Requests I Ignore

About six months ago I wrote a post titled, "Readers' Forum Page".

Part of my explanation for the creation of the page was as follows:

"Readers' Forum" Page

I've added a new page to this blog - it's titled "Readers' Forum". You'll see the tab for it in the bar just above the top post on the page you're reading now.

Some explanation is in order.

What?

The Readers' Forum is intended to be a "clearing house" for questions and requests relating to econometrics'

As I say in the preamble to the new page,

"Please feel free to use the "Comment" facility below to provide questions and answers relating to Econometrics. I won't be able to answer all questions myself, but other readers may be able to help. The Forum will be "lightly moderated" to avoid spam and inappropriate content."

Please note the italicized passage above.

Why?

Every day, readers post (or attempt to post) lots of "comments" on the various posts on this blog. In many cases, these are not comments at all - they're questions, requests for assistance, and the like.

All comments are moderated - I get to give them the "O.K." before they actually appear. That's just fine for genuine comments. Unless they're spam or contain inappropriate content, I invariably "approve" them right away.

However, in the case of questions and requests I prefer to delay approval and post a response simultaneously. Regrettably, this has meant that, increasingly, there is often a delay in getting this out there. 

Sometimes, the requests are, quite frankly, unreasonable.I won't go into the details here, but let's just say that there's a difference between a blog and a free consulting service.

I also try to be very careful when it's clear that the request comes form a student. I certainly don't want to get into a situation where I'm "getting between" that student and their instructor/supervisor.

In short, I like to try and be helpful, but I can't keep up with the demand. I do have a job!

Hopefully, the new forum will free up some time for me to focus on substantive posts, while still providing an opportunity for discussion.

© 2015, David E. Giles

And the Rest.......

Happy to make the cut! Thanks Noah, and BloombergView.


© 2015, David E. Giles

Marc Bellemare on Social Media

Marc Bellemare has been catching my attention recently. On Saturday I had a post that mentioned his talk on "How to Publish Academic Papers". I know that a lot of you have followed this up already.

Today, I just have to mention another of his talks, given last Friday, titled "Social Media for (Academic) Economists". Check out his blog post about the talk, and then look at this slides that are linked there.

Yep, I agree with pretty much everything he has to say. And nope, we're not related!

© 2014, David E. Giles

The Econometrics Bard Strikes Again!

Guy Judge (now retired from the University of Portsmouth in the U.K.) has been back at it again in the past couple of days.

In recent years Guy has shared several original econometrics poems/songs with us through his Guy's Econometrics Blog.

The latest two contributions go under the titles of "Granger" and "Backing Bayes".

Enjoy them!

© 2014, David E. Giles

Some Questions About ARDL Models

The majority of the blog-related comments and requests for help that I receive come from the one person - called "Anonymous". 

(S)he seems to have very broad interests.

Here's a very recent request for help relating to ARDL models - something that I've posted about here and here.

"I am working on income inequality. Can I use ARDL as I have only 27 annual observations? Also does ARDL itself takes care of problem of endogeneity? And what about if there is multicollinearity among explanatory variables - can we still use ARDL? Is any EViews code available to run ARDL?"

Taking the questions in order........

It's Not A Blog .......

This gem from @AcademicSay on Twitter today:

"It's not a blog. It's an independent open-access journal with a dedicated submission agreement."

© 2014, David E. Giles

No Pressure Here

This post might make me sound a little grumpy. I hope not. Anyway, here goes.

Comments that are posted on this blog come to me by email for "approval" prior to posting. This is standard practice, and believe me, you wouldn't want t see some of the spam that people try to post as "comments".

Among the comments waited to be vetted this morning were two at opposite ends of the non-spam spectrum.

One was a grateful and thoughtful comment from "Tom" on my post, ARDL Models - Part I . Here's the exchange in full:

Money 101: Top Resources for Finance Majors

Abigail Moore, the Content Creator at OnlineFinanceDegree.org, emailed me today:

"I'm writing with the exciting news that our latest article, "Money 101: Top Resources for Finance Majors," has been published, and Econometrics Beat: Dave Giles' Blog is cited on it.

Finance is an engaging and highly competitive professional field to get into. For those studying finance, the internet can offer a wealth of resources. That said, it can be hard to sift through and find the best. We hope this feature will help finance students find information about financial organizations, current economic news, financial modeling software and techniques, and the finance industry as a whole. Your site is a valuable addition to this resource.

We're hoping to share this article with as many finance students and professionals as possible and will be contacting our readers and followers. If you're able to post this on your website or share the article anywhere else you can think of too, I'd really appreciate it." 

No problem, Abigail - happy to oblige. You'll find this blog listed as site #8.

© 2013, David E. Giles

Blogs on Resources for Economists

Nice to see that we're now listed on the list of Economics blogs on Resources for Economists.

Thanks!

© 2013, David E. Giles

Blogging About Your Research

Hat-tip to Arthur Charpentier for this link: "28 Reasons Why You Should Blog About Your Research".

© 2013, David E. Giles

P-Values, Statistical Significance, and Logistic Regression

Yesterday, William M. Briggs ("Statistician to the Stars") posted on his blog a piece titled "How to Mislead With P-values: Logistic Regression Example".

Here are some extracts which, hopefully, will encourage to read the post:

"It’s too easy to generate “significant” answers which are anything but significant. Here’s yet more—how much do you need!—proof. The pictures below show how easy it is to falsely generate “significance” by the simple trick of adding “independent” or “control variables” to logistic regression models, something which everybody does...............

Logistic regression is a common method to identify whether exposure is “statistically significant”. .... (The) Idea is simple enough: data showing whether people have the malady or not and whether they were exposed or not is fed into the model. If the parameter associated with exposure has a wee p-value, then exposure is believed to be trouble.

So, given our assumption that the probability of having the malady is identical in both groups, a logistic regression fed data consonant with our assumption shouldn’t show wee p-values. And the model won’t, most of the time. But it can be fooled into doing so, and easily. Here’s how.

Not just exposed/not-exposed data is input to these models, but “controls” are, too; sometimes called “independent” or “control variables.” These are things which might affect the chance of developing the malady. Age, sex, weight or BMI, smoking status, prior medical history, education, and on and on. Indeed models which don’t use controls aren’t considered terribly scientific.

Let’s control for things in our model, using the same data consonant with probabilities (of having the malady) the same in both groups. The model should show the same non-statistically significant p-value for the exposure parameter, right? Well, it won’t. The p-value for exposure will on average become wee-er (yes, wee-er). Add in a second control and the exposure p-value becomes wee-er still. Keep going and eventually you have a “statistically significant” model which “proves” exposure’s evil effects. Nice, right?"

Oh yes - don't forget to read the responses/comments for this post, here.

© 2013, David E. Giles

Top Economics Blogs

Nice to be on the list - thanks, INOMICS!

© 2013, David E. Giles

R is His Friend

Marcus Beck has a nice (& relatively new) blog called R is My Friend. You can guess that his posts relate to the use of R.

I particularly liked his piece on the use of the XML package in R to mine data from the internet; and his post on using the integrate function in R, even when the anti derivative has no closed-form solution.

Grad. student readers will also like his post, How Long is the Average Dissertation.

My own take on a related question can be found here.

© 2013, David E. Giles

Top 100 Economics Blogs

I was happy to learn this morning that the Economics Degree website has just released a list of Top Economics Sites for Enlightened Economists. There are 100 blogs in total, and the preamble notes:

"Listed in no specific order, these sites are a must-see for anyone who wants to be considered a quality, “enlightened” economist. Sites were selected based on a variety of factors including readership size, update frequency, information quality, and other awards received. "

I was even more pleased to see that this blog made the list (see number 71 & remember they're in particular order!), with the following, very kind, description:

"This is a high-quality blog with a strong econometrics focus. The posts are jam-packed with information and ideas, and are clearly intended for readers with a background in statistics or econometrics."

(Blush. Blush.)

There are some great sites for students and professionals alike on this Top 100 list.

Nice job!

© 2012, David E. Giles