IDEAS home Printed from https://ideas.repec.org/p/tin/wpaper/20210027.html
   My bibliography  Save this paper

Sectoral slowdowns in the UK: Evidence from transmission probabilities and economic linkages

Author

Listed:
  • Eva Janssens

    (University of Amsterdam)

  • Robin Lumsdaine

    (Erasmus University Rotterdam)

Abstract

This paper studies shock transmission across macroeconomic sectors in the UK, using data from the Bank of England's Flow of Funds statistics. We combine two different approaches to quantify the spread of shocks to assess whether sectors with large bilateral economic linkages as measured through network data have a greater statistical likelihood of shock transmission between them. The combination of both approaches reveals the Monetary Financial Institutions sector's role as shock absorber, and identifies the most important channels of shock transmission. The inferential discrepancies between network data and the actual spillovers highlight the contribution of the proposed methodology.

Suggested Citation

  • Eva Janssens & Robin Lumsdaine, 2021. "Sectoral slowdowns in the UK: Evidence from transmission probabilities and economic linkages," Tinbergen Institute Discussion Papers 21-027/III, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20210027
    as

    Download full text from publisher

    File URL: https://papers.tinbergen.nl/21027.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2011. "Sectoral versus Aggregate Shocks: A Structural Factor Analysis of Industrial Production," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 1-38.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. repec:ulb:ulbeco:2013/13388 is not listed on IDEAS
    4. Paul Glasserman & Peyton Young, 2015. "Contagion in Financial Networks," Economics Series Working Papers 764, University of Oxford, Department of Economics.
    5. Burrows, Oliver & Cumming, Fergus, 2015. "Mapping the UK financial system," Bank of England Quarterly Bulletin, Bank of England, vol. 55(2), pages 114-129.
    6. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    7. Daron Acemoglu & Pablo D. Azar, 2020. "Endogenous Production Networks," Econometrica, Econometric Society, vol. 88(1), pages 33-82, January.
    8. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    9. Glasserman, Paul & Young, H. Peyton, 2015. "How likely is contagion in financial networks?," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 383-399.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eva F. Janssens & Robin L. Lumsdaine, 2024. "Sectoral slowdowns in the United Kingdom: Evidence from transmission probabilities and economic linkages," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 22-40, January.
    2. van de Leur, Michiel C.W. & Lucas, André & Seeger, Norman J., 2017. "Network, market, and book-based systemic risk rankings," Journal of Banking & Finance, Elsevier, vol. 78(C), pages 84-90.
    3. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    4. Agudze, Komla M. & Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco, 2022. "Markov switching panel with endogenous synchronization effects," Journal of Econometrics, Elsevier, vol. 230(2), pages 281-298.
    5. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    6. Maya Jalloul & Mirela Miescu, 2021. "Equity Market Connectedness across Regimes of Geopolitical Risks," Working Papers 324219805, Lancaster University Management School, Economics Department.
    7. Jose Arreola Hernandez & Sang Hoon Kang & Ron P. McIver & Seong-Min Yoon, 2021. "Network Interdependence and Optimization of Bank Portfolios from Developed and Emerging Asia Pacific Countries," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 613-647, December.
    8. Camehl, Annika, 2023. "Penalized estimation of panel vector autoregressive models: A panel LASSO approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1185-1204.
    9. Torri, Gabriele & Giacometti, Rosella & Tichý, Tomáš, 2021. "Network tail risk estimation in the European banking system," Journal of Economic Dynamics and Control, Elsevier, vol. 127(C).
    10. Kosmidou, Kyriaki & Kousenidis, Dimitrios & Ladas, Anestis & Negkakis, Christos, 2017. "Determinants of risk in the banking sector during the European Financial Crisis," Journal of Financial Stability, Elsevier, vol. 33(C), pages 285-296.
    11. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Hussain Shahzad, Syed Jawad & Výrost, Tomáš, 2022. "Measuring systemic risk in the global banking sector: A cross-quantilogram network approach," Economic Modelling, Elsevier, vol. 109(C).
    12. Kristina Barauskaite & Anh Dinh Minh Nguyen, 2021. "Direct and network effects of idiosyncratic TFP shocks," Empirical Economics, Springer, vol. 60(6), pages 2765-2793, June.
    13. Chan, Joshua C.C. & Yu, Xuewen, 2022. "Fast and Accurate Variational Inference for Large Bayesian VARs with Stochastic Volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    14. Foglia, Matteo & Addi, Abdelhamid & Angelini, Eliana, 2022. "The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness," Global Finance Journal, Elsevier, vol. 51(C).
    15. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    16. Mardi Dungey & John Harvey & Pierre Siklos & Vladimir Volkov, 2017. "Signed spillover effects building on historical decompositions," CAMA Working Papers 2017-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    17. Chen, Tingqiang & Wang, Yutong & Zeng, Qianru & Luo, Jun, 2020. "Network model of credit risk contagion in the interbank market by considering bank runs and the fire sale of external assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    18. Raddant, Matthias & Kenett, Dror Y., 2021. "Interconnectedness in the global financial market," Journal of International Money and Finance, Elsevier, vol. 110(C).
    19. Daniel Felix Ahelegbey & Monica Billio & Roberto Casarin, 2016. "Sparse Graphical Vector Autoregression: A Bayesian Approach," Annals of Economics and Statistics, GENES, issue 123-124, pages 333-361.
    20. Christian Gross & Pierre L. Siklos, 2020. "Analyzing credit risk transmission to the nonfinancial sector in Europe: A network approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 61-81, January.

    More about this item

    Keywords

    Flow of Funds; contagion; epidemiology; intersectoral networks; Gibbs sampling; Bayesian priors;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • G01 - Financial Economics - - General - - - Financial Crises

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tin:wpaper:20210027. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.