Some Recent, and Transparently Applicable, Results in Time-Series Econometrics

I think most of us would agree that when new techniques are introduced in econometrics, it's often a bit of a challenge to see exactly what would be involved in applying them. Someone comes up with a new estimator or test, and it's often a while before it gets incorporated into our favourite econometrics package, or until someone puts together an expository piece that illustrates, in simple terms, how to put the theory into practice.

In part, that's why applied econometrics "lags behind" econometric theory. Another reason is that a lot of practitioners aren't interested in reading the latest theoretical paper themselves.

Fair enough!

In any event, it's always refreshing when new inferential procedures are introduced into the literature in a way that exhibits a decent degree of "transparency" with respect to their actual application. For those of you who like you keep up with recent developments in time-series econometrics, here are some good examples of recent papers that (in my view) score well on the "transparency index":

Francis Diebold on GMM

On his blog, No Hesitations, Francis Diebold has two recent posts about GMM estimation that students of econometrics, and practitioners, definitely should read.

The first of these posts is here, and the second follow-up post is here.

Enjoy!

© 2013, David E. Giles

Recent, and Recommended.......

Recently, I griped posted about the need to get the economics back into papers that the authors characterize as "microeconometrics". Although I was venting (just a little!) about the "disconnect" that we so often see, between the theory section and the empirical section, in so many of the papers in this category, I also commented that there are plenty of papers out there that avoid this disconnect. I just wish there were more of them!

In response to one of the comments of that post, I gave just one such example, and afterwards I thought that although my choice was a good one, it was somewhat dated. So, on a more positive note, what about some recent papers that exemplify what I'm looking for, and what I'd like to see more of?

Information Criteria Unveiled

Most of you will have used, or at least encountered, various "information criteria" when estimating a regression model, an ARIMA model, or a VAR model. These criteria provide us with a way of comparing alternative model specifications, and selecting between them. 

They're not test statistics. Rather, they're minus twice the maximized value of the underlying log-likelihood function, adjusted by a "penalty factor" that depends on the number of parameters being estimated. The more parameters, the more complicated is the model, and the greater the penalty factor. For a given level of "fit", a more parsimonious model is rewarded more than a more complex model. Changing the exact form of the penalty factor gives rise to a different information criterion.

However, did you ever stop to ask "why are these called information criteria?" Did you realize that these criteria - which are, after all, statistics - have different properties when it comes to the probability that they will select the correct model specification? In this respect, they are typically biased, and some of them are even inconsistent.

This sounds like something that's worth knowing more about!

Former Students

It's always great to catch up with former students. I guess this is especially true of grad. students because (inevitably) you get to spend a lot of one-on-one time with them, and get to know them pretty well.

So, today I was thrilled to meet up with not one, but three, former grad. students! Peter Jacobsen, Cameron Woodbridge, and William Bi are all working for the B.C. Ministry of Forests, Lands and Natural Resource Operations, here in Victoria. I've known them all for quite some time. In fact, Peter was only the second M.A. student I supervised after I moved to UVic in 1994. 

Great lunch, guys!

© 203, David E. Giles

Some Current Projects

I often get emails asking me what research projects I'm working on. Generally, I have several projects underway at any given time - usually at various stages of development or completion. In that respect I guess I'm pretty typical.

I also tend to have a mixture of theoretical and applied projects, some econometric and some essentially statistical in nature. I find that this provides some continuity in my work. It's not easy to focus on just one or two research projects all of the time, especially if they're not progressing as well as you'd like them to!

So, what am I up to right now? Here are some of the papers/projects that I'm working on:

Vintage Years in Econometrics - The 1950's

Following on from my earlier posts about vintage years for econometrics in the 1930's and 1940's, here's my run-down on the 1950's.

As before, let me note that "in econometrics, what constitutes quality and importance is partly a matter of taste - just like wine! So, not all of you will agree with the choices I've made in the following compilation."

Let's Put the "ECON" Back Into Microeconometrics

You just couldn't resist the title, could you?

Don't worry, I'm not going to be too harsh. After all, I'm rather fond of those who practise "applied microeconometrics" - especially lightly sautéed, with a little pepper and garlic. Sorry! Sorry!

The point that I want to make is a simple one, and I'll be brief.

How many seminars have you attended where the speaker has gone through the details of a formal microeconomic model, and then proceeded to a potentially interesting empirical application? And in how many cases was there a total "disconnect" between the theoretical model and the empirical model?

Hand up! Don't be shy! Wow - that's almost everyone!

Conference and Seminar Papers - From Both Sides of the Podium

Here are three somewhat related posts from Rob Hyndman, Professor of Statistics in the Department of Econometrics and Business Statistics at Monash University. Rob blogs at Hyndsight.

I liked them all, and I commend them to you:

1. Giving a Research Seminar (2008)
2. Attending Research Seminars (2009)
3. Asking Good Questions (2013) - a guest post by Eran Raviv

For my own take on these matters, you might want to check here, here, and here.

© 2013, David E. Giles

Conference on Computing in Economics & Finance

The 19th. International Conference on Computing in Economics and Finance is coming up in Vancouver, B.C., this week. There's an interesting program.

One of my M.A. students, Yanan Li, and I have a paper that Yanan will be presenting at the conference. 

The paper is titled "Modeling Volatility Effects Between Emerging Asian Stock Markets and Developed Stock Markets".

© 2013, David E. Giles