Friday, November 29, 2013

Do You Have a Tattoo?

Significance Magazine  is a joint publication of the Royal Statistical Society and the American Statistical Association. The "News" section of the latest issue (which can be read by subscribers) contains an item titled, "More Than Skin Deep". It's about a mathematics teacher who has an interesting tattoo:

In case you need an interpretation, it reads:  
The item concludes:
"It attracts attention. Often on a beach someone will say something like 'You're either a math teacher or in a really, really odd motorcycle gang.'
Why should statisticians lag behind? A bottle of champagne to the first reader who can show a permanent tattoo of Bayes' theorem - preferably on a part of the anatomy that we can decently reproduce."
Needless to say, this got me thinking! Are there any Econometrics tattoos out there that I should be aware of?

© 2013, David E. Giles

Lawrence R. Klein Memorial Prize

Nobel Laureate Lawrence R. Klein passed away in October of this year in Philadelphia. (See here.) 

Empirical Economics has established a prize in his honour given for the best empirical paper published in the last two years in the journal. An upcoming issue of Empirical Economics will include an obituary written by Badi Baltagi.

© 2013, David E. Giles

Monday, November 25, 2013

A Bayesian View of P-Values

"I have always considered the arguments for the use of P (p-value) absurd. They amount to saying that a hypothesis that may or may not be true is rejected because a greater departure from the trial was improbable: that is, that it has not rejected something that has not happened'"
H. Jeffreys, 1980. Some general points in probability theory. In A Zellner (ed.), Bayesian Analysis in Probability and Statistics. North-Holland, Amsterdam, p. 453.

© 2013, David E. Giles

Thursday, November 21, 2013

Forecasting from a Regression Model

There are several reasons why we estimate regression models, one of them being to generate forecasts of the dependent variable. I'm certainly not saying that this is the most important or the most interesting use of such models. Personally, I don't think this is the case.

So, why is this post about forecasting? Well, a few comments and questions that I've had from readers of this blog suggest to me that not all students of econometrics are completely clear about certain issues when it comes to using regression models for forecasting.

Let's see if we can clarify some terms that are used in this context, and in the process clear up any misunderstandings.

Wednesday, November 20, 2013

Data, Data, Everywhere.....

Data - the life-blood of econometrics - we can't live without them.!

So, thank goodness for the recent re-vamp of the the FED's FRED data site. And also the recent additions to the Quandl site.

© 2013, David E. Giles

Saturday, November 16, 2013

How Science (Econometrics?) is Really Done

If you tweet, you may be familiar with #OverlyHonestMethods. If not, this link to Popular Science will set you on the right track. As it says: "In 140 characters or less, the info that didn't get through peer review."

Here are some beauties that may strike an accord with certain applied econometricians:
  • "Our results were non-significant at p > 0.05, but they're humdingers at p > 0.1"
  • "Experiment was repeated until we had three statistically significant similar results and could discard the outliers"
  • "We decided to use Technique Y because it's new and sexy, plus hot and cool. And because we could."
  • "I can't send you the original data because I don't remember what my excel file names mean anymore."
  • "Non-linear regression analysis was performed in Graph Pad Prism because SPSS is a nightmare."
  • "We made a thorough comparison of all post-hoc tests while our statistician wasn't looking."
  • "Our paper lacks post-2010 references as it's taken the co-authors that long to agree on where to submit the final draft."
  • "If you pay close attention to our degrees-of-freedom you will realize we have no idea what test we actually ran."
  • "Additional variables were not considered because everyone involved is tired of working on this paper."
  • "We used jargon instead of plain English to prove that a decade of grad school and postdoc made us smart."

Oh yes!!!!

© 2013, David E. Giles

A Talk With Lars Peter Hansen

Now that some of the commotion and excitement over this year's Economics Nobel Prize has died down a little, an informal chat with co-winner Lars Peter Hansen is definitely in order.

So, a hat-tip to Mark Thoma for alerting me to this interview of Hansen by Jeff Sommer in the New York Times, today. Jeff manages to get a comment about efficient markets from his interviewee.

And here's a comment that all students of econometrics should take to heart:

"The thing to remember about models is they’re always approximations and they will always turn out to be wrong at some point. When someone says all the models that economists use are wrong, well, in a sense that’s true. But you need to ask, are the models wrong in ways that are central to the questions, or are they wrong in ways that aren’t so central?
And so part of the task of statistical analysis is to look at models and try to figure out what the gaps are so that people will build better models in the future."

© 2013, David E. Giles

Monday, November 11, 2013

Calling All Forecasters!

The 34th International Symposium on Forecasting will be held in Rotterdam between 29 June and 2 July, 2014. Full details can be found here

I participated in the 2010 Symposium, in San Diego. It was a great meeting, very well run, and with a fabulous program. Definitely recommended!

© 2013, David E. Giles

Sunday, November 10, 2013

Free EViews Tutorials

Free Eviews tutorials - but not from me, I'm afraid!

"Free" is good, and you should keep in mind that free introductory tutorials are indeed available from the distributors of the EViews package. You can find the details here.

You can even download all of the associated Powerpoint presentations, and data files, in a zip file. Nice!

© 2013, David E. Giles

Friday, November 8, 2013

The Econometric Game, 2014

Doesn't time fly. We must be having fun! It's time to start thinking about The Econometric Game once again - this time, the 2014 edition.

April  15 to 17 2014 are the dates to keep in mind, and once again Amsterdam will be the place to be. Apparently entries are rolling in!

More on this in due course.

© 2013, David E. Giles

The Stock Market Crash - VECM's & Structural Breaks

A few weeks ago, Roger Farmer kindly drew my attention to a recent paper of his - "The Stock Market Crash Really Did Cause the Great Recession" (here). To whet your appetites, here's the abstract:
"This note shows that a big stock market crash, in the absence of central bank intervention, will be followed by a major recession one to four quarters later. I establish this fact by studying the forecasting ability of three models of the unemployment rate. I show that the connection between changes in the stock market and changes in the unemployment rate has remained structurally stable for seventy years. My findings demonstrate that the stock market contains significant information about future unemployment."

Sunday, November 3, 2013

Specification Testing for Panel Data Models

Recently, I received a query from Rolf Lyneborg Lund who asked for references to material on specification testing in the context of panel data models. After I responded to Rolf. it occurred to me that these references might also be of interest to others.

Going beyond the standard Hausman test for random versus fixed effects, here are some general references that may be helpful:
  • Baltagi, B. H., 1998. Panel data methods. In A. Ullah and D. E. A. Giles (eds.), Handbook of Applied Economic Statistics, Marcel Dekker, New York.
  • Baltagi, B. H., 1999. Specification tests in panel data models using artificial regressions. Annales d'Économie et des Statistiques, 55-56, 277-298.
  • Lee, Y-J., 2005. Specification testing for functional forms in dynamic panel data models.
  • Metcalf, G. E., 1996. Specification testing in panel data with instrumental variables. Journal of Econometrics, 71, 291-307.
  • Park, H. M., 2011. Practical guides to panel data modeling: A step by step analysis using stata. Public Management and Policy Analysis Program, Graduate School of International Relations, International University of Japan.
In addition, there's quite an extensive literature on testing for unit roots and cointegration in panel data models. I won't attempt to summarize this literature here, but a useful, recent, summary is provided by:
  • Chen, M-Y., 2013. Panel unit root and cointegration tests. Mimeo., Department of Finance, National Chung Hsing University.

© 2013, David E. Giles

Friday, November 1, 2013

Some Weekend Reading

Just what you need - some more interesting reading!
  • Al-Sadoon, M. M., 2013. Geometric and long run aspects of Granger causality. Mimeo., Universitat Pompeu Fabra. (Forthcoming in Journal of Econometrics.)
  • Barnett, W. A. and I. Kalondo-Kanyama, 2013. Time-varying parameter in the almost ideal demand system and the Rotterdam model: Will the best specification please stand up? Working Paper 335, Econometric Research Southern Africa.
  • Delgado, M. S. and C. F. Parmenter, 2013, Embarrassingly easy embarrassingly parallel processing in R. Journal of Applied Econometrics, early view, DOI: 10.1002/jae.2362 .
  • Doko Tchatoka, H., 2013. On bootstrap validity for specification tests with weak instruments. Discussion Paper 2013-05, School of Economics and Finance, University of Tasmania.
  • Fisher, L. A., H-S. Huh, and A. R. Pagan , 2013, Econometric issues when modelling with a mixture of I(1) and I(0) variables. NCER Working Paper Series, Working Paper #97.
  • Pesaran, H. H. and Y. Shin, 1998. Generalized impulse response analysis in linear multivariate models. Economics Letters, 58, 17-29.
  • Warr, R. L. and R. A. Erich, 2013. Should the interquartile range divided by the standard deviation be used to assess normality? American Statistician, online, 
    10.1080/00031305.2013.847385 .
  • Zhang, X. and X. Shao, 2013, On a general class of long run variance estimators. Economics Letters, 120, 437-441.

© 2013, David E. Giles