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One proxy of price rationing of credit is an aggregation of information on interest rates, while loan officer survey data measures quantity rationing of credit, meaning some borrowers are denied loans. The latter Granger causes real GDP but the former does not. The loan officer survey is a better leading indicator of credit market conditions that affect real activity.
In the aftermath of the crisis in 2008, the idea that credit market conditions affect real activity is undeniable, but the best measure of contemporaneous credit market conditions remains an open question. A natural measure is the cost of borrowing given by various interest rates. Recently, the Federal Reserve Bank of St. Louis has published an indicator of credit market stress that is primarily an aggregation of interest rates and spreads.
While undoubtedly important, interest rates cannot fully explain credit market conditions, particularly during a crisis. The survey of loan officers by the Board of Governors of the Federal Reserve provides a more qualitative measure of lending standards. Whether the credit market stress indicator or the survey data on lending standards has more explanatory power for real activity is the primary goal of the present work.
Waters [
In the dynamic stochastic general equilibrium (DSGE) model developed in Waters [
The fraction of loan officers who report a tightening of lending standards is a natural proxy for quantity rationing. Lown and Morgan [
Interest rate spreads have been used to forecast the state of the economy. A commonly held belief is that a downward sloping yield curve forecasts recessions. Such relationships have been given formal support by Estrella and Mishkin [
The contribution of this paper is to estimate a properly specified VAR that can determine whether the credit market stress indicator of the survey of lending standards has greater explanatory power for real economic activity. There are a number of indicators for financial markets, surveyed in Kliesen, Owyang and Vermann [
The primary empirical finding is that the lending standards data from the survey of loan officers is a leading indicator while the credit market stress indicator is not. The series TIGHT, the percentage of loan officers reporting a tightening (or loosening) of lending standards
Inspection of the graphs in
Time series graphs of the endogenous variables over the sample 1993Q42013Q1. DIFFLOGRGDP is the log difference of real GDP for the U.S. STLFSI is the St. Louis Fed stress indicator, and TIGHT is the percentage of loans officer reporting a tightening of standards.
Each row contains results of the Augmented DickeyFuller test. The number of lags was chosen according to the Akaike criterion.
lags  t  statistic  prob  


1  −3.38  0.01 

1  −3.14  0.03 

3  −3.20  0.02 
Preliminary examination of the crosscorrelograms in
CrossCorrelogram with lags and leads on the xaxis. See
CrossCorrelogram with lags and leads on the xaxis. See
CrossCorrelogram with lags and leads on the xaxis. See
Estimation of the unrestricted VAR shows considerable autocorrelation in the residuals requiring the inclusion of at least seven lags
Each statistic (not in parentheses) is the test for whether to column variable Granger causes the dependent variable in the row. The numbers in parentheses are pvalues for the null of no causality.
DIFFLOGRGDP  STLFSI  TIGHT  


4.67  22.36  
(0.700)  (0.002)  

12.83  15.09  
(0.076)  (0.035)  

5.08  4.40  
(0.650)  (0.733) 
As noted above, TIGHT Granger causes DIFFLOGRGDP at a high level of significance, but STLFSI does not at any reasonable level of significance. Lending standards and quantity rationing of credit are much more important than lending costs for explaining fluctuations in real activity. The lending standards variable and the log difference of real GDP both Granger cause STLFSI. The credit market stress indicator is correlated to the other variables, but the lending standards variable has much more explanatory power. Change in the ordering of the variables does not make any qualitative difference in the results.
Graphs of the impulse response functions and variance decomposition in
Impulse response functions for the three variable VAR with seven lags. The red lines are 5% confidence intervals.
Variance decomposition results for the three variable VAR with seven lags. The red lines are 5% confidence intervals.
The results show evidence that quantity rationing of credit is a key determinant in the relationship between financial markets and the real economy. Price rationing, as measured by interest rates, remains closely correlated with macro variables, but the present work shows that lending standards as represented by the loan officer survey data has greater importance as a leading indicator.
See Lown and Morgan [
The St. Louis Fed’s Financial Stress Index is a composite of seven interest rates, six interest rate spreads, two volatility indices, a bond fund, and financial equities index and the spread between the 10year U.S. Treasury and TIPS bonds. See [
The choice of seven lags is made according to the sequential modified likelihood ratio test. Furthermore, the Portmanteau test statistic is 16.67, meaning the null hypothesis of no autocorrelation in the residuals cannot be rejected at the 5% level for up to 7 lags.
The author declares no conflict of interest.