Diferentes formas de medir la rentabilidad en el sector agropecuario uruguayo mediante clústeres longitudinales
Authors/Creators
- 1. Universidad de la República
Description
The objective of this paper is to measure and describe the evolution of the profitability of the Uruguayan agricultural sector in the period 2010-2017. For this purpose, we use a database constituted by the accounting statements of the Uruguayan agricultural
Uruguayan agricultural companies that submitted their tax returns to the General Tax Directorate (DGI) during the aforementioned period. Profitability is measured through the ROA (return on assets) indicator. The methodological
The methodological strategy consists of identifying patterns of evolution through longitudinal clusters. The results show that profitability is positive during the period, although internally it presents very diverse levels and dynamics.
Thus, three groups are formed with similar ROA trajectories within them, but very different from each other. This serves as an input to characterize their economic structure and to obtain clues about the determinants of the sector's financial economic performance.
financial economic performance of the sector.s
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Additional details
Additional titles
- Translated title (En)
- Different ways of measuring profitability in the Uruguayan agricultural sector using longitudinal clusters
References
- Genolini, C., Alacoque, X., Sentenac, M., y Arnaud, C. (2015). kml and kml3d: R Packages to Cluster Longitudinal Data. Journal of Statistical Software, 65(04):1–34.
- enolini, C., Falissard, B., y Pingault, J.-B. (2017). kml3d: K-Means for Joint Longitudinal Data.
- Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., y Hornik, K. (2022). cluster: Cluster Analysis Basics and Extensions. R package version 2.1.3 — For new features, see the 'Changelog' file (in the package source).
- R Core Team (2021). R: A Language and Environment for Statistical Computing.