Shape-Constrained Kernel-Weighted Least Squares: Estimating Production Functions for Chilean Manufacturing Industries



: Yagi D, Chen YN, Johnson AL, Kuosmanen T

Publisher: AMER STATISTICAL ASSOC

: 2020

: Journal of Business and Economic Statistics

: JOURNAL OF BUSINESS & ECONOMIC STATISTICS

: J BUS ECON STAT

: 38

: 43

: 54

: 12

: 0735-0015

DOI: https://doi.org/10.1080/07350015.2018.1431128


In this article, 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 least squares (SCKLS). We prove uniform consistency of the SCKLS estimator with monotonicity and convexity/concavity constraints and establish its convergence rate. In addition, we propose a test to validate whether shape constraints are correctly specified. The competitiveness of SCKLS is shown in a comprehensive simulation study. Finally, we analyze Chilean manufacturing data using the SCKLS estimator and quantify production in the plastics and wood industries. The results show that exporting firms have significantly higher productivity.



Last updated on 2024-26-11 at 22:23