[IISE Faculty List] DA

[Vicki Bier]

Colleagues,

   As Editor-in-Chief of Decision Analysis, I am delighted to announce 
that one of the finalists for the Clemen-Kleinmuntz Decision Analysis 
Best Paper Award from the journal for 2022 is Dr. Eric Bickel of the 
Department of Operations Research and Industrial Engineering at UT 
Austin, for the following paper:

Colin Small, J. Eric Bickel
*Model Complexity and Accuracy: A COVID-19 Case Study 
<https://pubsonline.informs.org/stoken/default+domain/PR-2-2023/full/10.1287/deca.2022.0457>*
https://pubsonline.informs.org/stoken/default+domain/PR-2-2023/full/10.1287/deca.2022.0457

When creating mathematical models for forecasting and decision making, 
there is a tendency to include more complexity than necessary, in the 
belief that higher-fidelity models are more accurate than simpler ones. 
In this paper, we analyze the performance of models that submitted 
COVID-19 forecasts to the U.S. Centers for Disease Control and 
Prevention and evaluate them against a simple two-equation model that is 
specified using simple linear regression. We find that our simple model 
was comparable in accuracy to highly publicized models and had among the 
best-calibrated forecasts.This result may be surprising given the 
complexity of many COVID-19 models and their support by large 
forecasting teams. However, our result is consistent with the body of 
research that suggests that simple models perform very well in a variety 
of settings.
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