John Geanakoplos, Yale University
The Leverage Cycle
Geanakoplos notes that equilibrium determines leverage, not just interest rates. Variations in leverage cause wild fluctuations in asset prices. Since this leverage cycle can be damaging to the economy, perhaps it should be regulated.
Christopher Foote, Federal Reserve Bank of Boston, Kristopher Gerardi, Federal Reserve Bank of Atlanta, Lorenz Goette, Federal Reserve Bank of Boston, and Paul Willen, Federal Reserve Bank of Boston and NBER
Foote and his co-authors look skeptically at a leading argument about what is causing the foreclosure crisis and what should be done to stop it. They use an economic model to focus on two key decisions: the borrowers choice to default on a mortgage, and the lenders subsequent choice of whether to renegotiate or modify the loan. Their analysis illustrates that unaffordable loans -- defined as those with high mortgage payments relative to income at origination -- are unlikely to be the main reason that borrowers decide to default. They also provide theoretical results and empirical evidence supporting the hypothesis that the efficiency of foreclosure for investors is a more plausible explanation for the low number of modifications to date than contract frictions related to securitization agreements between servicers and investors. While investors might be foreclosing when it would be socially efficient to modify, there is little evidence to suggest that they are acting against their own interests when they do so. An important implication of this analysis is that policies designed to reduce foreclosures should focus on ameliorating the immediate effects of job loss and other adverse life events, rather than modifying loans to make them more affordable on a long-term basis.
Effi Benmelech, Harvard University and NBER, and Jennifer Dlugosz, Harvard University
The Credit Rating Crisis
Since June 2007, the creditworthiness of structured finance products has deteriorated rapidly. There were more than 2000 downgrades in November 2007 alone and many of them were severe, with 500 tranches downgraded more than 10 notches. Massive downgrades continued in 2008. More than 11,000 of the downgrades affected securities that were rated AAA. Benmelech and Dlugosz study the credit rating crisis of 2007-8 and in particular describe the collapse of the credit ratings of ABS CDOs. They provide suggestive evidence that ratings shopping may have played a role in the current crisis. They find that tranches rated solely by one agency, and by S&P in particular, were more likely to be downgraded by January 2008. Further, tranches rated solely by one agency were more likely to suffer more severe downgrades.
Fatih Guvenen, University of Minnesota and NBER, and Burhanettin Kuruscu, University of Texas at Austin
A Quantitative Analysis of the Evolution of the US Wage Distribution: 1970-2000
Guvenen and Kuruscu construct a parsimonious overlapping-generations model of human capital accumulation and study its quantitative implications for the evolution of the U.S. wage distribution from 1970 to 2000. A key feature of the model is that individuals differ in their ability to accumulate human capital, which is the main source of wage inequality in this model. The authors examine the response of this model to skill-biased technical change (SBTC), which is modeled as an increase in the trend growth rate of the price of human capital starting in the early 1970s.The models behavior is consistent with several important trends observed in the U.S. data, including: the rise in overall wage inequality; the fall and subsequent rise in the college premium, as well as the fact that this behavior was most pronounced for younger workers; the rise in within-group inequality; the stagnation in median wage growth, and the small rise in consumption inequality despite the large rise in wage inequality.The authors consider different scenarios regarding how individuals expectations evolve during SBTC. Specifically, they study the case where individuals immediately realize the advent of SBTC (perfect foresight) and the case where they initially underestimate the future growth of the price of human capital (pessimistic priors), but learn the truth in a Bayesian fashion over time. Lack of perfect foresight appears to have little effect on the main results of the paper. Overall, the model shows promise for explaining a diverse set of wage distribution trends observed since the 1970s in a unifying human capital framework.
George-Marios Angeletos, MIT and NBER, and Jennifer LaO, MIT
Noisy Business Cycles
Angeletos and LaO investigate a real-business-cycle economy that features dispersed information about aggregate shocks to productivity, tastes, and monopoly power (the fundamentals). First, they highlight why dispersed information is distinct from uncertainty about the fundamentals: only with dispersed information can agents face uncertainty about the level of economic activity, beyond what they face about the fundamentals. Next the researchers show how this type of uncertainty can: contribute to significant noise in the business cycle, even when agents are well informed about the fundamentals; increase inertia in the response of macroeconomic outcomes to aggregate productivity shocks; induce a negative short-run response of employment to aggregate productivity; formalize a certain type of demand shocks within an RBC economy; and generate cyclical variation in observed Solow residuals and labor wedges. Turning to the normative properties, the authors show that none of the aforementioned properties are symptoms of inefficiency: if there are no mark-up shocks and information is fixed, then the business cycle is constrained efficient.
Paul Beaudry, University of British Columbia and NBER, and Bernd Lucke, University of Hamburg
Letting Different Views about Business Cycles Complete (appendix)
There are several possible explanations for macroeconomic fluctuations. Two of the most commonly discussed are surprise changes in disembodied technology and monetary innovations. Another popular explanation is found under the heading of a preference, or more generally a demand shock. More recently, two other explanations have been advocated: surprise changes in investment-specific technology and news about future technology growth. Beaudry and Lucke quantitatively assess the relative merits of all these explanations by adopting a framework that allows them to compete. In particular, the researchers propose a co-integrated SVAR approach that encompasses all 5 shocks and thus offers a coherent evaluation of the dynamics they induce, as well as their contribution to macroeconomic volatility. The main finding here is that surprise changes in technology, whether disembodied or embodied in nature, account for very little of fluctuations. Instead, expected changes in technology appear to be an important force, with preference/demand shocks and monetary shocks also playing non-negligible roles.