Are public firm investment rates more sensitive than private firm rates to new investment opportunities? We offer a new explanation for differences in public and private firm investment sensitivities: investment sensitivities differ because the type of investments favored by firms varies with their listing status. Specifically, we consider the geography of investment opportunities and find that private firms have a much stronger investment home-bias than similar public firms which makes their investment decisions more sensitive to local investment opportunities than public firms. Controlling for local investment opportunities explains four-fifths of the differential sensitivity between public and private firms not explained by more traditional measures of investment opportunities.

This paper investigates the relevance of information acquisition costs for corporate bond spreads. We exploit the staggered introduction of the SEC’s EDGAR database and its XBRL initiative to show that these costs matter: Lower information acquisition costs are associated with a decline in credit spreads at the onset of both initiatives. Our results are stronger for bonds that are associated with higher information uncertainty. We also show that bond liquidity is an important channel through which lowering information acquisition costs affects credit spreads. We document a decline in the non-default component in spreads and a positive impact on transaction cost measures and trading volume following the introduction of XBRL.

We revisit the well-established puzzle that leverage is negatively correlated with measures of profitability. In contrast, we find that at times when firms are at or close to their optimal level of leverage, the cross-sectional correlation between profitability and leverage is positive. At other times, it is negative. These results are consistent with dynamic trade-off models in which infrequent capital structure rebalancing is optimal. The time series of market leverage and profitability in the quarters prior to rebalancing events match the patterns predicted by these models. Our results are not driven by investment layouts, market timing, payout, or mechanical mean reversion of leverage.