Academic career
He specializes in leadership and charismatic leadership in particular. [1] [2] He has communicated his work on leadership to a wide audiences, [3] [4] including work in applied statistics on endogeneity and causality, [5] and general problems in science. [6] His article "Predicting Elections: Child's Play" [7] published in the prestigious journal Science engendered a lot of interest because it showed that little children were able to predict results of election outcomes merely by rating the faces of the politician candidates. A summary of his work on charisma is available in a recent talk he gave at TEDx [8] and a keynote address at the British Psychological Society meeting [9]
U.S. Election prediction model
He has developed a model with Philippe Jacquart to predict the U.S. presidential elections; [10] their model predicted that Obama would win (refer to Antonakis's YouTube video on the Obama-Romney election race [11] ). He predicted a victory for Trump in the 2016 and 2020 elections. [12] [13] [14] A newly calibrated model predicting the electoral college vote share predicts a Trump victory for 2024 [15] with the Republican getting 295 electoral college vote. On the basis of this new model, [16] [17] and using the data available in 2020, this model would have predicted a Biden victory for 2020.
Various scientific positions
Antonakis has written broadly on topics germane to organizational behavior, including on leadership, social cognition, individual differences and methodology (psychometrics and applied econometrics). A common thread in his research is correct measurement, as well as correct causal specification, design, and analysis. For instance, he has been critical of the concept of emotional intelligence particularly self-measures; his research suggests that emotional intelligence measures are not developed enough to be used for clinical purposes or in work-related or educational settings, [18] and that emotional intelligence is not needed for leadership. As proponent of consistent estimators and causally identified models using econometrics and structural equation modeling techniques, he has also written critiques of Partial least squares path modeling, which he states should be abandoned. [19]
He has also shown that, because of endogeneity issues, much of the research done in management and applied psychology is devoid of causal interpretation. [20] [21] [22] [23]
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