Packages

This package implements the production function estimation approach from Trunschke and Judd (2024), with a GMM estimator and bootstrap standard errors. Currently only Cobb-Douglas functional forms with one flexible input are supported. However, the package supports multiple fixed inputs, arbitrary degrees of the polynomial form of the law of motion for productivity and to include additional shifters in the law of motion. The package uses state-of-the-art numerical optimizers, efficient implementations of performance critical functions and parallel execution of the bootstrap routines.
Development is ongoing and any comment or suggestion is welcome. Either email me or make a pull request on the GitHub repository.

This package implements the production function estimaton method from Gandhi, Navarro, Rivers (2020). This implementation allows for an arbitary number of fixed production function inputs and one flexible input. The user can freely choose the degree of each polynomial series. Its latest release added bootstrap-based standard errors and inference for key statistics. The package uses state-of-the-art numerical optimizers and efficient implementations of performance critical functions, allowing for fast and reliable usage.
Development is ongoing and any comment or suggestion is welcome. Either email me or make a pull request on the GitHub repository.