Welcome to the IRR Researcher Site!
What is IRR?
Incentivized Resume Rating (IRR) is a method that allows researchers to investigate how firms make employment decisions. In an IRR study, employers rate resumes they know to be hypothetical and are then matched with real job applicants based on how they rate the hypothetical resumes. This matching process incentivizes employers to spend time reviewing the hypothetical resumes and to truthfully report their preferences. This incentive distinguishes IRR from a typical unincentivized survey, while the transparent recruitment process distinguishes it from a resume audit study.
IRR was developed by economists Judd B. Kessler, Corinne Low, and Colin Sullivan. A paper describing IRR and its first application was published in the American Economic Review (Nov 2019, lead article). The study investigated the preferences of recruiters hiring undergraduates from the University of Pennsylvania. Among other results, it uncovered evidence of biases that may be present among recruiters at elite firms.
Planning your IRR Study
To help you run your own IRR study, we have outlined the steps to run an IRR study here.
1. Collect Resumes from applicants who are interested in being recommended to employers. You can use these resumes to create components for your hypothetical resumes. For example, we used work experience, extracurricular (or “leadership”) activities, and skills as components.
2. Create a survey tool that randomly combines resume components to generate hypothetical resumes and allows employers to rate them. You will need to decide what components you want to randomize and decide on the randomization rules. You will then need to clean these components from the resumes you collected in part 1 or obtain them from other sources (e.g., tables of birth names). To help you get started you can use the template survey tool in our Resource Library.
3. Partner with employers who are interested in being matched with applicants and have them complete your survey tool. After the employers have used the survey tool, use the employers responses to create a personalized list of recommended applicants for each employer.