Refereed journal article or data article (A1)

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




List of Authors: Yagi D, Chen YN, Johnson AL, Kuosmanen T

Publisher: AMER STATISTICAL ASSOC

Publication year: 2020

Journal: Journal of Business and Economic Statistics

Journal name in source: JOURNAL OF BUSINESS & ECONOMIC STATISTICS

Journal acronym: J BUS ECON STAT

Volume number: 38

Number of pages: 12

ISSN: 0735-0015

DOI: http://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