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We document a sizable effect of oil price fluctuations on US banking variables by estimating an SVAR with sign restrictions as in Baumeister and Hamilton (2019). We find that oil market shocks that lead to a contraction in world economic activity unambiguously lower the amount of bank credit to the US economy, tend to decrease US banks' net worth, and tend to increase the US credit spread. The effects can be strong and long-lasting, or more modest and short-lived, depending on the source of the oil price fluctuations. The effects are stronger for smaller and lower leveraged banks. [ABSTRACT FROM AUTHOR]

We study bank responses to the Paycheck Protection Program (PPP) and its effects on lender balance sheets and profitability. To address the endogene- ity between bank decisions and balance sheet effects, we develop a Bayesian joint model that examines the decision to participate, the intensity of partici- pation, and ultimate balance sheet outcomes. Overall, lenders were driven by risk-aversion and funding capacity rather than profitability in their decision to participate and the intensity of their participation. Indeed, with greater participation intensity, banks experienced sizable growth in their loan port- folios but a decline in their interest margins. In counterfactual exercises, we show that the PPP offset a large potential contraction in business lending, and that bank margins would have fallen even more precipitously if lenders had not participated in the program. Although the PPP was intended as a credit support program for small firms, the program indirectly supported the margins of banks that channeled these loans. [ABSTRACT FROM AUTHOR]

We introduce a new software package for determining linkages between datasets without common identifiers. We apply these methods to three datasets commonly used in academic research on syndicated lending: Refinitiv LPC DealScan, the Shared National Credit Database, and S&P Global Market Intelligence Compustat. We benchmark the results of our match using results from the literature and previously matched files that are publicly available. We find that the company level matching is enhanced by careful cleaning of the data and considering hierarchical relationships. For loan level matching, a tailored approach based on a good understanding of the data can be better in certain dimensions than a more pure machine learning approach. The R package for the company level match can be found on Github at https://github.com/seunglee98/fedmatch. [ABSTRACT FROM AUTHOR]

We introduce a new software package for determining linkages between datasets without common identifiers. We apply these methods to three datasets commonly used in academic research on syndicated lending: Refinitiv LPC DealScan, the Shared National Credit Database, and S&P Global Market Intelligence Compustat. We benchmark the results of our match using results from the literature and previously matched files that are publicly available. We find that the company level matching is enhanced by careful cleaning of the data and considering hierarchical relationships. For loan level matching, a tailored approach based on a good understanding of the data can be better in certain dimensions than a more pure machine learning approach. [ABSTRACT FROM AUTHOR]

I develop a model where the sovereign debt capacity depends on the capitalization of domestic banks. Low-capital banks optimally tilt their government bond portfolio toward domestic securities, link-ing their destiny to that of the sovereign. If the sovereign risk is sufficiently high, low-capital banks reduce private lending to fur-ther increase their holdings of domestic government bonds, lowering sovereign yields and supporting the home sovereign debt capacity. The model rationalizes, in the context of the eurozone periphery, the increase in domestic government bond holdings, the reduction of bank credit supply, and the prolonged fragility of the financial sector. [ABSTRACT FROM AUTHOR]

I develop a model where the sovereign debt capacity depends on the capitalization of domestic banks. Low-capital banks optimally tilt their government bond portfolio toward domestic securities, linking their destiny to that of the sovereign. If the sovereign risk is sufficiently high, low-capital banks reduce private lending to further increase their holdings of domestic government bonds, lowering sovereign yields and supporting the home sovereign debt capacity. The model rationalizes, in the context of the eurozone periphery, the increase in domestic government bond holdings, the reduction of bank credit supply, and the prolonged fragility of the financial sector. [ABSTRACT FROM AUTHOR]