Sometimes, asking for something you don't really want can be an indirect way of getting something you actually do want or need. A million dollars? Not quite what I had in mind, actually. Nice thought, though!
Actually, what I had in mind was something a little more mundane. In particular, getting an econometric package to save you a lot of work by delivering up some information you need, when it's not at all apparent that the package is able to do so. It's a matter of asking it for something else, and getting what you really want as a by-product. A bonus, if you will!
Last week, Takamitsu Kurita asked me "What do you think will be the big developments in Econometrics over the next decade". We were having a drink following his seminar, and I really didn't have a good answer. I think those of us present ducked the question by saying that, as econometricians, we know only too well the pitfalls associated with forecasting! But Taka's question was a good one, and it certainly deserved a better response than I had at the time.
Last Friday I went to a great seminar given by Takamitsu Kurita (Fukuoka University, Japan). Taka is currently a visiting scholar in our department, and his paper (here) dealt with an interesting application of cointegration analysis when we have both I(2) and I(1) data to contend with.
This is a topic in time-series econometrics that's of great practical importance, and (quite rightly) is currently attracting quite a bit of attention.
In this post I'm going to focus on understanding the extent to which there's an equivalence between two different ways of estimating an AR(p) model for a time-series, Yt, using EViews, and to see what information is generated in each case.
In particular, I want to show you how you can "trick" EViews into showing you if your estimated dynamic regression model is "dynamically stable". That is, if the estimated coefficients for the lagged values of Y are such that the model is stationary. If the lag-order is above 2, this isn't something that's always easy to do by just looking at the estimated coefficient values.
On this page you'll find a small selection of advertisements for interesting jobs in Econometrics, around the world. These have been chosen to provide information about the wide-ranging opportunities for Econometricians.
The list will change frequently, as new jobs are posted, and others expire.
We all know the difference between conditions that are necessary, and ones that are sufficient, for some result to hold. However, it's not uncommon for us to lose track of which is which when it comes to certain econometric results. I'm going to focus on just one example of this, and in doing so I'll try and clear up a common misconception.
When econometricians talk about the "asymptotic" properties of their estimators or tests, they're usually referring to their properties when the sample size becomes infinitely large. However, there are other types of "asymptotics" that are also interesting and important. It's worth being aware of this, and of the way they arise in econometric analysis.
This is a Wiki site devoted to discussing and explaining the methods of proof that are used in various areas of mathematics. Probability and Statistics are among the fields covered, although as yet there are no entries for the second of these two particular sections.
In short, there's a wealth of great information for students and teachers of Econometrics alike. I'll certainly be using it, and I'll be looking forward to seeing some entries in the Statistics section.
We've all taken, and/or taught, an introductory course in descriptive statistics where we encounter measures of "central tendency", variability, summarizing grouped data, and so on. In such courses students are usually told about three ways of calculating the mean, or average, of a sample. These are the Arithmetic Mean, Geometric Mean, and Harmonic Mean. In my experience, economists often fail to use the most appropriate of these three measures. I think this is because often we don't provide enough motivation and explanation in those introductory courses.
I don't know about you, but I'm highly envious of people who seem to be able to come up with the perfect retort, seemingly without even thinking. I tend to be of those who thinks of (what I consider to be) just the right remark - about 2 hours after it's needed! You could say I'm not that quick on my feet.
One of the really great things about this new Chair is that it's being used to support younger members of faculty in the UCSD Dept. of Economics. Santos and Beare are currently Assistant Professors there.
Earlier this year, Calyampudi Radhakrishna Rao received the Guy Medal in Gold, from the Royal Statistical Society. A statistician of world renown - indeed an icon in the profession - C. R. Rao is one of the last survivors of the "Golden Age of Statistics".