Ágoston Reguly
Quick bio
I am an Assistant Professor at the Institute of Economics, Corvinus University of Budapest (Corvinus), an affiliated researcher at Financial Services Innovation Lab (FSIL) part of Scheller College of Business at Georgia Institute of Technology and a visiting faculty at Central European University (CEU).
My research interests are in empirical finance and econometrics. My ongoing research covers topics on
- the long-run market performance of mergers and acquisitions,
- policy evaluation with machine learning techniques, and
- traditional econometrics.
See more on my research here.
News
- [2024-05-07] Beta version of
multisynthdid
package, which runs Synthetic Diff-in-Diffs with multiple outcomes. See more heremultisynthdid
. - [2024-03-22] New working paper version of Modelling with Discretized Varaibles is available on arxiv!
- [2024-03-15] Our working paper on The Long-Run Stock Market Performance of Mergers and Acquisitions is now available on SSRN!
- [2024-02-02] Electronic version of When and How Much Do Fixed Effects Matter? is now available. This is a book chapter from The Econometrics of Multi-dimensional Panels (2024) (Editor: Matyas, Publisher: Springer)
Teaching
Econometrics I for Applied Economists (BA) at Corvinus.
Prediction with Machine Learning methods – Data Analysis 3 for Business Analitics (MSc) at CEU.
Learn coding & data analysis with R
- This course material guides you from basic statistics towards machine learning methods.
- See my course material and problem description with tasks+solutions at the following github repo: Coding for Data Analysis in R.
- This supplements the book Data Analysis for Business, Economics, and Policy by Gábor Békés (CEU) and Gábor Kézdi (U. Michigan) Published on 6 May 2021 by Cambridge University Press, and developed for Data Analytics courses at CEU. Check out gabors-data-analysis.com for more detial.
- Thanks to Péter Duronelly and Ádám Víg you can access the same material in python as well here.
More information on the courses is available here.
Codes
- Multiple outcomes with synthetic difference-in-difference estimation. See more here
multisynthdid
.- Implements method used by Chava and Reguly (2024)
Contact
email: agoston.reguly-at-uni-corvinus.hu or areguly6-at-gatech.edu