Information Losses in a Dynamic Model of Credit

type="main" xml:lang="en"> <title type="main">ABSTRACT</title> <p>This paper examines dynamic information losses associated with loan terminations. We assume that the aggregated returns of current borrowers contain information about the mean returns to future borrowers. In a competitive loan market, the value of this information is not fully internalized by individual borrowers and lenders, and loan decisions fail to be first best. Introducing heterogeneous borrowers, who know their own risk characteristics better than lenders, safer borrowers are less willing to borrow when risk premia rise. As they cease borrowing, the information generated in credit markets becomes noisier and this tends to increase risk premia. The model produces alternating and persistent periods of “tight” and “loose” credit.