International Evidence on Bank Funding Profiles and Performance: Are Banks “Overbanked”? by Jose A. Lopez & Mark M. Spiegel Federal Reserve Bank of San Francisco Federal Reserve Bank of San Francisco IMF/DNB Conference on International Banking: Microfoundations and Macroeconomic Implications June 12-13, 2014, Amsterdam, The Netherlands Views expressed are our own and not those of the Federal Reserve
Bank Funding a Policy Concern April 15 speech by Federal Reserve Chair Janet Yellen: • “…. Basel Committee's first task was to strengthen bank capital requirements …. second task was to develop new liquidity standards for global banking firms… • (These steps) …. do not fully address the financial stability concerns associated with short-term wholesale funding. These standards tend to focus on … firms … in isolation, rather than on the financial system as a whole. • Federal Reserve staff are actively considering additional measures that could address these and other residual risks in the short- term wholesale funding markets.”
Some Countries are considered “Overbanked” • Literature finds some nations are “overbanked” [e.g. Eichengreen and Luengnaruemitchai (2006)] - banks account for abnormal share of intermediation - benefits of diversification of lending markets - Greenspan “spare tire” argument - role in Asian financial crisis • Overbanking said to hurt development of Argentina and others at turn of 20th century [Davis and Gallman (1978)]
Research on funding liquidity • Funding and lending strategies impact bank vulnerability • Brunnermeier et al. (2011) – Metrics such as “ CoVaR ” to measure contributions of banks to financial system vulnerability • Bai et al. (2013)
Optimal individual bank deposit funding share? • Extend “overbanking” idea to individual bank liabilities - Can banks “over - rely” on deposits? • Alternative may be longer-term funding through securities • Current regulatory stances favor deposits Considered stable funding sources However, stable sources may be difficult to increase Raising funds through deposits requires interest rate increases to both old and new • Banks may benefit from securities markets presence Difficult for “unseasoned” to raise funds in securities markets
Also potential systemic concerns • Hard to raise external funds during crisis – Local conditions important • Only so much liquidity in system – Easier to raise funds in stable system – Prudent funding and lending decisions at bank level depend on rest of system • We investigate spillovers in funding practices at national level
Plainview: “I drink your milkshake”
We investigate impact of funding conditions on ROA • Use Bankscope international bank-level data - Cross-section for 2007, also (2004-2012) - 16,000 banks in nearly 200 countries • Examine several funding liquidity measures - assets only - liabilities only - both as measured by bank net-stable-funding ratios (NSFRs), official BIS metric . • Also look at national funding environments - Same measures for all other banks in system
Data (1) • Bankscope data – Publicly available data on financial institutions from nearly 200 countries in 2007 • Look at wide set of firm types to characterize varied national financial systems – standard depository institutions, specialty finance firms, investment banks, and govt credit inst. – Focus on unconsolidated subsidiaries to identify liquidity funding profiles at national level
Data (2) • Truncated sample – Disproportionate share of base sample in Bankscope are US banks • Follow Claessens and Van Horen (2014) in limiting sample to 100 banks from countries with >4 banks – Reduces sample to <4,000 banks from 134 countries – 90% of assets in banking system
Results 1. Results suggest increased deposit funding lowers ROA - Less profitable with more standard funding sources - Profits also decrease with system reliance on deposits 2. In contrast, we obtain insignificant coefficient estimates on the share of cash in a bank asset portfolio - Also for share of cash in national banking system 3. Also obtain positive coefficient on NSFR of rest of banking system - Better off in a more stable system - Own NSFR enters insignificantly
Robustness checks • Truncated sample – Results are qualitatively similar • Domestic and foreign sub-samples – Most domestic variables significant with expected signs – Foreign banks do better in systems with low NSFRs • Samples from 2004-2012 – Negative deposit results robust over time – Others change over time
Liquidity funding measures • One side of the balance sheet – Liabilities only: dependence on retail deposits – Assets only: cash (& equivalents) on balance sheet – We examine these normalized by total assets. • Recently, measures incorporating both sides of balance sheet have been proposed – Liquidity mismatch index [Brunnermeier, et al (2011), Bai et al. (2013)]
Formal liquidity measures • Codified into banking regulation by the Basel Committee of Bank Supervisors (BCBS) • Liquidity coverage ratio (LCR) – Amount of one-month funding sources as well as high-quality liquid assets available • Net stable funding ratio (NSFR) – More useful for our analysis – One year measurement horizon – Covers larger set of assets and liabilities
Net Stable Funding Ratio (NSFR) • Ratio of funds owed relative to assets – Items weighted by expected availability • Example: interbank funding more likely to be lost during market disturbance than retail deposits – Retail deposits receive higher weighting in numerator of NSFR than interbank funding • Government securities more easily liquidated than commercial loans – Commercial loans therefore receive lower weight in denominator
Calculation of Net Stable Funding Ratio (NSFR) • NSFR for bank i in country j at time t is denoted as where P and Q represent liabilities and assets, and the weights are based on sensitivity to roll-over risk and market liquidity
Balance sheet data • For BCBS regulatory purposes, weight formulas are rich in detail, reflecting maturities and currency types - Bankscope data is contains much less detail - Use balance sheet and weights from Federico (2013)
National banking system liquidity • In addition to individual NSFRs, interested in liquidity profiles of national financial systems – National NSFR measure would obscure bank size and would lose country fixed effects • We therefore calculate NSFR for all other banks:
Summary statistics: liquidity measures • Retail deposits/TA (RETDEP) 52% avg. – Japan and developing Asia between 75% and 79% – US average ratio 61%, due to smaller US banks. – Euro core banks have a lower average of 35%. • Cash/TA (CASH) almost 2% avg. – Banks from Eastern Europe, developing Asia, and other non-OECD 5% - 7% avg. – Banks in Japan and euro core below 1% (US 2.1%) – Variation highlights how differences in accounting and regulatory standards lead to challenges in measuring liquidity using narrow categories
NSFR summary statistics • NSFR has average value of 0.88 – Recall NSFR < 1 suggests stable funding – More stable funding to illiquid assets • Developed countries had lower NSFR – US = 0.89; Euro-core = 0.76; Japan = 0.92 • Developing countries had higher values – Latin American banks averaged 1.07 – Other non-OECD country banks averaged 1.24
Model specification Examine effect of bank funding profiles have on bank performances: where Y ijt is ROA for firm i in country j in year t; L ijt is a vector of liquidity metrics; L -ijt is the corresponding vector of aggregate liquidity metrics for all the other firms in country j; X it is a vector of firm characteristics; - log total assets and leverage ratio Z jt is a vector of country-level characteristics - either fixed effects or Rose-Spiegel indicators
Full sample base specification results RETDEP -1.307*** -1.230** (0.477) (0.497) RETDEP_cn -5.553* -6.224** (3.165) (2.784) CASH 3.353 2.777 (2.281) (1.933) CASH_cn 11.548 8.725 (8.795) (6.315) NSFR 0.067 0.054 (0.160) (0.136) NSFR_cn 1.281* 1.722** (0.690) (0.700) LEV -0.030*** -0.031*** -0.030*** -0.030*** (0.005) (0.005) (0.006) (0.006) LNASSETS 0.023* 0.017 0.058** 0.055*** (0.013) (0.014) (0.023) (0.013) r2 0.193 0.188 0.171 0.169 N 15673 15673 15673 15673
Truncated sample base specification results RETDEP -0.849*** -0.730*** (0.161) (0.173) RETDEP_cn -4.546** -4.902*** (1.996) (1.444) CASH 0.680 0.503 (0.501) (0.504) CASH_cn 11.223*** 4.551* (2.933) (2.398) NSFR 0.202*** 0.160*** (0.043) (0.040) NSFR_cn 1.824* 1.888*** (0.912) (0.449) LEV -0.036*** -0.035*** -0.033*** -0.034*** (0.009) (0.010) (0.011) (0.011) LNASSETS 0.029 0.016 0.019 0.027 (0.031) (0.030) (0.020) (0.021) r2 0.232 0.226 0.219 0.222 N 3846 3846 3846 3846
Domestic and foreign sub-samples • Would think that domestic bank would differ in reliance of local financial system for funding – Claessens and van Horen sub-sample allows for separation of domestic and foreign firms – End up with samples of 653 global banks and 1,665 domestic banks – Results differ dramatically
Recommend
More recommend
