6 citations · 10 across the 4 of their papers we have counts for
4 papers · 1 filter
An axiomatic nonparametric production function estimator: Modeling production in Japan's cardboard industry
Daisuke Yagi, Yining Chen, Andrew L. Johnson +1
We develop a new approach to estimate a production function based on the economic axioms of the Regular Ultra Passum law and convex non-homothetic input isoquants. Central to the d…
Direction Selection in Stochastic Directional Distance Functions
Kevin Layer, Andrew L. Johnson, Robin C. Sickles +1
Researchers rely on the distance function to model multiple product production using multiple inputs. A stochastic directional distance function (SDDF) allows for noise in potentia…
Shape constrained kernel-weighted least squares: Application to production function estimation for Chilean manufacturing industries
Daisuke Yagi, Yining Chen, Andrew L. Johnson +1
In this paper we examine a novel way of imposing shape constraints on a local polynomial kernel estimator. The proposed approach is referred to as Shape Constrained Kernel-weighted…
Insights from Machine Learning for Evaluating Production Function Estimators on Manufacturing Survey Data
José Luis Preciado Arreola, Daisuke Yagi, Andrew L. Johnson
Organizations like U.S. Census Bureau rely on non-exhaustive surveys to estimate industry-level production functions in years in which a full Census is not conducted. When analyzin…