BIG Data

"Big Data" = data that come in amounts that are too large for current computer hardware and software to deal with. That sounds like fun!

When is the OLS estimator BLU?

Or, if you prefer, "When do the OLS and GLS estimators coincide?"

O.K., so you think you know the answer to this one? My guess is that you know a sufficient condition, but probably not a necessary and sufficient condition, for the OLS and GLS estimators of the coefficient vector in a linear regression model to coincide. Let's see if I'm right!

Just Crantastic!

If you're an econometrician and you don't use the R software environment - for at least some of your work, then you're missing out on all sorts of (free!) opportunities.

Festive Fun for all of the Family?

Courtesy of the Royal Statistical Society - The Great Significance Christmas Quiz!!

Information and Entropy Econometrics

The eminent physicist Ed. Jaynes (1957a) wrote:

"Information theory provides a constructive criterion for setting up probability distributions on the basis of partial knowledge, and leads to a type of statistical inference which is called the maximum entropy estimate. It is least biased estimate possible on the given information; i.e., it is maximally noncommittal with regard to missing information."

In other words, when we want to describe noisy data with a statistical model, we should always choose the one that has Maximum Entropy.

"An Information Theoretic Approach to Econometrics"

George Judge & Ron Mittelhammer have a new book, hot off the press: An Information Theoretic Approach to Econometrics (CUP, 2012).

Reported "Accuracy" for Regression Results

In a recent post I posed the question: "How many decimal places (or maybe significant digits) are appropriate when reporting OLS regression results?"

Heteros*edasticity

Earlier this year I had a post about the decline in the amount of attention paid to the concept of "multicollinearity" in econometrics texts over the years. It's a fully justifiable decline, in my view.

Confidence Bands for the H-P Filter: Correction!

Aaaaaghhhh!!

In a post a couple of days ago I posted about constructing confidence bands for the trend that's extracted from a time-series using the Hodrick-Prescott (HP) filter. There was an error in my EViews program code that affected the last graph I showed in that post.

So, Sue Me!

"In a case that’s sending a frightening message to the blogger community, a U.S. District Court judge ruled that a blogger must pay $2.5 million to an investment firm she wrote about — because she isn’t a real journalist."