In the aftermath of an earthquake, the number of occupants within destroyed housing is often used to approximate the number of people rendered homeless after the event. While this metric can provide rapid situational awareness, more recent research highlights the importance of additional factors beyond housing damage within the scope of household displacement (e.g., utility disruption, housing tenure, place attachment). This study models three recent earthquakes from different geographies (Haiti, Japan, and Nepal) to benchmark housing damage as a driver of population displacement against reported values and mobile location data-based estimates. The results highlight the promise of risk models to realistically estimate population displacement after earthquakes in the emergency phase as compared with official reports, but also indicate a large range of uncertainty in the predicted values. Furthermore, purely basing displacement estimates on housing damage may limit the ability of models to capture protracted displacement compared to more comprehensive models that include other factors influencing population return or alternative approaches such as using mobile location data. Although mobile location data offers potential to quantify displacement duration, the results of this study indicate further need to benchmark and validate such approaches.