More Tributes to Clive Granger

As a follow-up to my recent post, "Clive Granger Special Issue", I received an email from Eyüp Çetin (Editor of the European Journal of Pure and Applied Mathematics).

Eyüp kindly pointed out that "......... actually, we published the first special issue dedicated to his memory exactly on 27 May 2010, the first anniversary of his passing at https://www.ejpam.com/index.php/ejpam/issue/view/11 

We think this was the first special issue dedicated to his memory in the world. The Table of Contents may be found here https://www.ejpam.com/index.php/ejpam/issue/view/11/showToc .

Another remarkable point that we also published some personal and institutional tributes and some memorial stories for Sir Granger that never appeared elsewhere before at 

https://www.ejpam.com/index.php/ejpam/article/view/805 .

Some institutions such as Royal Statistical Society, Japan Statistical Society and University of Canterbury have sent their tributes to this special volume." 

© 2019, David E. Giles

Clive Granger Special Issue

The recently published Volume 10, No. 1 issue of the European Journal of Pure and Applied Mathematics takes the form of a memorial issue for Clive Granger. You can find the Table of Contents here, and all of the articles can be downloaded freely.

This memorial issue is co-edited by Jennifer Castle and David Hendry. The contributed papers include ones that deal with Forecasting, Cointegration, Nonlinear Time Series, and Model Selection.

This is a fantastic collection of important survey-type papers that simply must read!

© 2019, David E. Giles

Reading Suggestions for June

Well, here we are - it's June already.

Here are my reading suggestions:

• Abadie, A., S. Athey, G. Imbens, & J. Wooldridge, 2017. When should you adjust standard errors for clustering? Mimeo.
• Berk, R., A. Buja, L. Brown, E. George, A. K. Kuchibhotla, W. Su, & L, Shazo, 2019. Assumption lean regression. American Statistician, in press.
• Ghosh, T., M. Ghosh, & T. Kubokawa, 2019. On the loss robustness of least-square estimators, American Statistician, in press.
• Gustafsson, O. & P. Stockhammar, 2019. Variance stabilizing filters. Communications in Statistics - Theory and Methods, in press.
• Kocherlakota, N. R., 2019. A near-exact finite sample theory for an instrumental variable estimator. Mimeo. (Hat-tip to Frank Diebold.)
• Panagiotelis, A., G. Anathasopoulos, R. J. Hyndman, B. Jiang, & F. Vahid, 2019. Macroeconomic forecasting for Australia using a large number of predictors. International Journal of Forecasting, 35, 613-633.

© 2019, David E. Giles

Update on the "Series of Unsurprising Results in Economics"

In June of last year I had a post about a new journal, Series of Unsurprising Results in Economics (SURE).

If you didn't get to read that post, I urge you to do so. 

More importantly, you should definitely take a look at this piece by Kelsey Piper, from a couple of days ago, and titled, "This economics journal only publishes results that are no big deal - Here’s how that might save science".

Kelsey really understands the rationale for SURE, and the important role that it can play in terms of reducing publication bias, and assisting with replicating results.

You can get a feel for what SURE has to offer by checking out this paper  by Nick Huntington-Klein and Andrew Gill that they are publishing.

We'll all be looking forward to more excellent papers like this!

© 2019, David E. Giles

May Reading List

Here's a selection of suggested reading for this month:

• Athey, S. & G. W. Imbens, 2019. Machine learning methods economists should know about. Mimeo.
• Bhagwat, P. & E. Marchand, 2019. On a proper Bayes but inadmissible estimator. American Statistician, online.
• Canals, C. & A. Canals, 2019. When is n large enough? Looking for the right sample size to estimate proportions. Journal of Statistical Computation and Simulation, 89, 1887-1898.
• Cavaliere, G. & A. Rahbek, 2019. A primer on bootstrap testing of hypotheses in time series models: With an application to double autoregressive models. Discussion Paper 19-03, Department of Economics, University of Copenhagen.
• Chudik, A. & G. Geogiardis, 2019. Estimation of impulse response functions when shocks are observed at a higher frequency than outcome variables. Globalization Institute Working Paper 356, Federal Reserve Bank of Dallas.
• Reschenhofer, E., 2019. Heteroscedasticity-robust estimation of autocorrelation. Communications in Statistics - Simulation and Computation, 48, 1251-1263.

© 2019, David E. Giles

Recursions for the Moments of Some Continuous Distributions

This post follows on from my recent one, Recursions for the Moments of Some Discrete Distributions. I'm going to assume that you've read the previous post, so this one will be shorter. 

What I'll be discussing here are some useful recursion formulae for computing the moments of a number of continuous distributions that are widely used in econometrics. The coverage won't be exhaustive, by any means. I provide some motivation for looking at formulae such as these in the previous post, so I won't repeat it here. 

When we deal with the Normal distribution, below, we'll make explicit use of Stein's Lemma. Several of the other results are derived (behind the scenes) by using a very similar approach. So, let's begin by stating this Lemma.

Stein's Lemma (Stein, 1973):

"If  X ~ N[θ , σ²], and if g(.) is a differentiable function such that E|g'(X)| is finite, then 

                            E[g(X)(X - θ)] = σ² E[g'(X)]."

It's worth noting that although this lemma relates to a single Normal random variable, in the bivariate Normal case the lemma generalizes to:

"If  X and Y follow a bivariate Normal distribution, and if g(.) is a differentiable function such that E|g'(Y)| is finite, then 

                            Cov.[g(Y ), X] = Cov.(X , Y) E[g'(Y)]."

In this latter form, the lemma is useful in asset pricing models.

There are extensions of Stein's Lemma to a broader class univariate and multivariate distributions. For example, see Alghalith (undated), and Landsman et al. (2013), and the references in those papers. Generally, if a distribution belongs to an exponential family, then recursions for its moments can be obtained quite easily.

Now, let's get down to business............

Recursions for the Moments of Some Discrete Distributions

You could say, "Moments maketh the distribution". While that's not quite true, it's pretty darn close.

The moments of a probability distribution provide key information about the underlying random variable's behaviour, and we use these moments for a multitude of purposes. Before proceeding, let's be sure that we're on the same page here.

2019 Econometric Game Results

The Econometric Game is over for another year.

The winning team for 2019 was from the University of Melbourne.

The second and third placed teams were from the Maastricht University and Aarhus University, respectively.

Congratulations to the winning teams, and to all who competed this year!

© 2019, David E. Giles

EViews 11 Now Available

As you'll know already, I'm a big fan of the EViews econometrics package. I always found it to be a terrific, user-friendly, resource when teaching economic statistics and econometrics, and I use it extensively in my own research.

Along with a lot of other EViews users, I recently had the opportunity to "test drive" the beta release of the latest version of this package, EViews 11. 

EViews 11 has now been officially released, and it has some great new features. (Click on the links there to see some really helpful videos.) To see what's now available, check it out here. 

Nice update. Thanks!

© 2019, David E. Giles

SHAZAM!

This past weekend the new movie, Shazam, topped the box-office revenue list with over US$53million - and this is it's first weekend since being released.

Not bad!

Of course, in the Econometrics World, we associate the word, SHAZAM, with Ken White's famous computing package, which has been with us since 1977. 

Ken and I go way back. A few years ago I had a post about the background to the SHAZAM package. In that post I explained what the acronym "SHAZAM" stands for. If you check it out you'll see why it's timely for you to know these important historical facts!

And while you're there, take a look at the links to other tales that illustrate Ken's well-known wry sense of humour.

© 2019, David E. Giles