Bank credit allocation depends on the demand for credit. However, the availability of data on bank credit is limited, especially for Latin America. Moreover, few banks report loan maturity data in commercial data sets. To address this problem, the authors compiled a novel data set covering 21 Latin American and Caribbean countries during 2004-14. They later extended coverage to more than 100 countries. This study is one of the first to use such a data set for credit allocation.
Bank credit allocation is a key indicator of financial conditions. It can help predict the direction of financial conditions and corporate spreads. In particular, riskier allocation is associated with lower financial conditions. The authors also noted that risky credit allocation has characteristics of a risk sentiment indicator. In addition, they found evidence that behavioral biases influence the relationship between riskiness and future growth. They concluded that the association is stronger when financial conditions are loose.
The allocation of credit also responds to shocks to the banking system. For example, the entry of a low-cost competitor can lead to a change in credit allocation. This can cause banks to become more risky. Further, this can result in poorer quality of borrowers. This means banks should focus on lending to sectors with a lower risk profile.
While there is no consistent evidence of a relationship between riskiness and long-term growth, the patterns of credit riskiness are consistent with the cyclicality of financial conditions. In Japan, for example, the decline in corporate leverage in the early 2000s coincides with the phenomenon of zombie lending. In the United States, in contrast, corporate leverage increased across the board from 2010 to 2016, with the largest firms reporting the highest levels of debt.
The key issue for banks is the risk of non-performing loans. However, this should not cause undue worry. The risk of default is low but banks should consider the risk of default and stickiness when determining loan portfolio composition. For example, the riskiness of loans may be low if banks make loans to firms within the same economic group.
According to the fragility channel hypothesis, banks with high market power have greater incentive to invest in the acquisition of borrower information. Consequently, firms with more important bankfirm relationships suffer more from the change in credit supply. When the bank’s market power falls, the availability of bank credit and the amount of liquidity creation decreases.
Lastly, households with political connections are more likely to be approved for loans. They may self-select in the application process because they feel confident about their ability to obtain a loan from the bank. Banks may use this information to determine how much credit to give each sector. For instance, households with close political connections have higher chances of receiving a bank loan than households with weak political ties.