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in Estudios de economía
Quality managment and labor productivity of formal companies in Perú: A non – experimental design and causal machine learning techniques
Abstract:
This paper evaluates the impacts of quality management tools on the labor productivity of companies in Peru for the period 2014-2019 based on causal Machine Learning (ML) techniques (MLC), which reduce or eliminate three potential problems: the endogeneity of the variables of interest, the existence of confusing variables (confounding) and overfitting due to the introduction of many control variables. Using the National Survey of Companies (INEI-ENE 2023), the evaluation indicates that quality control tools affect the productivity of formal companies, particularly large and medium-sized companies.
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Copyright & License
Este es un artículo publicado en acceso abierto bajo una licencia Creative Commons
Author
Mario D. Tello
Faculty of Economic Sciences, University National Mayor of San Marco, Perú, Perú
Author
Daniel S. Tello Trillo
Frank Batten School of Leadership, Public University of Virginia, USA, USA