Mark E. Schaffer is affiliated with Heriot-Watt University in the United Kingdom. Their research spans multiple fields, primarily focusing on Mathematics and Economics, Econometrics, and Finance. Their work is distributed across several specialized subfields, including Statistics and Probability, General Economics, Econometrics and Finance, Management Science and Operations Research, Economics and Econometrics, and Artificial Intelligence.
Schaffer's research topics encompass a range of statistical and economic methods, with particular attention to Statistical Methods and Inference, Monetary Policy and Economic Impact, Advanced Causal Inference Techniques, Probability and Statistical Research, Advanced Statistical Methods and Models, Forecasting Techniques and Applications, and Statistical and Numerical Algorithms.
The scientist has published multiple recent papers, reflecting active contributions to methodological developments and applications. Some notable publications include:
Schaffer frequently collaborates with other researchers, including Achim Ahrens, Christian Hansen, Thomas Wiemann, Erkal Ersoy, and Tibor Szendrei. The collaborations indicate a strong network focused on econometrics, machine learning, and related statistical methodologies.
Publication venues where Schaffer's work appears regularly highlight the dissemination channels favored, such as arXiv (Cornell University), The Stata Journal Promoting Communications on Statistics and Stata, SSRN Electronic Journal, Journal of Applied Econometrics, and the Repository for Publications and Research Data (ETH Zurich).
Mark E. Schaffer was awarded the title Fellow of the Royal Society of Edinburgh in 2009.
Christopher F. Baum;Mark Edwin Schaffer;Steven Stillman
Christopher F. Baum;Mark E. Schaffer;Steven Stillman
Erkal Ersoy;Mark Edwin Schaffer;Jan Ditzen
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