The large global demand for store-of-value financial instruments accelerated the pace of complex financial innovations. The enormous confusion and fear caused by the sudden unravelling of many of the markets which were built on these innovations played a central role in the recent global financial crisis. It is no coincidence that the most effective economic policies implemented during this episode targeted the alleviation of this fear and confusion by providing extensive public guarantees. The purpose of this project is to provide a formal underpinning to each of these elements within a macroeconomic framework: The global macroeconomic forces behind financial innovation, complexity, Knightian uncertainty (fear), and the optimal policy response in settings where these ingredients play a central role. The intellectual merit of this proposal is to provide a new perspective on the endogenous sources of systemic fragility in a modern and global financial system. The goal is to provide a new set of macroeconomic models in which financial innovation stems from global macroeconomic forces, and shocks arise from the complexity of the financial network and the panics caused by the unmeasurable exposures that can arise from interacting with the financial network during times of systemic distress. While the core of the project is theoretical, it will be context-based (i.e., use extensive financial data to support the specific modeling). The PI also intends to use the models as an organizing device to make proposals on the kind of data that needs to be collected to measure the buildup of systemic risk in a financial system.
Broader Impact The broader impact of this proposal is to offer a foundation for a policy framework to deal with some of the most damaging aspects of financial crises and panics. Since the purpose of the project is to improve policy design, but to do so with formal models, its educational value beyond the specific models is to bring closer together the concerns of policymakers and the interests of Ph.D. students.
The project has two main branches. In the first one I study the confusion that arises during crises as a result of the complexity of the financial system. In the second one I explore the implications of the current shortage of safe assets for the global economy. In both cases I explore the policy implications of these features of the economic environment. In the main article of the first branch, I develop (jointly with Alp Simsek) a model of crises that builds upon the idea that complexity, which is a dormant factor during normal times, becomes acutely relevant and self-reinforcing during crises. Complexity matters in our model not directly but through the uncertainty it generates and how economic agents react to the latter. The basic structure of our model is a network of cross exposures between financial institutions that is susceptible to a domino effect of bankruptcies. In this context, we conceptualize complexity by banks' uncertainty about cross exposures. In particular, banks have only local knowledge of cross exposures: They understand their own exposures, but they are increasingly uncertain about cross exposures of banks that are farther away (in the network) from themselves. During normal times, banks only need to understand the financial health of their direct counterparties. In contrast, when a surprise liquidity shock hits parts of the network, a domino effect of bankruptcies becomes possible, and banks become concerned that they might be indirectly hit. Banks' uncertainty about cross exposures, a dormant factor in normal times, suddenly becomes relevant. In particular, banks now need to understand the financial health of the counterparties of their counterparties (and their counterparties). Since banks only have local knowledge of the exposures, they cannot rule out an indirect hit. They now perceive significant counterparty risk which leads them to retrench into a liquidity conservation mode. In the main article of the second branch, I develop (jointly with Emmanuel Farhi) a simple model of the Safe Asset Mechanism (SAM) and its policy antidotes. The central problem in SAM is one of "excess" demand for safe assets. This financial market problem spreads to the real economy through multiple channels. In particular, SAM is characterized by the strong downward pressure it puts on safe interest rates. If there is a limit on how much these rates can drop, a safety-trap emerges, akin to the Keynesian liquidity trap. In this context, a recession restores equilibrium in asset markets by reducing the wealth of safe-savers and hence their asset demand. Overall, SAM provides a parsimonious account for symptoms also found in environments experiencing the combined effect of a credit crunch and a liquidity trap. Public debt plays a central role in SAM. The central concept here is that of fiscal capacity: How much public debt can the government credibly pledge to honor, should a major macroeconomic shock take place in the future? The key issue is that the government owns a disproportionate share of the capacity to create safe assets, and the private sector owns too many risky assets. As long as the government has spare fiscal capacity to back safe asset production, the government can increase the supply of safe assets by issuing public debt. This reduces the root imbalance in the economy. We use this framework to analyze the impact of different policy options implemented recently in the U.S. and other developed economies. In general, policy-puts (such as QE1 in the U.S., LTRO in Europe, fiscal policy, etc.) that support future bad states of the economy play a central role in this environment, while policy-calls that support the good states of the recovery (e.g., some aspects of forward guidance) are less powerful.
