Macroprudential Policy Evaluation using Credit Register Big … · Macroprudential Policy...
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Macroprudential Policy Evaluation using
Credit Register Big Data
João Barata Ribeiro Blanco Barroso
Banco Central do Brasil – Research Department
Based on the country contributions to the BIS CCA CGDFS Working Group on “The impact of
macroprudential policies: na empirical analysis using credit register data”. The Brazilian team is
Douglas Araujo, João Barroso, Carlos Cinelli, Bernardus von Doornik and Rodrigo Gonzalez.
The views expressed in this
work are those of the author
and do not necessarily reflect
those of the Banco Central do
Brasil nor of its members.
Motivation
Financial cycles and business cycles do not necessarily coincide.
This creates opportunities to use different tools to address different
cycles (with care for possible interactions)
Macroprudential policies for the financial cycle
Monetary policy for the business cycle
With global financial integration, global liquidity and global risk
aversion are major factors in financial cycles for many economies
As a result: simultaneous macroprudential policy experiments in
several economies, around and after the global financial crisis
Evaluation is a challenging because econometric identification is
challenging: possible benefit of big credit register data.
Motivation
Credit register data allows identification of the credit operations of
several banks with the same agent (mostly firms in our case).
The common component is a proxy for the demand for credit
One can identify the effect of the policy on the supply of credit.
Computationally challenging when the time series dimension is
included in the model: several millions of observations in a dataset.
The challenge was undertaken by several Central Banks in the
Americas in a working group under the auspices of the Bank of
International Settlement, Americas Office.
Macroprudential Policies in the Americas
Canada: LTV
housing
Colombia:
Dynamic
Provisioning
Colombia:
Countercyclical
Reserve
Requirements
Colombia:
Limits on
exchange rate
risk
Argentina:
Liquidity Ratios
Canada: LTV
housing
Colombia:
Limits on
Dividend
Distribution
Colombia:
Liquidity Ratios
Brazil:
Countercyclical
reserve
requirements
Peru: Dynamic
Provisioning
US: SCAP
capital
assessement
program
Argentina: Capital
Buffer
Brazil: Risk
Weight on specific
loans
Brazil:
Countercyclical
reserve
requirements
Canada: LTV
housing
Peru:
Countercyclical
Reserve
Requirements
Peru: Limits on
exchange rate risk
Brazil:
Countercyclical
reserve
requirements
Brazil: Risk Weight
on auto loans
Canada: LTV
housing
Colombia: Limits
on derivatives
Mexico:
Provisioning on
Expected Losses
Peru:
Countercyclical
Reserve
Requirements
Peru: Limits on
exchange rate risk
Argentina:
Capital Buffer
Brazil:
Countercyclical
reserve
requirements
Canada: LTV
housing
Chile: Warning
of house prices
Peru: Liquidity
Ratios
Brazil: LTV cap
on housing
loans
Chile: Warning
of house prices
2007 2008 2009 2010 2011 2012 2013
pre-crisis buble global financial
crisis
begining of QE
policies
deepening of QE
policies
deepening of QE +
euro crisis
deepening of QE
+ euro crisis
deepening of QE
+ taper tantrum
Canada: LTV
housing
Colombia:
Limits on
exchange rate
risk
Canada: LTV
housing
Canada: LTV
housing
Peru: Limits on
exchange rate
risk
Canada: LTV
housing
Colombia: Limit
derivatives
Peru: Limits on
forex
Canada: LTV
housing
Chile: Warning
of house prices
Brazil: LTV cap
on housing
loans
Chile: Warning
of house prices
Colombia:
Countercyclical
Reserve
Requirements
Argentina:
Liquidity Ratios
Colombia:
Liquidity Ratios
Brazil:
Countercyclical
reserve
requirements
Brazil:
Countercyclical
reserve
requirements
Peru:
Countercyclical
reserve
Requirements
Brazil:
Countercyclical
reserve
requirements
Peru:
Countercyclical
reserve
Requirements
Brazil:
Countercyclical
reserve
requirements
Peru: Liquidity
Ratios
Colombia:
Dynamic
Provisioning
Colombia:
Limits on
Dividend
Distribution
Peru: Dynamic
Provisioning
US: SCAP
capital
assessement
program
Argentina:
Capital Buffer
Brazil: Risk
weight auto
loans
Brazil: Risk
Weight auto
loans
Mexico:
Provisioning on
expected
losses
Argentina:
Capital Buffer
2007 2008 2009 2010 2011 2012 2013
Asset Based Instruments
Liquidity Based Instruments
Capital Based Instruments
Capital based instruments affect risk-taking incentives, since it
impacts how much ‘skin in the game’ financial intermediaries have.
Similar risk-taking channel in monetary policy; see Barroso, Souza
and Guerra (2016) for the Brazilian case.
Liquidity/Liability based instruments affect the cost of funding of
financial intermediaries, and therefore credit supply conditions.
Monetary policy also affects the cost of funding, basically through
the same channel.
Asset based instruments affect the budget set of borrowers
Monetary policy affects the intertemporal budget constraint
Complementarity is at leas additive, possibly multiplicative
Relation with monetary policy
Initial findings of the working group based on time series
identification
This means banks are assumed to be homogeneously affected
by the policy, but heterogeneously so in time according to policy
intensity
So far only the Brazilian team presented results based on cross-
section identification (on top of baseline time series results).
This means banks are heterogeneously affected by the policy,
although homogeneously in time according to a policy elasticity
The results for both strategies are consistent in the Brazilian case,
therefore strenghening the overall results of the group.
Time Series x Cross-section identification
Findings: Capital Based Instrument
Colombia: Dynamic provisioning had a negative effect on credit growth,
with complementarities between monetary and macroprudential policy.
Argentina: Capital buffer are effective to reduce credit cycles
United States: Bank capital stress test in 2011 effective in reducing
credit in the jumbo mortgage segment
Mexico: Introduction of Provisioning based on expected loss reduced
credit growth, particularly in local currency
Peru: Dynamic provisioning has a significant effect on credit growth
Brazil*: Conditional risk weights contributed to increase the spread
charged to affected borrowers (Martins and Schechtman, 2010)
Findings: Liquidity Based Instruments
Colombia: Countercyclical reserve requirements had negative effect on
credit growth and complementarity with monetary policy.
Peru: Conditional reserve requirements on foreign currency deposits
reduced foreign currency denominated loans [note: explicitly
conditional policy based on credit growth]
Brazil*: Tightening reserve requirements had a negative effect on credit,
especially to riskier loans; easing reserve requirements had a positive
effect on credit supply; evidence of multiplicative complementarity with
monetary policy.
Findings: Asset Based Instruments
Colombia: LTV cap effective according to a semi-structural model
calibrated with household data.
Chile: Warning of high house prices shifted the LTV distribution towards
lower levels of LTV, which are known to be less risky.
Brazil*: LTV cap lead to higher interest rates, shorter maturities, lower
amouts, more affordable homes and less default in the following year,
for borrowers econometrically identified as constrained.
Liquidity Based Instrument:
Barroso, Cinelli, Doornik & Gonzales (2016): We show reserve
requirement policy innovations affects credit supply in the
expected direction.
Asset Based Instrument
Araujo, Barroso & Gonzales (2016): We show LTV cap is effective
in reducing credit risk , while also generating less favorable
contracts terms to borrowers.
This is consistent with a signaling effect of the policy on top of the
credit risk mitigation of the cap.
Capital Based Instruments: Risk weight and provisioning assessment
Findings for Brazil
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Brazil: Reserve Requirements: Innovation
Brazilian Credit Register (SCR); virtually all corporate loans
Data is quarterly from 2008Q1 to 2015Q2
We restrict our sample to firms with loans from more than one bank
36 million data points (27 periods, 132 banks and 478 thousand firms)
The dependent variable is the winsorized log change in the credit
granted to a firm (f), by a bank (b) in a quarter (t)
The firm risk indicator of the firm at the bank or system
Bank balance sheet variables: total assets (size), liquidity ratio
(liquidity), return over assets (ROA), Banks nonperforming loans to
total credit (NPL); and public, foreign or small bank dummy variables
Brazil: Reserve Requirements: Data
We find that RR policy impact credit in the expected direction
The quantitative impact is more sensible in the medium and long run
There is suggestive evidence that higher liquidity and capital ratios
appear to reduce the impact of RR policy
Monetary policy is a complement to RR policy in the sense that
tightening one policy increases the effect of the other on credit
We find that banks avoid riskier firms in the aftermath of policy
changes. During tightening phases, when there is credit contraction,
riskier firms receive less credit
Brazil: Reserve Requirements: Results
It is very well documented that high Loan-to-Value (LTV) is associated
with higher credit risk.
However there is no evidence of the effect of a policy that
unexpectedly imposes a LTV cap (say the effect on credit risk and
contractual terms such as interest rates and maturity )
We provide such evidence
The novelty is to identify who is constrained by the policy once it is
implemented. We cannot distinguish them from unconstrained
borrowers, since everyone respects the cap.
But we can estimate how likely one is to be constrained based on the
pre regulation sample. This is our empirical strategy.
Brazil: LTV cap
Economic activity, housing loans, and housing prices in Brazil All series are real annual growth rates. Sep 2013 LTV cap
Brazil: LTV cap
Frequency of new housing loans by LTV ranges SFH - Before SFH - After
FGTS - Before FGTS - After
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Brazil: LTV cap
In the SFH segment, but not the FGTS segments, the average housing
loan contracts for treated borrowers have
higher down payment requirements
higher interest rates,
shorter maturities.
In both cases, borrowers compensate these factors by purchasing
more affordable homes, and improve their repayment behavior.
The less favorable terms offered to SFH may result from official
communication: prudential concerns were signaled only for this
segment of the market.
Brazil: LTV cap: Results
Credit Register data offers good opportunities to identify the effects
of macroprudential policies.
There are computational challenges, but the payoff justifies exploring
this source of big data.
For the Americas, the evidence is consistent with effective capital,
liquidity and asset based macroprudential policies.
For Brazil, the evidence is particularly strong given the size of shocks,
the different directions of the shocks and the identification of control
groups through counterfactuals.
Summary