Libor due to concerns about the credit worthiness of banks, so the Libor-CD spread is viewed by some as a measure of pure liquidity scarcity. We view the premise that purchasers of CDs are not liquidity constrained during a crisis as questionable, but Libor-CD is nonetheless a clear candidate for a robustness check of our main liquidity variable. When Libor-CD is included in lieu of Libor-OIS (column _R1_ ), the coefficient is close to zero and statistically insignificant. When both Libor-CD and Libor-OIS are included (column _R2_ ), Libor-OIS retains its sign, magnitude, and significance.

Our preferred measure of balance sheet problems is an index of CDS spreads, which has the advantages of being forward-looking, and of being based on rates faced by a wide sample of banks in both the U.S. and Europe. However, more direct measures of solvency issues can be found in bank financial data. As a robustness check, loss allowances as a fraction of outstanding loans, as reported by U.S. banks to the FDIC, are included in place of the CDS index (column _R3_ ). The coefficient is insignificant, as is that on CDS in the benchmark estimates that do not include lagged channel variables. Although not reported, similar results are found for other variables reported to the FDIC: measures of noncurrent loans and net charge-offs as fractions of outstanding loans, and the fraction of lenders which are unprofitable. These results are broadly supportive of the idea that balance sheet problems have little, if any, contemporaneous impact on cross-border bank lending.

In the benchmark estimates, we rely on a GARCH (1,1) conditional volatility index as a measure of uncertainty, for reasons given above. Here, we consider the robustness of this measure by instead using an unconditional measure of volatility: an index of the rolling standard deviations of prices in the same 7 asset markets, along with VIX, used to compute the conditional volatility measure.<sup>17</sup> Results with this alternative measure of volatility are reported in column ( _R4_ ), and mirror the benchmark results, with a significant negative coeeficient on the alternative volatility measure.

As discussed in Section 2, the uncertainty channel variable is intended to measure shocks to uncertainty, as distinct from shocks to risk aversion. However, the two concepts are interrelated, as the effect of uncertainty on behavior depends on the degree of risk aversion; and the degree of perceived risk aversion, as well as the effect of a given degree of risk aversion on behavior, may depend on the level of uncertainty. Furthermore, there is a question of whether risk aversion itself changed during the crisis, or whether behavior to reduce risk exposure during the crisis was predominantly a reaction to heightened risk and uncertainty for a given degree of risk aversion. Results with a variable measuring U.S. loan officers’ risk aversion are reported in columns ( _R5_ ) and ( _R6_ ).<sup>18</sup> While the coefficient is insignificant when risk aversion is included in place of

> 17The results are robust to the method of aggregation. While we report here the weighted average of the first two principal components, using a simple average of the 8 series yields qualitatively similar results.

> 18The risk aversion variable is constructed from a question on the Fed’s Senior Loan Officer Survey that asks loan officers who reported that they tightened or eased credit standards or terms on C&I loans what factors were relevant to that decision, with reduced or increased tolerance for risk given as an option for the reason for tightening or easing, respectively. Banks’ responses are averaged, with each response that a change in risk tolerance was “very important” given twice the weight of a response that it was “important.”

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