Some Official Data Come With Standard Errors!

Without intending to, I seem to have been on a bit of a rant about data quality and reliability recently! For example, see here, here, and here.

This post is about a related topic that's bugged me for a long time. It's to do with the measures of uncertainty that some statistical agencies (e.g., Statistics Canada) correctly report with some of their survey-based statistics.

A good example of what I have in mind is the Labour Force Survey (LFS) from Statistics Canada.

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.