September Reading List

In North America, Labo(u)r Day weekend is upon us. The end of summer. Back to school. Last chance to get some pre-class reading done!

• Blackburn, M. L., 2014. The relative performance of Poisson and negative binomial regression estimators. Oxford Bulletin of Economics and Statistics, in press.
• Giannone, D., M. Lenza, and G. E. Primiceri, 2014. Prior selection for vector autoregressions. Review of Economics and Statistics, in press.
• Gulesserian, S. G. and M. Kejriwal, 2014. On the power of bootstrap tests for stationarity: A Monte Carlo comparison. Empirical Economics, 46, 973-998.
• Elliot, G. and A. Timmerman, 2008. Economic forecasting. Journal of Economic Literature, 46, 3-56.
• Kiviet, J. F., 1986, On the rigour of some misspecification tests for modelling dynamic relationships. Review of Economic Studies, 53, 241-261.
• Otto, G. D. and G. M. Voss, 2014. Flexible inflation forecast targeting: Evidence from Canada. Canadian Journal of Economics, 47, 398-421. 

© 2014, David E. Giles

N.Z. Econometrics Study Group, 2015

Thanks to Peter Phillips, the New Zealand Econometric Study Group has been going strong for a quarter of  a century. I last mentioned the group after my participation in the meeting last year - see here. 

In February of 2015 the NZESG meeting will be going off-shore for the first time, and will be held at the Queensland University of Technology (Australia). In particular, it will be held in collaboration with the National Centre for Econometric Research, about which I've posted previously.

The full details of the upcoming Meeting can be found here. Definitely something to be looking forward to!

© 2014, David E. Giles

On Rockets and Feathers

"Rockets and Feathers" is a term that is often used to describe the (apparent) asymmetric responses of downstream price changes to changes in upstream prices. I believe that the expression was coined by Bacon (1991), and it's been used frequently in the literature in connection with the prices of gasoline and crude oil.

When the price of crude oil falls, does the price of gasoline fall as quickly as it rises when the crude oil price rises? Many studies suggest that the answer is "No". The price goes goes up like a rocket, but it falls like a feather.

There are several explanations for this apparent phenomenon, and a really good analysis of these competing hypotheses is provided by Douglas and Herrera (2010), for example.

This phenomenon was mentioned in my recent post about the paper that I presented at the Joint Statistical Meetings a few weeks ago. Since then, I've received a nice email from Andrea Bastianin, a post-doctoral fellow at the University of Milan. Andrea sent me a paper that he and his co-authors have completed, and that's to appear in Energy Economics.

While dealing with the "Rockets and Feathers" hypothesis in relation to oil and gasoline prices, their paper has an important and novel twist to it- they focus on forecasting performance of models that incorporate asymmetry. Here's the abstract:

The Econometrics of Temporal Aggregation - III - Unit Roots

In two previous posts, I've talked a bit about the effect that aggregating time series data can have on some standard econometric results. The first of those posts was about a talk that I gave last month at the 2014 Conference of the New Zealand Association of Economists. That talk was on the general topic of "The Econometrics of Temporal Aggregation". The second post looked more specifically of the consequences of such aggregation on the results of testing for Granger causality.

Here, I'll provide some information about the impact of temporal aggregation on the existence of, and testing for, unit roots in time-series data.

Risk Analysis for Three Precious Metals

Qinlu (Louisa) Chen and I have recently completed a paper titled, "Risk Analysis for Three Precious Metals: An Application of Extreme Value Theory". It's based in part on work that Louisa undertook in her B.Sc. Honours program here at UVic.

Here's the abstract:

"Gold, and other precious metals, are among the oldest and most widely held commodities used as a hedge against the risk of disruptions in financial markets. The prices of such metals fluctuate substantially, introducing a risk of its own. This paper’s goal is to analyze the risk of investment in gold, silver, and platinum by applying Extreme Value Theory to historical daily data for changes in their prices. The risk measures adopted in this paper are Value at Risk and Expected Shortfall. Estimates of these measures are obtained by fitting the Generalized Pareto Distribution, using the Peaks‐Over‐Threshold method, to the extreme daily price changes. The robustness of the results to changes in the sample period is discussed. Our results show that silver is the most risky metal among the three considered. For negative daily returns, platinum is riskier than gold; while the converse is true for positive returns."

If you're interested, you can download the full paper here.

© 2014, David E. Giles

The Bracken Bower Prize

The Bracken Bower Prize is a new initiative that's intended to motivate younger authors to identify and analyse future business trends. It's an important award that could well be of interest to applied econometricians, so here are the details that were sent to me:

Introducing the Bracken Bower Prize

The Financial Times and McKinsey & Company, organisers of the Business Book of the Year Award, want to encourage young authors to tackle emerging business themes. They hope to unearth new talent and encourage writers to research ideas that could fill future business books of the year. A prize of £15,000 will be given for the best book proposal.

The Bracken Bower Prize is named after Brendan Bracken who was chairman of the FT from 1945 to 1958 and Marvin Bower, managing director of McKinsey from 1950 to 1967, who were instrumental in laying the foundations for the present day success of the two institutions. This prize honours their legacy but also opens a new chapter by encouraging young writers and researchers to identify and analyse the business trends of the future.

The inaugural prize will be awarded to the best proposal for a book about the challenges and opportunities of growth. The main theme of the proposed work should be forward-looking. In the spirit of the Business Book of the Year, the proposed book should aim to provide a compelling and enjoyable insight into future trends in business, economics, finance or management. The judges will favour authors who write with knowledge, creativity, originality and style and whose proposed books promise to break new ground, or examine pressing business challenges in original ways.

              

Only writers who are under 35 on November 11 2014 (the day the prize will be awarded) are eligible. They can be a published author, but the proposal itself must be original and must not have been previously submitted to a publisher.

The judging panel for 2014 comprises: 

Vindi Banga, partner, Clayton Dubilier & Rice

Lynda Gratton, professor, London Business School

Jorma Ollila, chairman, Royal Dutch Shell and Outokumpu

Dame Gail Rebuck, chair, Penguin Random House, UK

The proposal should be no longer than 5,000 words – an essay or an article that conveys the argument, scope and style of the proposed book – and must include a description of how the finished work would be structured, for example, a list of chapter headings and a short bullet-point description of each chapter. In addition entrants should submit a biography, emphasising why they are qualified to write a book on this topic. The best proposals will be published on FT.com.

The organisers cannot guarantee publication of any book by the winners or runners-up. The finalists will be invited to the November 11 dinner where the Bracken Bower Prize will be awarded alongside the Business Book of the Year Award, in front of an audience of publishers, agents, authors and business figures. Once the finalists’ entries appear on FT.com, authors will be free to solicit or accept offers from publishers. The closing date for entries is 5pm (BST) on September 30th 2014.

Full rules for The Bracken Bower prize are available at  http://membership.ft.com/PR/brackenbower/

© 2014, David E. Giles

David Mimno on "Data Carpentry"

There's a post on David Mimno's blog  today titled, "Data Carpentry".

I like it a lot, because it emphasises just how much effort, time and creativity can be required in order to get one's data in order before we can get on with the fun stuff - estimating models, testing hypotheses, making forecasts, and so on. I know that this was something that I didn't fully appreciate when I was starting my career. And when I did get the message, I found it rather irksome!

However, the message isn't going to change, so we just have to live with it, and accept the realities of working with "real" data.

In his post, David explains why he doesn't like the oft-used term"data cleaning" (which makes us sound like "data janitors"), and why he prefers the term "data carpentry". Certainly, the latter has more constructive overtones.

As he says:

"To me these imply that there is some kind of pure or clean data buried in a thin layer of non-clean data, and that one need only hose the dataset off to reveal the hard porcelain underneath the muck. In reality, the process is more like deciding how to cut into a piece of material, or how much to plane down a surface. It’s not that there’s any real distinction between good and bad, it’s more that some parts are softer or knottier than others. Judgement is critical.

The scale of data work is more like woodworking, as well. Sometimes you may have a whole tree in front of you, and only need a single board. There’s nothing wrong with the rest of it, you just don’t need it right now."

A nice post, and a very nice "take" on a crucial part of the work that we do.

© 2014, David E. Giles

Early Computing

During a recent visit to Harvard U. I came across this monstrosity thing of beauty in the Science Center - the building where the Dept. of Statistics is housed:

It's an "Aiken-IBM Automatic Sequence Controlled Calculator - I", and dates from 1944. (Obviously, those other people in the picture liked it a lot too - I couldn't get them out of the way! But they do give you a sense of scale.)

From left to right, the main components of the calculator are:

1. Panel of 60 constants.
2. Unit of 72 storage counters.
3. The multiply/divide unit.
4. Fractional counters.
5. Interpolators - 1, 2, 3.
6. Sequence control.
7. Typewriters (barely visible).
8. Card feed (out of sight).
9. Card punch (even more out of sight!).

It's about the size of strech limo, and a great piece of computing history.

It reminded me of "The Monkey Run" - ah, those were the days!

© 2014, David E. Giles

The A. R. Bergstrom Prize in Econometrics, 2015

A. R. (Rex) Bergstrom can reasonably be regarded as the "father" of modern econometrics in New Zealand. He made seminal contributions to continuous-time econometrics and the finite-sample properties of simultaneous equations estimators. He also taught and inspired a generation of young econometricians.

You can read Peter Phillips' 1988 "ET Interview" with Rex here.

Rex's contributions are recognized by a biennial award, named in his honour. Applications and nominations for the 11^th A. R. Bergstrom Prize are now being solicited:

© 2014, David E. Giles

A Trio of Texts

A Trio of Texts refers to three, free, econometrics e-texts made available by Francis Diebold, at U. Penn. Francis blogs at No Hesitations.

The three books on question are 

• Econometrics (undergraduate level)
• Forecasting (upper-level undergraduate/graduate level)
• Time Series Econometrics (graduate level)

Accompanying slides, data, and code are also available, and the material is updated regularly.

The material is of an extremely high quality, and I strongly recommend all three books.

© 2014, David E. Giles

Wrapping up at the JSM

Today was my last day at the 2014 JSM in Boston - unfortunately I'm unable to stay on for tomorrow's sessions.

As always, it was a terrific meeting - extremely well organized, and with a huge number of interesting papers from a very diverse range of contributors. There were too many highlights to cover here. Suffice to say that I'll be going home with a lot of material that I'll be wanting to follow up in the coming months.

In addition to catching up with various professional acquaintances, it was great to meet some new people. At the top of my list in this respect were Gareth Thomas and Glenn Sueyoshi, from EViews. 

Among the things that we discussed were some of the new features that will be included in EViews 9, when it is released. My lips are sealed, of course, but rest assured that followers of this blog will enjoy these new features a lot!

So, now it's back to reality..................

© 2014, David E. Giles

My Talk at the JSM

Tomorrow morning (Wednesday 6 August) I'll be presenting at the Joint Statistical Meetings in Boston.

The title for my talk is "Modelling Asymmetries in the Market for Gasoline in Western Canada", and it's based on some research that I have underway on this topic. 

The question that's addressed in this work is: "Are the upward and downward movements in retail gasoline prices, that follow increases and decreases in crude oil prices, symmetric?" There's a common perception that the "flow-through" from oil prices to gasoline prices is faster when prices are rising than when they are falling. I use ARDL models with an explicit allowance for possible asymmetry to test this hypothesis.

I'll have more to say on this when the work is completed, but in the meantime you can see some partial results by downloading the slides for my talk here.

© 2014, David E. Giles

The 7 Pillars of Statistical Wisdom

Yesterday, Stephen Stigler presented the (ASA) President's Invited Address to an overflow, and appreciative, audience at the 2014 Joint Statistical Meetings in Boston. The title of his talk was, "The Seven Pillars of Statistical Wisdom".

I'd been looking forward to this presentation by our foremost authority on the history of statistics, and it surpassed my (high) expectations.

The address will be published in JASA at some future date, and I urge you to read it when it appears. In the meantime, here are the "seven pillars" - the supporting pillars of statistical science - with some brief comments:

Estimation & Accuracy After Model Selection

This was the title of Brad Efron's invited paper at the 2014 Joint Statistical Meetings in Boston this morning. It was a great presentation, with excellent discussants - Lan Wang, Lawrence Brown, and Soumendra Lahiri.

The paper and discussion are scheduled to appear in the September 2014 issue of JASA.

A lot of what Brad and his discussants had to say related to one of the main points in one of my recent posts. Namely, if you search for a model specification, then this affects all of your subsequent inferences - and usually in a rather complicated way. Typically, even after searching for a preferred model, we tend to "pretend" that we haven't done this, and that the model's form was known from the outset. Naughty! Naughty!

What Brad has done is to address the "pre-test" issue in a rather nice way. You won't be surprised to learn that bootstrapping features heavily in the methodology that he's developed. Using two examples - one non-parametric, and one parametric - he showed how to take account of model selection via Mallows' C_p statistic, and the lasso (respectively), when constructing regression confidence intervals.

One important feature of his analysis involves "smoothing" the results to take account of the discontinuities that inherent in model selection. Although it wasn't mentioned in Brad's talk, these discontinuities are the source of some of the most important problems associated with pre-testing in general. For example, traditional pre-test estimators of regression coefficients (based, say, on a prior test of linear restrictions on those coefficients) are inadmissible under a range of standard loss functions. This inadmissibility is entirely due to the fact that these pre-test estimators are discontinuous functions of the random sample data.

All in all it was a great session, with some nice take-away quotes:

• "The discussants actually discussed my paper."
• "Simulations are hard to do."
• "Model averaging is perfectly easy to do, but model selection is not."

I took some comfort from the last two of these comments!

© 2014, David E. Giles

Correlation and Causation

A hat-tip to Judea Pearl, whose e-newsletter alerted me to this interesting post on the EvaluationHelp blog. It shows the original sixteen diagrams in Sewall Wright's classic 1921 paper on correlation and causality.

Philip and Sewall Wright were responsible for seminal contributions to the basic notions of instrumental variables estimation and parametric identification, though there is still some debate over their relative contributions to these important concepts.

Reference

Wright, S. (1921). Correlation and causation. Part I Method of path coefficients. Journal of Agricultural Research, 20, 557-585.

© 2014, David E. Giles