A Robust Approach to Estimating Production Functions : Replication of the ACF Procedure

We study Ackerberg, Caves, and Frazer (2015)'s production function estimation method using Monte Carlos simulations. First, we replicate their results by using the same procedure and confirm the existence, as noted by ACF, of a spurious minimum in the estimation. In the population, or when the sample size is large enough, this "global" identification problem may not be a concern because the spurious minimum holds only at the extreme values of the capital and the labor coefficients. However, in the finite samples, their estimator can produce estimates that may not be clearly regarded as the spurious ones. In our second experiment, we modify the ACF procedure and show that using additional lagged instruments or a sequential search help to obtain robust estimates. We also provide some arguments why such modifications help in the ACF setting