In this paper, we analyze the key drivers of bond covenant prices by employing a novel measurement approach based on secondary market data. We find that covenant prices vary significantly over time and are associated with market-wide credit risk, volatility, and macroeconomic variables. Apart from the time-series dynamics, there is also significant variation across bond and firm characteristics. In particular, covenant prices increase with the riskiness of bonds and are higher for firms that have more growth options, more tangible assets, and are smaller. Furthermore, we document a positive correlation between the prices of covenants and their subsequent inclusion rates.

ABSTRACT In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.