Estrategias de precios e incertidumbre económica un estudio de caso para la industria farmacéutica argentina usando aprendizaje automatizado
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Gutiérrez, Emiliano
Virdis, Juan Marcelo
Meller, Leandro
Domínguez, Diego Leandro
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Universidad Pablo de Olavide
Abstract
Introducción: En agosto de 2019, un resultado inesperado en las elecciones presidenciales generó una variación en el tipo de cambio y la inflación esperados. El objetivo de este estudio es analizar la relación entre la participación de mercado y la decisión de incrementar los precios en la industria farmacéutica en Argentina.Métodos: Se obtuvieron datos semanales en línea sobre las variaciones de los precios de algunos medicamentos mediante técnicas de web scrapping, y luego se aplicaron algoritmos de clasificación (Random Forests, Gradient Boosting Machiney regresión logística).Resultados: Los resultados fueron dispares. Se encontró que la participación de mercado es importante de acuerdo a los métodos basados en árboles (Random Forestsy Gradient Boosting Machine). Sin embargo, en la regresión logística, dicha variable no era significativa. Conclusiones: La volatilidad en el tipo de cambio que siguió al resultado de la elección causó varios cambios en los precios esperados, y la estructura del mercado farmacéutico influyó sobre las reacciones de precios resultantes. Los laboratorios que tenían una mayor participación de mercado incrementaron sus precios primero
Introduction: In August 2019 an unexpected presidential election result caused a change in expected exchange and inflation rates. The objective of this study is to analyze the relation between market share and the decision of increasing prices in the pharmaceutical industry in Argentina.Methods: Online weekly data on variations of some medicine’s prices were obtained using web scraping, and then classification algorithms (Random Forests, Gradient Boosting Machine and logistic regression) were applied.Results: The results were mixed: market share was found to have high importance in tree-based methods. (Random Forests and Gradient Boosting Machine). However, in logistic regression, this variable wasn’t significant. Conclusions: Exchange rate volatility after the election result caused several changes on price expectations, and pharmaceutical market structure influenced the resulting price reactions. Laboratories which owned a higher market share rose their prices first
Introduction: In August 2019 an unexpected presidential election result caused a change in expected exchange and inflation rates. The objective of this study is to analyze the relation between market share and the decision of increasing prices in the pharmaceutical industry in Argentina.Methods: Online weekly data on variations of some medicine’s prices were obtained using web scraping, and then classification algorithms (Random Forests, Gradient Boosting Machine and logistic regression) were applied.Results: The results were mixed: market share was found to have high importance in tree-based methods. (Random Forests and Gradient Boosting Machine). However, in logistic regression, this variable wasn’t significant. Conclusions: Exchange rate volatility after the election result caused several changes on price expectations, and pharmaceutical market structure influenced the resulting price reactions. Laboratories which owned a higher market share rose their prices first
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Revista de métodos cuantitativos para la economía y la empresa, ISSN-e 1886-516X, Vol. 38, 2024, págs. 1-16




