New Features in EViews 9 (Beta)

When you get a chance to check out the "beta" release of EViews 9 (which current users can download from here), you'll find lots of new features.

Many of these relate to the Eviews interface, data handling, and graphs and tables. And then (of course) there are lots of new Econometrics goodies! To summarize them, under the headings used in the documentation:

Computation
• Automatic ARIMA forecasting of a series
• Forecast evaluation and combination testing
• Forecast averaging
• VAR Forecasting

Estimation
• Autoregressive Distributed Lag regression (ARDL) with automatic lag selection
• ML and GLS ARMA estimation
• ARFIMA models
• Pooled mean group estimation of panel data ARDL models
• Threshold regression
• New optimization engine

Testing and Diagnostics
• Unit root tests with a structural break
• Cross-section Dependence Tests
• Panel Effects Tests

I just had to highlight ARDL models. My earlier posts on these models (here and here) attracted a lot of readers, and many questions and comments.

I've been promising a follow-up post on this topic for some time. You can guess why I've been holding off, and what one of my upcoming posts will be about!

© 2014, David E. Giles

Two Non-Problems!

I just love Dick Startz's "byline" on the EViews 9 Beta Forum: 

"Non-normality and collinearity are NOT problems!"

Why do I like it so much? Regarding "normality", see here, and here. As for "collinearity": see here, here, here, and  here

© 2014, David E. Giles

EViews 9 - Beta Version

If you're an EViews user then you'll be delighted to learn that the beta version of the new EViews 9 was released this morning.

Provided that you have EViews 8.1 on your machine, you can download the beta version of this latest release from http://register1.eviews.com/beta/.

Here's what you'll see:

There are no delays - just make sure that you know if you need the 32-bit or 64-bit version.

I've had the opportunity to play around with the alpha version of EViews 9 over the past few weeks (thanks, Gareth!), and I can assure you that there are lots of really nice goodies in store for you.

I'll be devoting a few posts to some of the new features over the next short while, so stay tuned.

© 2014, David E. Giles

Marc Bellemare on Social Media

Marc Bellemare has been catching my attention recently. On Saturday I had a post that mentioned his talk on "How to Publish Academic Papers". I know that a lot of you have followed this up already.

Today, I just have to mention another of his talks, given last Friday, titled "Social Media for (Academic) Economists". Check out his blog post about the talk, and then look at this slides that are linked there.

Yep, I agree with pretty much everything he has to say. And nope, we're not related!

© 2014, David E. Giles

"Mastering 'Metrics"

Mastering 'Metrics: The Path from Cause to Effect, by Joshua Angrist and Jörn-Steffen Pischke, is to be published by Princeton University Press later this month. This new book from the authors of Mostly Harmless Econometrics: An Empiricist's Companion is bound to be well received by students and researchers involved in applied empirical economics. My guess is that the biggest accolades will come from those whose interest is in empirical microeconomics.

You can download and preview the Introduction and Chapter 1.

Apparently the book focuses on:

"The five most valuable econometric methods, or what the authors call the Furious Five - random assignment, regression, instrumental variables, regression discontinuity designs, and differences in differences."

If this sounds interesting to you, then make sure that you take a look at Peter Dizikes' recent post, "How to Conduct Social Science Research", on the World Economic Forum website.

© 2014, David E. Giles

Advice on Publishing

I've put in a lot of time over the years as an Editor, Associate Editor, or Editorial Board member, for a number of economics and statistics journals, ranging from Journal of Econometrics and Econometric Theory, to Journal of International Trade & Economic Development.  I've also refereed more papers than care to think about. 

Students, rightly, are eager to get the scoop on how to get their work published in good journals. They often talk to me about this. My suggestion would be to read, and follow the advice given by Marc Bellemare in his talk, "How to Publish Academic Papers". 

Just do it!

(HT to David Stern for unwittingly making me aware of Marc's talk,)



© 2014, David E. Giles

More on Prediction From Log-Linear Regressions

My therapy sessions are actually going quite well. I'm down to just one meeting with Jane a week, now. Yes, there are still far too many log-linear regressions being bandied around, but I'm learning to cope with it!

Last year, in an attempt to be helpful to those poor souls I had a post about forecasting from models with a log-transformed dependent variable. I felt decidedly better after that, so I thought I follow up with another good deed.

Let's see if it helps some more:

Statistical Controls Are Great - Except When They're Not!

A blog post today, titled, How Race Discrimination in Law Enforcement Actually Works", caught my eye. Seemed like an important topic. The post, by Ezra Klein, appeared on Vox.

I'm not going to discuss it in any detail, but I think that some readers of this blog will enjoy reading it. Here are a few selected passages, to whet your collective appetite:

"You see it all the time in studies. "We controlled for..." And then the list starts. The longer the better." (Oh boy, can I associate with that. Think of all of those seminars you've sat through.......)

"The problem with controls is that it's often hard to tell the difference between a variable that's obscuring the thing you're studying and a variable that is the thing you're studying."

"The papers brag about their controls. They dismiss past research because it had too few controls." (How many seminars was that?)

"Statistical Controls Are Great - Except When They're Not!"

© 2014, David E. Giles

Here's Your Reading List!

As we count the year down, there's always time for more reading!

• Birg, L. and A. Goeddeke, 2014. Christmas economics - A sleigh ride. Discussion Paper No. 220, CEGE, University of Gottingen.
• Geraci, A., D. Fabbri, and C. Monfardini, 2014. Testing exogeneity of multinomial regressors in count data models: Does two stage residual inclusion work? Working Paper 14/03, Health, Econometrics and Data Group, University of York.
• Li, Y. and D. E. Giles, 2014. Modelling volatility spillover effects between developed stock markets and Asian emerging stock markets. International Journal of Finance and Economics, in press.
• Ma, J. and M. Wohar, 2014. Expected returns and expected dividend growth: Time to rethink an established literature. Applied Economics, 46, 2462-2476. 
• Qin, D., 2014. Resurgence of instrument variable estimation and fallacy of endogeneity. Economics Discussion Papers No. 2014-42, Kiel Institute for the World Economy. 
• Romano, J. P. and M. Wolf, 2014. Resurrecting weighted least squares. Working Paper No. 172, Department of Economics, University of Zurich.
• Tchatoka, F.D., 2014. Specification tests with weak and invalid instruments. Working Paper No. 2014-05, School of Economics, University of Adelaide.

© 2014, David E. Giles

The A. R. Bergstrom Prize, 2015

© 2014, David E. Giles