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Shape constrained kernel-weighted least squares: Estimating production functions for Chilean manufacturing industries

Yagi, Daisuke, Chen, Yining, Johnson, Andrew L. and Kuosmanen, Timo (2018) Shape constrained kernel-weighted least squares: Estimating production functions for Chilean manufacturing industries. Journal of Business and Economic Statistics. 0-0. ISSN 0735-0015

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Identification Number: 10.1080/07350015.2018.1431128

Abstract

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 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

Item Type: Article
Official URL: http://www.tandfonline.com/toc/ubes20/current
Additional Information: © 2018 Informa
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
Sets: Departments > Statistics
Date Deposited: 26 Jan 2018 14:45
Last Modified: 20 May 2019 00:06
URI: http://eprints.lse.ac.uk/id/eprint/86556

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