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Asymmetric information and imperfect competition in lending markets

Many studies argue that asymmetric information plays a key role in lending markets. This column presents new evidence on asymmetric information and imperfect competition on the Italian lending market. An increase in adverse selection causes most of the prices in the sample to increase, most of the quantities to fall, and most of the defaults to rise. However, there is substantial heterogeneity in the response to a rise in adverse selection. Market power could be an explanation why some markets can absorb such shocks better than others. 

Asymmetric information and lending markets

Following the seminal work of Stiglitz and Weiss (1981), a large theoretical literature has stressed the key role of asymmetric information in lending markets. A majority of studies shows that asymmetric information can generate market failures such as credit rationing, inefficient provision, mispricing of risk, and, in the limit, market breakdown. Moreover, a financial crisis can exacerbate the negative effects of adverse selection and moral hazard in financial markets (Mishkin 2012). Deepening our understanding of the extent and effects of asymmetric information is key for the design of a regulatory framework that limits their negative consequences. The theory has analysed the effects of asymmetric information mostly under the assumption of a perfectly competitive credit market, an assumption that is not likely to hold in many relevant markets. Correspondingly, there is no clear evidence of the effects of the interaction of asymmetric information and imperfect competition in lending markets.

New evidence

In our paper (Crawford et al. 2015), we measure the consequences of asymmetric information and imperfect competition in the Italian market for small business lines of credit. We show that the degree of competition in local credit markets can have significant consequences on the equilibrium effects of an increase in adverse selection. Intuitively, with perfect competition banks set the price equal to the average cost. When adverse selection increases, the price also rises, as a riskier pool of borrowers implies higher average costs in the form of more defaults. When banks exert market power, however, greater adverse selection can lower prices, as it implies a riskier pool of borrowers at any given price, lowering infra marginal benefits of price increases in the standard (e.g. monopoly) pricing calculus. As a consequence, a bank with market power facing an increase in adverse selection will also increase its market share and improve the quality of its borrowers. This is because a lower price attracts marginal borrowers, which are safer under adverse selection. That implies both that imperfect competition can moderate the welfare losses from an increase in adverse selection, and that higher adverse selection can moderate the welfare losses of market power.

The model

We construct a model where banks offer standardised contracts to observationally equivalent firms. Loan contracts are differentiated products in terms of, among other characteristics, the amount granted, a bank's network of branches, the years a bank has been in a market, and distance from the closest branch. These sources of product differentiation make local credit markets imperfectly competitive. Banks compete Bertrand-Nash on interest rates, which also act as a screening device as in Stiglitz and Weiss (1981). Firms seek lines of credit to finance the ongoing activities associated with a particular business project, the riskiness of which is private information to the firm. Firms choose the preferred loan, if any, according to a mixed logit demand system. They also choose how much of the credit line to use. Finally, they decide whether to repay the loan or default. Following Chiappori and Salanié (2000), the degree of adverse selection is determined by two correlations: That between the unobservable determinants of the choice to take up a loan and default (the extensive margin), and that between unobserved determinants of how much of that loan to use and default (the intensive margin). For a given interest rate, firms' expected profits are increasing with risk due to the insurance effect of loans – banks share a portion of the costs of unsuccessful projects. As a result, higher-risk firms are more willing to demand higher-rate loans. This, in turn, lowers the profitability of rate increases by banks. We show with a Monte Carlo simulation in Figure 1 that imperfect competition can indeed mitigate the effects of an increase in adverse selection. When markets are competitive (high price sensitivity), more adverse selection always leads to higher rates and less credit. This is shown in the figure by the increase in prices when moving from the lowest central point towards the northeast. As banks' market power increases (low price sensitivity), this relationship becomes weaker and eventually turns negative. This is shown in the figure by the decrease in prices when moving from the north westernmost point towards the east.

Figure 1. Adverse selection vs imperfect competition: Equilibrium prices

Note: The vertical axis shows the level of equilibrium prices. The left horizontal axis is level of price sensitivity (our measure of competition with the outside option), increasing towards southeast. The right horizontal axis is the level of adverse selection, increasing towards northeast.

Data and estimation

We estimate the model on highly detailed microdata covering individual loans between Italian firms and banks between 1988 and 1998. We define local markets at the level of provinces. Provinces are administrative units roughly comparable to a US county that, as discussed in detail by Guiso et al. (2013), constitute a natural geographical unit for small business lending. We estimate individual firms' demand for credit, banks' pricing of these lines, firms’ loan use and subsequent default. We extend the econometric approach taken by Einav et al. (2012) to the case of multiple lenders by assuming unobserved tastes for credit independent of the specific bank chosen to supply that credit. We combine this framework with the literature on demand estimation for differentiated products (Berry 1994, Berry et al. 1995, Goolsbee and Petrin 2004). Data on default, loan use, demand, and pricing separately identify the distribution of private riskiness from heterogeneous firm disutility from paying interest.

We provide reduced form evidence of adverse selection along both the intensive and the extensive margin, but focus our efforts on structural estimation of the adverse selection parameters. In the structural model, we find that the choice to borrow, the amount used, and the decision to default depend on observables as expected. In particular, a higher interest rate and higher distance from branches reduce the probability that a firm borrows. In terms of correlation between unobservables, we find a positive correlation both between the choice to borrow and default, and between how much loan to use and default. We interpret this as evidence of adverse selection.

Counterfactual

We run a counterfactual to quantify the extent of adverse selection and understand its interaction with imperfect competition. In this policy experiment, we increase the degree of adverse selection, identified by the correlation between both demand and default, and loan use and default unobservables. Then we look at how equilibrium prices, quantities, and defaults vary in response to this. The economic motivation for this exercise can be thought as the consequences of a credit crunch, where risky firms become more exposed to financial distress than safe ones and demand more credit. This counterfactual delivers two important findings.

  • First, equilibrium prices, market shares, and defaults both increase and decrease in response to an increase in adverse selection.

Figure 2 shows the distribution of percentage price variations as adverse selection rises, and Table 1 shows descriptive statistics on the price, quantity, and default variations.

Table 1. Descriptive counterfactual % price, market shares, defaults changes

Note: These variations are at the bank-year-province level.

The rise in adverse selection causes prices to increase on average by 8.4%, but with substantial variation, as some increase by almost 30% or above (95th percentile), and some actually decrease by around 3% or more (5th percentile). As expected, quantities react in the opposite direction. On average, banks experience a 7.7% decrease in their quantities in a year-province, but again with a large variation. If, on one hand, some banks lose more than half of their amount lent in a market (-62% at the 5th percentile), others increase their shares by 27% or above (95th percentile). Finally, higher adverse selection tends to worsen banks' pool of borrowers, as there is an average 6.8 percentage points increase in the share of a bank's defaulters in a year-province, but in some cases default rates actually decrease.

Figure 2. Kernel density of counterfactual % price change

Note: An observation is a year-province-bank. The vertical axis is the density. The horizontal axis is the % price variation between the baseline case and the counterfactual scenario. The graph is trimmed to avoid outliers.

  • Second, these variations are correlated with banks' market power, measured by their estimated markup at the year-province level.

We find that banks with higher markups decrease prices as adverse selection increases, and consequently increase their share of borrowers and decrease their share of defaulters. We find that one standard deviation increase in markup reduces a bank's prices by 3.7%, increases market shares by 13.8%, and reduces the share of defaulters by 2.4 percentage points.

Policy implications

These results highlight several important policy implications.

  • First, an increase in adverse selection causes most of the prices in our sample to increase, most of the quantities to fall, and most of the defaults to rise.

This implies that, consistent with the theoretical literature on the adverse effects of asymmetric information, such asymmetries can severely worsen lending conditions in this market, and suggests that additional policies to mitigate this market failure would be beneficial.

In other words, while market power can soften the adverse effects of asymmetric information, these effects are not sufficient on average.

  • The second implication is that some markets are different. There is substantial heterogeneity in price, quantity, and default responses to this rise in adverse selection across banks and markets.

It is of crucial importance for policymakers to understand how some banks and/or markets can absorb these shocks and others cannot.

We offer one possible explanation for this heterogeneity, which is market power. We show that banks with higher markups have a counter-cyclical effect on credit supply, responding to an increase in adverse selection with a reduction in prices and an increase in quantity lent. Hence, on one hand competition in lending markets is beneficial for borrowers as it can reduce interest rates. On the other hand, it forces banks to follow the business cycle and increase rates as adverse selection rises, making borrowing firms more likely to be credit rationed during this kind of shocks.

References

Berry, S (1994), “Estimating discrete-choice models of product differentiation”, The RAND Journal of Economics 25(2), 242–262.

Berry, S, J Levinsohn,  and A Pakes (1995), “Automobile prices in market equilibrium”, Econometrica 63(4), 841–890.

Chiappori, P A  and B Salanié (2000), “Testing for asymmetric information in insurance markets”, Journal of Political Economy 108(1), 56–78.

Crawford, G S, N Pavanini, and F Schivardi (2015), “Asymmetric information and imperfect competition in lending markets”, CEPR Discussion Paper 10473.

Einav, L, M Jenkins, and J Levin (2012), “Contract pricing in consumer credit markets”, Econometrica 80(4), 1387432.

Goolsbee, A  and A Petrin (2004), “The consumer gains from direct broadcast satellites and the competition with cable tv”, Econometrica 72(2), 351–381.

Guiso, L, L Pistaferri,  and F Schivardi (2013), “Credit within the firm”, The Review of Economic Studies 80(1), 211–247.

Mishkin, F S (2012), The Economics of Money, Banking, and Financial Markets, Pearson Education.

Stiglitz, J and A Weiss (1981), “Credit rationing in markets with imperfect information”, The American Economic Review 71(3), 393–410.

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