DOCSLIB.ORG

Leverage Cycle John Geanakoplos

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Leverage Cycle John Geanakoplos Leverage Cycle John Geanakoplos Zhe Li SUFE Zhe Li (SUFE) Leverage Cycle 1 / 78 Leverage A homeowner takes a loan using a house as collateral, he negotiates: (a) interest rate (b) how much he can borrow Example house costs $100, loan $80, he pays $20 in cash margin or haircut: 20% loan to value: 80/100 = 80% collateral rate: 100/80 = 1.25 leverage: 1/margin = 5 Zhe Li (SUFE) Leverage Cycle 2 / 78 Motivation In times of crisis: Interest rate (main policy instrument) Collateral rate (equivalently margins, leverage) E¤ectiveness of two instruments: During a crisis, leverage can fall by 50% overnight, and by more over a few days or months A homeowner who brought a house in 2007 by taking out a subprime mortgate with only 5% down payment cannot take out a similar loan in 2009 without putting 30% The odds are great that he won’thave the cash to do it, and reducing the interest rate by 1 or 2% won’tchange his ability to act Zhe Li (SUFE) Leverage Cycle 3 / 78 Heterogeneous beliefs For many assets there is a class of buyer for whom the asset is more valuable than it is for the rest of the public (standard economic theory, in contrast, assumes that asset prices re‡ect some fundamental value). These buyers are willing to pay more, perhaps because they are more sophisticated and know better how to hedge their exposure to the assets, or they are more risk tolerant, or they simply like the assets more Zhe Li (SUFE) Leverage Cycle 4 / 78 Distribution of wealth If the optimistic buyers can get their hands on more money through more highly leveraged borrowing (that is, getting a loan with less collateral), they will spend it on the assets and drive those prices up If they lose wealth, or lose the ability to borrow, they will buy less, so the asset will fall into more pessimistic hands and be valued less Zhe Li (SUFE) Leverage Cycle 5 / 78 Leverage cycle: meaning De…nition In the absence of intervention, leverage becomes too high in boom times, and too low in bad times (leverage is procyclical). As a result, in boom times asset prices are too high, and in crisis times they are too low. This is the leverage cycle. Leverage here (a ratio of collateral values to the downpayment that must be made to buy them) is di¤erent from the usuall de…nition: debt+equity/equity, which is misleading since equity is wiped out during crisis and it seems like that the leverage increases Zhe Li (SUFE) Leverage Cycle 6 / 78 Leverage cycle: U.S. boom Leverage dramatically increased in the United States from 1999 to 2006 A bank that in 2006 wanted to buy a AAA-rated mortgage security could borrow 98.4% of the purchase price, using the security as collateral, and pay only 1.6% in cash. The leverage was thus 100 to 1.6, or about 60 to 1 The average leverage in 2006 across all of the US$2.5 trillion of so-called ‘toxic’mortgage securities was about 16 to 1, meaning that the buyers paid down only $150 billion and borrowed the other $2.35 trillion Home buyers could get a mortgage leveraged 20 to 1, a 5% down payment. Security and house prices soared Zhe Li (SUFE) Leverage Cycle 7 / 78 Leverage cycle: U.S. current crisis Today leverage has been drastically curtailed by nervous lenders wanting more collateral for every dollar loaned Those toxic mortgage securities are now leveraged on average only about 1.5 to 1 Home buyers can now only leverage themselves 5 to 1 if they can get a government loan, and less if they need a private loan De-leveraging is the main reason the prices of both securities and homes are still falling Zhe Li (SUFE) Leverage Cycle 8 / 78 What causes crises? Bad news More than one bad news For example: output is 1 unless two things go wrong, in which case output becomes 0.2 Zhe Li (SUFE) Leverage Cycle 9 / 78 Optimist Suppose that the chance of each thing going wrong is independent and equal to 10% 1 At the beginning: 1 The chance of ultimate breakdown is 1% 2 The expected output is 0.99 1 + 0.01 0.2 = 0.992 2 2 3 The variance of …nal output is 0.99 0.008 + 0.01 (0.992 0.2) = 6. 336 10 3 2 After the …rst piece of bad news, 1 The expected output drops to 0.9 + 0.1 0.2 = 0.92 2 2 2 The variance jumps to 0.9 0.08 + 0.1 0.72 = 0.057 6 Zhe Li (SUFE) Leverage Cycle 10 / 78 Pessimist Suppose that the chance of each thing going wrong is independent and equal to 20% 1 At the beginning: 1 The chance of ultimate breakdown is 4% 2 The expected output is 0.96 1 + 0.04 0.2 = 0.968 3 The variance of …nal output is 0.96 (1 0.968)2 + 0.04 (0.968 0.2)2 = 2. 457 6 10 2 2 After the …rst piece of bad news, 1 The expected output drops to 0.8 + 0.2 0.2 = 0.84 2 2 2 The variance jumps to 0.8 (1 0.84) + 0.2 (0.84 0.2) = 0.102 4 Zhe Li (SUFE) Leverage Cycle 11 / 78 Disagreement Expectations di¤ered Originally by 0.992 0.968 = 0.024 After the bad news: 0.92 0.84 = 0.08 This kind of bad news increases uncertainty and disagreement — scary news The news in current crisis, forecasts on subprime losses ranged from 30% to 80% Zhe Li (SUFE) Leverage Cycle 12 / 78 Heterogeneity between optimists and pessimists Have di¤erent priors A continnum of agents uniformly arrayed between 0 and 1 Agent h on that continnum thinks the probability of good news (Up) is γh = h, and the probability of bad news (down) is γh = 1 h. U D The higher the h, the more optimistic the agent, the more natural a buyer he is Zhe Li (SUFE) Leverage Cycle 13 / 78 Sides of the market The more optimistic the agent, the more natural a buyer he is. There will be some break point h such that those more optimistic with h > h are on one side of the market and those less optimistic, with h < h, are on the other side. But h is endogenous. Zhe Li (SUFE) Leverage Cycle 14 / 78 Borrowing and asset pricing One consumption good C One asset Y Two time periods 0, 1 Two states of nature U and D in the last period Zhe Li (SUFE) Leverage Cycle 15 / 78 Borrowing and asset pricing Each unit of Y pays either 1 or 0.2 of the consumption good, in the two states U and D, respectively Imagine the asset as a mortgage that either pays in full or defaults with recovery 0.2 Or an oil well that might be a gusher or small Zhe Li (SUFE) Leverage Cycle 16 / 78 Endowment and consumption Endowment: eh = (eh , eh , eh , eh ) = (1, 1, 0, 0) C0 Y0 CU CD Preference: h u (c0, y0, w0, cU , cD ) = c0 + hCU + (1 h)CD c is canned food, can be consumed at time 0, c0, or stored costlessly, w0 Zhe Li (SUFE) Leverage Cycle 17 / 78 Asset pricing suppose the price of the asset Y at time 0 is p : Buyer if h 1 + (1 h) 0.2 > p Seller if h 1 + (1 h) 0.2 < p Zhe Li (SUFE) Leverage Cycle 18 / 78 Budget set without borrowing The price of the consumption good in each period to be 1 The price of the asset Y at time 0 is p 5 (c0, y0, w0, cU , cD ) R+ : c0 + w0 + py0 = 1 + p Bh (p) = c2= w + y N 8 U 0 0 9 < cD = w0 + 0.2y0 = : ; Zhe Li (SUFE) Leverage Cycle 19 / 78 Markets clear In equilibrium all markets must clear: 1 h h (c0 + w0 )dh = 1 0 Z 1 h y0 dh = 1 0 Z 1 1 h h cU dh = 1 + w0 dh 0 0 Z 1 Z 1 h h cD dh = 0.2 + w0 dh Z0 Z0 Zhe Li (SUFE) Leverage Cycle 20 / 78 Equilibrium In equilibrium, p = h 1 + (1 h) 0.2 Markets clear: Optimists spend all consumption goods (money) today to buy the asset Money of optimists = asset of pessimists 1 1 (1 h) = p 1 h h = 0.597, p = 0.677 Zhe Li (SUFE) Leverage Cycle 21 / 78 Equilibrium In equilibrium, agents are indi¤erent to storing or consuming right away, so we can describe equilibrium as if everyone warehoused and postponed consumption. (c0, y0, w0, cU , cD ) = (0, 2.5, 0, 2.5, 0.5) for h 0.597 (c0, y0, w0, cU , cD ) = (0, 0, 1.677, 1.677, 1.677) for h < 0.597 Zhe Li (SUFE) Leverage Cycle 22 / 78 Collateral A borrower can use the asset itself as collateral, so that if he defaults the collateral can be seized If the promise is j in both states, he will only receive min(j, 1) if good news min(j, 0.2) if bad news The biggest promise that is sure to be covered by the collateral: 0.2y0 Zhe Li (SUFE) Leverage Cycle 23 / 78 Budget set with collateralized borrowing Leveraging: using collateral to borrow, gives the most optimistic agents a chance to spend more 6 (c0, y0, ϕ0, w0, cU , cD ) R+ : 2 1 c0 + w0 + py0 = 1 + p + ϕ 8 1+r 0 9 Bh (p, r) = ϕ < 0.2y 0.2 > 0 0 > > cU = w0 + y0 ϕ > < 0 = cD = w0 + 0.2y0 ϕ0 > > > > Subscript 0.2 : we have arbitrarily:> …xed the maximum promise;> that can be made on a unit of collateral Zhe Li (SUFE) Leverage Cycle 24 / 78 Equilibrium Equilibrium is de…ned by the price and interest rate (p, r) and agent h h choices (c0, y0, ϕ0, w0, cU , cD ) in B0.2(p, r) that maximizes his utility u .
Load more

Recommended publications
  • Intermediary Leverage Cycles and Financial Stability Tobias Adrian and Nina Boyarchenko Federal Reserve Bank of New York Staff Reports, No
    Federal Reserve Bank of New York Staff Reports Intermediary Leverage Cycles and Financial Stability Tobias Adrian Nina Boyarchenko Staff Report No. 567 August 2012 Revised February 2015 This paper presents preliminary findings and is being distributed to economists and other interested readers solely to stimulate discussion and elicit comments. The views expressed in this paper are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author. Intermediary Leverage Cycles and Financial Stability Tobias Adrian and Nina Boyarchenko Federal Reserve Bank of New York Staff Reports, no. 567 August 2012; revised February 2015 JEL classification: E02, E32, G00, G28 Abstract We present a theory of financial intermediary leverage cycles within a dynamic model of the macroeconomy. Intermediaries face risk-based funding constraints that give rise to procyclical leverage and a procyclical share of intermediated credit. The pricing of risk varies as a function of intermediary leverage, and asset return exposures to intermediary leverage shocks earn a positive risk premium. Relative to an economy with constant leverage, financial intermediaries generate higher consumption growth and lower consumption volatility in normal times, at the cost of endogenous systemic financial risk. The severity of systemic crisis depends on two state variables: intermediaries’ leverage and net worth. Regulations that tighten funding constraints affect the systemic risk-return tradeoff by lowering the likelihood of systemic crises at the cost of higher pricing of risk. Key words: financial stability, macro-finance, macroprudential, capital regulation, dynamic equilibrium models, asset pricing _________________ Adrian, Boyarchenko: Federal Reserve Bank of New York (e-mail: [email protected], [email protected]).
    [Show full text]
  • Deleveraging and the Aftermath of Overexpansion
    May 28th, 2009 Jeffrey Owen Herzog Deleveraging and the aftermath of overexpansion [email protected] O The deleveraging process for commercial banks is likely to last years and overshoot compared to fundamentals Banking System Asset and Leverage Growth O A strong procyclical correlation exists between asset growth and Nominal Values, 1934-2008 leverage growth over the past 75 years 25% O At the level of the firm, boom times generate decreasing 20% 1942 collateralization rates and increasing average loan sizes 15% O Given two-year loan losses of $1.1tr and leverage declines of -5% 10% 2008 to -7.5%, we expect deleveraging to curtail commercial bank 5% credit by $646bn and $687bn per year for 2009-2010 0% -5% Trends in deleveraging and commercial banking over time Leverage Growth -10% 2004 -15% 1946 Deleveraging is the process whereby commercial banks reduce their ratio of -20% assets to equity capital, thus bringing down their aggregate exposure to the 0% 5% -5% 10% 15% 20% 25% 30% economy. Many commentators point to this process as an eventual destination -10% Asset Growth for the US commercial banking system, but few have described where or how Source: FDIC we arrive at a more deleveraged commercial banking system. Commercial Bank Assets and Equity Adjusted for Inflation by CPI, $tr Over the past seventy years, the commercial banking sector’s aggregate 0.6 6 balance sheet has demonstrated a strong positive correlation between leverage and asset growth. For the banking industry, 2004 was an 0.5 5 S&L Crisis, 1989-1991 exceptionally unusual year, with equity increasing yoy by 22%.
    [Show full text]
  • Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling
    NBER WORKING PAPER SERIES FACTS AND CHALLENGES FROM THE GREAT RECESSION FOR FORECASTING AND MACROECONOMIC MODELING Serena Ng Jonathan H. Wright Working Paper 19469 http://www.nber.org/papers/w19469 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 September 2013 We are grateful to Frank Diebold and two anonymous referees for very helpful comments on earlier versions of this paper. Kyle Jurado provided excellent research assistance. The first author acknowledges financial support from the National Science Foundation (SES-0962431). All errors are our sole responsibility. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w19469.ack NBER working papers are circulated for discussion and comment purposes. They have not been peer- reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. © 2013 by Serena Ng and Jonathan H. Wright. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling Serena Ng and Jonathan H. Wright NBER Working Paper No. 19469 September 2013 JEL No. C22,C32,E32,E37 ABSTRACT This paper provides a survey of business cycle facts, updated to take account of recent data. Emphasis is given to the Great Recession which was unlike most other post-war recessions in the US in being driven by deleveraging and financial market factors.
    [Show full text]
  • 1 Solving the Present Crisis and Managing the Leverage Cycle John Geanakoplos We Are at the Acute Crisis Stage of a Leverage
    Solving the Present Crisis and Managing the Leverage Cycle John Geanakoplos1 We are at the acute crisis stage of a leverage cycle, a very big cycle. I write to propose a plan with concrete steps that the government could take to address the severe financial condition that we now find ourselves in. It is critical that any rescue plan be clear and transparent, implementable and not subject to fraud, and comprehensive enough to succeed and to convince the public it will succeed. The law already enacted by Congress was admittedly an emergency measure designed to staunch further immediate hemorrhaging. What to do next is the question; understanding how we got here will help us find the right set of answers. The leverage cycle is a recurring phenomenon in American financial history. Most recently, one ended in the derivatives crisis in 1994 that bankrupted Orange County, and another ended in the Emerging Markets-mortgage crisis of 1998 that bankrupted Long Term Capital. A proper understanding of the origins of the cycle shows the way to manage it and to deal with the final crisis stage. A critical aspect of the leverage cycle is that collateral margin rates change. Two years ago a home buyer could make a 5% downpayment on a house, and borrow the other 95%. Now he must put 25% down. Two years ago a mortgage security buyer could put 3% or 10% down, borrowing the rest. Now he must pay 100% in cash. All leverage cycles end with (1) bad news creating more uncertainty and disagreement, (2) sharply increasing collateral margin rates, and (3) losses and bankruptcies among the leveraged optimists.
    [Show full text]
  • When Credit Bites Back: Leverage, Business Cycles, and Crises∗
    February 2012 When Credit Bites Back: Leverage, Business Cycles, and Crises∗ Abstract This paper studies the role of leverage in the business cycle. Based on a study of nearly 200 recession episodes in 14 advanced countries between 1870 and 2008, we document a new stylized fact of the modern business cycle: more credit-intensive booms tend to be followed by deeper recessions and slower recoveries. We find a close relationship between the rate of credit growth relative to GDP in the expansion phase and the severity of the subsequent recession. We use local projection methods to study how leverage impacts the behavior of key macroeconomic variables such as investment, lending, interest rates, and inflation. The effects of leverage are particularly pronounced in recessions that coincide with financial crises, but are also distinctly present in normal cycles. The stylized facts we uncover lend support to the idea that financial factors play an important role in the modern business cycle. Keywords: leverage, financial crises, business cycles, local projections. JEL Codes: C14, C52, E51, F32, F42, N10, N20. Oscar` Jord`a(Federal Reserve Bank of San Francisco and University of California, Davis) e-mail: [email protected]; [email protected] Moritz Schularick (Free University of Berlin) e-mail: [email protected] Alan M. Taylor (University of Virginia, NBER, and CEPR) e-mail: [email protected] ∗The authors gratefully acknowledge financial support through a grant of the Institute for New Economic Thinking (INET) administered by the University of Virginia. Part of this research was undertaken when Schularick was a visitor at the Economics Department, Stern School of Business, New York University.
    [Show full text]
  • Liquidity, Part 2: Debt, Panics, and Flight to Quality: Lecture 6
    14.09: Financial Crises Lecture 6: Collateralized Debt and Information Based Panics Alp Simsek Alp Simsek () Lecture Notes 1 Revisiting runs: Is Diamond-Dybvig the whole story? Diamond-Dybvig provides a plausible account of runs in history, and after some relabeling, a contributing factor to the subprime crisis. However, there is reason to think that it might not be the whole story. Recently (and in history), much debt has been collateralized. An example of collateralized debt is repo (sale-repurchase agreement)... Alp Simsek () Lecture Notes 2 Roadmap 1 Understanding the run on the collateralized debt 2 Information insensitivity of collateralized debt 3 Information-based panics and the leverage cycle 4 Revisiting the run(s) on Bear Stearns Alp Simsek () Lecture Notes 3 Alp Simsek () Lecture Notes 4 What is repo? Repo is effectively a collateralized loan. B (the borrower/the bank), receives some money by temporarily giving collateral such as treasuries, MBSs etc to F (the financier). B pays back the loan with interest and reclaims the collateral. The loan is often short term, e.g., one day, but could also be longer. (The deal is technically structured as an initial sale of the collateral and a right to repurchase with a prespecified price that refiects the interest rate– hence the name.) Alp Simsek () Lecture Notes 5 Repo haircuts As we discussed earlier, the loan usually has a haircut or margin. Recall B could borrow ρ from the Fs by using 1 dollar of the asset as collateral. The difference, 1 ρ, would be the REPO haircut. − Alp Simsek () Lecture Notes 6 Courtesy of the American Economics Association.
    [Show full text]
  • Procyclical Leverage and Value-At-Risk
    Procyclical Leverage and Value-at-Risk Tobias Adrian Federal Reserve Bank of New York Hyun Song Shin Downloaded from https://academic.oup.com/rfs/article/27/2/373/1580738 by Bank for International Settlements user on 21 March 2021 Princeton University The availability of credit varies over the business cycle through shifts in the leverage of financial intermediaries. Empirically, we find that intermediary leverage is negatively aligned with the banks’ Value-at-Risk (VaR). Motivated by the evidence, we explore a contracting model that captures the observed features. Under general conditions on the outcome distribution given by extreme value theory (EVT), intermediaries maintain a constant probability of default to shifts in the outcome distribution, implying substantial deleveraging during downturns. For some parameter values, we can solve the model explicitly, thereby endogenizing the VaR threshold probability from the contracting problem. (JEL G01, G23, G32) The availability of credit and how credit varies over the business cycle have been subjects of keen interest, especially in the wake of the financial crisis. Some cyclical variation in total lending is to be expected, even in a frictionless world where the conditions of the Modigliani and Miller (1958) theorem hold. There are more positive net present value (NPV) projects that need funding when the economy is strong than when the economy is weak. Therefore, we should expect total credit to increase during the upswing and decline in the downswing. The debate about procyclicality of the financial system is therefore more subtle. The question is whether the fluctuations in lending are larger than would be justified by changes in the incidence of positive NPV projects.
    [Show full text]
  • Credit Cycles with Market-Based Household Leverage∗
    Credit Cycles with Market-Based Household Leverage∗ William Diamond Tim Landvoigt Wharton Wharton & NBER June 2019 Abstract We develop a model in which mortgage leverage available to households depends on the risk bearing capacity of financial intermediaries. Our model features a novel transmission mechanism from Wall Street to Main Street, as borrower households choose lower leverage and consumption when intermediaries are distressed. The model has financially-constrained young and unconstrained middle-aged households in overlapping generations. Young households choose higher leverage and riskier mortgages than the middle-aged, and their consumption is particularly sensitive to credit supply. Relative to a standard model with exogenous credit constraints, the macroeconomic importance of intermediary net worth is magnified through its effects on household leverage, house prices, and consumption demand. The model quantita- tively demonstrates how recessions with housing crises differ from those driven only by productivity, and how a growing demand for safe assets replicates many features of the 2000s credit boom and increases the severity of future financial crises. ∗First draft: December 2018. Email addresses: [email protected], tim- [email protected]. We thank Carlos Garriga for useful feedback on our work. We further benefited from comments of seminar and conference participants at the 2019 AEA meetings, LSE, NYU, Wharton, the 2019 Cowles GE conference, and the 2019 Copenhagen MacroDays. 1 Introduction The financial sector grew during the boom of the early 2000s and crashed in the finan- cial crisis of 2008, contributing to a boom and bust in asset prices. Low spreads between mortgage rates and risk free interest rates during the boom meant that highly levered households could borrow cheaply, while after 2008 spreads on risky mortgages reached historical highs, making household borrowing extremely expensive.
    [Show full text]
  • Solving the Present Crisis and Managing the Leverage Cycle
    John Geanakoplos Solving the Present Crisis and Managing the Leverage Cycle 1. Introduction (equivalently, collateral rates) must also be monitored and adjusted if we are to avoid the destruction that the tail end of an he present crisis is the bottom of a leverage cycle. outsized leverage cycle can bring. TUnderstanding that tells us what to do, in what order, Economists and the public have often spoken of tight credit and with what sense of urgency. Public authorities have acted markets, meaning something more than high interest rates, but aggressively, but because their actions were not rooted in (or without precisely specifying or quantifying exactly what they explained with reference to) a solid understanding of the causes meant. A decade ago, I showed that the collateral rate, or of our present distress, we have started in the wrong place and leverage, is an equilibrium variable distinct from the interest paid insufficient attention and devoted insufficient resources rate.1 The collateral rate is the value of collateral that must be to matters—most notably, the still-growing tidal wave of pledged to guarantee one dollar of loan. Today, many foreclosures and the sudden deleveraging of the financial businesses and ordinary people are willing to agree to pay bank system—that should have been first on the agenda. interest rates, but they cannot get loans because they do not In short and simple terms, by leverage cycle I mean this. have the collateral to put down to convince the banks their loan There are times when leverage is so high that people and will be safe.
    [Show full text]
  • REVIEWING the LEVERAGE CYCLE by Ana Fostel and John Geanakoplos September 2013 COWLES FOUNDATION DISCUSSION PAPER NO. 1918 COWLE
    REVIEWING THE LEVERAGE CYCLE By Ana Fostel and John Geanakoplos September 2013 COWLES FOUNDATION DISCUSSION PAPER NO. 1918 COWLES FOUNDATION FOR RESEARCH IN ECONOMICS YALE UNIVERSITY Box 208281 New Haven, Connecticut 06520-8281 http://cowles.econ.yale.edu/ Reviewing the Leverage Cycle∗ Ana Fostel † John Geanakoplos ‡ September, 2013 Abstract We review the theory of leverage developed in collateral equilibrium models with incomplete markets. We explain how leverage tends to boost asset prices, and create bubbles. We show how leverage can be endogenously determined in equilibrium, and how it depends on volatility. We describe the dynamic feedback properties of leverage, volatility, and asset prices, in what we call the Leverage Cycle. We also describe some cross-sectional implications of multiple leverage cycles, including contagion, flight to collateral, and swings in the issuance volume of the highest quality debt. We explain the differences between the leverage cycle and the credit cycle literature. Finally, we describe an agent based model of the leverage cycle in which asset prices display clustered volatility and fat tails even though all the shocks are essentially Gaussian. Keywords: Leverage, Leverage Cycle, Volatility, Collateral Equilibrium, Collateral Value, Liquidity Wedge, Flight to Collateral, Contagion, Adverse selection, Agent Based Models. 1 Introduction Before the great financial crisis of 2007-09, mainstream macroeconomics regarded interest rates and technology shocks as the most important drivers of economic ac- tivity and asset prices. The Federal Reserve, charged with maintaining stable prices ∗Paper is submitted to the Annual Review of Economics. DOI for the paper is 10.1146/annurev- economics-080213-041426. †George Washington University, Washington, DC ‡Yale University, New Haven, CT, Santa Fe Institute, Ellington Capital Management.
    [Show full text]
  • Managing the Leverage Cycle
    Managing The Leverage Cycle John Geanakoplos 1 Fed Should Manage Leverage as well as Interest Rates • From Irving Fisher in 1890s and before it has been commonly supposed that the interest rate is the most important variable in the economy. • When economy slows, public clamors for lower rates, and Fed obliges. • Fed has been pumping out billions of dollars in bank loans. Fed lowered fed funds rate in December 2008 to zero. • But collateral rates or leverage more important in times of crisis. 2 Shakespeare got this Right 400 years ago. 3 Negotiation • Over interest rate (many pages) • And over collateral. 4 Which did Shakespeare think more important: Interest or Collateral? • What interest did Shylock charge? Nobody remembers. • Everybody remembers collateral of pound of flesh. 5 Judgment: Wrong Collateral level! • P: “Wait a moment. There is something else. This bond • Does not give you one drop of blood. The words • Expressly are “a pound of flesh”. So take your • Bond. Take your pound of flesh. But if, in cutting it, you shed • One drop of Christian blood, your lands and goods, under the • Laws of Venice, will be confiscated to the sate of Venice.” Pound of flesh but not a drop of blood. 6 Leverage Cycle Papers • Geanakoplos 1997 “Promises Promises” • Geanakoplos 2003 “Liquidity, Default, and Crashes: Endogenous Contracts in General Equilibrium”. Invited address World Econometric Society Congress 2000. • Fostel-Geanakoplos 2008 “Leverage Cycles and the Anxious Economy”. AER. • Geanakoplos (2009) “The Leverage Cycle” 7 Collateral papers • Bernanke-Gertler-Gilchrist 1996, 1999 • Kiyotaki-Moore 1997 • Geanakoplos-Zame 1997, 2002, 2005, 2009 • Araujo-Pescoa 2005 and many others • Kubler et al many • Collateral, but not looking at endogenous leverage.
    [Show full text]
  • Monetary Policy Transmission Over the Leverage Cycle: Evidence for the Euro Area
    Working Paper Series Leonie Bräuer, Gerhard Rünstler Monetary policy transmission over the leverage cycle: evidence for the euro area No 2421 / June 2020 Disclaimer: This paper should not be reported as representing the views of the European Central Bank (ECB). The views expressed are those of the authors and do not necessarily reflect those of the ECB. Abstract We study state dependence in the impact of monetary policy shocks over the leverage cycle for a panel of 10 euro area countries. We use a Bayesian Threshold Panel SVAR with regime classifications based on credit and house prices cycles. We find that monetary policy shocks trigger a smaller response of GDP, but a larger response of inflation during low states of the cycle. The shift in the inflation-output trade-off may result from higher macro-economic uncertainty in low leverage states. For an alternative regime classification based on turning points we find larger effects on GDP during contractions. Keywords: Monetary Policy, Financial Cycle, Bayesian Threshold Panel VAR JEL classification: C32, E32, E44 ECB Working Paper Series No 2421 / June 2020 1 Non-technical summary We study state dependence in the effects of monetary policy over the leverage cycle for a panel of 10 euro area countries over 1982 to 2017. We extract medium-term fluctuations in credit volumes and in real house prices from univariate filtering meth- ods and define country-specific regimes of high and low states in the cycles. We then estimate the effects of monetary policy shocks on GDP, inflation, and the short-term interest rate separately for the two regimes from a Bayesian structural panel VAR.
    [Show full text]