Research output per year
Research output per year
Personal profile
Research interests
Research interests:
Economics of transition in Central and Eastern Europe, the former Soviet Union, and China
Applied econometrics
Biography
AB, Magna Cum Laude in Social Studies, Harvard University, 1982
MScEcon in Economics, London School of Economics, 1984
MA in Economics, Stanford University, 1984
PhD in Economics, London School of Economics, 1990
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Fingerprint
Dive into the research topics where Mark Edwin Schaffer is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
-
ddml: Double/debiased machine learning in Stata
Ahrens, A., Hansen, C., Schaffer, M. E. & Wiemann, T., Mar 2024, In: The Stata Journal. 24, 1, p. 3-45 43 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile4 Citations (Scopus)59 Downloads (Pure) -
Model Averaging and Double Machine Learning
Ahrens, A., Hansen, C., Schaffer, M. E. & Wiemann, T., 27 Sept 2024, (Accepted/In press) In: Journal of Applied Econometrics.Research output: Contribution to journal › Article › peer-review
-
Model Averaging and Double Machine Learning
Ahrens, A., Hansen, C. B., Schaffer, M. E. & Wiemann, T., 10 Jan 2024, Bonn, Germany: IZA Institute of Labor Economics, (Discussion Paper Series; no. 16714).Research output: Working paper
-
Stacking Regression for Time-Series, with an Application to Forecasting Quarterly US GDP Growth
Ersoy, E., Li, H., Schaffer, M. E. & Szendrei, T., 2024, Studies in Systems, Decision and Control. Springer, p. 131-149 19 p. (Studies in Systems, Decision and Control; vol. 483).Research output: Chapter in Book/Report/Conference proceeding › Chapter
-
Using Machine Learning Methods to Estimate the Gender Wage Gap
Forshaw, R. J., Iakovlev, V., Schaffer, M. E. & Tealdi, C., 2 Jun 2024, Machine Learning for Econometrics and Related Topics. Springer, p. 109–129 21 p. (Studies in Systems, Decision and Control; vol. 508).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
-
Energy-Saving Interventions: Framing Information Based on Personal Values
Sophie Watson (Speaker), Mioara Cristea (Contributor), Claudia Aravena (Contributor) & Mark Edwin Schaffer (Contributor)
3 Jul 2023 → 6 Jul 2023Activity: Talk or presentation › Oral presentation
-
What’s wrong with how we teach estimation and inference in econometrics? And what should we do about it?
Mark Edwin Schaffer (Speaker)
10 Jan 2022Activity: Talk or presentation › Invited talk
-
Double-debiased machine learning in econometrics
Mark Edwin Schaffer (Speaker)
17 Mar 2022Activity: Talk or presentation › Invited talk
-
An introduction to stacking regression for economics
Mark Edwin Schaffer (Speaker)
5 Jan 2022Activity: Talk or presentation › Invited talk
-
4th International Econometric Conference of Vietnam 2021
Mark Edwin Schaffer (Speaker)
Jan 2021Activity: Talk or presentation › Invited talk
Press/Media
-
Economics Nobel 2019: why Banerjee, Duflo and Kremer won
Bhattacharjee, A. & Schaffer, M. E.
14/10/19
1 Media contribution
Press/Media: Research