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What is Random Effects Model Regression Results about?

The document presents the results of a Random Effect Model (REM) regression analysis on panel data from 2010 to 2022, focusing on the dependent variable LOG_Y. Key findings include significant coefficients for LOG_X1, LOG_X2, and LOG_DUMMY, with an R-squared value of 0.2827 indicating moderate explanatory power. Additionally, a second regression using pooled EGLS shows minimal explanatory power with a low R-squared of 0.0046 for the dependent variable Y?.

Author

muhiban.suyani18

Language

EN