Statistical laws for career longevity

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  • 7 March 2009
Abstract
Career length distinguishes successful long tenures from unsuccessful short stints, and partially reflects the contributions of an employee to the goals of the employer. In some professions, there are well-defined metrics that quantify career longevity, success, and prowess, which together contribute to the overall success rating for an individual employee. We develop a stochastic model for career development that relies on two key ingredients: random progress within the career and random stopping times terminating the career. We solve the model exactly and find a functional form for the probability density function (pdf) P(x) of career longevity, characterized by two parameters, \alpha and x_{c}. The parameter \alpha quantifies the scaling of the pdf, which is terminated by an exponential cutoff after a crossover value x_{c}, representing a characteristic lifetime that distinguishes newcomers from veterans. We are able to test our model with the large quantity of empirical data available for professional sports leagues.

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