• Graduate Programs
    • Tinbergen Institute Research Master in Economics
      • Why Tinbergen Institute?
      • Research Master
      • Admissions
      • All Placement Records
      • PhD Vacancies
    • Facilities
    • Research Master Business Data Science
    • Education for external participants
    • Summer School
    • Tinbergen Institute Lectures
    • PhD Vacancies
  • Research
  • Browse our Courses
  • Events
    • Summer School
      • Applied Public Policy Evaluation
      • Deep Learning
      • Development Economics
      • Economics of Blockchain and Digital Currencies
      • Economics of Climate Change
      • The Economics of Crime
      • Foundations of Machine Learning with Applications in Python
      • From Preference to Choice: The Economic Theory of Decision-Making
      • Inequalities in Health and Healthcare
      • Marketing Research with Purpose
      • Markets with Frictions
      • Modern Toolbox for Spatial and Functional Data
      • Sustainable Finance
      • Tuition Fees and Payment
      • Business Data Science Summer School Program
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • 2026 Tinbergen Institute Opening Conference
    • Annual Tinbergen Institute Conference
  • News
  • Summer School
  • Alumni
    • PhD Theses
    • Master Theses
    • Selected PhD Placements
    • Key alumni publications
    • Alumni Community

Janssens, \EvaF.\ and Lumsdaine, \RobinL.\ (2024). Sectoral slowdowns in the United Kingdom: Evidence from transmission probabilities and economic linkages Journal of Applied Econometrics, 39(1):22--40.


  • Journal
    Journal of Applied Econometrics

This paper studies spillovers across macroeconomic sectors in the United Kingdom, using data from the Bank of England's Flow of Funds statistics. We combine two different approaches to quantify the spread of economic deterioration to assess whether sectors with large bilateral economic linkages as measured through network data have a greater statistical likelihood of spillovers 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 spillovers. The inferential discrepancies between network data and statistical spillovers highlight the contribution of the proposed methodology.