Information Losses in a Dynamic Model of Credit

Authors

  • WILLIAM W. LANG,

    Visiting ScholarSearch for more papers by this author
  • LEONARD I. NAKAMURA

    Search for more papers by this author
    • Lang is from Rutgers University and is a Visiting Scholar in the Research Department of the Federal Reserve Bank of Philadelphia. Nakamura is from Rutgers University and the Federal Reserve Bank of Philadelphia. The authors would like to thank Deborah Lucas, Eugene White, and seminar participants at Rutgers, Princeton, and the Philadelphia Fed. The views expressed herein are solely those of the authors and do not necessarily represent the views of the Federal Reserve Bank of Philadelphia or of the Federal Reserve System.


ABSTRACT

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.

Ancillary