We focus on the supply of credit (the bank lending channel) and the ultimate effect on borrowers (the credit channel), but also examine how the shock affects banks’ overall risk profile and security holdings.
Our shock is derived from variation across banks in their loan exposure to industries adversely affected by the precipitous oil price declines of 2014.
We also find that innovations to news sentiment predict future economic activity.
While affected banks substantially de-risked their portfolios through adjusting their residential lending in this way, we again find that the ultimate effect on borrowers was minimal.
Fixing the exchange rate constrains monetary policy.
Affected banks tightened credit on mortgages that they would ultimately hold in their portfolio but appear to have expanded credit for those mortgages that would predominantly be securitized.
This tendency is reflected in a contemporaneous expansion in their holdings of MBS after the shock.
We reach this startling conclusion using newly collected data on the liability side of banks’ balance sheets in 17 countries.
A solvency indicator, the capital ratio has no value as a crisis predictor; but we find that liquidity indicators such as the loan-to-deposit ratio and the share of non-deposit funding do signal financial fragility, although they add little predictive power relative to that of credit growth on the asset side of the balance sheet. labor market unemployed individuals that are actively looking for work are more than three times as likely to become employed as those individuals that are not actively looking for work and are considered to be out of the labor force (OLF).For some of these economic outcomes, there is evidence that the news sentiment measures have significant predictive power even after conditioning on these survey-based measures.We document novel, economically important correlations between children’s future credit risk scores, default, and homeownership status and their parents’ credit characteristics measured when the children are in their late teens.We use a simple model to relate this “missing growth” to the frequency and size of various kinds of innovations. The first approach exploits information on the market share of surviving plants.The second approach applies indirect inference to firm-level data.We do not find significant evidence of a credit channel.