financial Conditions for Macro Predictive Purposes: Pilot Application to USA Data," Econometrics, MDPI, vol. 10(2), pages 1-22, April.
    6. Syed Jawad Hussain Shahzad & Elie Bouri & Jose Arreola-Hernandez & David Roubaud & Stelios Bekiros, 2019. "Spillover across Eurozone credit market sectors and determinants," Applied Economics, Taylor & Francis Journals, vol. 51(59), pages 6333-6349, December.
    7. Mohsin, Muhammad & Ullah, Hafeez & Iqbal, Nadeem & Iqbal, Wasim & Taghizadeh-Hesary, Farhad, 2021. "How external debt led to economic growth in South Asia: A policy perspective analysis from quantile regression," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 423-437.
    8. Lodge, David & Soudan, Michel, 2019. "Credit, financial conditions and the business cycle in China," Working Paper Series 2244, European Central Bank.
    9. Carla Soares & Nikolay Iskrev & Rita Fradique Lourenço, 2021. "Indicators of monetary policy stance and financial conditions: an overview," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    10. Bui Thanh Trung, 2022. "Measuring Monetary Policy in Emerging Economy: The Role of Monetary Condition Index," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 70(6), pages 499-522, June.

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    Keywords

    Forecasting; Financial conditions index; Targeted data reduction; Multivariate partial least squares; Credit shocks;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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