Solved – Documented/reproducible examples of successful real-world applications of econometric methods

Question

This question might sound very broad, but here is what I am looking for. I know there are many excellent books about econometric methods, and many excellent expository articles about econometric techniques. There are even excellent reproducible examples of econometrics, as described in this CrossValidated question. In fact the examples in this question come very close to what I am looking for; the only thing missing in those examples is that they are only research reports, without any mention of how the results of the study fared in a real-world application.

What I am looking for are documented/reproducible examples of real-world applications of econometric theory that ideally have the following characteristics:

1. They should be reproducible, i.e. contain detailed description of (and pointers to) data, econometric techniques, and code. Ideally the code would be in the R language.
2. There should be detailed documentation showing that the technique succeeded in the real world, according to a well-quantified measure of success (e.g. "the technique helped increase revenues because it enabled improved forecasting of demand, and here are the numbers involved")

I am using the term econometric quite broadly here — I mean any sort of data-mining, statistical data-analysis, predictiion, forecasting or machine-learning technique.
One immediate problem in finding such examples: many successful applications of econometrics are done in a for-profit setting and are therefore proprietary, so if a technique worked well, it probably will not be published (this is especially true in the case of proprietary trading strategies), but I am nevertheless hoping there are published examples that have at least property (2) above if not both (1) and (2).

Answer 1

As mentioned in the comments, travel demand forecasts often use inputs from discrete choice models (multinomial logit, nested logit, mixed logit, etc) to assist in the development of behavioral mode choice or route assignment in their travel demand forecasts. DCM certainly has many applications outside travel demand forecasting, but it has been used in the transportation industry for 30+ years so there should be lots of good examples.

As for reproducible examples:

• Biogeme is an open source piece of software that is optimized for estimating logit models. The website provides the data, code, and a paper write up describing their methods.
• travelR is a project to make travel demand forecasts with R. There was a presentation at useR! 2010 about the project, abstract here and slides here. There is also a webinar coming up in a few weeks regarding R and travel demand forecasting that I'll find the link to and update here for those interested.
• Transportation Review Board Conference has made a list of all papers available online this year. I don't have a specific paper to link to, but there are several committee's worth of papers regarding the application of choice models in the transportation context.