Chris Sims on Bayesianism

I just love this piece by Chris Sims: "Bayesian Methods in Applied Econometrics, or, Why Econometrics Should Always and Everywhere Be Bayesian", from 2007.

In addition to the solid content, there are some great take-away snippets, such as:

"Bayesian inference is hard in the sense that thinking is hard."

"(People) want to characterize uncertainty about parameter values, given the sample that has actually been observed."

"Good frequentist practice has a Bayesian interpretation."

And Sims' conclusion: "Lose your inhibitions: Put probabilities on parameters without embarrassment."

I can live with that!

© 2013, David E. Giles

Solution to the Segmented Regression Problem

Here's my solution to the "segmented regression" problem that I posed yesterday. Thanks for the comments and suggestions!

You'll recall that what we wanted to do was to end up with a fitted least squares "line" looking like this:

In particular, the "kink" in the line is at a pre-determined point - in this example when x = 30.

Here's how we can achieve this:

Money 101: Top Resources for Finance Majors

Abigail Moore, the Content Creator at OnlineFinanceDegree.org, emailed me today:

"I'm writing with the exciting news that our latest article, "Money 101: Top Resources for Finance Majors," has been published, and Econometrics Beat: Dave Giles' Blog is cited on it.

Finance is an engaging and highly competitive professional field to get into. For those studying finance, the internet can offer a wealth of resources. That said, it can be hard to sift through and find the best. We hope this feature will help finance students find information about financial organizations, current economic news, financial modeling software and techniques, and the finance industry as a whole. Your site is a valuable addition to this resource.

We're hoping to share this article with as many finance students and professionals as possible and will be contacting our readers and followers. If you're able to post this on your website or share the article anywhere else you can think of too, I'd really appreciate it." 

No problem, Abigail - happy to oblige. You'll find this blog listed as site #8.

© 2013, David E. Giles

Lawrence R. Klein, 1920-2013

One of the great figures of econometrics passed away yesterday. Lawrence Klein was the father of whole-economy macroeconometric modelling, and his massive contributions to this field earned him the Nobel Prize in 1980.

Klein created some of the earliest simultaneous equations models of the U.S. economy (e.g., see here), and he was the driving force behind countless such models for other economies around the world. Among other things, Klein was responsible for the foundation of Project LINK, in 1968. This ambitious endeavour now brings together econometric models for 78 countries to provide a "world econometric model".

Lawrence Klein shaped econometric modelling, and his passing marks the end of an amazing era.

Businessweek's obituary for Lawrence Klein can be found here.

© 2013, David E. Giles

A "Segmented" Regression Problem

Here's a little exercise for the students among you.

Suppose that we want to fit a least squares regression model that allows for a "break" in the underlying relationship at a particular sample value for the regressor(s). In addition, we want to make sure that the fitted model passes through that sample value.

In other words, we want to end up with a fitted model that gives a result such as this:

Here, the two segments of the regression line "join" when X=30. What's a simple way to achieve this?

© 2013, David E. Giles

Economics Nobel Prize, 2013

The waiting is over - the 2013 Nobel in Economics was announced this morning! Most deservedly, it has been awarded to Eugene F. Fama (U. Chicago), Lars Peter Hansen (U. Chicago), and Robert J. Shiller (Yale U.). The citation says: "For their empirical analysis of asset prices". 

For more details, see here.

It's really  nice to see the recognition of empirical research.

And let's not forget that Hansen gave us GMM estimation; and do you recall Shiller distributed lag models?

© 2013, David E. Giles

Project-Based Learning of Modern Econometrics

The U.K.  Economics Network is supported by, and housed at, the University of Bristol. It provides a wealth of resources for those teaching Economics.  These resources include material produced by various funded projects, including one by Steve Cook (Swansea University). His project (in 2010-11) was titled, "Project-Based Learning of Modern Econometrics. Here's Steve's overview:

Do Better Economic Models Lead to Better Forecasting?

Earlier this month I had a post drawing attention to a short video by David Hendry. Here's another one - this time titled, "Do Better Economic Models Lead to Better Forecasting?" 

© 2013, David E. Giles

Seven Deadly Sins

Xiao-Li Meng has an interesting piece in the September 2013 issue of the IMS Bulletin. (IMS = Institute of Mathematical Statistics). You'll find it on page 4, and it's titled "Rejection Pursuit".

In short, it's about the author's repeated efforts, as a young researcher, to get a particular paper published. The story has a happy ending, and Xiao-Li leaves us with a list of "Seven Deadly Sins of Research Papers, and Seven Virtues to Cultivate":

This looks like excellent advice, regardless of your discipline.

And yes, the article does have an econometric connection. If you read the article and you're interested in non-stationary time-series, you'll probably see the connection coming before the author mentions it!

© 2013, David E. Giles

Beyond MSE - "Optimal" Linear Regression Estimation

In a recent post I discussed the fact that there is no linear minimum MSE estimator for the coefficients of a linear regression model. Specifically, if you try to find one, you end up with an "estimator" that is non-operational, because it is itself a function of the unknown parameters of the model. It's note really an estimator at all, because it can't be computed.

However, by changing the objective of the exercise slightly, a computable "optimal estimator" can be obtained. Let's take a look at this.