In order to satisfy my own curiosity, I recently decided to code and analyze the data points posted in last year’s OCI/EIW results thread (http://www.top-law-schools.com/forums/viewtopic.php?f=23&t=130597). As the dataset is somewhat unique, and some of the results are potentially useful, I thought I would share a bit of what I found.
I chose three dependent variables to use in the analysis:
- The absolute number of offers from law firms [note that this is mostly included as a point of comparison--it's not especially informative when viewed in isolation because it depends upon a number of important factors that are not controlled for (e.g., bidder strategy, confidence, luck, and the number of callback interviews that the respondent decided to attend)]
- The percentage of OCI/EIW screening interviews that were converted into callback interview offers (“Screening Interview Conversion Rate”)
- The percentage of callback interviews accepted that were converted into offers of employment for the following summer (“Callback Interview Conversion Rate”)
I used the following explanatory variables:
- School rank, based on average 2010 USNWR ranking in each grouping of schools (e.g., CCN = 5)
- Transfer differential – the difference in USNWR ranking between the school attended during 1L and the school attending during 2L (0 if the respondent did not transfer)
- Approximate law school rank as a percentile (e.g., top 10% = 90, not .10 or .90)
- Legal markets in which the respondent pursued employment
- Law review membership
- Work experience (1 if any, 0 otherwise)
- IP background
- URM status
- Self-assessed interview ability*
*This variable is slightly problematic: several posts suggested respondents were considering their results when assessing their interview ability, which creates what stats people call an endogeneity problem. Nevertheless, the variable is potentially interesting, so I’ve posted versions of each regression with and without this variable.
Caveat: The sample is weighted in two ways that could potentially bias the results: (1) most respondents attended a T50 or better school; and (2) most respondents did quite well during 1L (the median reported class rank was better than top 25%). Without getting into too much detail here, I think both of these weightings are likely to bias the results in the direction of understating the importance of law school rank and class rank.
These results could be discussed at length in an academic format, but let me draw your attention to the aspects that I find most interesting:
- School rank appears to play a role that goes beyond the mere contextualization of law school grades. Compare the magnitude and significance of law school rank during the screening stage and during the callback stage with the magnitude and significance of class rank during the same stages, respectively—law school rank actually becomes more important during the callback stage while class rank appears to play a much smaller (if any) role.
- Transferring pays off! While transfer students appear to be treated as though they did not transfer at all during the screening stage, which is what we might expect ex ante, they get a significant boost during the callback stage (the importance of school rank goes up, yet the magnitude and significance of the transfer differential variable goes down).
- Law review membership doesn’t appear to buy much during OCI. This result surprised me enough that I ran another halfdozen regressions (including regressions incorporating various interaction terms and proxies for firm selectivity/prestige), but I was unable to find a statistically significant effect in any regression.
Anyway, I’m happy to elaborate on any aspect of this if anyone is interested in discussing this admittedly nerdy endeavor.