Do the Macroeconomy & Credit Industry Move Together?


To demonstrate the close connection between macroeconomic variables and the credit industry, let us build a simple regression model. If, using only macroeconomic variables, we can build a model that closely follows, for example, industry wide default rates, then we can estimate just how important following economic indicators is for lenders.

Little research exists that includes macroeconomic (e.g. unemployment, interest rates) variables when modeling lending default rates. As such, this paper builds an econometric model for forecasting credit card default rates from scratch. A study performed in the UK (Bellotti and Crook, 2009), found that Ordinary Least Squares (OLS) regression models with macroeconomic variables perform best for forecasting credit card default at both portfolio and account level so that this is the method used herein. As the longest time series data for credit card defaults is available for the US, the data for that country is used and shown below. The variables included in the model are described in Table 2 below. The economic rationale for their inclusion is included as well.




The final best fit specifications for the default rate, or charge-off rate, model are given in Table 3. Default rate sensitivity to various macroeconomic variables is clearly listed here. Model Specification-1 and Model Specification-2 contain only macroeconomic variables. Model Specification-3 also includes aggregate credit card delinquency rates as an input, which improves overall model fit from an R2 = 72.5% to R2 = 80.0%. So what does all this mean?

Simply put, macroeconomic variables on their own can be shown to account for the majority of charge off rate changes (72.5% in model specification-2). If we cheat a bit and add an arguably microeconomic indicator such as delinquency rates, the model R2 only improves by ~7% (model specification-3). Macroeconomics matter to individual lenders.  

So how can lenders use them? One idea is to use macroeconomic indicators as timing tools for judging risk on and risk off time periods for lending. Lending strategies could also be different for such different periods.

Lending Standards, Delinquencies, & Charge-Offs

What happens  first in a crisis? Tightening standards lead delinquencies and charge-offs. When tightening standards cross above zero, expect increasing delinquencies and charge-offs. When delinquencies peak, expect a falling charge-off environment.


Interest Rates & Charge-Off Rates

 As we saw from the simple regression model above, rising central bank interest rates do not negatively impact charge-off rates. In fact, there’s a negative relationship between the two. It is only when central bank interest rate peak and begin their move downward, should lenders expect rising default rates.


Productive Loans & Recessions

As already described in detail in the theoretical section above, productive investment drives economic growth. Whenever the growth of such loans is above zero, the economy is expanding. However, towards the peak of the expansion cycle lenders observe increasing tightening standards and charge-offs. These are good early warning signals before productive loans expansion goes negative.

As a general rule then, lenders should expand business after productive loans growth has bottomed and credit standards have crossed below the zero line from above. Conversely, they should reign in loan issuance when productive loans have been above zero for a while and loan standards have crossed above the zero line from below.