Comparison of CEM, FEM and REM models, case study of Return On Assets
DOI:
https://doi.org/10.54065/likelihood.1076Keywords:
Common Effect Model, Fixed Effect Model, Random Effect Model, Return On AssetsAbstract
This research compares three panel data regression models Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM) to analyze Return on Assets (ROA) in state-owned banks in Indonesia in the period 2022 to 2024. ROA is used to measure bank efficiency in utilizing assets to generate profits and operational profitability. The panel data approach combines cross-section and time series dimensions, which allows dynamic analysis between individuals and periods. The results of the analysis show that for the Chow, Hausman, and Lagrange Multiplier tests, the CEM model is more appropriate to use compared to the FEM and REM models because there are no significant differences that support the use of other models. BOPO (x?) has a significant effect on ROA with a p-value of 0.000, while LDR/FDR (x?) and NIM (x?) do not have a significant effect. The CEM model can explain 97.60% of the variation in ROA, although several independent variables are not significant.
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Copyright (c) 2025 Leny Yuliyani, Dicky Rahardiantoro, Muh Idham Kurniawan
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