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I present a new estimation procedure for production functions with latentgroup structures. I consider production functions that are heterogeneous acrossgroups but time-homogeneous within groups, and where the group membership ofthe firms is unknown. My estimation procedure is fully data-driven and embedsrecent identification strategies from the production function literature intothe classifier-Lasso. Simulation experiments demonstrate that firms areassigned to their correct latent group with probability close to one. I applymy estimation procedure to a panel of Chilean firms and find sizabledifferences in the estimates compared to the standard approach ofclassification by industry.

A Classifier-Lasso Approach for Estimating Production Functions with Latent Group Structures