Welcome to the repository for the project "Assessing the Impact of Gender Equality Policies on Wage Disparities and Employment Rates: A Causal Analysis".
In this project, we investigate the effects of gender equality policies on wage disparities and employment rates in the United States.
The goal is to provide insights that could inform gender equality policies in Germany.
The project is based on data from the year 2010 and employs advanced statistical techniques for causal analysis.
The dataset used in this analysis, named "genderinequality," contains information on individual workers in the U.S.
Some workers are employed in firms subject to the new gender equality policies (treated workers), while others work in firms without these policies (untreated workers).
The dataset includes various variables, such as hourly wage (natural logarithm), IQ, education, experience, age, marital status, race, and more.
The methodology of this project revolves around evaluating the effects of gender equality policies using advanced statistical methods.
Causal Forests and R Learner approaches are employed to estimate treatment effects within different subgroups.
Key assumptions underlying the analysis include unconfoundedness and overlap, which are essential for deriving meaningful causal relationships from the data.
Feel free to explore the repository and delve into the code and analysis files to gain a comprehensive understanding of the project's findings and implications.
Note: This README is a summary of the project's content and aims to provide an overview for readers.
For in-depth details and analyses, refer to the project's specific R files and associated documents in the repository.