The department has a longstanding international reputation in econometrics and is especially well known for its work in econometric methodology. Econometrics is a tool that enables economic theory to confront data.

The interplay between theory and data is fundamental to all the main concerns of the subject, ranging from problems of identification and endogeneity through to the effects of various forms of data dependence on estimation and testing.

Ongoing departmental research addresses many of these topics and includes the following:

  • Stationary and non-stationary time series econometrics
    Bayesian methods, econometric model determination and autometrics, time series forecasting, finite sample and higher order econometrics.
  • Nonparametric and semiparametric techniques in structural cointegrated systems
    For example, applications in time-series data.
  • Dynamic nonlinear modelling and specification
    Applications in financial econometrics, realised volatility, and the econometric study and "date stamping" of bubble phenomena.
  • Structural econometrics
    Empirical study of bidders’ behaviour, for example in Treasury bonds’ auctions or the electricity spot market, and applications to game theoretical models.
  • Econometric analysis of panel data
    Transitional behaviour of heterogeneous individuals over time, estimation and testing of the idiosyncratic components in panel data, panel unit-root tests and cointegration, and applications in empirical economic growth and international finance.
  • Behaviour of minimum norm estimators
    Including the least absolute deviations’ estimator in regression models with non-standard error distributions.

Researchers in econometrics

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