This chapter is PART 1 of the following three part section on Panel Data Analysis: In fact, in many panel data sets, the Pooled OLSR model is often used as the reference or baseline model for comparing the performance of other models. We will take an even deeper look at the goodness-of-fit of the model via a detailed analysis of its residual errors.Īlong with the Fixed Effects, the Random Effects, and the Random Coefficients models, the Pooled OLS regression model happens to be a commonly considered model for panel data sets.
In this chapter, we’ll get to know about panel data datasets, and we’ll learn how to build and train a Pooled OLS regression model for a real world panel data set using statsmodels and Python.Īfter training the Pooled OLSR model, we’ll learn how to analyze the goodness-of-fit of the trained model using Adjusted R-squared, Log-likelihood, AIC and the F-test for regression. And a detailed analysis of its goodness-of-fit using Python and statsmodels
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