This can be done by estimating proportional hazard rates by using the Kaplan-Meier estimator which estimates the survival function (the probability that someone will “survive in a specified status” beyond a certain time, even when the sample is censored and biased, Denisova, 2011). However, these are not unconditional probabilities that can be used to depict the general chances of moving in and out of poverty, these are conditional hazard rates indicating, for example, what the chances are of someone exiting poverty, if he/she has been in poverty for, say, two years, given a set of specified characteristics (e.g. household characteristics, labour market status of adults, eligibility to public transfers, human capital characteristics, but also region and time). These conditional probability functions can be estimated both regarding relative and absolute poverty lines.