Oliver Linton

My research contribution has mostly been to do with nonparametric and semiparametric methods. I am also interested in Financial Econometrics. Investigation of the curse of dimensionality, leads one to consider models like additive regression that only involve one-dimensional functions. My work with Jens Perch Nielsen led to a number of papers on estimating additive and other separable models. We introduced a new method which we called marginal integration for estimating additive nonparametric regression. More recently, I have worked with Jens Perch Nielsen and Enno Mammen on deriving the asymptotic properties of a general class of iterative smoothing procedures which includes as a special case a variant of backfitting.

It turns out that the backfitting method can be shown to be more efficient than the marginal integration method (under homoskedasticity) and to be better behaved in the boundaries, although the finite sample comparison is more complex, see the simulation study by Stefan Sperlich. I am also working with Arthur Lewbel on estimating a general class of nonparametric index models, which includes models for censored and truncated regression as well as models representing homotheticity. These structures also lead to non-standard estimation problems. I am also interested in financial econometrics.

I am interested in discrete time volatility models like GARCH models, their properties and estimation methods thereof, both parametric and nonparametric. I am interested in the econometrics of continuous time, realized volatility and its uses. I have been working with Greg Connor on estimating a class of semiparametric factor models that are useful for large cross-section and low frequency (ie monthly) time series. There is still an important role to play for nonlinearity in such models.