Prosperity, Thriving, & Economic Growth

A while ago I posted a couple of pieces (here and here) relating to the Better Life Index (BLI) that the OECD released in May of this year. Not surprisingly, the BLI caught the attention of a number of bloggers.

Some of the most thoughtful posts on this topic came from the Australian economist, Winton Bates. In the last few days Winton has extended his earlier analysis and comments in a series of posts that look at other, somewhat similar, indices.

These include the Legatum Prosperity Index, which Winton correlates with the BLI  here, and relates to GDP growth here. If you check these out you'll find links to his earlier posts on the BLI. 

In another interesting post (here), Winton asks "Does economic growth help people to thrive?" He uses Gallup's World Poll data on "thriving", "struggling" and "suffering", and relates it to per capita GDP in different countries. The Gallup data are interesting in their own right, being based on the Cantril self-striving anchoring scale, which you can learn more about here.

If you have an interest in these various measures of  "well being", and the linkages between them and standard measures of economic output and growth (e.g., GDP), Winton's blog, "Freedom and Flourishing", is definitely worth following.

© 2011, David E. Giles

Econometrics Without Borders?

We're all familiar with the "Doctors Without Borders" organization, and the valuable international medical work that it performs. Perhaps you didn't know that there's also a group called "Statistics Without Borders"? To quote from their web site, their mission statement is as follows:

"Statistics Without Borders (SWB) is an apolitical organization under the auspices of the American Statistical Association, comprised entirely of volunteers, that provides pro bono statistical consulting and assistance to organizations and government agencies in support of these organizations' not-for-profit efforts to deal with international health issues (broadly defined)."

It's great to see The American Statistical Association, which I've been a member of for 38 years, supporting this type of venture.

Now, a new initiative, provisionally called "Data Without Borders" (DWB), has been established by data scientist, Jake Porway. You can read about it on Porway's web site, of course, and also in a recent post on The Guardian's DataBlog here. Briefly, the aim is to match important data from not-for-profit organizations with experts in the analysis of data. According to a recent item in the Royal Statistical Society's newsletter, RSSeNEWS, there were over 300 expressions of interest, internationally, within the first 24 hours of DWB being announced.

So, don't let anyone ever tell you that being a "quant" who works with data can't be socially meaningful. Even econometricians can make a difference if we want to!

© 2011, David E. Giles

Choosing Your Co-Authors Carefully

The choice of your co-authors in academic work can be very important - you all have to be able to bring something to the table, and hopefully there'll be enough synergies to ensure that the paper (or book) is better than any of you could have achieved individually.

I must say that I've certainly been extremely fortunate with my own past and current co-authorship "liasons".

There's plenty that could be said about deciding on the order of the authors - but I'll leave that for another post. That being said, there may be some other interesting considerations.

I was recently re-reading Stephen Hawking's A Brief History of Time. In Chapter 6 Hawking has a great story about an important quantum physics paper published in Physical Review in 1948. Two of the authors were George Gamow and his Ph.D. student, Ralph Alpher, at George Washington University. Gamow, persuaded the renowned physicist Hans Bethe to join them as a co-author, simply so that the final line-up of authors was Alpher, Bethe and Gamow.

A much more detailed account of the background to the "Alpha-Beta-Gamma" paper is provided by Simon Singh, in his book Big Bang: The Origin of the Universe. The paper, titled simply 'The Origin of Chemical Elements' was (Singh, p.323) "...a milestone in the Big Bang versus eternal universe debate", and "....the first major triumph for the Big Bang model since Hubble had observed and measured the redshifts of galaxies." (Singh, p.319).

Unfortunately, there was a darker side to this story that I was unaware of until Jeremy Austin brought it to my attention in a comment to the original version of this post (see below).

However, it certainly made me think about some possibilities for interesting co-authorships in other disciplines.

For instance, ........ they lived centuries apart, and their contributions to pure mathematics don't really overlap, but wouldn't it be nice if we could time-travel and get (Fields Medal winner) Klaus Roth to team up with Michel Rolle. A kind of mathematical jam session!

Moving closer to home, I see that both Yixiao Sun and Hyungsik Roger Moon have (separately) co-authored papers with Peter Phillips. However, it seems the first two of these econometricians haven't taken the opportunity to co-author a paper together. Pity - I'd enjoy that!

And what about trying to persuade Fallaw Sowell and John Pepper to cook up some interesting econometrics for us? Or perhaps my friend John Knight could collaborate with Rohit Deo? They'd undoubtedly produce a paper that was the epitomy of econometric clarity.

So, whatever your last name is, choose your co-authors carefully, and maybe even have a bit of fun in the process! 

© 2011, David E. Giles

Alexander Aitken

Can you imagine what it would be like  trying to learn and teach econometrics without the use of matrix algebra? O.K., I know that some of you are probably thinking, "that would be great!" But give it some serious thought. We'd be extremely limited in what we could do. It would be a nightmare to go beyond the absolute basics.

Only in the 1960's, with the classic texts by Johnston (1963) and Goldberger (1964), did the use of matrix algebra become standard practice in the teaching of econometrics. We used that first edition of Johnston's text in the first undergraduate econometrics course I took. Thank goodness!

Every student of econometrics is indebted to Alexander Craig Aitken (1895 - 1967) for his development of what is now the standard vector/matrix notation for the linear  regression model (and its extensions). Econometricians also use the Generalised Least Squares ("Aitken") estimator when this model has a non-standard error covariance matrix.

The seminal Generalised Least Squares contribution, together with the first matrix formulation of the linear regression model appeared in Aitken's paper, "On Least Squares and Linear Combinations of Observations", Proceedings of the Royal Society of Edinburgh, 1935, vol. 55, pp. 42-48. In this paper we find the well-known extension of the Gauss-Markhov Theorem to the case where the regression error vector has a non-scalar covariance matrix - the Aitken estimator is shown to be "Best Linear Unbiased".

Aitken's most influential statistical paper was co-authored with (another New Zealander) Harold  Silverstone - "On the Estimation of Statistical Parameters", Proceedings of the Royal Society of Edinburgh, 1942, vol. 61, pp. 186-194. This paper extends earlier ideas by Sir Ronald Fisher to derive (only for the unbiased case) the result that we now usually refer to as the "Cramér-Rao Inequality" for the lower bound on the variance of an estimator. Interestingly, this contribution pre-dates the 1945 work by Rao and Cramér's 1946 paper.

So who was Alexander Craig Aitken?

The Econometric Game

If you're not familiar with The Econometric Game, you might find it interesting. It's a great concept, and it's become an important international event for graduate students in Econometrics.

I was especially pleased when a team from my old department at Monash University, in Melbourne, Australia, won the Game in 2010.

© 2011, David E. Giles

One Good Turn Deserves Another

A couple of days ago I received an email from a Ph.D. student in the U.K.. I don't know him, or his supervisor, but the message came with a simple enough request. The student was having trouble getting hold of a copy of a paper published as a chapter in a book (Handbook of Applied Economic Statistics) that Aman Ullah and I edited a few years - could I help in some way?

This sort of thing comes up from time to time for all of us, I'm sure. When I got the email I was reminded of the first time that I was on the other end of such a request - in 1973, as a Ph.D. student in New Zealand, trying to get on top of what was then a newly emerging field - Bayesian Econometrics.

Arnold Zellner's classic book had appeared just two years earlier. I'd been through it from cover to cover - I still have my notes that fill in all of those gaps where there are statements such as: "Completing the square and then integrating, it can be shown that...." (Two pages of integration later....!)

Anyway, I was trying to get hold of a particular Ph.D. dissertation that Arnold had recently supervised. The University of Chicago didn't participate in the dissertations microfiche distribution service that the University of Michigan then ran, internationally. (Microfiche?? You had to be there!) So, our library couldn't help me. I was on my own.

Decline and Fall of Econometrics?

"Please bear in mind throughout that IT IS MEANT TO BE FUNNY."

(Evelyn Waugh, 'Author's Note' in Decline and Fall, 1^st ed., 1928)

I'm not sure that there's anything funny about the decline and fall of Econometrics, especially if you're an econometrician - that's if it were true, of course. But is it? Personally I don't think so.

Econometricians seem to be very much in demand. To take one example, if you take a look at the EconJobMarket site right now you'll see that over the past 6 months, and also in total since that site began, more jobs have been posted in the Econometrics category than in any other economics category (except for "Any Field").

BTW, don't be put off by the fact that there don't seem to have been very many jobs posted at all in the past 6 months - that period doesn't cover the annual recruitment season job posts. With that recruitment season  in mind, if you look back at last October's issue of JOE, you'll find that there were over 130 job postings in the "Mathematical & Quantitative Methods" (which is primarily Econometrics)category.

It will be interesting to see how the job numbers for econometricians stack up in JOE after this summer's break.

Imagine my alarm, then, when I obtained this chart while playing around the other day with Google Trends:

p-Values for Cointegration Tests With Breaks in the Data

In an earlier post I went through some econometrics that involved the problem of testing for multivariate cointegration in the case where there are one or more trend-breaks or level-breaks in the time-series data.  Specifically, I talked about the modified Trace tests introduced by Johansen et al. (2000), and I mentioned the really nice discussion of the application of these tests that is provided by Joyeux (2007).

Two things relating to this occurred to me recently. The first was that while I'd provided EViews code for calculating asymptotic critical values to be used with these tests, it would also be useful to have the corresponding code for calculating p-values for any calculated values of the Trace test statistics.

Second, given the discussion and comments in my recent posts (here and here) about open-source software, I thought it would be a good idea to make the p-values and critical values code available for users of R. (Thanks for the earlier comments, "Ben" and Tal Galili!)

So, in a joint effort, Ryan Godwin and I have written the R code, and extended the earlier EViews code to compute the p-values. Both of them are on the Code  page that goes with this blog - in two places: under this post, and also in place of the code for the earlier post. (You can thank Ryan for the nice windows that open when you run the R program.) In addition, an Excel workbook with a big selection of critical values is avalable on the Data page for this blog.

We hope you find the programs useful!


Note: The links to the following references will be helpful only if your computer's IP address gives you access to the electronic versions of the publications in question. That's why a written References section is provided.

References

Johansen, S., R. Mosconi and B. Nielsen (2000). Cointegration analysis in the presence of structural breaks in the deterministic trend. Econometrics Journal, 3, 216-249.

Joyeux, R. (2007). How to deal with structural breaks in practical cointegration analysis? In B. B. Rao (ed.), Cointegration for the Applied Economist, Second Edition, Palgrave Macmillan, New York, 195-221.

© 2011, David E. Giles

Your Very Own Theorem

Too many term papers to grade? Tenure clock running? Don't have the time to crank out a new theorem today?

Fear not! TheoryMine can come to your rescue. As they so delightfully explain:

"You can name your very own mathematical theorem, newly generated by one of the world's most advanced computerised theorem provers (a kind of robot mathematician), and you can immortalise your loved ones, teachers, friends and even yourself and your favourite pets".

And:

"You can buy new theorems which become yours to name. You will receive a printable certificate in PDF form of the theorem and its discovery (including an outline of the proof). You can then give this away, frame it, sing it, as you like!"

At only £15.00, this looks to me like a bargain just waiting to be snapped up! I mean, how long did you spend proving that last theorem of yours? I'll bet that (No. of Hours x Hourly Salary) > 15!

I particularly like the idea of "immortalising your teachers" (hint, hint), and I promise not to sing it!

HT to Ken Stewart.

© 2011, David E. Giles

gretl

In comments on a recent post, "Ben" and Tal Galili very sensibly asked if I could make R code available for the econometric analysis in my posts, in addition to EViews code. I'll be trying to do this wherever I can, given the time constraints.

The important point implicit in these comments is that R is free, open-source, software, whereas EViews is not. I'm definitely a supporter of open-source. Here's a suggestion that may be helpful in the meantime, especially if you aren't feeling up to learning R.

There's a nice open-source package called gretl that has much in common with EViews. It's specifically econometrics-oriented, with lots of the time-series features that are part of EViews' strength, and that are hard to match in a freindly way in a lot of other econometrics packages.

In case you're wondering, gretl is an acronym for Gnu Regression, Econometrics and Time-series Library.

The really good news is that is is very simple to open foreign data files in gretl, including EViews workfiles, SAS, STATA, and SPSS files. This might help some readers of this blog who don't have access to EViews.

Right now, there seem to be a few problems with opening some EViews 7 files in gretl - earlier versions of EViews are fine. Allin Cottrell is kindly checking this out, and I'll keep you posted on this point.

From here on I'll try and supply data in EViews.wf1, Excel, R, and STAT.dta files to maximize accessibility.

I'm only just starting to play around with gretl, but it looks just great!

(HT to Martina Lui - long overdue!)

© 2011, David E. Giles