Accurate predictions of future magnitudes of the unemployment rate are crucial for monetary policy.This paper investigates whether the use of disaggregated household survey data improves the forecasts of the Colombian 13 cities unemployment rate.We conduct an outof-sample forecast exercise to compare the performance of a model that incorporates flows of workers across different states of the labour market to that of various macroeconomic non-structural models.The paper follows the approach proposed by Barnichon & Nekarda (2013).Our results indicate that the two-state-flow model provides substantially better forecasts of the unemployment rate over longer horizons (more than five months ahead).Additionally, when forecasts are combined, significant gains in every forecasting horizon occurs.This combined forecast shows a 23% reduction in overall RMSE.