Adverse selection and moral hazard in japan public credit guarantee schemes for SMEs
Kuniyoshi Saito, Daisuke Tsuruta 14 November 2014
In Japan, loans with 100% guarantees take into account more than half of most loans included in public credit guarantee schemes, but banks declare that they don’t offer loans without sufficient screening and monitoring even if the loans are guaranteed. This column presents proof adverse selection and moral hazard in Japanese credit guarantee schemes. The problem is less severe for loans with 80% guarantees.
Credit rationing due to capital market imperfections is widely viewed as a significant phenomenon in the loan market, specifically for small and medium enterprises (SMEs). Among other ways of alleviating the problem, credit guarantee schemes are the most important policy tools in lots of countries. An economic rationale for such public intervention is that it could enhance efficiency by giving additional funds for SMEs that are actually healthy but struggling to safe enough loans as a result of informational gap between lenders and borrowers.
Despite many empirical studies (e.g. Riding and Haines Jr 2001, Riding et al. 2007, Cowling 2010, Uesugi et al. 2010) that measure the good thing about credit guarantee schemes, empirical analyses on the price side of the policy are scarce. Two important costs of providing credit guarantees are adverse selection and moral hazard. Since credit guarantees insure banks against incurring losses from default, they are enticed to ask seemingly risky borrowers to use for credit guarantees. Also, because credit guarantee corporations cannot distinguish low-risk borrowers from risky ones, credit guarantee schemes attract a big part of risky borrowers, which results in inefficient resource allocation. This potential problem could possibly be especially grim in Japan, where in fact the proportion of 100% credit guarantees makes up about over fifty percent of the full total loans with credit guarantees.
Problems in Japanese credit guarantee schemes
The credit guarantee schemes in Japan involve some seemingly problematic features in the light of asymmetric information. First, public credit guarantee corporations (CGCs) mainly provide full credit guarantees. Until October 2007, the coverage rate in Japan was 100%, and 80% thereafter. However, for emergency guarantee programmes for the time October 2008 to March 2011, it returned to 100%. Therefore, a large part of guaranteed loans covers 100% of defaulted loans.
Second, the Japan Finance Corporation (JFC), that is a public corporation wholly owned by japan government, offers credit insurance that covers losses from subrogation. Coverage rates of credit insurance range between 70% to 80%, and therefore the CGCs themselves suffer little loss from subrogation. The JFC accepts all credit insurance for CGCs, implying that CGCs have only a weak incentive to monitor banks and smaller businesses. Notably, the JFC has suffered substantial losses in credit insurance accounts each year – for instance, 568 billion yen in fiscal year 2009 and 436 billion yen in fiscal year 2010.
Third, the rejection rate of credit guarantees is low, at approximately 10%, implying that a lot of credit guarantee applicants are accepted. As we’ve mentioned, this may be because of the fact that CGCs have weak incentives to screen small company applicants due to high coverage of credit insurance.
Finally, CGCs cannot collect sufficient soft information from applicants. Many reports (e.g. Berger et al. 2005) declare that soft information plays a significant role in assessing the credit threat of smaller businesses. Unlike banks, that may acquire soft information through relationship lending from continuous transactions, CGCs cannot, or usually do not, gather enough soft information, and for that reason need to rely only on hard information on smaller businesses. Moreover, banks that cannot measure the risks of smaller businesses have strong incentives to provide them guaranteed loans.
Testing for adverse selection and moral hazard
Using data on city, regional, and shinkin banks, in Saito and Tsuruta (2014) we apply the essential positive correlation test proposed by Chiappori and Salanie (2000) to research whether: (i) banks that transact with risky smaller businesses will offer loans with guarantees (adverse selection); and (ii) smaller businesses with guaranteed loans will default (moral hazard).
In both cases, a positive correlation is observed between your rate of loans with guarantees and ex-post default risk. As this correlation ought to be assessed within the band of observationally equivalent firms, we control for the consequences of observable variables with a seemingly unrelated regression (SUR).
Our findings are in keeping with the adverse selection and/or moral hazard hypotheses. The estimation results of the SUR model claim that the null hypothesis of no correlation between your rate of loans with guarantees and ex-post default risk is rejected at the 1% or 5% level for all banks, city and regional banks, and shinkin banks. These claim that our data are in keeping with the adverse selection and/or moral hazard hypotheses. Further analyses provide us some additional understanding of the role of self-payment in the general public credit guarantee schemes. For the 100% guarantee, we observe a positive and statistically significant correlation between your rate of loans with guarantees and ex-post default risk whatever the bank type. However, for the 80% guarantee, the email address details are slightly different. Correlation between your rate of loans with guarantees and ex-post default risk are positive, however, not statistically significant.
To research the non-linear relationships between your rate of loans with guarantees and ex-post default risk, we also estimate a partial linear model. Figures 1 to 3 show the results from the partial linear model. The plotted data are dispersed widely, but Figures 1 and 2 indicate a positive correlation between your rate of loans with guarantees and ex-post default risk for all samples and 100% guarantees. Figure 3 indicates that the slope for 80% guarantees is flatter than regarding 100% guarantees, indicating that the info problem is less severe due to the 20% self-payment.
Figure 1 . Partial linear model using all samples
Note: This figure supplies the estimates of a partial linear regression model with the quantity of loans with guarantees/amount of loans for smaller businesses (y) and the quantity of subrogation/amount of guarantees (z).
Figure 2 . Partial linear model using 100% guarantees
Note: This figure supplies the estimates of a partial linear regression model with the quantity of loans with 100% guarantees/amount of loans for smaller businesses (y) and the quantity of subrogation/amount of guarantees (z).
Figure 3 . Partial linear model using 80% guarantees
Note: This figure supplies the estimates of a partial linear regression model with the quantity of loans with 80% guarantees/amount of loans for smaller businesses (y) and the quantity of subrogation/amount of guarantees as the dependent variables (z).
We find statistically significant positive correlations between credit risk (subrogation rate) and the quantity of guaranteed loans, indicating a public credit guarantee programme is influenced by asymmetric information. Further investigation shows that the association between your subrogation rate and the ratio of guaranteed loans to total loans is stronger for 100% credit guarantees than for 80% credit guarantees, implying that the ‘20% self-payment’ criteria is working as a highly effective mechanism for alleviating the problem, but isn’t enough for eliminating it.
Some economists argue that, with out a rigorous empirical study, it really is obvious that japan credit guarantee scheme is severely suffering from adverse selection and moral hazard. Simultaneously, however, bank officers declare that banks usually do not offer loans without sufficient screening and monitoring even if the loans are credit-guaranteed. Given these differing opinions, we think that empirical analyses are crucial to assess whether adverse selection and/or moral hazard are detected in japan credit guarantee scheme. We also think that our study plays a part in the recent policy debate on whether CGCs should lower the rate of self-payment to under 80%. 1
Editor’s note: The primary research where this column is situated (Saito and Tsuruta 2014) first appeared as a Discussion Paper of the study Institute of Economy, Trade and Industry (RIETI) of Japan.
Berger, A N, N H Miller, M A Petersen, R G Rajan, and J C Stein (2005), “Does function follow organizational form? Evidence from the lending practices of large and small banks”, Journal of Financial Economics 76(2): 237-269.
Chiappori, P-A and B Salanie (2000), “Testing for Asymmetric Information in Insurance Markets”, Journal of Political Economy 108(1): 56-78.
Cowling, M (2010), “The role of loan guarantee schemes in alleviating credit rationing in the united kingdom”, Journal of Financial Stability 6(1): 36-44.
Riding, A L and Haines Jr, G (2001), “Loan Guarantees: Costs of Default and Advantages to Small Firms”, Journal of Business Venturing 16(6): 595-612.
Riding, A, J Madill, and G Haines (2007), “Incrementality of SME Loan Guarantees”, SMALL COMPANY Economics 29(1): 47-61.
Uesugi, I, K Sakai, and G Yamashiro (2010), “The potency of Public Credit Guarantees in japan Loan Market”, Journal of japan and International Economies 24(4): 457-480.
1 See Nihon Keizai Shimbun (Nikkei), p.5 each morning problem of 2 June 2014.