THEAMERICAN ECONOMIC REVIEW MARCH 2009 income and with the number of dependents, closely mirroring the federal earned income tax credit schedule. Second, we find that demand is highly responsive to changes in minimum down payment requirements. A S100 increase in the required down payment, holding car prices fixed, reduces demand by 9 percent. In contrast, generating the same reduction in demand requires an increase in car prices of almost $3,000. We calculate that in the absence of borrowing con straints, rationalizing these effects requires an annual discount rate of 1, 415 percent. These findings raise the question of whether consumer liquidity constraints can be tied to underlying credit market conditions. One possibility is that high default rates, coupled with legal caps on interest rates, simply rule out some forms of lending. A second possibility is that funda mental features of the consumer credit market are responsible. We focus on the latter, turning to the information economics view of credit markets as developed by Jaffee and Thomas Russell (1976)and Stiglitz and Andrew Weiss(1981) Modern information economics emphasizes that credit constraints can arise in equilibrium even if financing terms can adjust freely and lenders are fully competitive. Its explanation lies in the problems of moral hazard and adverse selection. In the moral hazard version of the story, individual borrowers are more likely to default on larger loans. This leads to problems in the loan market because borrowers do not internalize the full increase in default costs that come with larger loan sizes. As a result, lenders may need to cap loan sizes to prevent overborrowing In contrast, adverse selection problems arise if borrowers at high risk of default also desire large loans, as might be expected given that they view repayment as less likely. As the theoretical literature has pointed out, adverse selection can give rise not only to loan caps, but also to some worthy borrowers being denied credit. 2 The second half of the paper explores these ideas, first from the standpoint of theory and then empirically In Section Ill we present a simple model of consumer demand for credit and competitive lending, along the lines of Jaffee and Russell(1976). We show that such a model can explain many of the institutional features we observe on the lender side of the market, such as the adoption of credit scoring and risk-based pricing, and the use of interest rates that increase with loan size. We also explain why informational problems, compounded by interest rate caps, cre- ate a rationale for lenders to limit access to credit. The model therefore provides a simple credit market-based explanation for why purchasing behavior might reflect liquidity constraints. Having outlined the theoretical framework, we investigate the empirical importance of moral hazard and adverse selection for subprime lending. Separately identifying these two forces is often a challenge because they have similar implications: both moral hazard and adverse selec tion imply a positive correlation between loan size and default. A useful feature of our data is that we can exploit exogenous( to the individual) variation in car price and minimum down pay ment to isolate the moral hazard effect of increased loan size on default. This in turn. allows us to back out a quantitative estimate of self-selection from the cross-sectional correlation between loan size and default. We explain the econometric strategy in detail in Section IV. We find compelling evidence for both moral hazard and adverse selection. We estimate that for a given borrower, a $1,000 increase in loan size increases the rate of default by 16 percent. This alone provides a rationale for limiting loan sizes because the expected revenue from a loan is not monotonically increasing in the size of the loan. Regarding adverse selection, we find that borrowers who are observably at high risk of default are precisely the borrowers who desire the I If s denotes the discount rate, the discount factor is 1/(1 +s). So an annual discount rate of 1, 415 percent implies an annual subjective discount factor of less than 0.07. Such an individual is indifferent between paying $100 today and The fact that imperfect information in the credit market leads to limits on lending is analogous to Michael Rothschild and Stiglitz,s(1976)famous observation that imperfect information in an insurance market may lead to underinsurance relative to the full-information optimum50 THE AMERICAN ECONOMIC REVIEW March 2009 income and with the number of dependents, closely mirroring the federal earned income tax credit schedule. Second, we find that demand is highly responsive to changes in minimum down payment requirements. A $100 increase in the required down payment, holding car prices fixed, reduces demand by 9 percent. In contrast, generating the same reduction in demand requires an increase in car prices of almost $3,000. We calculate that in the absence of borrowing con￾straints, rationalizing these effects requires an annual discount rate of 1,415 percent.1 These findings raise the question of whether consumer liquidity constraints can be tied to underlying credit market conditions. One possibility is that high default rates, coupled with legal caps on interest rates, simply rule out some forms of lending. A second possibility is that funda￾mental features of the consumer credit market are responsible. We focus on the latter, turning to the information economics view of credit markets as developed by Jaffee and Thomas Russell (1976) and Stiglitz and Andrew Weiss (1981). Modern information economics emphasizes that credit constraints can arise in equilibrium even if financing terms can adjust freely and lenders are fully competitive. Its explanation lies in the problems of moral hazard and adverse selection. In the moral hazard version of the story, individual borrowers are more likely to default on larger loans. This leads to problems in the loan market because borrowers do not internalize the full increase in default costs that come with larger loan sizes. As a result, lenders may need to cap loan sizes to prevent overborrowing. In contrast, adverse selection problems arise if borrowers at high risk of default also desire large loans, as might be expected given that they view repayment as less likely. As the theoretical literature has pointed out, adverse selection can give rise not only to loan caps, but also to some worthy borrowers being denied credit.2 The second half of the paper explores these ideas, first from the standpoint of theory and then empirically. In Section III we present a simple model of consumer demand for credit and competitive lending, along the lines of Jaffee and Russell (1976). We show that such a model can explain many of the institutional features we observe on the lender side of the market, such as the adoption of credit scoring and risk-based pricing, and the use of interest rates that increase with loan size. We also explain why informational problems, compounded by interest rate caps, cre￾ate a rationale for lenders to limit access to credit. The model therefore provides a simple credit market–based explanation for why purchasing behavior might reflect liquidity constraints. Having outlined the theoretical framework, we investigate the empirical importance of moral hazard and adverse selection for subprime lending. Separately identifying these two forces is often a challenge because they have similar implications: both moral hazard and adverse selec￾tion imply a positive correlation between loan size and default. A useful feature of our data is that we can exploit exogenous (to the individual) variation in car price and minimum down pay￾ment to isolate the moral hazard effect of increased loan size on default. This, in turn, allows us to back out a quantitative estimate of self-selection from the cross-sectional correlation between loan size and default. We explain the econometric strategy in detail in Section IV. We find compelling evidence for both moral hazard and adverse selection. We estimate that for a given borrower, a $1,000 increase in loan size increases the rate of default by 16 percent. This alone provides a rationale for limiting loan sizes because the expected revenue from a loan is not monotonically increasing in the size of the loan. Regarding adverse selection, we find that borrowers who are observably at high risk of default are precisely the borrowers who desire the 1 If s denotes the discount rate, the discount factor is 1/11 1 s2. So an annual discount rate of 1,415 percent implies an annual subjective discount factor of less than 0.07. Such an individual is indifferent between paying $100 today and $1,515 in a year. 2 The fact that imperfect information in the credit market leads to limits on lending is analogous to Michael Rothschild and Stiglitz’s (1976) famous observation that imperfect information in an insurance market may lead to underinsurance relative to the full-information optimum