Quality managment and labor productivity of formal companies in Perú: A non – experimental design and causal machine learning techniques

Mario Tello and Daniel Tello

Estudios de Economia, 2024, vol. 51, issue 1 Year 2024, 117-158

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.

Keywords: Labor Productivity; Quality Management; Machine Learning. (search for similar items in EconPapers)
JEL-codes: J24 L15 P42 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:udc:esteco:v:51:y:2024:i:1:p:117-158

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