The diversification discount (multiple segment firm value below the value imputed using single segment firm multiples) is commonly thought to be generated by agency problems, a lack of transparency, or lackluster future prospects for diversified firms. If multiple segment firms have lower uncertainty about mean profitability than single segment firms, rational learning about mean profitability provides an alternative explanation for the diversification discount that does not rely on suboptimal managerial decisions or a poor firm outlook. Empirical tests which examine changes in firm value across the business cycle and idiosyncratic volatility are consistent with lower uncertainty about mean profitability for multiple segment firms.

Investment spending by US public firms is highly concentrated. The 100 largest spenders account for 60% of total capital expenditures and drive most of the variation in aggregate investment. This high concentration creates a disconnect between the average public firm and macroeconomic aggregates. For large firms, cash flow remains the primary driver of investment spending and has not declined in importance as it has for smaller public firms. The cash flowing to big spenders provides a better forecast of future investment opportunities than noisy proxies for Tobin's q even though these firms are not financially constrained. These results suggest that, at least for the largest spenders, it is unlikely that measurement error drives the significance of cash flow. Our results are also inconsistent with recent models that predict higher investment-cash flow sensitivity for small young growth firms and suggest that cash flow is still the most important determinant of macroeconomic fluctuations in investment spending.

We test whether ratings are comparable across asset classes. We examine default rates by initial rating, accuracy ratios, migration metrics, instantaneous upgrade and downgrade intensities, and rating changes over bonds’ lives in multivariate regressions. These approaches reveal substantial and persistent differences across broad asset classes, as well as across subcategories of structured finance products. Our results are best explained by variation in rating agency incentives and variation in underlying risk profiles. We conclude that regulations requiring ratings to perform comparably across asset classes will prove difficult to enforce. We advocate instead a regulatory framework that better distinguishes risks and incentives across asset classes.

This paper develops three distinct methods to quantify the risk of a systemic failure in the global banking system. We examine a sample of 334 banks (representing 80% of global bank equity) in 28 countries around five global financial crises. Our results suggest statistically significant, but economically small, increases in systemic risk. Although policy responses are endogenous, the low estimated probabilities suggest that the distress of central bankers, regulators and politicians about the events we study could be overstated and that current policy responses to financial crises could be adequate to handle major macroeconomic events.

We investigate the effects of opioid abuse on municipal finance. We employ instrumental variables, border discontinuity difference-in-differences regressions, and coarsened exact matching to identify consistent causal effects, while controlling for variation in economic conditions and demographics. Opioid abuse lowers credit ratings, increases new offer yields, and reduces bond issuance. Reversal of these effects following effective antiopioid legislation further supports causality. Differential effects due to investor heterogeneity suggest that opioid abuse affects municipal finance through a capital supply channel. Overall, we conclude that local opioid abuse impedes municipalities’ access to capital and thus hurts their ability to provide public services and infrastructure.