Markov and renewal models for total manpower system

This study compares the predictive utility of three stochastic models for both total manpower system and cohort personnel movement. The models are all discrete time versions, including a first order Markov chain, a Markov chain with duration of stay (semi-Markov) and a vacancy model having both renewal and Markov properties. The analysis covers a continuous 20 year period: 1950-1970 for a state police (U.S.A.) internal labor market. The simple Markov chain model is inadequate for long term cohort forecasts, but reasonably adequate for long term organizational forecasts. The semi-Markov model outperforms the simple Markov model for cohorts, but is surprisingly less accurate for the total organization. The heuristic information it portrays for the cohort is, however, quite informative. The best model for intermediate (5 year) and long term (10 year) forecasts in both cohort and organizational tests is the renewal type vacancy model. This finding is viewed as particularly important both in terms of empirical performance, which we expect can be improved due to the initial simplifying assumptions used, and in terms of further theoretical explication of the underlying causal process since internal staff flows are conceptualized as contingent on the opportunities available.