Collaborative Research: Good Booms, Bad Booms

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The recent financial crisis poses challenges for economists: Models that display financial crises are needed, but these models must be consistent with the robust finding that credit booms precede crises. However, not all booms end in a crisis; some do and some do not. Why do only some booms end in a crisis? Are these different types of booms related to macroeconomic variables, such as labor productivity or total factor productivity (TFP), differently? This is important for determining whether one integrated framework can encompass recessions, financial crises and growth, or whether financial crises are so special that a completely different model is needed. The PIs use both empirical methods and formal modeling to answer these questions. In the empirical part they study macroeconomic and financial panel data. They first identify credit booms and classify them between good and bad depending on whether they ended in a crisis or not. Then they analyze the anatomy of good booms and bad booms to understand their main differences in terms of productivity. They then build a formal economic model that uses a simple framework to explain their empirical results. If a credit boom is not sustained by a parallel increase in productivity, at some point the collateral sustaining the credit triggers information acquisition in credit markets, less credit is available and there is a financial crisis, even in the absence of any negative shock to the economyThe intellectual merit of the project is to show that the explanation of financial crises does not need to rely on contemporaneous shocks, but rather on the dynamic preceding interaction between productivity and credit in the economy. An understanding of this link is essential to identify warning signals that make financial crises more likely. The research can be broadly subdivided into three components. The first is to expand and refine the theoretical framework to provide a comprehensive analysis of the evolution of productivity The second step is to undertake historical and empirical research that documents how productivity evolves differently during credit booms that end in crises and those that do not. The third step is to take a policy perspective, with the aim of assessing how policymakers can distinguish elements of credit booms that make financial crises more likely to evolve.