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    银行信贷标准[文献翻译].doc

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    银行信贷标准[文献翻译].doc

    原文 Bank Credit Standards By Mitchell BerlinBankers and the business press often speak of cycles in bank credit standards, periods in which banks lending standards are too lax, followed by periods in which standards are too stringent. In this view, bank lending policies tend to amplify fluctuations in GDP;easy money during the upturn sows the seeds of tight money episodes in the downturn. But this pattern is also consistent with variations in bank lending driven by changes in borrowers default risk over the business cycle or changes in the demand for loans, which rises and falls with GDP. To make sense of the idea of a lending cycle, we must uncover a systematic reason for banks to make unprofitable loans in an upturn and to forgot profitable loans in a downturn. I emphasize that the tendency must be systematic to distinguish the idea of a credit cycle from the truism that loans made near the peak of an expansion are more likely to go bad simply because bankers (just like economists and other businessmen) have difficulties predicting downturns. What is the evidence for an independent effect for changing bank lending standards that is, a systematic reason why banks might be too lax or too stringent? And what factors might explain this type of behavior? Economists have proposed a number of plausible models of a bank lending cycle, emphasizing changes in bank capital, competition, or herding behavior. To date, only the channel relating changes in bank capital to lending standards has firm empirical support.The available evidence is too weak to give us much confidence in assigning an important role for other theories of bank lending standards. WHAT ARE CREDIT STANDARDS? It is helpful to be a little clearer about what we mean by a change in bank credit standards. Lets begin with a straightforward prescription from investment theory: A profitmaximizing bank should make any loan with a positive net present value (NPV). The NPV of a loan is just the sum of discounted future repayments (principal plus interest) on the loan minus the loan amount. Future repayments must be discounted for two different reasons: First, $10 in the bank now is worth more than $10 paid a year from now. After all, the bank could receive a years interest by purchasing Treasury bills on the $10 paid back tomorrow. Second, the bank recognizes that the borrower may default in the future, so the bank may never receive some future payments. The firm may have a healthy balance sheet at the time the loan is made; a year from now, the borrowing firm may suffer financial setbacks and may be unable to pay back its loan. Using this framework, we can define a change in bank credit standards as a change in a banks loangranting decisions for some reason other than a change in the NPV of the loan. We can define a credit cycle as a systematic tendency to fund negative NPV loans during an expansion and a systematic tendency to reject positive NPV loans during a contraction. Since bankslending decisions also involve the pricing and design of loan contracts, a credit cycle might also take the form of a systematic tendency to relax or tighten loan terms by more than would be justified by changes in borrower risk. Conceptually, it is not too difficult to define a credit cycle. Empirically, it may be much harder to tell whether one has occurred. For example, think about some of the things that happen in an economic downturn. As economic conditions become more difficult, more firms experience economic difficulties and the probability that a firm will default increases. This reduces the NPV of a given stream of repayments and would probably induce the bank to raise the loan rate, impose new contractual restrictions, or refuse to make the loan at all. While these actions might be interpreted as a tightening of standards by an outside observer or by an aggrieved borrower, credit standards havent changed according to our definition. Figures 1a and 1b illustrate the distinction between the effects of a tightening of credit standards and the effects of an increase in credit risk. Figure 1a shows a probability distribution of loan applicants NPVs. The profit-maximizing rule for a bank is to make a loan as long as its NPV is positive (the sum of the shaded regions). If the bank tightens its credit standards, for example, making only loans with an NPV greater than $A, the bank will make a smaller number of loans (just the darker region). Figure 1b illustrates the effects of a downturn: Loans become riskier and the distribution of NPVs shifts to the left. But this figure shows a bank that retains the profit-maximizing rule. Note that the number of loans made falls in this case also (from the sum of the shaded regions to just the darker region). Slightly more subtly, in a downturn many loans often go bad at once. Typically, a bank will charge a borrower a higher loan rate if the borrower is likely to default at the same time as other borrowers in a banks portfolio default. To see this, consider a Detroit bank that has a portfolio with a high concentration of loans to auto parts suppliers. This bank is evaluating two prospective loans with identical probabilities of default. One of the loans is to an auto parts supplier, and the other is to a department store. Even though the probability of default is identical for both projects, the bank will not charge the same default risk premium to both. Instead, the bank will charge a higher risk premium for the loan to the auto parts supplier because its performance is more highly correlated with the rest of the banks portfolio. Taking this idea a step further, economists have found that firms defaults tend to be correlated.Thus, we should not be surprised that a bank would demand a higher premium for default risk in a downturn as compensation for the higher probability that many loans will go bad at the same time. Although the bank has charged borrowers a higher price for bearing risk, this should not be viewed as a change in credit standards. In an economic downturn, nonfinancial firms also cut back on investments in plant and equipment and inventories, and, in turn, they cut back on borrowing. A decline in the demand for loans should certainly not be viewed as a change in bank credit standards. We can see the empirical challenge in identifying an independent effect for lending standards on the quantity of loans. Consider an economic downturn. In a downturn, default risk increases, risks become more correlated, and the demand for loans declines. None of these factors reflects a change in lending standards, but all lead to a decline in the quantity of loans made. To uncover a lending cycle, the researcher must find some way todisentangle the effects of changing lending standards from these other effects. THE BROAD FACTS Economists have documented a number of empirical observations that are broadly consistent with the existence of a lending cycle.The first empirical observation is that declines in bank capital are associated with declines in bank lending. Ben Bernanke and Cara Lown (among many others) have found evidence that large negative shocks to bank capital (such as those experienced by banks in New England at the end of the 1980s )are associated with declines in bank lending. The relationship between capital and lending is a robust empirical finding, but since the weak economic conditions associated with a decline in bank capital are also associated with higher default risk, more correlated risks, and a decline in loan demand, economists have had to be ingenious in providing compelling evidence for the capital channel (as I discuss in the next section). A second observation is the well-documented flight to quality during economic downturns. For example, William Lang and Leonard Nakamura show that bank portfolios shift from high- to low-risk loans during a downturn; specifically, they show that bank portfolios shift away from loans made above the prime rate. Their finding is consistent with evidence that during a downturn, banks systematically shift their portfolios toward larger borrowers and toward borrowers with pre-existing loan commitments.While these studies shed light on the ways that bank lending may amplify negative economic shocks, the observed portfolio shifts may simply reflect a rise in default risk during an economic downturn, rather than an independent role for lending standards, according to our definition. With a rise in default risk, some borrowers are shut out of public debt markets and shift toward bank borrowing, while bank portfolios shift toward lower risk borrowers. A third observation is that loan terms vary systematically over the business cycle in a way that may amplify economic fluctuations. Patrick Asea and Asa Blomberg find that commercial loan markups (the spread between the loan rate and the rate on a riskless Treasury security) fall continuously right up to the beginning of a recession. Their interpretation of this finding is that credit standards are excessively easy at the end of an expansion, sowing the seeds of future portfolio problems. Jianping Mei and Anthony Saunders provide evidence of trendchasing behavior by banks. They find that banks increase real estate lending when past real estate returns are high, but that bank real estate investments are unprofitable, on average. These results are consistent with a systematic tendency for excessively lax credit standards during an expansion, and they may also be evidence of a tendency for banks to invest in a herd-like manner. However, the evidence from commercial lending and real estate lending markets may simply mean that banks have difficulty predicting a downturn (just like everyone else). Thus, banks may continue lending strongly even as the downturn begins. The most direct evidence for a direct role for bank credit standards comes from survey results. Cara Lown and Donald Morgan analyze the Federal Reserve Boards Senior Loan Officer Opinion Survey, in which bankers are asked periodically whether they changed their credit standards in the previous three months. They are also asked to explain how their standards changed, e.g., changes in collateral requirements, covenants, and loan markups, as well as the underlying reasons for any change. Using a statistical analysis called a vector autoregression (VAR), Lown and Morgan find that changes in credit standards (as measured by survey responses) have a significant effect on both the quantity of bank loans and GDP.Interestingly, changes in GDP do not have a significant effect on lending standards, suggesting an independent role for credit standards. While this is perhaps the most convincing evidence that changes in bank credit standards have an independent effect, Lown and Morgan do not provide evidence that banks systematically choose excessively lax or risky lending standards. To sum up, there is survey evidence of an independent role for bank credit standards, and a number of empirical observations are broadly consistent with the existence of a lending cycle. Making further progress requires a theoretical framework that would permit us to disentangle the various effects on banks lending behavior. CAPITAL CONSTRAINTS LEAD BANKS TO TIGHTEN STANDARDS Bank Lending Is Limited by Bank Capital. A wide range of models show that a firms investments in plant, equipment, and inventories are limited by the firms capital, i.e., the funds committed by the firms owners. A bank is just a particular type of firm, but instead of investment in goods and machines, its main investments are loans. While the precise link between capital and investment differs from model to model, the element common to all of them is that agency problems limit firms access to outside funding. In our context, the term “agency problem” refers to a conflict of interest between a firms insiders owners and top managers, who are influential in a firms decision-making and outside investors depositors, bondholders, and perhaps small stockholders, who control only their willingness to provide funds. For example, in Bengt Holmstrom and Jean Tiroles model, the banks insiders have a choice between carefully monitoring borrowers and avoiding the costs of monitoring. A carefully monitored loan has low risk and positive NPV; a loan that is not monitored has a high risk of default and a negative NPV. The underlying agency problem is that a firms insiders will forgo monitoring and make high-risk loans unless they receive a sufficiently large share of the total profits.But providing insiders with incentives to monitor limits the share of the returns left over for outside investors, who will refuse to provide funds unless their own expected rate of return is adequate. The role of bank capital in all this is that a firms insiders have a stronger incentive to engage in costly monitoring of loans when more of their own funds are at risk, i.e., when bank capital is higher. Outside investors will refuse to provide funds to banks that are not well-capitalized.In Holmstrom and Tiroles model, a bank with insufficient capital may be unable to convince outside investors to fund loans that would have positive NPV if the bank could make a credible guarantee to monitor. When Bank Capital Falls, Banks Tighten Lending Standards. Loan losses are countercyclical; in particular, in an economic downturn, more borrowers default and loan losses increase (Figure 2). Higher loan losses reduce bank capital, and the availability of outside financing also decreases. In turn, banks may be forced to forgo loans with positive NPV (if properly monitored); that is, banks will have excessively tight lending standards. Most models that focus on the link between capital and the availability of outside funds focus on economic capital, but similar limits on lending arise if regulators limit bank lending when loan losses press banks against regulatory capital requirements. Note that this model predicts that capital shortages will restrict lending but it doesnt predict that banks would ever have excessively lax credit standards. That is, according to Holmstrom and Tirole, banks will forgo positive NPV loans when access to outside funds is restricted because their capital is low, but high bank capital doesnt increase the likelihood that a bank will make a negative NPV loan. Empirical Evidence for the Capital Channel. A large empirical literature documents the effect of negative shocks to banks capital on bank lending. In particular, a number of studies of the 1990-92 credit crunch in the U.S. show that declines in bank capital were systematically associated with declines in bank lending, consistent with the statements of bankers, borrowers, and bank re

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