The Job Rating Game: Revolving Doors and Analyst Incentives

Elisabeth Kempf is Assistant Professor of Finance at the University of Chicago Booth School of Business. This is based on her recent article, forthcoming in the Journal of Financial Economics.

Investment banks frequently hire analysts from rating agencies. A widespread concern is that this “revolving door” encourages leniency among rating analysts who hope to exchange optimistic credit ratings for well-paying future jobs. For example, a prominent narrative of the financial crisis is that conflicts of interest due to the revolving door contributed to inflated credit ratings, which in turn enabled the financial meltdown: “You are rating someone and then you want to go work for them and make much more money—the notion that you would be critical of some entity and then hope they hire you goes against what we know about human nature” (former Representative Barney Frank in an interview with the Wall Street Journal).

Theoretically, it is not obvious whether the revolving door between rating agencies and investment banks will reduce or improve ratings accuracy. On the one hand, if analysts get hired as an explicit quid pro quo for favors to their future (or potential) employers, then they may indeed be encouraged to be lenient (Stigler (1971); Peltzman (1976); Eckert (1981)). On the other hand, if analysts are also hired for their expertise, they will have a greater incentive to invest in their qualifications or to signal their expertise during their employment at the agency (Che (1995); Salant (1995); Bar-Isaac and Shapiro (2011)). While previous work on revolving doors in the context of rating agencies has focused on capture concerns, my article, forthcoming in the Journal of Financial Economics, sheds light on the magnitude of potential positive incentive effects.

My data set links the career paths of 245 credit rating analysts at Moody’s to 24,406 ratings of securitized finance securities issued between 2000 and 2009, prior to the enactment of Dodd-Frank. Twenty-seven percent of the analysts in my sample subsequently join a prestigious investment bank that underwrites deals rated by Moody’s, and 13% join a prestigious investment bank whose deals they personally rated. The data set allows me to circumvent one of the most important difficulties for empirical studies of revolving doors: the availability of micro data on employee decisions and career paths. Credit ratings represent a publicly observable and relatively frequent measure of output by individual analysts, and subsequent corrections of the initial ratings issued by these analysts provide a useful proxy for analyst (in)accuracy. An attractive institutional feature of Moody’s organization is that subsequent rating adjustments are performed by a separate internal surveillance team and are therefore not under the direct influence of the analyst who assigned the initial rating. Moreover, by comparing accuracy across analysts at the same rating agency for the same type of product and at the same point in time, my research design ensures that the compared analysts face the same task difficulty and organizational environment.

I begin my analysis by documenting a novel finding: accurate credit rating analysts are more likely to be hired by underwriting investment banks. Specifically, analysts who are one standard deviation more accurate are 78% (5.5 percentage points) more likely to be hired by a prestigious underwriting investment bank, compared to the average analyst who rates similar products at the same point in time. The positive relation also holds for departures to underwriters personally rated by the analyst and is robust to various alternative measures of ratings accuracy, including a measure based on realized tranche losses, which cannot be influenced by Moody’s surveillance team.

One potential reason why revolving-door analysts outperformed their peers is that they have been working harder, attempting to develop their skills in order to signal their abilities to potential employers. To identify the magnitude of this incentive effect, I exploit two distinct sources of variation in the likelihood of being hired, while controlling for analyst heterogeneity via analyst fixed effects. First, I use discontinuous changes in the demand for investment banking positions as a shock to the likelihood of being hired by an investment bank. Second, I exploit departures of connected analysts as an instrument for the analyst’s own departure to an investment bank. Connected analysts are defined as analysts who started in the same calendar year as the analyst in question but rated different types of securities. Both approaches suggest the possibility to be hired by an underwriting investment bank has a sizable effect on ex-ante analyst effort: they imply a 38%-44% improvement in ratings accuracy in response to a one standard deviation increase in the likelihood of being hired by an underwriting bank. To the best of my knowledge, these are the first estimates of the magnitude of the incentive effect in the revolving door literature. They suggest that the possibility to be hired by an underwriting bank represents a strong incentive for credit analysts to perform well, and that restricting these employment transfers without changing other aspects of analyst compensation may lead to lower ratings quality.

However, I also find evidence consistent with capture, in line with the findings by Cornaggia, Cornaggia, and Xia (2016) on corporate bond ratings. While being optimistic does not increase an analyst’s overall prospect of being hired, being optimistic on a deal underwritten by a specific bank does increase the likelihood of being hired by that same bank. Hence, the revolving door may also encourage analysts to curry favors toward specific employers. Combined, my results suggest that optimal regulation should trade off the benefits of reducing capture against the cost of reducing labor mobility and weakening incentives for analysts to develop and showcase their skill. For example, a broad ban would likely lead to a greater reduction in labor mobility and, hence, to a greater reduction in effort provision by analysts, relative to a more targeted revolving door policy that only prohibits transitions to entities that analysts have recently rated. These consequences should be taken into account by policymakers when designing revolving door policies.

The complete article is available for download here.

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