Insights from machine learning for evaluating production function estimators on manufacturing survey data
José Luis Preciado Arreola, Daisuke Yagi, Andrew L. Johnson
| Year of publication: |
2020
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| Authors: | Preciado Arreola, José Luis ; Yagi, Daisuke ; Johnson, Andrew L. |
| Published in: |
Journal of productivity analysis : an official journal of the International Society for Efficiency and Productivity Analysis. - New York, NY : Springer Science+Business Media LLC, ISSN 1573-0441, ZDB-ID 1478730-1. - Vol. 53.2020, 2, p. 181-225
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| Subject: | Convex nonparametric least squares | Adaptive partitioning | Multivariate convex regression | Nonparametric stochastic frontier | Nichtparametrisches Verfahren | Nonparametric statistics | Produktionsfunktion | Production function | Schätztheorie | Estimation theory | Künstliche Intelligenz | Artificial intelligence | Regressionsanalyse | Regression analysis |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1007/s11123-019-00570-9 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012228831