In the previous 2 articles we discussed the theoretical and practical implications of the Pooled OLS, Fixed Effect and Random Effect Models. This article will discuss the significance of dummy variables such as time or industry dummies in our panel data. We will use the same dataset we used in the previous article. The data […]
Panel Data With Fixed Effects (Time, year, country fixed effect) Read More »
In the previous article, we discussed the theoretical aspect of the panel data analysis, including the basic knowledge and limitation of the OLS, Fixed, and Random Effect Models. This article will demonstrate the application of various statistical models using Stata. Along with that, we will also look into the Breusch Pagan test and Hausman Test.
Researchers and analysts consistently endeavour to derive significant insights to inform decision-making and policy development in an era of abundant data. Panel data analysis is a robust methodology that offers insights into longitudinal patterns and reveals valuable information within intricate datasets. This article explores panel data analysis, explaining its fundamental nature and various applications. Definition
In the previous article, we discussed the theoretical aspects of the estimation strategy. In this article will look into the practical aspects of the estimation strategy (Between estimation, First difference estimation, and within estimation). Between Estimation: We will first implement the manual method of between estimation analysis and then use the Stata command to do
Between, First Difference and Within Estimation in Stata Read More »
In the previous 3 articles, we discussed the theoretical and practical implications of the Pooled OLS, Fixed Effect, and Random Effects Models and the significance of dummy variables such as time or industry dummies. This article will look into other techniques that come under panel data analysis. The techniques are listed below: Download Example File
