• Graduate Program
  • Research
  • Browse our Courses
  • Events
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • Summer School
      • Deep Learning
      • Economics of Blockchain and Digital Currencies
      • Foundations of Machine Learning with Applications in Python
      • Marketing Research with Purpose
      • Modern Toolbox for Spatial and Functional Data
      • Sustainable Finance
      • Tuition Fees and Payment
      • Tinbergen Institute Summer School Program
    • Annual Tinbergen Institute Conference archive
  • News
  • Summer School
    • Deep Learning
    • Economics of Blockchain and Digital Currencies
    • Foundations of Machine Learning with Applications in Python
    • Marketing Research with Purpose
    • Modern Toolbox for Spatial and Functional Data
    • Sustainable Finance
  • Alumni

Boswijk, H. and Franses, P. (2006). Robust inference on average economic growth Oxford Bulletin of Economics and Statistics, 68(3):345--370.


  • Journal
    Oxford Bulletin of Economics and Statistics

We discuss a method to estimate the confidence bounds for average economic growth, which is robust to misspecification of the unit root property of a given time series. We derive asymptotic theory for the consequences of such misspecification. Our empirical method amounts to an implementation of the subsampling procedure advocated in Romano and Wolf (Econometrica, 2001, Vol. 69, p. 1283). Simulation evidence supports the theory and it also indicates the practical relevance of the subsampling method. We use quarterly postwar US industrial production for illustration and we show that non-robust approaches rather lead to different conclusions on average economic growth than our robust approach. JEL Classification numbers: C15, C22, O47.