THE TWENTIETH DUBROVNIK ECONOMIC CONFERENCE Organized by the Croatian National Bank Pierre L. Siklos Macroeconomic Implications of Financial Frictions in the Euro Zone: Lessons from Canada Hotel "Grand Villa Argentina" Dubrovnik June 11-13, 2014 Draft version Please do not quote
MACROECONOMIC IMPLICATIONS OF FINANCIAL FRICTIONS IN THE EURO ZONE: LESSONS FROM CANADA Pierre L. Siklos WLU and Viessmann European Research Centre JUNE 2014 Prepared for the 20 th Dubrovnik Economic Conference, JUNE 2014
The Role of Credit Credit availability is an essential part of MP effectiveness Known for a long time (e.g., Roosa1951) but ignored, forgotten, or under-appreciated Until 2007 (At least) Two macroeconomics channels are believed to exist price channel (i.e., interest rate) non-price or credit rationing channel (e.g., stemming from asymmetric information problems)
Current Research: Motivation & Background Current economic environment highlights the links between the real and financial sectors Of special interest: the role of credit Credit supply has long been known to have a price and a non-price element Price: interest rate Non-price: credit standards Could the non-price element be macroeconomically important?
The Questions Asked Do changing credit conditions influence real economic outcomes? Credit constraints can put a a break on the recovery in stressed countries, which adds to disinflationary pressures (Draghi, MAY 26, 2014) An under-appreciated source? Surveys of lending standards Do (monetary) policy rate shocks influence loan standards? How does the picture change when real time data are used? Comparisons between Small and Large Open Econ could be indicative of spillover type effects
The Canadian Dimension: SOE Influenced by Large Neighbours Canada has had a good crisis.but Real & financial conditions conspired to spillover into the CAD economy, in spite of FLEX and IT There are (negative) spillovers from the EZ crisis in 2010 Imagining the worst? A (permanent) deterioration of financial on the scale of Greece would lead to an 8% drop in CAD real GDP over 10 quarters
Related Literature From Roosa(1951) to Fuerst(1994) Credit availability influences the effectiveness of MP Blanchard and Fischer (1989) Credit rationing exists, so interest rates are not market clearing Stiglitz and Weiss (1981) Interest rate changes create adverse selection (withdrawal of risk averse borrowers) and moral hazard problems (incentives to engage in risky behavior): imperfect information in credit markets means they are not market clearing Schreft and Owens (1991) Lending standards can change before cost of funds does. Therefore, non-price lending standards represent an important link between MP and the financial sector Measured via surveys
Does the Type of Financial System Matter? Put simply, YES Proposed model works best where bank credit dominates (e.g., Canada, EZ). Focus is on business loans But SLOS type data are being extended to other sources of lending (e.g., Housing, Consumer credit) When there are other sources (e.g., stock market) there is a missing variable (e.g., US) and then there is shadow banking Financial frictions are NOT unique
Non-Price Lending Standards and the Macro-economy Lown et.al. (2000) Lownand Morgan (2006) Swiston(2008) Beaton et. Al. (2009) 1% tightening leads to 2.5% reduction in loans, > 2% fall in investment Tightening of standards leads to a fall in GDP ( 0.25-1%) Tightening of MP leads to a tightening of standards ( 8%) SLOS data anticipates macro-data that would also be reflected in a fall in loans
Testing Strategy: Outline Core Core + Extended VAR/ VECM Macro Credit Macro Demand factors Credit
Testing Strategy: Extension Core FAVAR Extended VAR/ VECM CANADA U.S. PCA CAD VAR Macro Credit Core + Credit
Testing Strategy: Equations y = A + A y + ε t 0 1 t 1 t y = A + A y + A z + ε t 0 1 t 1 2 t 1 t y = A + πy + ε ' t 0 t 1 t y = A + A y + A z + ε * ' ' * ' t 0 1 t 1 2 t 1 t y = Λ F + e US US t t t F ψ F t t 1 = ( L) + yt yt 1 ν t
Alternative Testing Strategy: A GVAR (To Come) Block 1 Block 2 Block 3 USA EZ EZ member FAVAR No EXT FAVAR Individual EZ FAVAR EXT factors
Data & Stylized Facts SLOS U.S. (since 1970s) & Canada (since late 1990s) ~ balance of opinion Over the past three months, how have your bank s credit standards for approving loan applications for C&I loans or credit likes excluding those to finance mergers and acquisitions changed? 1) Tightened considerably 2) tightened somewhat 3) remained basically unchanged 4) eased somewhat 5) eased considerably "How have your institution s general standards (i.e. your appetite for risk) and terms for approving credit changed in the past three months? Canada has price versus non-price distinction but differences not informative
Severe recession + means net tightenin ng/ - means net loosening Senior Officer Loan Survey : U.S. 100 80 60 40 20 0-20 Tech bubble United States Sub-prime and its aftermath -40 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Large & Medium enterprises Prime loans Small enterprises Credit card loans
Senior Officer Loan Survey and Commercial Loans, 1999-2011: Canada 100 80 Generally Inversely correlated Coincident? Granger causal? 2.5 2.0 SLOS in ndex 60 40 20 0 1.5 1.0 0.5 0.0 Annual pr recent change -20-0.5-40 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010-1.0 Balance of Overall credit standards Growth in business credit
Data & Stylized Facts SLOS U.S. (since 1970s) & Canada (since late 1990s) ~ balance of opinion Over the past three months, how have your bank s credit standards for approving loan applications for C&I loans or credit likes excluding those to finance mergers and acquisitions changed? 1) Tightened considerably 2) tightened somewhat 3) remained basically unchanged 4) eased somewhat 5) eased considerably "How have your institution s general standards (i.e. your appetite for risk) and terms for approving credit changed in the past three months? Canada has price versus non-price distinction but differences not informative
Price and Non-Price Survey Indicators: SLOS for Canada 100 ing / - means net looseining + means net tighteni 80 60 40 20 0-20 -40-60 2000 2002 2004 2006 2008 2010 2012 Pricing less Non-price Non-price Pricing Something new? Rise of macroprudential?
BLS Housing credit -Eurozone I 80 + net increase / - net decrease 40 0-40 -80-120 03 04 05 06 07 08 09 10 11 12 13 14 AT - demand - fw CY - demand - fw DE - demand - fw ES - demand - fw FR - demand - fw IR - demand - fw IT - demand - fw PT - demand - fw
BLS Consumer credit -eurozoneii 120 + net tightening / - net loosening 80 40 0-40 Italy -80 2005 2008 2011 2014 AT - supply - fw CY - supply fw DE - supply - fw ES - supply - fw FR- supply - fw IR - supply - fw IT - supply - fw PT - supply - fw
Other Series Real GDP, GDP Deflator, Commodity prices Defines basic macro model Add: Loans, SLOS Defines core or benchmark model Add: expected real GDP growth, term spread, FCI* Defines extended model * acts as a quasi Fsince it measures risk, liquidity, and leverage in money markets and equity markets as well as in the traditional and shadow banking systems
An Important Addition: real-time data Vintages: U.S. Real GDP Significance Vintages: U.S. Potential Output 2000 December Just before P 2000 July 2002 March Just after T 2002 February 2007 September Just before P PRE-CRISIS 2007 August 2009 September Just after T FIN CRISIS 2009 August Vintages: CAN real GDP Significance From Bank of Canada 2002 March See US 2007 Q3 See US 2007 Q4 Peak CAD bus cycle 2009 Q3 BoC interest rate comm. Ongoing work involves using EZ real-time data see below
An Important Addition: real-time data U.S. Output Gap (rleative to CBO po otential output estimates) 6 4 2 0-2 -4-6 -8 1998 2000 2002 2004 2006 2008 2010 December 2000 March 2002 September 2007 September 2009
More real time data Can be disaggregated By EZ economy 4 3 2 Euro Zone Perc cent 1 0-1 -2-3 I II III IV I II III IV I II III IV I II III IV 2007 2008 2009 2010 May 2014 December 2010 December 2011
VAR/VECM Issues I Lag length? AIC, HQ, SC...but parsimony wherever results are robust Series transformations? All in log levels EXCEPT: SLOS, Spread, forecasted growth rate Real GDP, GDP Deflator, loans ~ I(1) SLOS, Comm. Prices, Spread, Policy rate, FCI ~ I(0) S.E. via MC
VAR/VECM Issues II What CI? {policy rate Loans}, {policy rate-slos}, {real GDP- Loans} Does the ordering matter? [MACRO, CREDIT]: Core [MACRO, DEMAND IDENTIFIERS, CREDIT] Conventional IRFs & VDs + GIRFs
Macroeconomic Implications of Frictions in the Eurozone: Lessons from Canada SELECTED EMPIRICAL RESULTS
Key Economic Aggregates: Canada, the United States and the Eurozone Loan Officer Surveys 1999-2012 Economic growth 1999-2012 100 80 Germany > Germany > France Italy > Austria < Italy 6% 4% 60 Loan survey 40 20 0 real GDP growth 2% 0% -2% -20-40 -4% -60 2000 2002 2004 2006 2008 2010 2012-6% 2000 2002 2004 2006 2008 2010 2012 USA Canada euro zone USA Canada euro zone Real Credit Growth 1999-2012 Inflation rates 1999-2012 30% 6% 20% 5% 4% Real credit growth 10% 0% -10% CPI inflation 3% 2% 1% 0% -20% -1% -30% 2000 2002 2004 2006 2008 2010 2012-2% 2000 2002 2004 2006 2008 2010 2012 USA Canada euro zone USA Canada euro zone
Senior Loan Officer Surveys and GDP Growth Forecasts:the Eurozone Euro Zone one year ahead real GDP growth forecast 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% -0.5% < Germany > < France > France Spain > Austria Italy> Germany < > < Italy 40 30 20 10 0-10 -20-30 -40 Senior Off ficer Loan Survey -1.0% -50 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 BLS - supply BLS - demand Forecast
Correlations: Loan Surveys, Credit and GDP Growth Forecasts, Canada, the United States and the Eurozone Canada United States Eurozone SLOS, GDP growth forecast 0.31 (0.02) 0.54 (.00) 0.60 (.00) SLOS, real credit 0.31 (.02) 0.54 (.00) 0.60 (.00)
Real and Financial Factors: the Eurozone 1.6 1.2 Germany trough > Euro zone Germany < > 0.8 0.4 0.0 Scores -0.4-0.8-1.2-1.6-2.0-2.4 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 real factor financial factor
Impulse Responses by Canada to US and Eurozone Shocks Response of Canada's real GDP to US real and financial factors.0020.0015 Response to a 1% shock.0010.0005.0000 -.0005 -.0010 -.0015 Relative size of shocks quite different.0004.0003.0002 1 2 3 4 5 6 7 8 9 10 real factor financial factor Response of Canada's real GDP to euro zone real and financial factors Patterns broadly Comparable BUT cumulative US Impact larger Response to a 1% shock.0001.0000 -.0001 -.0002 -.0003 -.0004 -.0005 1 2 3 4 5 6 7 8 9 10 real factor financial factor
CONTAGION TESTS GFC has a BIG impact Contagion test Sample 1 Sample 2 Sample 3 USA real to Canada real? NO YES NO Euro zone real to Canada real? NO YES NO USA financial to Canada financial? NO NO NO Euro zone financial to Canada financial? NO YES NO USA real & financial to Canada real? NO YES NO Euro zone real & financial to Canada real? NO YES NO #1: 2008Q3-2012Q2; #2: 2008Q1-2012Q2; #3: 2007Q1-2012Q2.
Factor Analysis: Eurozone Not necessarily a N-S divide A BC factor? EZ MP factor? F1 F2 Communality Austria 0.54-0.20 0.33 Germany 0.02 0.50 0.25 Proportion Spain 0.33 0.78 0.72 0.73 France 0.41 0.56 0.47 Italy 0.96 0.25 0.98 0.27 Netherlands 0.54 0.37 0.43 Portugal 0.65 0.24 0.48 Demand for loans: HOUSING F1 F2 Austria 0.48 0.27 Germany -0.26 0.39 Spain 0.63 0.09 France 0.71-0.10 Italy 0.30 0.27 Netherlands 0.03 1.00 Portugal 0.51 0.42 Domestic banking environment? Not entirely clear yet how best to interpret these factors Communality 0.30 0.22 0.41 0.52 0.16 1.00 0.44 Proportion 0.50 0.50 Supply of credit: HOUSING
Conclusions Incorporating credit conditions/frictions in macro models has a definite impact on inferences There may, of course, be other ways of capturing financial frictions but more CB directly take account of this kind of data Changing credit conditions impact the macro-economy in ways insufficiently captured by CB policy rates In the EZ Demand vs Supply mis-matches may be far more important than for CAN or the US Unclear so far how large or persistent spillover effects inside the EZ are Ongoing research will, hopefully, provide some answers