Refereed journal article or data article (A1)

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




List of AuthorsYagi D, Chen YN, Johnson AL, Kuosmanen T

PublisherAMER STATISTICAL ASSOC

Publication year2020

JournalJournal of Business and Economic Statistics

Journal name in sourceJOURNAL OF BUSINESS & ECONOMIC STATISTICS

Journal acronymJ BUS ECON STAT

Volume number38

Start page43

End page54

Number of pages12

ISSN0735-0015

DOIhttp://dx.doi.org/10.1080/07350015.2018.1431128


Abstract
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 2022-04-10 at 19:29