Measures of increasing financial intensity 300% 300% 300% 300% - PowerPoint PPT Presentation

T OO M UCH D EBT , F INANCIAL S YSTEM S TABILITY AND W IDER E CONOMIC I MPACTS 16 th Annual Chicago Federal Reserve Bank International Banking Conference: Shadow Banking Within and Across National Borders 7 November 2013 Adair Turner Senior Fellow www.ineteconomics.org | www.facebook.com/ineteconomics 300 Park Avenue South - 5 th Floor New York, NY 10010

Measures of increasing financial intensity 300% 300% 300% 300% Global issuance of asset-backed US debt as a % of GDP by borrower securities type 250% 250% 250% 250% 200% 200% 200% 200% 150% 150% 150% 150% 100% 100% 100% 100% 50% 50% 50% 50% 10% 10% 10% 10% 1965 1965 1971 1971 1971 1971 1977 1977 1977 1977 1983 1983 1983 1983 1990 1990 1990 1990 1996 1996 1996 1996 1929 1929 1929 1929 1935 1935 1935 1935 1941 1941 1941 1941 1947 1947 1947 1947 1953 1953 1953 1953 1959 1959 1959 1959 2002 2002 2002 2002 2007 2007 2007 2007 1,100 450 FX Trading values & world GDP Growth of interest rate derivatives 1,000 400 1977-2007 900 350 values, 1987-2009 800 300 700 250 $Tr $Trn 600 200 $bn 500 150 400 100 300 50 200 0 100 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 0 1977 1982 1987 1992 1997 2002 2007 OTC interest rate contracts, notional amount outstanding Global nominal GDP, $bn Global FX turnover, annual, $bn Global exports, $bn 1

Household deposits and loans: 1964 – 2009 100% 90% Securitisations and loan transfers Loans 80% Deposits 70% 60% % of GDP 50% 40% 30% 20% 10% 0% 1964 1967 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 Source: Bank of England, Tables A4.3, A4.1 2

Measures of increasing financial intensity US debt as a % of GDP by borrower type 300% 250% 200% 150% 100% 50% 10% 1929 1935 1941 1947 1953 1959 1965 1971 1977 1983 1990 1996 2002 2007 3

US financial sector assets Banks MMMFs GSE Agency and GSE- Mortgage Pools Issuers of ABS Finance Companies Security Broker-Dealer Funding Corporation 300% 250% 200% 150% 100% 50% 0% 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 4

NASDAQ index 1990 – 2003 6,000 5,000 4,000 3,000 2,000 1,000 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Source : Datastream 5

Categories of credit Loans to businesses / … to finance real investment projects “entrepreneurs” Loans to businesses / speculators / investors … to finance purchase of existing assets Mortgage loans to … to finance residential houses households Loans to “impatient” / temporarily cash limited / … to bring forward consumption poorer households 6

Categories of debt: UK, 2009 £bn Other corporate Primarily productive investment 232 Some productive investment and some 243 leveraged asset play Commercial real estate Residential mortgage Mainly purchase of existing assets (including securitizations 1235 and loan transfers) Pure life-cycle consumption smoothing Unsecured personal 227 7

Credit and asset price cycles Increased credit extended Increased Increased lender Increased borrower supply of credit asset prices demand for credit Expectation of future asset price increases Favourable assessments of credit risk Low credit losses: high bank profits • Confidence reinforced • Increased capital base 8

Lending to UK households Percentage changes on a year earlier Percentage changes on a year earlier 20 Unsecured Unsecured 15 Secured Secured Households Households 10 5 0 -5 2000 2002 2004 2006 2008 2010 2012 1994 1996 1998 Source: Bank of England “Trends in Lending” 9

Sectoral financial surpluses/deficits as % of GDP: Japan 1990 – 2012 10 5 0 % -5 -10 -15 PNFCs Government Source: IMF, Bank of Japan Flow of Funds Accounts 10

Japanese government and corporate debt: 1990 – 2010 250 200 150 % GDP 100 50 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 20010 0 Bank lending to non-financial corporates General Government debt Source : BoJ Flow of Funds Accounts, IMF WEO database (April 2011), FSA calculations 11

Shifting leverage: private and public debt-to-GDP US UK 120 140 100 120 80 100 % GDP 80 % GDP 60 60 40 40 20 20 0 0 Q1 2002 Q1 2003 Q1 2004 Q1 2005 Q1 2006 Q1 2007 Q1 2008 Q1 2009 Q1 2010 Q1 2011 Q1 2002 Q1 2003 Q1 2004 Q1 2005 Q1 2006 Q1 2007 Q1 2008 Q1 2009 Q1 2010 Q1 2011 Household Public PNFCs Household Public PNFCs Source : ONS Note: PNFC = private, non-financial corporates; Public = central Source : BEA Note: PNFC = private, non-financial businesses; Public = and local government federal, state and local government Spain 160 140 120 100 % GDP 80 60 40 20 Source : ECB Note: PNFC = private, 0 Q1 2002 Q1 2003 Q1 2004 Q1 2005 Q1 2006 Q1 2007 Q1 2008 Q1 2009 Q1 2010 Q1 2011 non-financial corporates; Public = central and local government Household Public PNFCs 12

Private credit to GDP and growth Source : S. Cecchetti and E. Kharroubi, BIS Working Paper No. 381 "Reassessing the impact of finance and growth" 13

Credit and asset prices: with securitised credit and mark-to-market accounting Increased credit extended Increased asset prices – fewer defaults Increased short- term liquidity Increased trading Increased price of credit securities Decreased VAR Decreased margin calls Mark-to-market accounting and VAR based risk management • Bank profit and capital • Required bank capital • Bonuses and animal spirits 14

Irrational exuberance in equity and debt markets Financial firm CDS and share prices Source : Moody’s KMV, FSA Calculations 15

Private and public leverage cycles: US Public and Private debt as a % of NGDP 250 200 WWII ends Financial Repression Housing bursts 150 100 50 0 2005 1995 1975 1985 1965 1945 1955 1935 1925 1915 Source: McCulley and Pozsar 16

China: total social finance to GDP 220 200 180 % of GDP 160 140 120 100 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 17

Non-financial private sector* credit outstanding, % GDP Brazil China India Hungary Indonesia Korea Mexico 2002 Russia 2007 South Africa 2012 Turkey 0 50 100 150 200 Source: BIS, Citi Research *Households + corporates 18

Leaning against credit cycles: monetary or macro-prudential levers? Monetary policy – Macro-Prudential interest raises levers • Gets into all the cracks • Can address specific Pros credit categories • Elasticity of response • Will stimulate Cons variable by category of innovation to avoid credit 19