Publications by Dave Giles
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: Wil...
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Rob Hyndman on Forecasting
If you have an interest in forecasting, especially economic forecasting, the Rob Hyndman’s name will be familiar to you. Hailing from my old stamping ground – Monash University – Rob is one of the world’s top forecasting experts. Without going into all of the details, Rob is very widely published, and also has a great blog, Hyndsight. He...
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The Statsguys on Data Analytics
It’s good to see that more and more students of econometrics are taking an interest in “Data Analytics” / “Big Data” /”Data Science” literature. As I’ve commented previously, there’s a lot that we can all learn from each other. Moreover, many of “boundaries” are very soft, and are more perceived than real.So, I was delighted...
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MCMC for Econometrics Students – II
This is the second in a set of posts about Monte Carlo Markov Chain (MCMC, or MC2) methods in Bayesian econometrics. The background was provided in this first post, where the Gibbs sampler was introduced.The main objective of the present post is to convince you that this MCMC stuff actually works!To achieve this, what we’re going to do is work ...
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MCMC for Econometrics Students – III
As its title suggests, this post is the third in a sequence of posts designed to introduce econometrics students to the use of Markov Chain Monte Carlo (MCMC, or MC2) methods for Bayesian inference. The first two posts can be found here and here, and I’ll assume that you’ve read both of them already.We’re going to look at another example i...
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Data Transfer Advice From Francis Smart
I always enjoy reading the posts by Francis Smart on his Econometrics by Simulation blog. A couple of days ago he wrote a nice piece titled, “It is Time for RData Files to Become the Standard for Data Transfer”. Francis made some very nice points about the handling of large amounts of data, and he provided some good examples regarding the c...
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MCMC for Econometrics Students – IV
This is the fourth in a sequence of posts designed to introduce econometrics students to the use of Markov Chain Monte Carlo (MCMC, or MC2) simulation methods for Bayesian inference. The first three posts can be found here, here, and here, and I’ll assume that you’ve read them already. The emphasis throughout is on the use of the Gibbs sample...
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MCMC for Econometrics Students – Part IV
This is the fourth in a sequence of posts designed to introduce econometrics students to the use of Markov Chain Monte Carlo (MCMC, or MC2) simulation methods for Bayesian inference. The first three posts can be found here, here, and here, and I’ll assume that you’ve read them already. The emphasis throughout is on the use of the Gibbs sample...
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Open Science Through R
There’s so much being written about R these days, and justifiably so. If you use R for your econometrics, you should also keep in mind that its applicability is far wider than statistical analysis. A big HT to the folks at Quandl for leading me to a nice overview of the way in which R is enabling some big changes in the way in which scientifi...
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Great Resource for Teaching Statistics with R
If you’re having trouble teaching statistics using R, then you’ll just love the statsTeachR collaboration.It’s being launched officially at the 2014 New England Statistics Symposium today.Here’s what it’s about:“statsTeachR is an open-access, online repository of modular lesson plans, a.k.a. “modules”, for teaching statistics usi...
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