Modern econometric analysis started with the invention of regression analysis, and one of its predominant forms is ordinary least square methodology, which is commonly known as OLS technique among the economic analysts across the world. However, as time is progressing, new mathematical techniques are emerging, and in accordance with that, econometric methodologies are also going through a transformation. One of the modern trends in the regression methodology is the panel regression technique, which is carried out only on panel data. This regression technique is categorized into two parts, namely fixed effect and random effect regression. Out of all the available softwares in the market, STATA is the one, which is the most efficient in performing panel regression.

Performing panel regression in STATA involves several sequential steps. First, the data has to be imported in the STATA and the data should be defined as panel data. Unless the data has been defined properly, it will be impossible for the software to identify the cross sections and the time series variables. Second, the dependent variable and the set of independent variables have to be selected in order to define the regression model. Third, the effect has to be selected, i.e. researcher has to choose between fixed and the regression effects. However, it can prove out to be tough for anyone to guess the model to be fit in either of these two effects, and therefore, it is suggested to run both the effects. Fourth, after running each of the effects, the results have to be stored with specific titles, so that they can be used for further steps. Fifth, once results of both the effects are present, Hausman specification test is needed to be run in order to find out which one of the two is performing better to explain the model.

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