Global Evidence on Capital Buffers and Net Stable Funding Ratios - PowerPoint PPT Presentation

Global Evidence on Capital Buffers and Net Stable Funding Ratios Oscar Carvallo Valencia Alberto Ortiz Bolaños CEMLA CEMLA and EGADE XI Seminar on Risk, Financial Stability and Banking Sao Paulo August 10-12, 2016 The views expressed in this presentation are those of the authors, and not necessarily those of CEMLA. We appreciate the contributions to this work of CEMLA’s economists Jonathan Barboza and Ignacio Garron.

Global evidence on capital buffers and net stable funding ratios Motivation : banking crisis are costly. Basel III, through capital and • liquidity regulations, tries to enhance the supervision and risk management of the banking sector. However, these regulations were calibrated mostly against BIS membership information. There is need to understand these variables at a global scale and undercover potential heterogeneities across countries and income groups. • Objective : (i) understand the determinants of banks’ choice of capital buffers, and (ii) analyze the role of banks’ net stable funding ratio (NSFR) in explaining future financial instability. • Methodology : aided by theoretical frameworks, we designed econometric specifications to test different hypotheses exploiting the information of almost 11,000 banks across 143 countries for the 2001 – 2015 period. • Contribution : give a global analysis of the regulated variables by examining a large sample of banks and countries while we factor in multiple dimensions, incorporate methodological improvements and conduct robustness checks.

Where to find the extended versions: Bank capital buffers around the world: cyclical patters and the • effect of market power . Oscar A. Carvallo and Alberto Ortiz. • Net Stable Funding Ratio and Financial Stability: Global Evidence. Oscar A. Carvallo, Alberto Ortiz, Jonathan Barboza and Ignacio Garrón. • Both available upon request with Oscar Carvallo (ocarvallo@cemla.org) or me (ortiz@cemla.org).

Costs of systemic banking crises in Latin America and the Caribbean Output loss (% of GDP) during systemic banking crises * 120 100 80 60 40 20 0 Argentina 1980 - 1982 Argentina 2001 - 2003 Brazil 1990 - 1994 Bolivia 1986 Chile 1976 Chile 1981 - 1985 Colombia 1982 Colombia 1998 - 2000 Ecuador 1982 - 1986 Ecuador 1998 - 2000 Haiti 1994 - 1998 Jamaica 1996 - 1998 Mexico 1981 - 1985 Mexico 1994 - 1996 Nicaragua 1990 - 1993 Panama 1988 - 1989 Paraguay 1995 Peru 1983 Uruguay 1981 - 1985 Uruguay 2002 - 2005 United Kingdom 2007 - United States 2007 - * Cumulative sum of the differences between actual and trend real GDP over the period ( T, T+3 ), expressed as a percentage of trend real GDP, with T the starting year of the crisis. Source: Laeven and Valencia (2013). Systemic banking crisis database. IMF Economic Review 61: 225-270

Banking crisis outcomes, 1970 - 2011 Peak Liquidity Output Increase Fiscal Fiscal Duration Peak Monetary Country liquidity support loss in debt expansion costs costs NPLs Medians % of financial % of deposits and % of total % of GDP In years system foreign liabilities loans assets All 23.0 12.1 1.7 6.8 12.7 2.0 20.1 9.6 25.0 Advanced 32.9 21.4 8.3 3.8 2.1 3.0 11.5 5.7 4.0 Emerging 26.0 9.1 1.3 10.0 21.4 2.0 22.3 11.1 30.0 Source: Laeven and Valencia (2013). Systemic banking crisis database. IMF Economic Review 61: 225-270

Banking regulatory framework • "Basel III" is a comprehensive set of reform measures, developed by the Basel Committee on Banking Supervision, to strengthen the regulation, supervision and risk management of the banking sector. These measures aim to: – improve the banking sector's ability to absorb shocks arising from financial and economic stress, whatever the source – improve risk management and governance – strengthen banks' transparency and disclosures. • The reforms target: – bank-level, or microprudential, regulation, which will help raise the resilience of individual banking institutions to periods of stress. – macroprudential, system wide risks that can build up across the banking sector as well as the procyclical amplification of these risks over time. • These two approaches to supervision are complementary as greater resilience at the individual bank level reduces the risk of system wide shocks. • It builds on the International Convergence of Capital Measurement and Capital Standards document (Basel II).

Basel III phase-in arrangements

Bank capital buffers • Bank capital buffers, which are holdings of banks’ capital-to-asset ratio in excess of the regulatory minimum, are persistent both across countries and over time. Developed Developing 4,934 banks 2,184 banks 20 80 20 80 37 countries 106 countries 18 70 18 70 average:8.6% average:10.4% 16 60 16 60 14 50 14 50 12 40 12 40 10 30 10 30 8 20 8 20 6 10 6 10 4 0 4 0 2 -10 2 -10 0 -20 0 -20 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Q75/Q25 range Average Capital Buffer Q75/Q25 range Average Capital Buffer Capital Buffer (right axis) Capital Buffer (right axis) • What are the determinants of the observed levels of banks’ capital buffers? Following Jokipii and Milne (2008) we define the capital buffer as the bank capital ratio less the Minimum Capital Ratio (MCR). The bank capital ratio is approximated by the Total Capital Ratio (TCR), which measures the actual regulatory capital ratio in each jurisdiction. TCR data comes from Bankscope, MCR data from WB database “The Regulation of Banks around the World”, surveys I, II, III and IV. Barth et al. (2001, 2004, 2006, 2012).

Partial adjustment model • The presence of highly persistent capital buffers could indicate that banks approach their optimum target with a partial adjustment. 100 Capital Buffer 50 0 50 100 0 Capital Buffer(t-1) Developed Developing Linear regression Fitted values ∗ 𝐶𝐶𝐶 𝑗 , 𝑢 = 𝛽 𝐶𝐶𝐶 + 1 − 𝛽 𝐶𝐶𝐶 𝑗 , 𝑢−1 + 𝜃 𝑗 ⏟ 𝑗 , 𝑢 bank−specific determinants not observable • The empirical model will be specified as: 𝑗 , 𝑢−1 + 𝜀 𝑗 𝐶𝐶𝐶 𝑗 , 𝑢 = 𝛽 0 + 𝛽 1 𝐶𝐶𝐶 𝑌 𝑗 , 𝑢 + 𝜃 𝑗 + 𝑣 𝑗 , 𝑢 � � vector of variables i . i . d error term ∗ that determine 𝐶𝐶𝐶 𝑗 , 𝑢 𝑠𝑠𝑠 𝑀 𝐸 ∗ = 𝔽 𝑢 𝛾𝛭 𝑢+1 𝑆 𝑢+1 − 𝔽 𝑢 𝛾𝛭 𝑢+1 𝑆 𝑢 𝐸 − 𝐹 𝐶𝐶𝐶 𝑢 𝑀 𝑢 𝛭 𝑢 − 𝔽 𝑢 𝛾𝛭 𝑢+1 − 𝔽 𝑢 𝛾𝛭 𝑢+1 𝑆 𝑢

𝑗 , 𝑢 = 𝛽 0 + 𝛽 1 𝐶𝐶𝐶 𝑗 , 𝑢−1 + 𝜀 𝑗 𝐶𝐶𝐶 𝑌 𝑗 , 𝑢 + 𝜃 𝑗 + 𝑣 𝑗 , 𝑢 ⏟ � � bank−specific vector of variables that i . i . d error term ∗ determine 𝐶𝐶𝐶 determinants 𝑗 , 𝑢 Total Variable Description Hypotheses Mean Sd. Obs. Following Jokipii and Milne (2008) we define the capital buffer as the bank capital ratio less the Minimum Capital Ratio (MCR). The bank capital ratio is 9.14 10.97 40,181 Buffer (BUF) approximated by the Total Capital Ratio (TCR), which measures the actual regulatory capital ratio in each jurisdiction. Bank variables Moral hazard motives could imply a Bank size (Size) Logarithm of total bank’s asset negative relation with capital 14.20 2.08 40,053 buffers, charter value a positive one. Return Over According to the model, profitability Net income/ average total assets is positively associated with the level 0.75 2.20 40,103 Average Assets of capital buffers. (ROAA) Return Over According to the model, profitability Average Equity Net income / average total equity is positively associated with the level 6.90 21.10 40,099 (ROAE) of capital buffers. Higher competition could lead to lower (EME) levels of buffers due to Boone Indicator lower profitability and charter value, Measure of competition linking marginal costs to market share -0.05 0.12 35,649 (BOONE) but if pool of borrowers is affected by competition, then could lead to higher (OECD) levels to cover losses. The higher the ratio of non- Loan Loss Reserve performing loans as a percentage of Gross Loans Non-performing loans / total bank assets 3.29 5.13 31,731 total bank assets, the larger the (LLRGL) capital buffers, a positive relation. According to the model, the cost of Cost of Funding Interest Expenses/ total funding capital is positively associated with 1.20 66.21 19,496 Source: Bankscope. (CF) the level of capital buffers. Sources: Bankscope for bank variables and World Bank database “The Regulation of Banks around the World”, surveys I, II, III and IV. Barth et al. (2001, 2004, 2006, 2012).