Research
In the past, I have been working on a range of topics. Some of these
made it into my thesis, others did not.
Therefore, below I give a range of topics I have been working on at some
time, or hope to work on soon.
See the list of publications to check if
I already prepared a paper on the topic.
- Long memory
- Part of the Ph.D. project was directed at distinguishing
long-lasting effects in the model from sudden changes in the model
parameters. ARFIMA models, fractional integration, are all topics that
I looked into. This effect is often found in inflation rates, or more
generally in series that are constructed/aggregated from many
underlying series.
- Bayesian statistics
- As long as the information content of the data is large enough,
specifying rather precisely the location of the maximum likelihood,
often a classical analysis can go quite far. On the other hand, when
decisions have to be made under uncertainty, the imprecision in
parameter estimates may very well influence the final outcome. In such
situations, the Bayesian method of analysis may be better suited.
- Simulation methods
- Bayesian statistics cannot exist without all kind of Markov Chain
Monte Carlo simulation techniques, in order to find the posterior
density of the parameters in the model. Over the years I used many
different sampling methods, and at last combined all of those into an
Ox package,
called MC2Pack.
- Financial econometrics
- Without data, an econometrician can do little. Financial
econometricians tend to have loads of high quality data, allowing for
a detailed analysis. New problems occurring in this field, like
irregularly spaced timing of observations, differences in importance
of observations on different parts of the day, those leave many
unsolved riddles for future research.
- State space models
- With the myriads of possible models, the class of state space
models provides a, in my view, useful guideline from which to start.
Enlarging these models, with non-linear components, non-Gaussian
error terms or combinations of the two can be rather cumbersome. Even
so, I am in the process of modelling a series where these models
allow for contemporaneous effects of the mean on the variance of the
components of the series.