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.

My research interests are in empirical corporate economics and econometrics. My ongoing research covers topics on the mergers and acquisitions, firms’ technology adoption, policy evaluation with machine learning techniques and traditional econometrics.

Some selected works:

• Discovering Heterogeneous Treatment Effects in Regression Discontinuity Designs
• The Long-Run Stock Market Performance of Mergers and Acquisitions - joint with Sudheer Chava
• Modelling with Sensitive Variables - joint with Felix Chan and Laszlo Matyas
• When and How Much Do Fixed Effects Matter? - joint with Felix Chan and Laszlo Matyas. This is a book chapter from The Econometrics of Multi-dimensional Panels (2024) (Editor: Matyas, Publisher: Springer)

See more on my research here.

Codes(./codes.html)

• Beta version of multisynthdid R-package, which runs Synthetic Diff-in-Diffs with multiple outcomes. See more here multisynthdid.
• RD-tree implements the machine learning algorithm from Discovering Heterogeneous Treatment Effects in Regression Discontinuity Designs. This is a MatLab implementation. There is a python implementation by Firat Yaman, however this only implements the parametric version.
• Split-sampling method which allows data-protection for sensitive variables discussed in Modelling with Sensitive Variables

Teaching

• Econometrics I for Applied Economists (BA) at Corvinus.

• Previously I have taught various Data Analysis courses 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.

Contact

email: agoston.reguly-at-uni-corvinus.hu or areguly6-at-gatech.edu