  Detailed knowledge of individual income dynamics is crucial for investigating
the existence of the American dream: Are we able to improve our income status
during our working life? This key question simply boils down to observing
individual status and how it moves between two thresholds: the current income
and the desired income. Yet, our knowledge of these temporal properties of
income remains limited since we rely on estimates coming from transition
matrices which simplify income dynamics by aggregating the individual changes
into quantiles and thus overlooking significant microscopic variations. Here,
we bridge this gap by employing First Passage Time concepts in a baseline
stochastic process with resetting used for modeling income dynamics and
developing a framework that is able to crucially disaggregate the temporal
properties of income to the level of an individual worker. We find analytically
and illustrate numerically that our framework is orthogonal to the transition
matrix approach and leads to improved and more granular estimates. Moreover, to
facilitate empirical applications of the framework, we introduce a publicly
available statistical methodology, and showcase the application using the USA
income dynamics data. These results help to improve our understanding on the
temporal properties of income in real economies and provide a set of tools for
designing policy interventions.
