Euro-area sovereign bond and interbank interest rate spreads spiked in the 2007–2009 Global Financial Crisis and the subsequent European Debt Crisis, substantially elevating financing costs. I use a model-free measure of market liquidity to precisely identify the relative contribution of credit versus liquidity to spreads in these episodes. In the Financial Crisis, liquidity is paramount, accounting for 36% of trough-to-peak widening, after controlling for credit. However, default risk becomes relatively more important to sovereign spreads in the Debt Crisis. Aggregate bond liquidity explains a substantial portion of interbank spreads throughout the sample.

This paper traces the evolution of extreme illiquidity discounts among Treasury securities during the financial crisis; bonds fell more than six percent below more-liquid but otherwise identical notes. Using high-resolution data on market quality and trader identities and characteristics, we find that the discounts amplify through feedback loops, where cheaper, less-liquid securities flow to investors with longer horizons, thereby increasing their illiquidity and thus their appeal to these investors. The effect of the widened liquidity gap on transactions costs is further amplified by a surge in the price liquidity providers charged for access to their balance sheets in the crisis.

We examine the efficiency of using individual stocks or portfolios as base assets to test asset pricing models using cross-sectional data. The literature has argued that creating portfolios reduces idiosyncratic volatility and allows more precise estimates of factor loadings, and consequently risk premia. We show analytically and empirically that smaller standard errors of portfolio beta estimates do not lead to smaller standard errors of cross-sectional coefficient estimates. Factor risk premia standard errors are determined by the cross-sectional distributions of factor loadings and residual risk. Portfolios destroy information by shrinking the dispersion of betas, leading to larger standard errors.