1. 1.Read Cunha, Menichini, and Crockett (2015) “The retention effects of high years of service cliff-vesting pension plans,”
Economics Letters.
2. 2.Reproduce the 2 tables and the 3 survival curves presented in the paper using the Stata dataset “retirement_data.dta” with
R Studio. I should be able to run your script without errors by only changing the parent directory.
3. Additional questions to answer:
a. Do you need to drop any observations? Why? Was there a different way to handle the missing data?
b. In a few sentences, discuss the issues surrounding causal inference in this paper. Do you believe whether the removal of the 20-year cliff vest
causes
higher attrition? What are some threats to this causal interpretation of the empirical results?
4. Submit (1) do-file; (2) Word or PDF file with 3 survival curve graphs copy/pasted from
R Studio. Include your answers to “Additional questions” in the Word file.
Helpful hints:
· The file “retirement_data.dta” is fully labeled with the following variables:
o hiredate: This is the day/month/year in which the individual started service.
o birthdate: Date of birth
o sex: M==male, F==female
o service: branch of service, Air Force, Army, or Navy
o firstsepartiondate: Date of first separation from service (data on subsequent active duty and separations is not available)
o superfund: The superannuation (retirement) fund the service member is subject to, either DFRDB or MSBS
o officer: Officer==1, Enlisted==0
· If you are not familiar working with dates, reading the Stata manual
https://www.stata.com/manuals/u25.pdf
may be a good first step. Keep in mind that you can calculate the difference between 2 dates by subtracting them.
I'm having trouble reproducing similar values for table 1, I was able to get close to table 2. I am also struggling to reproduce the two other lines for each of the 3 graphs.