Comments on Assessing Policies to Revive Credit Markets

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Comments on Assessing Policies to Revive Credit Markets Chapter 2 of Global Financial Stability Report, IMF, October, 2013 Rafael Doménech Madrid, October 18, 2013

Main results Chapter 2 of the GFSR offers a timely and comprehensive empirical analysis of the factors that underlie the weakness in credit Three different approaches to identify the constraints to credit: Lending surveys Structural determinants of the supply and demand of bank lending to firms Firm-level regressions of changes in debt-to-asset ratio for manufacturing firms Results: Constraints in credit markets differ by country and evolve over time Importance of careful country-by-country assessments and Need for better data on new lending (production sectors, firms, etc.) Page 2

Main results Two main economic policy implications Policymakers should also recognize that there are limits to credit policies and not attempt to do too much Policymakers need to continually weigh the near-term benefits against the longer-run costs of policies aimed to boost credit This chapter finds very interesting results, makes original empirical contributions to the literature, and offers sound economic policy recommendations on a very relevant issue in the economic recovery of countries with high levels of credit to GDP ratios Page 3

Main comments The analysis focuses on the stock of credit and not on flows (new loans), due to the lack of data Alternative approaches to identify supply and demand factors: estimation of a DSGE model with a banking sector Policy implications Some additional comments Page 4

1. Flows vs the stock of credit Assume a very simple model in which: the economy was in steady state (real growth 2% yoy, credit stock/gdp=100%), a (positive) financial shock occurred (credit growth from 2% to 10%), and the economy returns to its steady state Also assume that: in steady state, new loans represent a fraction of GDP (10%) repayments represent a constant fraction of the credit stock (10%) Main result: for an extended period of time the stock of credit is falling (deleveraging) but the economy is in steady state Weak growth of the stock of credit is not the appropriate measure Page 5

1. Flows vs the stock of credit Simulation of new loans and repayments (% GDP) Source: BBVA Research Simulation of the stock of credit and GDP growth Source: BBVA Research Growth of credit stock 0.15 0.1 0.05 0-0.05-0.1-0.15-0.2-0.25-0.3-0.35-0.4 Credit stock (left) New loans (right) Repayments (right) 1 5 9 13 17 21 25 29 Quarters 33 37 41 45 49 53 57 61 65 69 0.35 0.3 0.25 0.2 0.15 0.1 0.05 New loans and repayments over GDP GDP growth 0.05 0.04 0.03 0.02 0.01 0-0.01-0.02 Credit stock (right) GDP (left) 20 quarters 1 5 9 13 17 21 25 29 Quarters 33 37 41 45 49 53 57 61 65 69 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0-0.02-0.04-0.06-0.08-0.1-0.12-0.14 Growth of credit stock Page 6

1. Flows vs the stock of credit Spain: new loans and repayments (sa, % GDP) Source: BBVA Research Spain: stock of credit and nominal GDP growth Source: BBVA Research New loans and repayments over GDP 1.40 1.30 1.20 1.10 1.00 0.90 0.80 0.70 0.60 0.50 0.40 New loans Repayments (right) mar-03 sep-03 mar-04 sep-04 mar-05 sep-05 mar-06 sep-06 mar-07 sep-07 mar-08 sep-08 mar-09 sep-09 mar-10 sep-10 mar-11 sep-11 mar-12 sep-12 mar-13 sep-13 mar-14 sep-14 Nominal GDP growth 0.12 0.10 0.08 0.06 0.04 0.02 0.00-0.02-0.04-0.06-0.08 Crédit stock (right) Nominal GDP (left) jun-03 dic-03 jun-04 dic-04 jun-05 dic-05 jun-06 dic-06 jun-07 dic-07 jun-08 dic-08 jun-09 dic-09 jun-10 dic-10 jun-11 dic-11 jun-12 dic-12 jun-13 dic-13 jun-14 dic-14 0.30 0.25 0.20 0.15 0.10 0.05 0.00-0.05-0.10-0.15-0.20 Growth of Credit stock New loans include refinancing operations The growth of the credit stock is affected by SAREB Page 7

2. DSGE model for EMU with a banking sector Alternative decompositions of supply and demand shocks can be obtained with other approaches, for example, with estimated DSGE models Loans to firms and households could have been affected by supply and demand shocks in different ways Results for EMU using an estimated DSGE model with a banking sector indicate that differences across sectors are relevant Page 8

2. DSGE model for EMU with a banking sector Production sector Labour market Capital goods Retail sector Households Patient households Impatient households Entrepreneurs Deposits Loans Loans Monetary shock Financial shocks Macroeconomic shocks External sector Banks Retail Wholesale Public sector Central Bank Extended version of Gerali, Neri, Sessa and Signoretti (2010), with public and external sector.

2. DSGE model for EMU with a banking sector Historical decomposition of EMU corporate loans growth (% y/y) Source: BBVA Research 10 8 6 4 2 0-2 -4-6 -8 1998Q1 1998Q3 1999Q1 1999Q3 2000Q1 2000Q3 2001Q1 2001Q3 2002Q1 2002Q3 2003Q1 2003Q3 2004Q1 2004Q3 2005Q1 2005Q3 2006Q1 2006Q3 2007Q1 2007Q3 2008Q1 2008Q3 2009Q1 2009Q3 2010Q1 2010Q3 2011Q1 2011Q3 2012Q1 2012Q3 2013Q1 2013Q3 (f) FISCAL MACRO MONETARY FINANCIAL Historical decomposition of EMU households loans growth (% y/y) Source: BBVA Research 10 8 6 4 2 0-2 -4-6 -8 1998Q1 1998Q3 1999Q1 1999Q3 2000Q1 2000Q3 2001Q1 2001Q3 2002Q1 2002Q3 2003Q1 2003Q3 2004Q1 2004Q3 2005Q1 2005Q3 2006Q1 2006Q3 2007Q1 2007Q3 2008Q1 2008Q3 2009Q1 2009Q3 2010Q1 2010Q3 2011Q1 2011Q3 2012Q1 2012Q3 2013Q1 2013Q3 (f) FISCAL MACRO Loans to households pc growh rate MONETARY FINANCIAL Page 10

3. Policy implications Changes in rejection rates of new loans Source: BBVA Research It is difficult to know without uncertainty when policy interventions are justified (R) or not (NR ) In NR there is no change in risk evaluation rules but the rejection rate increases because more applications are non-profitable In R there is an additional increase in rejection rates (higher risk aversion, less liquidity, regulatory uncertainty, etc.) Page 11

4. Additional comments Lending survey analysis: consider the inclusion of credit over GDP (in t-1) as an additional regressor Credit growth t = α+ βcredit growth t + γ i Demand factors t i + δ i Supply factors t i + φ Credit t 1 GDP t 1 + ε t Page 12

4. Additional comments Firm-Level regressions of changes in debt-to-asset ratio for manufacturing firms: Include the real interest rate from 1991 to 2012 The estimated effects for bank capital are not clear, given the increase in capital ratios from 2007 to 2012 Page 13

4. Additional comments Decomposition of change in Debt-to-Asset ratios for firms Source: IMF (2013) Capital and reserves over banks assets Source: BBVA Research 11.3% 6.9% 2007 2012 Page 14

Concluding remarks A timely and comprehensive empirical analysis of the factors behind the weakness in credit A relevant issue in the economic recovery of countries with high levels of credit to GDP ratios (e.g., Spain) Very interesting results Original empirical contributions Sound economic policy recommendations Page 15

Comments on Assessing Policies to Revive Credit Markets Chapter 2 of Global Financial Stability Report, IMF, October, 2013 Rafael Doménech Madrid, October 18, 2013