@article{PreussHennecke2018, author = {Preuss, Malte and Hennecke, Juliane}, title = {Biased by success and failure}, series = {Labour economics : an international journal}, volume = {53}, journal = {Labour economics : an international journal}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0927-5371}, doi = {10.1016/j.labeco.2018.05.007}, pages = {63 -- 74}, year = {2018}, abstract = {We test the stability of locus of control, a measure that has been attributed substantial explanatory power for economic outcomes since it depicts how much people believe in their ability to affect life outcomes. Using the German Socio-Economic Panel, we find that a job loss due to a plant closure has no long-lasting effect on locus of control. The common assumption of its stability is thus not rejected. However, during unemployment, control perception decreases by 30 percent of one standard deviation. The effect holds true independent from unemployment duration or socio-demographic characteristics and vanishes as soon as the unemployed find a new job. We therefore conclude that stated locus of control is affected by unemployment. Using this trait as explanatory variable can thus lead to biased estimations when this temporary deviation in measurement is not accounted for.}, language = {en} } @article{KononKritikos2018, author = {Konon, Alexander and Kritikos, Alexander}, title = {Prediction based on entrepreneurship-prone personality profiles:}, series = {Small business economics : an international journal}, volume = {53}, journal = {Small business economics : an international journal}, number = {1}, publisher = {Springer}, address = {Dordrecht}, issn = {0921-898X}, doi = {10.1007/s11187-018-0111-8}, pages = {1 -- 20}, year = {2018}, abstract = {The human personality predicts a wide range of activities and occupational choices-from musical sophistication to entrepreneurial careers. However, which method should be applied if information on personality traits is used for prediction and advice? In psychological research, group profiles are widely employed. In this contribution, we examine the performance of profiles using the example of career prediction and advice, involving a comparison of average trait scores of successful entrepreneurs with the traits of potential entrepreneurs. Based on a simple theoretical model estimated with GSOEP data and analyzed with Monte Carlo methods, we show, for the first time, that the choice of the comparison method matters substantially. We reveal that under certain conditions the performance of average profiles is inferior to the tossing of a coin. Alternative methods, such as directly estimating success probabilities, deliver better performance and are more robust.}, language = {en} }