Publications by Dave Giles
Explaining the Almon Distributed Lag Model
In an earlier post I discussed Shirley Almon’s contribution to the estimation of Distributed Lag (DL) models, with her seminal paper in 1965.That post drew quite a number of email requests for more information about the Almon estimator, and how it fits into the overall scheme of things. In addition, Almon’s approach to modelling distributed l...
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Trading Models and Distributed Lags
Yesterday, I received an email from Robert Hillman.Robert wrote:“I’ve thoroughly enjoyed your recent posts and associated links on distributed lags. I’d like to throw in a slightly different perspective. To give you some brief background on myself: I did a PhD in econometrics 1993-1998 at Southampton University. ………… I now manage c...
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Monte Carlo Simulations & the "SimDesign" Package in R
Past posts on this blog have included several relating to Monte Carlo simulation – e.g., see here, here, and here.Recently I came across a great article by Matthew Sigal and Philip Chalmers in the Journal of Statistics Education. It’s titled, “Play it Again: Teaching Statistics With Monte Carlo Simulation”, and the full reference appears ...
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How Good is That Random Number Generator?
Recently, I saw a reference to an interesting piece from 2013 by Peter Grogono, a computer scientist now retired from Concordia University. It’s to do with checking the “quality” of a (pseudo-) random number generator.Specifically, Peter discusses what he calls “The Pickover Test”. This refers to the following suggestion that he attribu...
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Interpolating Statistical Tables
We’ve all experienced it. You go to use a statistical table – Standard Normal, Student-t, F, Chi Square – and the line that you need simply isn’t there in the table. That’s to say the table simply isn’t detailed enough for our purposes.One question that always comes up when students are first being introduced to such tables is:“Do I...
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Econometrics Reading for the New Year
Another year, and lots of exciting reading!Davidson, R. & V. Zinde-Walsh, 2017. Advances in specification testing. Canadian Journal of Economics, online.Dias, G. F. & G. Kapetanios, 2018. Estimation and forecasting in vector autoregressive moving average models for rich datasets. Journal of Econometrics, 202, 75-91. González-Estrada, E. & J....
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More Sandwiches, Anyone?
Consider this my Good Deed for the Day!A re-tweet from a colleague whom I follow on Twitter brought an important paper to my attention. I thought I’d share it more widely.The paper is titled, “Small-sample methods for cluster-robust variance estimation and hypothesis testing in fixed effect models”, by James Pustejovski (@jepusto) and B...
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December Reading for Econometricians
My suggestions for papers to read during December:Askanazi, R., F. X. Diebold, F. Schorfheide, & M. Shin, 2018. On the comparison of interval forecasts. PIER Working Paper 18-013, Penn. Institute for Economic Research, University of Pennsylvania.Meintanis, S. G., J. Ngatchou-Wandji, & J. Allison, 2018. Testing for serial independence in vector au...
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Forecasting From a Regression with a Square Root Dependent Variable
Back in 2013 I wrote a post that was titled, “Forecasting From Log-Linear Regressions“. The basis for that post was the well-known result that if you estimate a linear regression model with the (natural) logarithm of y as the dependent variable, but you’re actually interested in forecasting y itself, you don’t just report the exponential...
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What is a Permutation Test?
Permutation tests, which I’ll be discussing in this post, aren’t that widely used by econometricians. However, they shouldn’t be overlooked.Let’s begin with some background discussion to set the scene. This might seem a bit redundant, but it will help us to see how permutation tests differ from the sort of tests that we usually use in eco...
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