The credit supply effect on commercial real estate loans in commercial banks.

摘要

In commercial real estate lending two general theories attempt to address the reasons for default---interest rates or credit supply. The interest rate theory suggests that higher interest rates will reduce the number of borrowers, thereby reducing the defaults. The credit supply theory suggests that when too much credit is available, defaults increase. The significance of this paper is that it will add research on the commercial real estate loan defaults in the commercial banking industry to determine if the credit supply effect is present in commercial banking.; Ten hypotheses were tested to explore the relationships between outstanding commercial real estate loans, interest rates, and loan delinquency in commercial banks in the United States. The hypotheses focus on the major relationships affecting nonperforming loans---the Outstanding Loan Volume, the Credit Spread, the Prime Rate, the Average Vacancy Rate, and the Unemployment Rate. The impact on the Outstanding Loan Volume by the Prime Rate, the Average Vacancy Rate, the Unemployment Rate, the Credit Spread, and the Delinquency Rate will all be examined to test the strengths of relationships influencing the independent variables.; The results indicated that a relationship existed in nine of the ten hypotheses. The study concluded that the credit supply effect exists in commercial banks for commercial real estate loans, and is significantly correlated to delinquency rates. From the variables considered in this study, the highest correlations with the delinquency rates were the vacancy rate, the outstanding loan volume, and the unemployment rate. Likewise these same variables had the highest correlations to the outstanding loan volume with the addition of the credit spread.; To further enhance the analysis, specific rates charged to borrowers could be incorporated, as well as using specific geographic and property type market vacancy rates and local unemployment rates. By doing so, lenders could have better tools to predict loan delinquencies in their specific lending markets.