[open-economics] Project idea OpenEcon and call for coders

Fri Apr 22 13:25:49 UTC 2011

First off: I think both Guo's idea -- "Right or Wrong" -- (or perhaps
"Yes or No") and Dirk's -- Progress Vote -- are excellent.

They've also got me thinking. I'd like to propose that:

i) We take the World Bank prize money ($5k) and allocate it to fund the next app

ii) We choose the next app by a mini 'cfp' using
http://ideas.okfn.org/ over the next 2 weeks
  * Just post your idea and tag with 'open-economics' plus 'cfp-2011'

iii) People can vote and comment on ideas. Then following discussion
here we can decide what to work on.

Rufus

PS: I am also interested in Dirk's suggestion of submitting to
appsforscience though it does seem to be *very* tied to Elsevier's
platform (not only do you have to use their material you have to
upload to their  SciVerse system, use their eclipse plugin etc)

On 18 April 2011 12:21, Dirk Heine <dirk at common-future.org> wrote:
> This is a great idea!, and -despite not being a noncoder unfortunately-
> I would be interested in contributing what I can (like: feeding
> database).
>
> Your idea would also fit http://appsforscience.com/
>
> And the price we gained from the appsfordevelopment competition could
> finance a starter (even though I still very much hope that you guys will
> consider ProgressVote).
>
> Best wishes,
>
> Dirk
>
> On Mo, 2011-04-18 at 09:50 +0200, Guo Xu wrote:
>> I am reposting this because last e-mail was jumbled up for some weird reason...
>>
>> ###
>>
>> Dear list,
>>
>> Just wanted to share an idea I had for quite a while. So far, I
>> haven't been able to explore this further - just wanted to use this
>> list as an opportunity to get some feedback.
>>
>> In the course of my studies and research, I have come across many
>> empirical (macro) econ papers. Basically, all papers are about the
>> relationship between X and Y, for example GDP growth and education
>> etc.
>>
>> Even though presumably rigorous, most relationships prove very
>> fragile: After 20 years of growth regressions (Y=GDP growth), for
>> example, we still have not found any robust explanatory variable (X).
>> Another notorious example comes from the democracy-growth research: In
>> a review of 81 empirical studies (all using growth as Y and democracy
>> as X), 16% of the papers find a negative significant relationship, 20%
>> a negative insignificant, 38% a positive insignificant and 26% a
>> positive significant relationship.
>>
>> Why is this so? Basically, there are too many degrees of freedom: You
>> can choose among a large number of datasets, use a different time
>> period, restrict the number of countries, vary with the number of
>> control variables and play around with the econometric estimation
>> (OLS, robust, clustered, FE, RE etc.). This means that you can always
>> get the result you want, as long as you just try hard enough and
>> recombine the different choices - this is what people call "kitchen
>> sink regressions", a result of data mining and confirmation bias.
>>
>> Why is this a problem? Unfortunately, published articles will not tell
>> you how many different specifications they have tried until they
>> finally got their results (of course, this is a very unscientific
>> approach but it does happen a lot) - instead, the result will be
>> presented as if it was obtained at first trial. There is also a huge
>> pile of "novel contributions" that claim to have finally found the
>> "real" relationship, adding to the pile of contradicting empirical
>> work.
>>
>> My idea now is to create a public database where relationships can be
>> entered (let's call this project "X on Y" for now) and searched.
>> Basically, you would choose your Y and X and the website would throw
>> out all existing results, either entered by users or scraped from the
>> pile of existing studies (most of the output tables are almost
>> standardized so it should be doable). This would be incredibly useful
>> for researchers. For example, if I am considering to test the
>> relationship between Co2 reductions and democracy, I would not need to
>> go through a literature research but can simply check on the website.
>> The website would then throw out all existing findings (how many
>> positive significant, how many negative significant etc.), maybe
>> including the link to the paper or the datasets. This would save a lot
>> of redundant work and help to advance in research.
>>
>> The website would also capture those regressions that are NOT reported
>> in the final
>> research paper. This would also allow others to check whether the
>> result is based on confirmation bias (how many different variations
>> did s/he try before reporting the final result?). Eventually, the
>> website might even turn out to be a source of validation for
>> researchers. The website would be THE departing point for empirical
>> research. People need not go through piles of literature review but
>> can get the results in a standardized format.
>>
>> Such a website does not exist (to my knowledge) but can have a
>> profound impact on how research in economics is done: 1) We could also
>> write a plugin for econometric software like Stata that reports each
>> regression you run (the resulting relationship) to the website. 2) By
>> doing so, the app would even ADVANCE research as it would allow the
>> creation of meta-regressions. These are regressions that use existing
>> studies (for example all 81 democracy-growth studies) to estimate a
>> robust relationship by controlling for differences in the method of
>> estimation (sample, measures, etc). Meta-regressions have become
>> increasingly popular these days but generally require a lot of
>> literature review, which could be avoided if we had that database.
>>
>> As a researcher, I am quite certain that this tool will be very
>> useful. Unfortunately, I do not have the technical knowledge to
>> program such a website (I have an ASP 3.0 background but will not be
>> able to use all the new technologies). Just wanted to check if anyone
>> is interested in investing some time in this? I could also try to
>> mobilize some resources for this - this is a HUGE gap and filling this
>> could really change the way macroeconometrics is done.
>>
>> Guo
>>
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