Credit Booms, Aggregate Demand, and Financial Crises
Sunday, Jan. 7, 2018 1:00 PM - 3:00 PM
- Chair: Luc Laeven, European Central Bank
How Do Credit Supply Shocks Affect the Real Economy? Evidence from the United States in the 1980s
AbstractWe study the business cycle consequences of credit supply expansion in the U.S. The 1980’s credit
boom resulted in stronger credit expansion in more deregulated states, and these states experience
a more amplified business cycle. A new test shows that amplification is primarily driven by the
local demand rather than the production capacity channel. States with greater exposure to credit
expansion experience larger increases in household debt, the relative price of non-tradable goods,
nominal wages, and non-tradable employment. Yet there is no change in tradable sector employment.
Eventually states with greater exposure to credit expansion experience a significantly deeper
Identifying Banking Crises: A Bank Equity Based Approach
AbstractWe identify historical banking crises in 47 countries over the period 1800 - 2016 using new historical data on bank equity returns. We argue bank equity crashes provide an objective, quantitative, and theoretically‐motivated measure of banking crises, which can help refine existing historical approaches. We show that bank equity crashes often pick up an impending crisis first, before credit and non‐financial equity measures. We validate our measure by showing that bank equity crashes line up well with other indicators of banking crises (e.g., panics, bank failures, government intervention) and predict the severity of crises. Our approach also uncovers some “new” banking crises not identified by previous historical approaches but which are backed up by the historical narrative. Bank equity returns provide additional forecasting power of macroeconomic outcomes relative to traditional predictors.
When to Lean Against the Wind
AbstractThis paper shows that policy-makers can distinguish between good and bad credit booms with high accuracy and they can do so in real time. Evidence from 17 countries over nearly 150 years of modern financial history shows that credit booms that are accompanied by house price booms and a rising loan-to-deposit-ratio are much more likely to end in a financial crisis. We evaluate the predictive accuracy for different classification models and show that the characteristics of the credit boom contain valuable information for sorting the data into good and bad booms. Importantly, we demonstrate that policymakers have the ability to spot dangerous credit booms on the basis of data available in real time. We also show that these results are robust across alternative specifications and time-periods.
International Monetary Fund
Bank of Finland
Johns Hopkins University
- E3 - Prices, Business Fluctuations, and Cycles
- G2 - Financial Institutions and Services