What (Some of) My Colleagues Are Up To

There's plenty of empirical research going on in the Department of Economics at the University of Victoria, where I work. Readers of the blog get to read plenty about what I've been doing, but what about other empirical work by some of my colleagues?

The following is a small cross-section of some of the quantitative papers that have been produced recently in this department. I've limited myself to very papers that are readily available for downloading, so not all of my empirically oriented colleagues are represented here - sorry!.

Confidence Intervals for Impulse Response Functions

An impulse response function gives the time-path for a variable explained in a VAR model, when one of the variables in the model is "shocked". We get a "picture" of how the variable in question responds to the shock over several periods of time.

An impulse response function (IRF) is essentially a type of conditional forecast. It's a messy function of the estimated coefficients in the VAR model, and the data. So, it's really just a point estimate, period by period. There's some uncertainty associated with the IRF, of course - this comes from the uncertainty associated with the estimated coefficients in the model. So, we really need to report a confidence band, period by period, to go with the IRF.

More on the Quality of Economic Data

Yesterday I posted two pieces relating to the quality of economic data, in general terms, and with reference to China.

I'm firmly of the view that we need to be paying more attention to data quality than we currently do as economists. We also need to keep in mind that data are frequently revised, and this has implications for policy conclusions based on preliminary figures.

To help you with your reading on this topic, here's a small selection of papers that touch on different aspects of this topic:

Now That the Semester is Over....

Another teaching term is done, and the exams are all graded!

HT to my colleague, Emma Hutchinson, for this timely item:

Bias Reduction Paper Published

Another of our papers on bias reduction for Maximum Likelihood estimators has now been published. This one is titled, "On the Bias of the Maximum Likelihood Estimator for the Two-Parameter Lomax Distribution", and is co-authored with Ryan Godwin and Helen Feng. It's in Vol. 42 (11) of Communications in Statistics - Theory and Methods, and is available here.

This paper stems from an ongoing research program with Helen, Ryan, and others. Other posts relating to this program can be found here and here. There's more of this on the way!

© 2013, David E. Giles

The Reliability of China's Economic Data

There have long been concerns about the reliability of published macroeconomic data for China. About 3 months ago, the U.S. - China Economic and Security Review Commission published a timely report, titled, "The Reliability of China's Economic Data - An Analysis of National Output". The report certainly makes interesting reading.

In a post earlier today I warned about the importance of data quality. When the data relate to an economy that's size and importance as that of China, then it's time to sit up and take notice!

Data Quality is Paramount

Yesterday, in a post on the Worthwhile Canadian Initiative, Frances Woolley rightly drew attention to some rather disturbing issues associated with the upcoming release of the 2011 National Household Survey (NHS), by Statistics Canada. In a nutshell, she asks the question, "How can we be sure that the NHS information about the religious beliefs of Canadians is accuarate?"

Recently, I made the comment: Data - the econometrician's lifeblood! Can't function without it." I wish I'd been more specific, and said "reliable data."

The T. D. Dwivedi Memorial Lecture

Yesterday, I was greatly honoured to present the 2nd. invited T. D. Dwivedi Memorial Lecture, in the Department of Mathematics & Statistics at Concordia University, in Montreal. The late Try Dwivedi was instrumental in the establishment of statistics at Concordia, and he also played a leading role in the development of the statistical profession in Canada generally

I'm linked to Dr. Dwivedi through the work that each of us did with V. K. (Viren) Srivastava. So, I have a "Dwivedi number" of 2.  You'll find more about this in an earlier post about Viren here.

The talk that I gave was titled, "Bas Adjustment for Nonlinear Maximum Likelihood Estimators", and you can download my slides from here if you're interested. The material for the lecture was based on a research program that I've been involved with in recent years, jointly with Helen Feng, Ryan Godwin, Jacob Schwartz, and others. A previous post on this blog discussed some of this research.

I'd like to thank the Dwivedi family, Yogen Chaubey (Department Chair), and the faculty of the Department of Mathematics and Statistics at Concordia University, for the kind invitation, their outstanding hospitality, and for a memorable visit to Montreal.

© 2013, David E. Giles

A First Encounter With Monte Carlo Simulation

In my second-year undergraduate course on Statistical Inference for economists, I use Monte Carlo simulation with EViews to illustrate the notion of the "sampling distribution" of a statistic, such as an estimator. This is hardly unusual. However, before we get started I have to persuade the students that this whole Monte Carlo thing might actually work!

So, we go through an exercise where we use simulation to approximate the value of π.

You Can Quote Me on That

The other day I came across the Empirical Quotes page on Mark Byran's blog. Some of his quotes related specifically to econometrics, and I thought I'd share a few others. That certainly doesn't mean that I agree with them all!