Fixed-Effects Regression in Panel Data Analysis using Stata

See text: https://phantran.net/fixed-effects-regression-in-panel-data-analysis-using-stata/
Database: https://drive.google.com/file/d/1G3NF-jL6Eoz9zrOjad5dMZrv33-Sp_D2/view?usp=sharing
Data in excel: https://docs.google.com/spreadsheets/d/135p2zph7SL6I5Y5UyCu7eKFzcOitrBLb/edit?usp=sharing&ouid=100029919331612689631&rtpof=true&sd=true
Fixed-effects model is used whenever we are only interested in analyzing the impact of variables that vary over time. This model is “designed to study the causes of changes within an entity. A time-invariant characteristic cannot cause such a change, because it is constant for each entity” (Kohler and Kreuter. 2008). Fixed-effects model explores the relationship between independent variable and dependent variable within an entity as province in our empirical study. Each entity has its own individual characteristics as independent variables, that may or may not influence the dependent variable. When using Fixed-effects model, we assume that something within the individual may impact or bias the independent variables and we need to control for this. This is the rationale behind the assumption of the correlation between entity’s error term and independent variables. Fixed-effects model remove the effect of those time-invariant characteristics so we can assess the net effect of the independent variables on the dependent one. Another important assumption of the Fixed-effects model is that those time-invariant characteristics are unique to the individual and should not be correlated with other individual characteristics. Each entity is different therefore the entity’s error term and the constant (which captures individual characteristics) should not be correlated with the others.