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reproducible_science.html
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reproducible_science.html
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<!DOCTYPE html>
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<title>Adrien Pacifico </title>
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<h1>Adrien Pacifico</h1>
<p><b><font style="font-size:30px" color='red'>Warning: Alpha version <br> in construction</font></b></p>
<p>Economics of taxation, Fiscal Microsimulation </p>
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<h2>Reproducible Science (in economics)</h2>
In this section I plan to write about reproducibility in economics, especially for articles that are based on administrative databases with restricted access.
For the time being, here is some links that nourrish my reflexions on the subject:
<ul compact>
<li>
Economics research is not replicable 2/3 of the time:
<a href="https://www.federalreserve.gov/econresdata/feds/2015/files/2015083pap.pdf"> Chang & Li, 2015
</a>
</li>
<li>
A great book on how to do reproducible research with exemples:
<a href="https://www.practicereproducibleresearch.org/">
The Practice of Reproducible Research
</a>
</li>
<li>
The usage of Binder to communicate code and make easily reproducible examples:
<a href="https://conference.scipy.org/proceedings/scipy2018/project_jupyter.html">
Binder 2.0 - Reproducible, interactive, sharable environments for science at scale (2018)
</a>
</li>
<li>
How Notebooks are used at Netflix:
<a href="https://medium.com/netflix-techblog/notebook-innovation-591ee3221233">
Beyond Interactive, Notebook Innovation at Netflix
</a>
</li>
<li>
The Berkeley Initiative for Transparency in the Social Sciences:
<a href="https://www.bitss.org/">
https://www.bitss.org/
</a>
</li>
<li>
Open Science Framework:
<a href="https://osf.io/">
https://osf.io/
</a>
</li>
<li>
Statistics Done Wrong:
<a href="https://www.statisticsdonewrong.com/">
https://www.statisticsdonewrong.com/
</a> , and especially the <a href="https://www.statisticsdonewrong.com/mistakes.html#reproducibility"> Everybody makes mistakes/ reproducibility section</a>
</li>
<li>
<a href="https://wol.iza.org/articles/big-data-in-economics/long">Big Data in economics</a> An IZA working paper to translate computer scientist doing "machine learning" to economist doing "regressions" and vice versa.
</li>
<li>
<a href="https://www.euroscipy.org/2018/descriptions/Reproducibility%20and%20exploratory%20computing%20with%20a%20Jupyter-based%20workflow.html">
Reproducibility and exploratory computing with a Jupyter-based workflow
</a>
</li>
<li>
<a href="http://www.nber.org/papers/w22989">Transparency, Reproducibility, and the Credibility of Economics Research</a>, <a href="https://youtu.be/aprFsDq5KGY?t=4095">video of the presentation.</a>
</li>
<li>
This post advocates for a progressive consolidation effort of scientific code, rather than putting too high a bar on code release:
http://gael-varoquaux.info/programming/software-for-reproducible-science-lets-not-have-a-misunderstanding.html
</li>
<li>
https://osf.io/kgnva/wiki/Open%20Science%20Literature/
</li>
</ul>
https://conference.scipy.org/proceedings/scipy2018/project_jupyter.html <br>
https://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261
https://web.stanford.edu/~gentzkow/research/CodeAndData.pdf
Economist in tech: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3247794
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