Homework 3
Introduction
Here is a guide to the experimental data of Bertrand & Mullanaithan (2001)
Each row of this dataset contains the variables related to one job application. Here is a summary of the variables you will need:
call
: a binary variable equal to 1 if the application receives a callbackrace
: a string variable equal to “w” if white sounding name, “b” if black soundingeducation
: an integer variable between 0 and 4 that indicates level of education reported on the applicant’s resumeyearsexp
: a variable with the applicant’s years of experienceh
: a dummy variable indicating that the resume was of a high quality
Question 1
Use a regression framework to replicate the paper’s evidence that (1) white sounding names receive more callbacks than black sounding names; and (2) white sounding names receive significantly more (at a significance of 10%) callbacks when the resume quality is “high”, while black sounding names do not.
Question 2:
Re-run the same analysis to document racial bias in callbacks (finding 1) using a regression framework, this time controlling for education and years of experience in the regression.
Question 3:
Use a regression framework to test the null hypothesis that racial differences in callbacks are the same regardless of the applicant’s years of experience.
Question 4
Consider the model:
\[ \mathbb{E}[white|eduction] = \beta_{0} + \beta_{1}education \]
where white
is a dummy variable equal to 1 if the applicant has a white sounding name.
What does the random assignment of race imply about \(\beta_{1}\) in this linear model? Run a regression to test this implication.