An Evaluation of Inertia Models of Unemployment

Two approaches have been used to model unemployment. The first, conventional, approach involves linking the unemployment outcome to observed indices of productivity, structural factors and discrimination such as educational attainment, location and birthplace. The second approach, the inertia model, involves using a person's labor market history as a way of including in unemployment models information on the unobservables that influence employability. This paper evaluates the performance of both models of unemployment. The results provide unambiguous support for the inertia model when modelling unemployment. The inertia model has higher explanatory power, higher within-sample prediction rate success and fewer out-of-sample forecasting errors than the conventional model. The estimates from the inertia model can be used to provide quite accurate predictions of the risk of becoming unemployed. This is important if individuals at high risk of becoming unemployed are to be targeted for labor market assistance.