Many studies on the relationship between labor supply and health status generally do not illustrate a unanimous agreement on the usage of subjective and objective health due to the difficulty in employing the right measures to obtain the precise and up-to-date information on the health status of subjects in question. Thereby, to resolve this quandary, we propose two models; the first model addresses how a researcher could obtain more appropriate estimate in health measure with measurement error; the other model examines whether probabilities questions within and across waves could potentially result in another measurement error.

In the first model allowing to justification bias, we found the health and financial compensation’ lower and upper bounds for labor force exit and in views of bounds concept, health status plays a larger role in labor force exit than financial compensation.

In the second model, we found that measurement error from survey effect has an impact on the survival probability along with the measurement errors from an inherent errors-in-variable bias by using two methods: the former employing the averaged survival probabilities and the latter incorporating the instrumental variables.