We show that banks use industry knowledge acquired through corporate lending in mortgage lending, a phenomenon we refer to as the “industry expertise channel.” Specifically, banks that specialize in particular industries expand their mortgage lending activity in regions where those industries are concentrated. The impact of industry expertise increases with information asymmetry and borrower risk. In addition, mortgages originated from this channel contain more soft information and perform better. The effect of the channel increases after unexpected industry distress and the 2008 financial crisis, suggesting that the effect is likely causal.

We propose a Cramér–von Mises–type test for testing whether the mean potential outcome given a specific treatment level has a weakly monotonic relationship with the continuous treatment under unconfoundedness. To flexibly control for a possibly high-dimensional set of covariates, our test is based on a double debiased machine learning method. We show that our test controls asymptotic size and is consistent against any fixed alternative. We apply our test to evaluate the Job Corps program and reject a weakly negative relationship between the treatment (hours in academic and vocational training) and labor market performance among relatively low treatment values.