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acknowledgements.html

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@@ -295,7 +295,7 @@ <h3 class="anchored" data-anchor-id="instrumental-variables">Instrumental variab
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<td><a href="https://yiqingxu.org/packages/ivDiag/"><strong>ivDiag</strong></a></td>
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<td>R</td>
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<td>The IV diagnostics implementations are validated against ivDiag.</td>
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<td>The IV diagnostics implementations are validated against ivDiag by Lal et al.</td>
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@@ -314,7 +314,7 @@ <h3 class="anchored" data-anchor-id="quantile-regression">Quantile regression</h
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<td><a href="https://cran.r-project.org/package=quantreg"><strong>quantreg</strong></a></td>
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<td>R</td>
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<td>PyFixest’s <code>quantreg()</code> implementation is tested against R’s quantreg package (by Roger Koenker) for coefficient and NID standard error equivalence</td>
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<td>PyFixest’s <code>quantreg()</code> implementation is tested against R’s quantreg package (by Roger Koenker) for coefficient and NID standard error equivalence.</td>
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<td><a href="https://ideas.repec.org/c/boc/bocode/s457369.html"><strong>qreg2</strong></a></td>
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<td><a href="https://github.com/alexCardazzi/lpdid"><strong>lpdid</strong></a></td>
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<td>R</td>
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<td>PyFixest’s local-projections DID estimator is highly influenced by Alex Cardazzi’s R code (published under MIT) for the lpdid package. We also test against the R implementation</td>
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<td>PyFixest’s local-projections DID estimator is highly influenced by Alex Cardazzi’s R code (published under MIT) for the lpdid package. We also test against Alex’ package.</td>
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<td><a href="https://github.com/danielegirardi/lpdid"><strong>lpdid</strong></a></td>
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<td>Stata</td>
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<td>We also test our implementation against Daniel Busch’s and Daniele Girardi’s Stata implementation of local-projections DID.</td>
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<td>We also test our implementation against Daniel Busch and Daniele Girardi’s Stata implementation of the local-projections estimator.</td>
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@@ -386,7 +386,7 @@ <h3 class="anchored" data-anchor-id="randomization-inference">Randomization infe
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<td><a href="https://github.com/grantmcdermott/ritest"><strong>ritest</strong></a></td>
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<td>R</td>
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<td>PyFixest’s <code>ritest()</code> method’s API heavily borrows from Grant McDermott’s R port and is tested against it.</td>
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<td>PyFixest’s <code>ritest()</code> method’s API heavily borrows from Grant McDermott’s R package and is tested against it.</td>
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<td><a href="https://github.com/simonheb/ritest"><strong>ritest</strong></a></td>
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<td><a href="https://github.com/s3alfisc/wildwyoung"><strong>wildwyoung</strong></a></td>
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<td>R</td>
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<td>An R implementation of the Westfall-Young correction using the wild bootstrap</td>
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<td>An R implementation of the Westfall-Young correction using the wild bootstrap.</td>
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<td><a href="https://github.com/damiancclarke/rwolf"><strong>rwolf</strong></a></td>
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<td><a href="https://github.com/Daniel-Pailanir/TSCB-CCV"><strong>TSCB-CCV</strong></a></td>
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<td>Stata</td>
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<td>Pailanir &amp; Clarke. PyFixest’s CCV implementation (Abadie et al., QJE 2023) is tested against Daniel Pailanir and Damian Clarke’s Stata implementation. Test data is loaded from Stata <code>.dta</code> files</td>
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<td>Pailanir &amp; Clarke. PyFixest’s CCV implementation (Abadie et al., QJE 2023) is tested against Daniel Pailanir and Damian Clarke’s Stata implementation.</td>
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<td><a href="https://gist.github.com/apoorvalal/e7dc9f3e52dcd9d51854b28b3e8a7ba4">Apoorva’s Linear Mediation Gist</a></td>
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<td>Python</td>
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<td>The initial implementation of Gelbach’s decomposition was based on Apoorva’s gist</td>
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<td>The initial implementation of Gelbach’s decomposition in <code>PyFixest</code> was based on Apoorva’s gist</td>
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<td><a href="https://github.com/jeffgortmaker/pyhdfe"><strong>pyhdfe</strong></a></td>
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<td>Python</td>
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<td>PyFixest’s demeaning results are tested against pyhdfe to ensure equivalence. <code>pyfixest</code>’s first MVP was built using <code>pyhdfe</code> it ran its demeaning algorithm via <code>pyhdfe</code> MAP algo.</td>
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<td>PyFixest’s demeaning results are tested against Jeff Gortmaker’s <code>pyhdfe</code>. <code>pyfixest</code>’s first MVP was built using <code>pyhdfe</code> it ran its demeaning algorithm via <code>pyhdfe</code> MAP algo.</td>
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<td><a href="https://rpy2.github.io/"><strong>rpy2</strong></a></td>
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<td>Python</td>
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<td>The bridge between Python and R that powers all cross-language test comparisons</td>
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<td>The bridge between Python and R that powers all cross-language test comparisons.</td>
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