Since the public policy is a powerful but expensive tool, policymakers need to use evaluation and monitor tools to test the effectiveness of the policies. Cooperated with World Bank Group, Chilean government initiated the P900 program in the 1990s, which provided extra funds for extra courses to adjust educational inequity in needed schools. As an investor, the WBG wanted to evaluate the impacts of the P900 program on the students. In the course of Applied Econometrics , my group and I were asked to test the correlation between P900 and the students’ performance in the national exams. My goal is to test the effectiveness of P900 program on addressing the educational inequality.
The outputs included a STATA file, a clean data, and a data report. In the process, I utilized the Propensity Score Matching (PSM) and Implement Variable (IV) methods to analyze the data. Originally, the data was a panel data, including multiple variables, covering different schools, regions and time. The data was cleaned and treated in the process to adopt the analysis, such as excluding outliers and trimming data. The outcome proved the validity of the P900 project. Based on the outcome, the policy had insignificant impacts on the student’s performance in the first 2 years, but had significant effects after four years. Controlling other variables and potential measurement errors, the models showed that, in the exam, the students covered by the P900 program would outperform the students not in the P900 by 2.84 points in the first 2 years, and 6.5 points after 4 years.
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