Question
Question 6 Use the dataset data4 to examine if attending an after-school program has a causal effect on the improvement of students' scores (y) using
Question 6
Use the dataset "data4" to examine if attending an after-school program has a causal effect on the improvement of students' scores (y) using a difference-in-difference model. Students in class A, B, and C attend the after-school program, while students in class D do not. The after-school program runs in year 2018. Each row of data represents the observation of a student in the sample.
Create two dummy variables. The first dummy variable is the treatment dummy variable, which indicates whether the student receives the treatment (i.e. whether the student attends the after-school program). If the student attends the program (i.e. is in class A, B, or C), then the first dummy variable is equal to one, otherwise, it is equal to zero. The second dummy variable is the post-treatment period dummy variable, which indicates whether the is taken in the post-program period. If the is taken in the post-program period (i.e., in 2019), then the second dummy variable is equal to one, otherwise, it is equal to zero.
- Run the difference-in-difference model with control variables. Please write the regression equation below.
- Analyze the summary of regression results (i.e. state the estimated values of regression coefficients, interpret the use of R-squared, determine if each population regression coefficient is different from zero by using t-value or P-value) and determine if attending the after-school program has a causal effect on improving students' scores. Use 10% as the significance level
- Screenshot the code and results
| Score | Class | Year |
| 66 | A | 2019 |
| 77 | B | 2017 |
| 79 | C | 2019 |
| 87 | D | 2017 |
| 40 | A | 2017 |
| 31 | A | 2017 |
| 97 | C | 2019 |
| 42 | B | 2017 |
| 96 | D | 2019 |
| 77 | B | 2017 |
| 60 | B | 2017 |
| 87 | B | 2019 |
| 99 | C | 2019 |
| 25 | C | 2017 |
| 100 | C | 2019 |
| 42 | D | 2017 |
| 60 | C | 2017 |
| 57 | D | 2017 |
| 50 | C | 2019 |
| 72 | D | 2017 |
| 46 | B | 2019 |
| 39 | B | 2019 |
| 42 | D | 2017 |
| 87 | B | 2019 |
| 30 | C | 2017 |
| 42 | C | 2019 |
| 76 | C | 2017 |
| 47 | A | 2017 |
| 72 | A | 2017 |
| 42 | D | 2019 |
| 57 | A | 2017 |
| 55 | A | 2019 |
| 80 | A | 2017 |
| 98 | A | 2019 |
| 27 | D | 2017 |
| 72 | B | 2019 |
| 87 | C | 2017 |
| 100 | A | 2019 |
| 57 | A | 2017 |
| 72 | A | 2019 |
| 27 | C | 2017 |
| 100 | A | 2019 |
| 88 | B | 2017 |
| 57 | D | 2019 |
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