Before revision:  The nonparametric MIDAS estimation method is more flexible but substantially less costly to estimate than existing approaches. The proposed clustering algorithm successfully recovers true membership in the cross-section  both in theory and in simulations  without requiring prior knowledge such as the number of clusters.
After revision:  The nonparametric MIDAS estimation method is more flexible and substantially simpler to implement than competing approaches. We show that the proposed clustering algorithm successfully recovers true membership in the cross-section both in theory and in simulations without requiring prior knowledge such as the number of clusters.