Econometricians are also sensitive

One of my favorite podcasts is EconTalk.While last weeks edition featured Ed Leamer from UCLA. Most of the podcast was a discussion about Macroeconomics within thescope of Ed's latest book, the host (Russ Roberts) gave Ed an opportunity to discuss econometrics. Ed made a point that any econometric study should include a sensitivity analysis to see verify if the study is robust. If the study is too sensitive then the study should be considered but not seen as absolute.

This compliments an earlier post on sensitivity analysis for Linear Programming. The lesson I am learning is that while each technique of data modeling can guide organizations to the best answer, it is also important to understand under what conditions does the result remain valid. Without understanding the sensitivity of the model and its results, the effort to make a better decision with scientific skills, could be wasted given the skills may not be applied within the proper conditions. Model building for decisions is not complete until a sensitivity analysis and applying it's results has been performed.

Listen to the EconTalk podcast

OpenOpt and I started following someone's Blog

So I carved out a little more time to work with OpenOpt. I ran a built-in example named lp_1.py, since it was a Linear Programming example. By default the example script calls on a solver that is not included with the install of OpenOpt . Below is the line of code. The funny part is read the comment next to it and ponder why would this line be the default?

r = p.solve('cvxopt_lp') # CVXOPT must be installed

Any way you can see my current progress here.

On my journey to find why the example problem did not work by default, I found another blog that has similar interests to mine. Except this blogger seems to have experience in Operations/Decision Science vs. where I am just at the beginning of this journey. So I added myself as a follower to his blog: http://industrialengineertools.blogspot.com/

A good example of where we seem to be of similar interest is this article: http://industrialengineertools.blogspot.com/2009/02/does-software-hinder-innovation-in.html
I look forward to catching up with some of his other posts and future content.