derivative based on expectations of such costs, it captures the compensation demanded by investors to insure against default. However, the Libor-OIS spread also captures an element of liquidity. Since an OIS contract does not require the exchange of loan principal, but only the interest component, this premium can also be viewed as an inducement to forgo liquid assets; such premia may be especially important in the environment of a financial crisis, where liquidity is very scarce. Moreover, it appears that liquidity may in fact be the larger component of Libor-OIS spreads (Schwarz 2010).

Consequently, while the Libor-OIS rate does in fact comprise risk premia for both (interbank) credit risk and liquidity risk, in our application it nevertheless serves as a reasonable proxy for the _availability_ of liquidity, as adjudged by the ability of a bank to secure short-term liquidity from the wholesale market. Another way to interpret this choice is that, when thinking about the liquidity channel, we are concerned not primarily with market liquidity—which is certainly well measured by more traditional spreads, such as those between Libor and certificates of deposit (CD), or that between bid and ask prices within a given securities market—but with funding liquidity for banks, which is well referenced by the Libor-OIS spread.

To measure solvency, our benchmark specification uses a synthetic global bank CDS, which is a foreign claims-weighted average of the 5-year (the most liquid term) banking sector CDS indexes for U.S. and European banks, which are in turn averages of the mid-spread CDS rate for each constituent bank in the respective index.<sup>10</sup> Since contingent payment on a CDS is typically triggered by credit events such as, _inter alia_ , bankruptcy and restructuring, CDS spreads for the banking sector serve as important indicators of market _expectations_ of bank solvency. While the accuracy of such spreads in predicting the actual strength of banks’ balance sheets has been certainly called into question by the financial crisis, they nevertheless remain valuable forwardlooking signals of potential solvency issues (as opposed to accounting-based indicators, which are typically lagging).

For the uncertainty channel, we construct an index of asset price volatility by doing principal component analysis of the VIX (an index of the volatility of the S&P 500) and the GARCH(1,1) conditional variance of first differences in prices in 7 other asset markets, and averaging the first two components (since those two have eigenvalues greater than 1), weighted by their proportions of the cumulative variance of the components. The conditional variance of a return on an asset captures uncertainty of its future path, given past observations, and is thus an appropriate measure for testing the effect of volatility on forward looking lending behavior. The assets included in the index are debt (the TED spread), equity (the VIX), foreign exchange (the exchange rate of the dollar to the euro, Japanese yen, and pound sterling), and commodities (agricultural, energy, and industrial metals prices) (the complete list is reproduced in the data annex).

The working dataset for the benchmark is quarterly, beginning in 2004Q1 and ending 2011Q1, the last quarter where the European sovereign debt crisis remained largely contained

> 10Since banking sector CDS were only widely traded beginning in 2004, using this measure limits the sample coverage to begin in 2004Q1.

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