By Andrea Ajello
How important are financial friction shocks in business cycles fluctuations? To answer this question, I use micro data to quantify key features of US financial markets. I then construct a dynamic equilibrium model that is consistent with these features and fit the model to business cycle data using Bayesian methods. In my micro data analysis, I establish facts that may be of independent interest. For example, I find that a substantial 33% of firm investment is funded using financial markets. The dynamic model introduces price and wage rigidities and a financial intermediation shock into Kiyotaki and Moore (2008). According to the estimated model, the financial intermediation shock explains around 40% of GDP and 55% of investment volatility. The estimation assigns such a large role to the financial shock for two reasons: (i) the shock is closely related to the interest rate spread, and this spread is strongly countercyclical and (ii) according to the model, the response in consumption, investment, employment and asset prices to a financial shock resembles the behavior of these variables over the business cycle.
This is the latest in a new direction for business cycle models where the model itself is used to estimate the shock process, the goal being to figure out with shocks are more important. Contrast this with the traditional literature that tried to see how far one could get with an exogenously calibrated shock or two. And this particular exercise shows that financial frictions are important. Of course, this result could disappear by applying the same data to a different model, but the fact that one needs such shocks to obtain countercyclical interest rate spreads is quite compelling.