Mark Himmelstein

Assistant Professor

Education

Ph.D. (2023) in Psychometrics and Quantitative Psychology, Fordham University

Research Interests

Decision making, quantitative methods, judgmental forecasting, advice taking, belief updating, Bayesian statistics, elicitation methods, psychological measurement, missing data

About

My work is at the intersection of human judgment and decision-making, probabilistic reasoning, belief revision, and statistical inference. The study of how people make decisions under uncertainty is the study of how people make judgments with incomplete information. Put another way, it’s how we function as intuitive statisticians in our day to day lives. As such, I believe the study of judgment and decision-making is inseparable from the study of statistical inference, and they are in fact two sides of the same coin. Becoming better parsers and communicators of statistical information is crucial for becoming better decision-makers.
 
More concretely, I have two primary active research tracks. The first involves understanding what makes a person a good forecaster. I am currently partnered with the Forecasting Research Institute on several projects—most notably to develop a test of forecasting proficiency. The second involves understanding how people take advice or revise their judgments and beliefs when presented with new information. There are many subtle but important nuances to the psychological process of belief revision that depend not only on the content domain, but the format of the belief report or elicitation and situational context as well.

Awards

Decision Analysis Society Publication Award Finalist (2023; for Himmelstein et al., 2021)   European Association for Decision Making de Finetti Prize for best publication from an early career scholar (2021; for Himmelstein et al., 2021)

Selected Publications

Himmelstein, M., Budescu, D.V., & Ho, E. H. (2023). The wisdom of many in few: Finding
individuals who are as wise as the crowd. Journal of Experimental Psychology: General,
152(5), 1223–1244.
https://doi.org/10.1037/xge0001340
 
Himmelstein, M. & Budescu, D.V. (2023). Preference for human or algorithmic forecasting advice does not predict if and how it is used. Journal of Behavioral Decision Making. 36(1), e2285.
https://doi.org/10.1002/bdm.2285
 
Benjamin, D. M., Morstatter F, Abbas, A. E., Abeliuk A., Atanasov, P., Bennett, S., Beger, A., Birari, S., Budescu, D.V., Catasta, M., Ferrar, E., Haravitch, L., Himmelstein, M., … Galstyan, A. (2023). Hybrid forecasting of geopolitical events. AI Magazine, 44. 112-128.
https://doi.org/10.1002/aaai.12085
 
Himmelstein, M., Budescu, D. V., & Han, Y. (2023). The wisdom of timely crowds. In M. Seifert (Ed.), Judgment in Predictive Analytics (pp. 215–242). Springer International Publishing.
https://doi.org/10.1007/978-3-031-30085-1_8
 
Atanasov, P., & Himmelstein, M. (2023). Talent spotting in crowd prediction. In M. Seifert (Ed.), Judgment in Predictive Analytics (pp. 135–184). Springer International Publishing.
https://doi.org/10.1007/978-3-031-30085-1_6
 
Himmelstein, M. (2022) Decline, adopt or compromise? A dual hurdle model for advice utilization. Journal of Mathematical Psychology. 110, 102695.
https://doi.org/10.1016/j.jmp.2022.102695
 
Himmelstein, M., Atanasov, P., & Budescu, D. V. (2021). Forecasting forecaster accuracy: Contributions of past performance and individual differences. Judgment and Decision Making. 16(2), 323-362.
https://doi.org/10.1017/S1930297500008597
 
Fan, Y., Budescu, D.V., Mandel, D.R. & Himmelstein, M. (2019). Improving accuracy by coherence weighting of direct and ratio probability judgments. Decision Analysis. 16(3), 197-217.
https://doi.org/10.1287/deca.2018.0388