David Van Dijcke (@packlesshepherd) 's Twitter Profile
David Van Dijcke

@packlesshepherd

PhD @umichECON. Academic Visitor @bankofengland. Alum @lmhoxford, @LeuvenEconomics. 🇧🇪🇺🇲. Views mine.
Apple says my research draws 'inaccurate conclusions'.

ID: 717403817155960832

linkhttp://davidvandijcke.com calendar_today05-04-2016 17:29:33

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John B. Holbein (@johnholbein1) 's Twitter Profile Photo

#RDDers check it out. Regression Discontinuity Design with Distribution-Valued Outcomes "This article introduces Regression Discontinuity Design (RDD) with Distribution-Valued Outcomes (R3D), extending the standard RDD framework to settings where the outcome is a distribution

#RDDers check it out. 

Regression Discontinuity Design with Distribution-Valued Outcomes

"This article introduces Regression Discontinuity Design (RDD) with Distribution-Valued Outcomes (R3D), extending the standard RDD framework to settings where the outcome is a distribution
Nick Bloom (@i_am_nickbloom) 's Twitter Profile Photo

*Call for papers for the 2025 Remote Work Conference* Stanford, October 22 to 24 2025. In person presentations, and streamed if folks want to watch remotely. Research papers on cause/effect of remote, WFH or hybrid please submit here: remoteworkconference.org/call-for-papers

*Call for papers for the 2025 Remote Work Conference*

Stanford, October 22 to 24 2025. In person presentations, and streamed if folks want to watch remotely.

Research papers on cause/effect of remote, WFH or hybrid please submit here: remoteworkconference.org/call-for-papers
Norm Matloff 一啲都唔明 (@matloff) 's Twitter Profile Photo

#rstats Most applications in R run pretty quickly. But these days, many R users are faced with huge datasets and/or long-running applications, making parallel computation attractive. If you've done this, you likely have used the 'parallel' package, either directly or via

Eva Janssens (@evajanster) 's Twitter Profile Photo

New! Efficient Estimation of Nonlinear DSGE Models, w/ Sean McCrary 📄 papers.ssrn.com/sol3/papers.... We propose a broadly applicable computationally efficient method for full-information estimation of nonlinear DSGE models.