The U.S. labor market has been experiencing unprecedented high average unemployment duration. The shift in the unemployment duration distribution can be traced back to the early nineties. In this study, censored quantile regression methods are employed to analyze the changes in the US unemployment duration distribution. We explore the decomposition method proposed by Machado and Mata (2005) to disentangle the contribution of the changes generated by the covariate distribution and by the conditional distribution. The data used in this inquiry are taken from the nationally representative Displaced Worker Surveys of 1988 and 1998. We provide evidence that the change in the unemployment duration distribution is mainly produced by the opposing effects of a sharp rise in job-to-job transition rates and an increased sensitivity of unemployment duration to unemployment rates. Compositional changes in the labor force played a limited role. We rationalize our findings by arguing that improved screening technology is likely to be the relevant underlying mechanism at work.