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«Research Division Federal Reserve Bank of St. Louis Working Paper Series Understanding the Accumulation of Bank and Thrift Reserves during the U.S. ...»

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We find that the cash-to-assets ratio for both groups increased over time (examining AT T 2 rows or, alternatively, comparing actual cash-to-assets ratios in the top two rows). Comparing the treatment group (that received TARP funding) with the control group between the pre-TARP period and one period following the treatment, we find that treated banks had approximately 1 percent lower cash-to-assets ratios than the control group (see AT T 2 in Table 12). We find this effect persists for at least four quarters beyond treatment. In the period of treatment, the average treatment effect (on the treated) is small and not significant. Our interpretation of this result is that the capital injections were initially left idle on the asset side of the balance sheet (when the payment was made), but in subsequent quarters, TARP-treated banks reduced their cash holdings (possibly by increasing their lending, though they may have alternatively purchased other assets, such as securities), effectively maintaining lower cash-to-assets ratios on average. This interpretation is consistent with the view that the capital injection provided precautionary liquidity for the beneficiaries. Alternatively, considering reasons for the larger increase in the control group’s cash-to-assets, these banks, on average, may have moved more loans into nonaccrual status, thereby reducing their asset position and raising their cash-to-assets ratio.

Although treated banks subsequently had lower ratios than untreated banks, there is a rising trend for cash-to-asset ratios during this period. Deposits were increasing by an average of 1 percent: 3.5 percent for CPP banks and 0.52 percent for non-CPP banks. Increasing deposits likely affected banks’ cash holdings, both as a matter of accounting (deposits are initially most likely held as cash and cash equivalents) and banks’ heightened sensitivity to penalty rates. In addition, the results noted in the previous section may reflect an environment with insufficient low-risk lending opportunities. The fact that banks receiving CPP funds in this environment accumulated less cash suggests that the CPP injection possibly resulted in more risk-taking in the form of new lending and less precautionary accumulation; see Black and Hazelwood (2013) for a formal analysis of this conjecture. Our results are suggestive regarding lending, but we cannot draw formal inference based on them. For example, lower cash ratios, ceteris paribus, are also consistent with larger securities holdings.

In conclusion, based on our matching procedure, we find evidence that banks (or BHCs) receiving TARP funds maintained approximately 1 percent lower cash-to-assets ratios (and thus excess reserves ratios) post-treatment than similarly matched banks for at least one period following their receipt of TARP funds.

6. Conclusion

This paper undertakes a systematic analysis of the massive accumulation of ER using bank-level data for more than 7,000 commercial banks and almost 1,000 savings institutions during the U.S. financial crisis.

To answer the question “Why would profit-maximizing banks hoard liquidity?”, we focus on institutions’ balance-sheet risk, concerns about payment shocks, and the opportunity cost of hoarding liquidity. As do the findings of Acharya and Merrouche (2013), our evidence points strongly to precautionary motives for reserves accumulation due to banks’ concerns about their balance-sheet risks and doubts about the availability of short-term liquidity. We do not find evidence that the generalized rise in macroeconomic uncertainty, as measured by standard markers, played a role in banks’ reserves accumulation strategies, suggesting that concerns about counterparty risk as the crisis developed were not a prime factor. Another potential explanation is that the frequency of our data may not capture high-frequency changes in counterparty risk or, alternatively, that such risks were heightened during our period of observation and therefore not separately identifiable.

We also examined whether CPP funding contributed to the massive reserves accumulation by combining PSM technique with a difference-in-differences approach. We found that bank holding companies that received CPP funds accumulated fewer cash and reserves. This evidence is consistent with the view that the capital injection provided precautionary liquidity for the beneficiaries.

Although our analysis provides information on the determinants of ER and cash accumulation, we do not provide any link between reserves accumulation (at the individual depository institution level) and lending behavior. The question we are most interested in is “How did reserve and cash accumulation during and shortly after the crisis affect lending?” With the guidance of recent theoretical contributions (Martin et al., 2013), empirically examining the effects of reserves and cash accumulation on lending in the aggregate, as well as across the distribution of banks by size, capitalization, institution type, and by receipt of TARP funds, is an important exercise that we leave for future research.

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Figure 1: Federal Reserve Bank Balance Sheet (2007-2010)

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.

.

.

–  –  –

Note: ERR is the excess-to-required reserves ratio. Source: FRASER and FRED II, Federal Reserve Bank of St. Louis.

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4 0.8 3 0.6 2 0.4 1 0.2

-1 -0.2 Note: ERR is the excess-to-required reserves ratio. Source: Bank of Japan.

Figure 5: Differential between Yield on 1-year Treasury Bonds and IOR and ERR in the United States Since the Great Financial Crisis Began

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15 1.5 5 0.5

-5 -0.5

-10 -1 Note: ERR is the excess-to-required reserves ratio. Source: FRED II, Federal Reserve Bank of St. Louis.

Figure 6: Cross-Sectional Distribution of ERR for Commercial Banks (2008:Q2–2010:Q2) Note: We truncate our histograms at a ratio of 70. Source: Authors’ calculations based on the Reports of Income and Condition.

Figure 7: Interest Rate Variables (2008:M7–2010:M12)

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