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Curbing the credit cycle

Curbing the credit cycle. The role for countercyclical macroprudential policies. by David Aikman* Bank of England Turkiye Cumhuriyet Merkez Bankasi Conference on “Incorporating Financial Stability into Inflation Targeting”, November 25-26 2011.

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Curbing the credit cycle

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  1. Curbing the credit cycle The role for countercyclical macroprudential policies by David Aikman* Bank of England TurkiyeCumhuriyetMerkezBankasi Conference on “Incorporating Financial Stability into Inflation Targeting”, November 25-26 2011 * The views expressed are those of the author and not necessarily those of the Bank of England

  2. Financial Deepening… Bank Assets / GDP, 1870-2008 Source: Schularick & Taylor (2009), Bank calculations

  3. … to Financial Disaster G7 nominal credit growth Price-to-book ratios

  4. Trends, cycles, and policy • Staggering growth in Assets:GDP and Loans:GDP points to Financial Deepening e.g. a la Kiyotaki-Moore (JEEA, 2005)… • … ‘Great Moderation’ and nominal stability… • … but accompanied by growing real imbalances that were unsustainable in the medium run • Key message: • Real frictions can generate medium term imbalances • Imbalances are inefficient from a social perspective • New (‘Macroprudential’) policy instruments needed to affect relative prices … act on the private marginal cost of ‘risk’

  5. Plan for the talk Some stylised facts on credit over the medium term Sketch outline of modelling framework within which strategic complementarities drive excessive risk taking Optimal policy in this context Broader lessons for macroprudential policy design

  6. Medium term credit cycles Fisher (Ecta, 1933): “The old an apparently still persistent notion of “the” business cycle … is a myth. Instead of one cycle, there are many co- existing cycles, constantly aggravating or neutralising each other…” Business cycle frequency (2-8 years) versus medium term frequency (8-20 years) Business cycle frequency fluctuations in credit matter less than ‘stickier’ medium term cycles in credit when it comes to financial crises egSchularick & Taylor (AER, 2011): lagged real credit growth (5-6 years) jointly significant in determining banking crisis probability

  7. Medium term credit cycles (real bank credit) Band-pass filtered series. Solid line = (2,20) year cyclical component. Dashed line = (8,20) year component. Blue lines = banking crisis (Reinhart & Rogoff)

  8. Real credit versus real income: UK Medium term component of credit is large … … dominates medium term component of real income … ‘Great moderation’…

  9. Credit cycle and banking crises (b) (e) (a) (c) (d) Secondary banking crisis Johnson Matthey ‘Small banks crisis’ Barings Sub-prime … (a), (c) and (e) were (are) systemic

  10. Credit cycle and banking crises (b) (e) (a) (c) (d) Secondary banking crisis Johnson Matthey Small banks crisis Barings Sub-prime … (a), (c) and (e) were (are) systemic … Also currency crises!

  11. Cycle has spanned many monetary regimes Band pass filtered real credit, (8,20) year components UK, 1880-2008.

  12. Credit and crises Growing econometric evidence that , inter alia, credit matters for crises (e.g. Alessi & Detken (2009), Borio & Lowe (2002, 2004), Drehmann et al (2010), Schularick & Taylor (2011)) Inefficient credit booms can result from failure of atomistic agents to internalise ex post impact of borrowing on others’ collateral constraints (Bianchi, 2010; Lorenzoni, 2008) But financial actors rarely behave in isolation => strategic complementarities (e.g. Acharya & Yorulmazer (2008); Sharfstein & Stein (1990); Gorton & He (2008); Rajan (1994))

  13. Complementarities and crises Keynes’ sound banker: “A sound banker, alas, is not one who foresees danger and avoids it, but one who, when he is ruined, is ruined in a conventional and orthodox way with his fellows, so that no- one can really blame him” (1931) Chuck Prince’s sound banker: “As long as the music is playing, you’ve got to get up and dance. We’re still dancing” Keeping up with the Joneses  “Keeping up with the Goldmans”

  14. Simple model • f’(.) > 0: better fundamentals => high ability more likely to make high returns • If get 0, exit. If not, face choice t = 0, 1, 2 Continuum of banks make initial investment at t = 0 Initial return depends on fundamentals (θ) and ability {high,low} Neither observed by the market

  15. Choice at t = 1 0 < αf(θ) < 1 high ability invest again and obtain RH again. ≈ 1 - αf(θ) obtained RL < RH … some are high ability and some are low ability Choice: {gamble, safe} If {safe}, don’t invest and announce low returns for sure in t = 2. If {gamble}, invest => if lucky, t = 2 payoff could resemble lucky high ability. Gamble is risky. k% of investment financed by capital at marginal cost c > 0 (costly)

  16. Reputation => “Prince constraint”: Reputation worse when fundamentals better => “Keynes constraint”: Reputation worse as more banks risk up Banks care about returns and reputation Gambling is negative NPV… … but might still occur if probability of avoiding “low ability stigma” is high enough. If 0 < l < 1 is fraction of gamblers, reputational penalty of failing to achieve RH captured by:

  17. Equilibrium • Banks receive private signals xi about fundamentals • Global games techniques (Morris & Shin, 2002) • Threshold equilibrium: Gamble if xi > θ* Safe if xi ≤ θ* • Non-linear effects: even small changes in fundamentals can spark large credit booms => ‘stable’ fundamentals but ‘unstable’ credit (Great Moderation) • Threshold satisfies θ* = θ(k,…), θk > 0 • Higher capital requirements discourage gambling at the margin. • Intuition: Gambling requires rapid balance sheet expansion, which is costlier when capital requirements are higher.

  18. Implications for policy Policymaker’s problem is non-trivial: discourage gambling vs punish all banks regardless of ability Suppose policymaker cares about expected returns to the aggregate banking system S(k,.) Raising capital requirements reduces gambling probability (“gambling effect”) … but reduces all banks’ payoffs (“cost effect”):

  19. Cyclicality Gambling incentives change over the cycle High types more likely to make high returns from t = 0 investments… … but reputational penalty to failing rises as fundamentals improve => gambling incentives rise => optimal policy is counter-cyclical

  20. Macroprudential policy • Optimal policy here is ‘macroprudential’ in nature: • Looks ‘across-the-system’ (cross-sectional externality) • Varies with the cycle • Plays an allocational role • Not modelled: loss absorbancy role • Role of public information

  21. Broader policy context • Early phase of debate on appropriate macroprudential toolkit • UK: key role for new Financial Policy Committee • Europe: ESRB • FSB-IMF-BIS report to G20 • Cyclical tools: countercyclical capital buffer; variable risk weights; leverage ratio; countercyclical liquidiity buffers; LTVs; margins/haircuts • Structural tools: SIFIs; CCPs and other financial market infrastructure; trading platforms; disclosure policy • Priority area for research!

  22. Conclusions Medium term fluctuations in credit are large and have spanned many monetary regimes Growing evidence that they are related to crises Credit booms and busts can arise from cross-institution externalities that require a macroprudential approach A new set of instruments to tackle these frictions

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