• Graduate program
    • Why Tinbergen Institute?
    • Program Structure
    • Courses
    • Course Registration
    • Facilities
    • Admissions
    • Recent PhD Placements
  • Research
  • News
  • Events
    • Summer School
      • Behavioral Macro and Complexity
      • Econometrics and Data Science Methods for Business and Economics and Finance
      • Experimenting with Communication – A Hands-on Summer School
      • Inequalities in Health and Healthcare
      • Introduction in Genome-Wide Data Analysis
      • Research on Productivity, Trade, and Growth
      • Summer School Business Data Science Program
    • Events Calendar
    • Tinbergen Institute Lectures
    • Annual Tinbergen Institute Conference
    • Events Archive
  • Summer School
  • Alumni
  • Times

Blasques, F., Koopman, S.J. and Nientker, M. (2022). A time-varying parameter model for local explosions Journal of Econometrics, 227(1):65--84.


  • Journal
    Journal of Econometrics

Financial and economic time series can feature locally explosive behaviour when bubbles are formed. We develop a time-varying parameter model that is capable of describing this behaviour in time series data. Our proposed dynamic model can be used to predict the emergence, existence and burst of bubbles. We adopt a flexible observation driven model specification that allows for different bubble shapes and behaviour. We establish stationarity, ergodicity, and bounded moments of the data generated by our model. Furthermore, we obtain the consistency and asymptotic normality of the maximum likelihood estimator. Given the parameter estimates in the model, the implied filter is capable of extracting the unobserved bubble process from the observed data. We study finite-sample properties of our estimator through a Monte Carlo simulation study. Finally, we show that our model compares well with existing noncausal models in a financial application concerning the Bitcoin/US dollar exchange rate.